Speedshield Technologies, a global leader in industrial connectivity and safety solutions, today announced the appointment of Nathan McKenzie as Chief Executive Officer.  McKenzie steps into the role following more than two decades with the company, having most recently served as Chief Technology Officer. As one of Speedshield’s earliest employees, he has played a central role in shaping the company’s evolution from its early engineering roots into a global provider of AI-powered safety and perception systems used across material handling, mining, construction, and heavy industry.  His appointment comes at a pivotal moment for Speedshield, as demand accelerates for intelligent safety technologies that can operate reliably in complex, high-risk environments. With increasing pressure on operators to balance productivity, compliance, and worker safety, the company is expanding its focus beyond standalone systems toward a broader ecosystem of integrated, perception-led solutions.  Under McKenzie’s leadership, Speedshield will continue to advance its core mission of improving on-site safety by enhancing how machines understand and respond to their surroundings. Drawing on deep experience in product development and engineering, he will guide the company’s next phase of innovation, with a focus on scalable, cost-effective technologies that deliver real-world impact across diverse industries.  “Speedshield has always been, at its core, an engineering and solutions-driven business,” said McKenzie. “Our customers aren’t looking for technology for its own sake. They’re looking for ways to solve real problems on site, particularly when it comes to the interaction between people and machines. That challenge is consistent across industries and regions, and it’s where we continue to focus our efforts.”  McKenzie continued: “We’re now at a point where advances in AI and edge computing allow us to rethink how safety is delivered. It’s no longer just about capturing data or providing visibility, but about creating a clear, real-time understanding of the environment around a machine. By simplifying how that information is delivered to operators, we can improve both safety outcomes and operational efficiency without adding unnecessary complexity.”  Having led the development of Speedshield’s core technologies, including its AI-powered perception capabilities, McKenzie brings a uniquely hands-on perspective to the role. His leadership is expected to strengthen the company’s product-led approach, while supporting continued expansion into new industries and applications where pedestrian and vehicle interactions present significant risk.  As Speedshield builds on its recent growth, the company is also investing in the continued evolution of its product portfolio, with a focus on greater integration, ease of deployment, and adaptability across different operating environments. This includes expanding its ability to detect and respond to a wider range of real-world scenarios, enabling customers to address both safety and operational challenges through a single, unified platform.  “With the technology now reaching a point of broader market acceptance, the opportunity ahead is to make these systems more accessible, more intuitive, and more widely deployed,” McKenzie added. “Our goal is to ensure that advanced safety is not seen as an optional add-on, but as an expected part of every industrial operation.” 

The Industrial Truck Association (ITA) and its members advocate for lift truck safety year-round. But once a year, they dedicate an event to mark the significance. This year’s National Forklift Safety Day (NFSD) event falls on June 9, with the presentations held live on that day from Willard Intercontinental hotel and the National Press Club, in Washington, DC. The event also will be live streamed.   The NFSD event brings together executives from lift truck manufacturers and industry safety experts, with presentations and discussions focused on how to increase the level of safety in the use of industrial trucks. To register for the live, in-person event or streamed broadcast, visit ITA’s website (indtrk.org) and navigate to the events tab. The main session on June 9 is scheduled for 9 a.m. to 11 a.m. ET With forklifts being heavy equipment that carry pallet loads that may weigh 4,000 pounds or more, lift truck safety has long been a focus for ITA and industrial truck OEMs. According to statistics gathered by National Safety Council, there were 84 fatal incidents in 2024, and several thousands of non-fatal incidents. Reducing such incidents through best practices, operator training and industry education is a key goal of NFSD, especially as the number of lift trucks and lift truck workflows increase. This year marks the 13th edition of ITA’s NFSD event, which is traditionally held the second Tuesday of June. From its start with ITA, similar lift truck safety day events have spread to other countries, including Japan, China, the United Kingdom, Australia and other countries as well. But the event is only one way to make lift truck safety a priority for your operations. For Nathan McKenzie, CEO of Speedshield, who devised its AI-powered pedestrian detection system, AiVA, to tackle preventable injuries and fatalities caused by heavy industrial machinery, the issue goes beyond operator error or non-compliance. He believes many industrial sites are still relying on outdated approaches to safety in environments that have become faster, busier, and more complex than ever before. “Spend a few days on a warehouse floor and you realize pretty quickly that forklift safety is something workers have to think about every hour of every day, regardless of the safety protocols put in place” McKenzie said. “Any environment where a forklift is used, whether it’s a manufacturing plant, a distribution center, or as part of a mining operation, share something in common—they’re constantly moving. Operators are navigating tight spaces, people are crossing shared walkways, pallets are stacked high, and everybody is working under pressure to keep things ticking along at speed. When ‘stuck-by’ and other vehicle-related incidents occur, it’s easy to assume it’s because somebody wasn’t following safety procedures. But that’s rarely the case.” McKenzie said in his experience, these incidents tend to occur during ordinary moments that escalate faster than people are able to react—a worker steps into an operator’s blind spot while carrying out a routine task, or an operator focuses on maneuvering a load and loses visibility for a second or two. In busy sites where alarms, reversing buzzers, radios, and machinery are all competing for attention at once, it becomes very easy for important warnings to simply fade into the background. “I think National Forklift Safety Day is important because these incidents are still affecting thousands of workers and families every year,” McKenzie said. “Behind every statistic is somebody who went to work expecting a normal shift and ended up seriously injured, or worse. At the same time, there’s a real opportunity for the industry to rethink how training, site design, and technology all work together to reduce preventable accidents.”   Advanced object and pedestrian detection features aren’t mandated safety features for all industrial trucks, but they are a safety-related technology, helping operators make better decisions within a busy warehouse. What’s more, with vision/AI-based solutions, there is no tag or beacon infrastructure to add to key points like rack uprights. Alex Johns, the new president of ELOKON North America, said there are advantages of vision-based object detection versus other technologies like tags or LiDAR. “The biggest thing that jumps out is that you don’t have to carry anything extra,” Johns says. “With tag-based systems, you’re always relying on a human not to forget their badge. With LiDAR, you’re dealing with a very “linear” way of seeing—it’s basically just breaking a light plane.” Vision-based objection/pedestrian detection is often deployed in situations where the end user has a fairly large mixed fleet of trucks from more than one OEM. “In the U.S., about 85% of facilities are running a ‘mixed fleet’—they might have a Crown here, a Raymond there, and a Hyster over there,” Johns added. “You can’t have a safety system that only speaks one language. You need a system that fits the environment, not just the truck, because the safety variables change from one corner of the warehouse to the other.”

For a long time now, we’ve judged industrial equipment by a fairly unforgiving logic: the older it gets, the closer it moves to replacement.  Age is treated as decline. Capabilities narrow, maintenance costs climb, and eventually the conversation shifts from how to get more out of a machine to when to retire it. That mindset has shaped capital planning across warehouses, job sites, mines, and plants for decades.  But it’s starting to look a little outdated in 2026. As AI and machine vision mature, and as edge processing becomes more powerful and more commercially viable, we’re entering a period where aging equipment does not have to become less useful with time.  In some cases, it can become more capable, more aware, and more valuable than it was on the day it was first put into service. All that’s needed it a little ingenuity and adaptation.  Instead of waiting for the next generation of factory-built machinery to arrive, we need to start thinking more about what can be added in the aftermarket we rely on every day. A forklift, loader, crane, or mining vehicle no longer has to be viewed as a static asset with a fixed ceiling on performance.  With the right retrofit technology, it can keep learning, keep improving, and keep adapting to the environment around it. That opens the door to a very different way of thinking about industrial modernization. Instead of a cycle of discard and replace, there’s a smarter way to extend the life, intelligence, and return of the assets already doing the work.  Intelligence Should be Factory-Fitted One of the biggest misconceptions I see is that this next wave of “smart” industrial equipment must come straight from the factory. Like buying a new car, or replacing an old phone.  But that’s not how things are playing out on the ground. The real magic is happening in the aftermarket, where we now have the ability to take equipment that’s already in service and layer in new intelligence without having to redesign or replace it. That’s important, because most fleets aren’t made up of brand-new machines. They’re a mix of assets at different stages of their lifecycle, all of which still have a job to do.  If the only path to modernization is full replacement, then any progress is immediately capped by budget. If you can retrofit intelligence onto what’s already there, you can move a lot faster.  Of course, that only works if the technology fits into the reality of industrial operations. Equipment can’t be taken offline for half a day just to install something new, and solutions that are too complex or too expensive won’t scale beyond a handful of use cases.  That’s why the form factor, deployment time, and overall simplicity matter just as much as the capability itself. If you can walk up to a piece of equipment, install a system in under an hour, and immediately start adding value without disrupting operations, you’ve changed the entire equation.  It becomes less about “Do we replace this machine?” and more about “How do we make the machines we already have safer, smarter, and more productive?”  AI at the Edge At the heart of this movement is a combination of machine vision and edge processing that allows equipment to interpret what’s happening around it in real time. Instead of just capturing video or data, these systems are actually making sense of the environment, identifying people, objects, movement, and potential hazards as they happen.  What’s powerful here is that the hardware doesn’t have to change every time the use case does. The same system can be trained and retrained to solve different problems, whether that’s pedestrian detection, identifying misplaced inventory, monitoring blind spots, or recognizing edge cases that could lead to an incident. It opens up a much broader set of possibilities than most site managers realize.  What really stands out to me is that this is one of the few investments in industrial environments that doesn’t lose value the moment it’s deployed. In most cases, you buy a piece of equipment and, from that day forward, it slowly depreciates in capability.  With AI-driven systems, it can flip the other way. As models improve and processing becomes more efficient, the same piece of equipment can become more accurate, more responsive, and more useful over time. You’re not just buying what it can do today, you’re buying into what it can become. That’s a very different way of thinking about technology on the shop floor, and it’s one that has real implications for how businesses plan, invest, and operate.  The way we think about industrial equipment is starting to shift, and not before time. Instead of asking how long a machine has left before it needs replacing, we should be asking how much more it can learn while it’s still in service. When intelligence can be added, updated, and refined over time, the value of an asset no longer peaks on day one.  In many cases, it’s just getting started.

Pedestrian safety in the warehouse is quite literally a matter of life or death. The Occupational Safety and Health Administration (OSHA) estimates about 85 forklift fatalities happen per year, as well as 34,900 serious injuries and 61,800 non-serious injuries—most of which can be prevented with better training and solutions. Expectations are high on organizations to move faster and more efficiently; however, workflows and traffic patterns are constantly changing to meet new demands. These added pressures combined with high turnover rates can result in inexperienced forklift operators, and an innately dangerous industrial environment means finding flexible safety solutions should be top of mind for every warehouse manager. “Pedestrian safety is one of the most significant risks in industrial environments,” says Nathan McKenzie, CEO of Speedshield Technologies. “When people and equipment operate in close proximity, the potential for serious injuries is very real.” The challenge isn’t just operator awareness, McKenzie notes, but also the unpredictability of human behavior and the dynamic and complex nature of the working environment. “Even well-designed sites still rely on people doing the right thing every time, which is not a reliable safety control on its own,” he says. Reducing these immense risks requires a layered approach to safety solutions that first and foremost should start with operator training. From there, a combination of active and passive systems designed around your facility’s unique needs can help reduce accidents and improve operational workflows. “A strong safety culture and performance is closely linked to overall operational excellence,” says McKenzie. “Companies who make safety truly their highest priority see improved productivity, higher employee engagement, retention and output.” Identifying weak points Managing site design and workflows is a good place to start when navigating safety concerns. The most dangerous areas of an operation will vary greatly from case to case, but a few keys areas are important to prioritize. For example, blind corners, intersections and areas where a high rate of speed come into play all pose a significant risk to pedestrians. While McKenzie says speed controls are the single most important variable when it comes to pedestrian-equipment collisions, he also points out several key challenges operators and pedestrians face when working side by side. They include: • Mixed traffic where pedestrians, forklifts and increasing levels of automation operate in proximity to each other. • Dynamic environments where stock, traffic movements and flow change in real time. • Compromised machine and pedestrian separation due to site layout. • Mixed levels of training and compliance. For Joshua Eby, global product manager at Hyster, the hot spots are simply any area where you have forklifts and pedestrians interacting. “Not always are you going to have pedestrians and forklifts in the same area, but where you do have that in a facility, that’s definitely somewhere you would want to focus on,” Eby says. Dave Dalleske, senior vice president of sales at A-Safe, recommends looking at a building’s traffic flow of goods and asking: Where are your busiest areas? "You should try to eliminate any kind of pedestrian crossing there, no matter what,” Dalleske says. “That’s my first approach—let’s try to segregate this as much as possible. We don’t want employees and forklifts in the same vicinity if we can avoid it. There are just too many variables that lead to unfortunate delays and accidents.” The first line of defense Once the problem areas are identified, simple, low-tech solutions like gates, guardrails, crosswalk systems and lighting system sensors often act as the initial layer of protection. These solutions are considered passive safety precautions and work to separate pedestrians from mobile plants. This equipment can prevent pedestrian employees from walking freely through a facility and just hoping they don’t come upon a quickly moving piece of equipment. “A common approach I see is the facilities will tell their employees, ‘Be careful.’ That’s your safety measure,” says Dalleske. “Well, oftentimes we need to do more than just say, ‘Be careful out there.’ That’s where I think the guardrail with another platform or another technology or another measure really gives that that extra layer of safety.” The guardrail really acts as that first line of defense, according to Dalleske. “It keeps a corral of employees and how they’re supposed to move through a facility and where it’s safe to move through a facility,” he says. “The gates and so forth provide a level of hesitation. It provides a very visible, clear line of separation.” Graduating to an active approach Good site design, training and separation through physical barriers can only take you so far, though. Combining all that with data and assistive technologies is often the next layer of defense when you’ve tried everything else. If people are still coming too close to forklifts, the first question Alex Johns, president of ELOKON Group, asks is: What does your operation look like today, and have you done all you can to separate pedestrians and forklifts within the bounds of productivity? “If the answer is you’ve done everything that you can passively—gates, barriers, fences, lasers and strobes—to warn when something comes in, then where can you go from there?” asks Johns. The remedy is likely adding a more active technology to your safety stack. “There are some situations that barriers and defenses just can’t account for,” says Johns. “There’s never been any two facilities that had exactly the same scenario, so you have that solution set that gives you the flexibility to assess what they have today and give them options on how they can graduate to something more active tomorrow.” Ty Kim, chief strategy officer at Kyungwoo Systech, has found the same to be true, especially in noisy, busy environments like manufacturing plants where it can be very difficult for pedestrians to notice approaching vehicles even with flashing lights and audible alerts. “Even with all that, people get distracted and things happen, so this third step is to alert the forklift and pedestrians to be aware of each other,” Kim says. He adds that those are the ideal environments that will benefit the most from active safety alert systems, sensors and cameras. Advanced technologies like proximity sensors and pedestrian detection video systems come into play when low-tech options are no longer enough. They work in instances when pedestrians are not where an operator would expect them to be and act as additional aids in times of transitions. Speedshield’s AiVA pedestrian detection system, for example, was designed to address the limitations of and risks associated with operating equipment around people. It uses stereoscopic lenses to both detect and range to any pedestrians in view and automatically alert the operator using visual, audible and in some applications haptic feedback. “This is the second set of eyes that’s always looking,” says McKenzie. “They don’t get tired. They’re really there for those scenarios where a person really isn’t expected to be there.” The pedestrian awareness camera from Hyster and Yale works similarly to monitor exclusively for pedestrians. It provides a two-alert system that gives both an audible and visual alert to the operator when a pedestrian is picked up on the camera. The system also features a three-alert option, with the third alert cutting power to decelerate and slow down the truck if a pedestrian is spotted by the camera. “Obviously, nothing is going to replace proper forklift training; the first and foremost focus is making sure that your operators are properly trained on the lift truck, as well as making sure that pedestrians know what’s going on and are aware of their surroundings. But, anything we can do to help assist an operator, to make sure that they know when pedestrians are around, that is the goal,” says Eby. Gaining visibility A layered safety approach also allows a facility to really adapt and flex systems as operational and safety needs change. Knowing what is working or not working, though, requires a level of visibility into what is happening throughout the day. Smart sensors like those in A-Safe’s new guardrail, for example, provide data points to measure the overall safety of a building. Embedded with a smart cap system that has built-in sensors, anytime the guardrail is hit by something, these sensors provide a visual alert for the driver, notifying them that they hit something. “That sensor provides that reporting capability of intensity and frequency and time of day to build those insights to allow from an operations or safety team measured to say, ‘Hey, listen, I need to provide some more training, perhaps for this shift of employees. I need to maybe rework my traffic flows within my facility because this is a very tight corner,’” explains Dalleske. Dashboards that continuously monitor metrics take that analysis a step further. “The bigger picture of that is understanding the recordables, and how to prevent them,” says Johns. “More importantly, having visibility through dashboards to monitor and keep a handle on the metrics side by side. That’s the next step in the graduation—being able to access and have reference to all those events and metrics that evolve over time.” These metrics include knowing how many pedestrians have reached a proximity to a forklift that said they were too close or how many severe impacts are happening per shift, month or year. “We deal with companies that have hundreds of forklifts at a single site and imagine trying to keep up with all the impacts,” says Johns. “It’s very useful for these fleet managers and fleet contract specialists and safety managers to be able to compare metrics among their sites. Which sites are being safe? Which sites are doing a good job and which sites do you need to improve on, do some retraining. It gives you one source of truth, a record to help you update your safety plan and ultimately keep folks from getting hurt.” ELOKON’s ELOfusion forklift safety system combines elements of proximity detection with fleet management in one solution that gives operators that much sought after flexibility. “Today you come to us and your focus is on pedestrian to forklift interaction, but tomorrow, you would like to put something in place to help coach operator behavior. Having both capabilities in one device, it gives you the option to graduate,” says Johns. The pedestrian awareness camera from Hyster and Yale offers a similar combination that works with its telemetry system to communicate metrics of pedestrian detection events to a dashboard that a warehouse manager and operations manager can review. “The telemetry system can help suggest, ‘Hey, these are some situations where we can target changes as a company, as an organization, to then reduce the number of pedestrian interactions that occur with the materials handling equipment,’” explains Clay Hendricks, telemetry and operator assist product manager, Yale Lift Truck Technologies. Over time, Hendricks says this information helps companies make changes to foot traffic, how they are using passive safety solutions like guards and railing throughout the facility, and update training scenarios. 

Welcome to Construction Safety Week 2026! We have reached an inflection point. A shift is underway when it comes to safety in the construction industry. Many companies in the industry are no longer just enforcing rules to maintain compliance. Rather, many are now completely rethinking how safety is achieved in the first place. Here at Constructech, we have been examining a trend in the past couple of years that is important to note. Process, culture, and strategy are all changing as it relates to safety. Many companies are taking a different approach. This foundation is perhaps more important than ever before. Construction companies are faced with challenges like tighter project timelines, new regulations, constrained supply chains, and a labor shortage, just to name a few. One of the notable trends helping to shape this shift is the rise of AI (artificial intelligence)-driven safety systems. AI can help improve safety in myriad ways in the construction industry. Sensors, cameras, and machine learning can help interpret jobsite activity in realtime. Many of those working in the construction industry know OSHA’s (Occupational Safety and Health Admin.) fatal four account for roughly 60% of all fatalities in the construction industry: falls, struck-by, electrocution, and caught-in/between. Let’s look at one specific use case. Struck-by are when workers are hit by falling objects, vehicles, or swinging equipment, and account for roughly 10% of fatalities in the construction industry. Traditional mitigation strategies include high-visibility clothing, spotters, and exclusion zones. This is a great start but rely heavily on consistent human execution. What if AI could help here? As one example, Speedshield Technologies offers technology that improves hazard recognition by identifying risks around heavy equipment, especially blind spots, pedestrian interactions, and dynamic jobsite conditions. Michael Barnard, vice president of sales, Speedshield Technologies, suggests what is starting to change in 2026 is how we think about responsibility for safety. “Rather than placing the burden solely on the operator, there’s a shift toward systems that can actively support decision making in realtime,” he says. “That means technology that can interpret what’s happening around a machine, understand when someone is entering a danger zone, and communicate that risk clearly and at the right moment.” Of course, this is only one example of technology. There are hundreds of solutions out there that can help improve safety in construction. Data-driven safety programs can ultimately improve how contractors are using near-miss insights and equipment-interaction analytics. Although, let’s be clear. Humans are still a big part of the safety equation. As we have always said, we must first start with the strategy and culture shifts and not turn to technology just for the sake of turning to technology. Construction Safety Week serves as a reminder of both the progress we have made and the work that still needs to be done. The industry is moving to a model where human expertise is augmented by intelligent systems, and a collaborative approach is central to all of it.

In mining, construction and materials handling, the most serious incidents continue to involve machinery and moving equipment. MICHAEL BARNARD, VP of Sales at Speedshield Technologies, sets out how a systems-based approach may be able to help.  Australia’s workplace safety record has improved steadily over the past decade, but one question is still troubling industries such as mining, construction and materials handling: why do the most serious incidents continue to involve machinery and moving equipment? According to Safe Work Australia, machine operators and drivers account for a disproportionate share of injuries and fatalities, with a rate of around 6.7 deaths per 100,000 workers.1 That’s more than five times the national average across all workplaces. It’s a pattern we’ve seen emerging for some time, even as safety frameworks, training programs and compliance standards have matured. If progress has been made in these areas, why do these risks remain so stubbornly embedded in industrial, construction and mining environments? Part of the answer is that these industries, in particular, are moving faster than some safety practices can keep up with. Worksites in 2026 are faster, more complex and far less predictable than traditional safety models were originally designed for. Heavy vehicles, automated systems and human workers now operate side by side in environments that are constantly shifting, and visibility is sporadic and limited. Conditions change by the minute, decision-making happens under pressure and machine safety is still too often treated as a checklist or set of isolated controls. This points to something far broader and more systemic, shaped by how people, equipment and environments interact in real time. The challenge facing these environments is unique — it’s not enough to simply attempt to prevent accidents in isolation; teams need to gain a deeper understanding of how risk emerges across the entire site and how it can be anticipated before it leads to harm. Have traditional safety models reached their limit? Machine safety has typically been built on a simple premise — identify hazards, put controls in place and expect operators to follow procedures. In more stable and predictable environments, like a small, well-organised warehouse, that approach can be effective. But in larger, fast-paced industrial settings, the cracks start to show. Operators are unfairly expected to maintain full and complete awareness of their surroundings while they manage incredibly complex equipment, navigate unpredictable terrain and keep their eyes “on the job.” Dust clouds and fog can obscure vision, rain can change ground conditions, workers can unknowingly step into blind spots, and that’s only scratching the surface. The reality is that many of these environments place an extraordinary mental burden on individuals, asking them to process multiple streams of information at once while making split-second decisions. Add to this the reliance on alarms, cameras and warning systems that aren’t always accurate or calibrated to real risk, and a new problem begins to emerge. When alerts are too frequent or poorly timed, or false flags are constantly raised, operators become desensitised to them. It’s important to stress that this isn’t the fault of operators, it’s simply a natural result of humans being placed in environments where noise, fatigue, distraction and pressure are common. We call this the ‘boy who cried wolf’ effect. If a poorly implemented or calibrated system flags too many non-critical events or false alarms, it gradually loses credibility, and the moments that truly matter get overlooked. How can an operator be expected to trust in a system that is constantly bombarding them with unnecessary lights, sounds and prompts? Most incidents aren’t the result of carelessness on the part of the operator, but a mismatch between the demands of the environment and the way safety systems have been designed, with too much responsibility placed on human attention and not enough consideration given to how those systems behave under real-world conditions. Why machine safety is systemic issue If traditional models focus on individual hazards, a systems-based approach asks a different question: how do risks emerge from the interaction between people, machines and the environment as a whole? On a busy worksite, these elements are constantly influencing one another. A vehicle changes direction, a worker steps into a shared space, visibility shifts due to dust or lighting, and suddenly a routine task carries a different level of risk. None of these factors exist in isolation, and yet safety is often managed as though they do. Looking at the system instead of the individual event makes it easier to see how seemingly minor changes can combine to create dangerous situations. This perspective also highlights something else: many incidents that appear unpredictable at the moment they occur are, in fact, the result of patterns that develop over time. Repeated near misses, consistent blind spots or common movement paths between people and machinery all point to underlying risks that can be identified earlier if the system is being observed as a whole. Truly designing for safety means moving beyond static controls and thinking about how workflows, site layouts and real-time conditions shape behaviour. Site managers need to recognise that risk is dynamic, not fixed, and that effective safety strategies need to adapt to what is happening on-site rather than relying on assumptions about what should happen in theory. From reactive compliance to predictive resilience The good news is that technology is catching up and things are beginning to change. For a long time, safety improvements have been driven by investigation. An incident happens, it is analysed in detail and controls are introduced to prevent it from happening again. That process is still important, of course, but it’s inherently retrospective. It depends on something going wrong first, and that’s not acceptable in such a high-stakes environment, particularly when many incidents are preceded by patterns that go unnoticed in day-to-day operations. Those patterns often take the form of near misses, repeated interactions between people and machinery in high-risk zones, or small deviations from expected workflows that gradually become normalised. On their own, these events may not trigger formal reporting, but taken together they offer valuable insight into where risk is building. The challenge here is visibility. Without a clear view of what is happening in real time, these signals are easy to miss. When operators are given timely, relevant feedback, it changes how they respond in the moment, allowing them to adjust behaviour before a situation escalates. ************************************************** Designing machine safety systems that operators trust Prioritise signal over noise Focus on real, actionable risk. Too many alerts dilute attention and reduce response times. Make interventions immediate and intuitive In fast-moving environments, operators should not have to interpret or second-guess a warning. Reduce cognitive load wherever possible Safety systems should simplify decision-making, not add another layer of complexity. Align with real-world workflows Systems must reflect how work actually happens on site, not how it is assumed to happen. Maintain consistency in how risk is communicated Clear, predictable signals help build trust and enable faster reactions. ************************************************** What’s needed is a different approach to how risk is detected and communicated on site. Rather than relying on operators to interpret camera feeds or respond to constant streams of alerts, newer safety approaches are beginning to focus on delivering clear, context-aware signals only when they are needed. By combining AI-powered machine vision with real-time processing at the edge, these systems can distinguish between routine activity and genuine risk, identifying when a person enters a hazardous proximity zone and triggering a response that is immediate, accurate and completely unambiguous. This also builds trust in the system itself, because the volume of unnecessary alerts is massively reduced. When a warning is delivered, it carries weight and prompts action. At the end of the day, safety technology in these environments only works if it can earn trust, support operators and provide a “joined up” overview of risk that can feed into broader safety policies and processes.

Material handling environments are no stranger to AI. In warehouses and logistics facilities, where forklifts weave through narrow aisles and workers move constantly between shelving and loading areas, AI-driven vision systems are widely used to detect pedestrians and obstacles in real time. Because these environments are structured and have predictable layouts, they’re an ideal starting point for computer vision technologies designed to reduce collisions and improve situational awareness. Naturally, operators working in warehouses now view this kind of AI-assisted technology as a practical extension of existing safety practices – it just clicks.   Construction sites, however, pose a very different challenge. Unlike warehouses, which have predictable patterns of movement, both in terms of people and materials, the only certainty on construction sites is uncertainty. If a warehouse was a track race, with every participant running along a predefined lane, construction sites are more like a football game, with dozens of participants running in different directions on an open-play pitch. Only this pitch shifts – structures rise, materials are loaded and unloaded, terrain changes under heavy machinery, and dust can be kicked up into the environment, affecting visibility. In the US, roughly 1 in 5 workplace fatalities occur on construction sites, and more than a quarter of those are caused by collisions or “struck-by” incidents involving heavy machinery. Attention is now rightly turning toward whether the same real-time detection systems that have improved safety inside warehouses could also help address the far more complex hazards found in construction.   Why construction remains one of the most dangerous workplaces  Despite decades of progress in training, regulation, and protective equipment, construction continues to rank among the most hazardous industries in the world. According to the US Bureau of Labor Statistics, the sector recorded more than 1,000 worker fatalities in 2023, the highest total of any industry, with transportation incidents, equipment strikes, and falls among the leading causes. These risks are closely tied to the nature of construction itself, where workers routinely operate around large, powerful machinery while navigating incomplete structures, unstable ground, and temporary work zones. Unlike controlled industrial facilities like warehouses, construction sites rarely remain the same from one hour to the next. Machines such as excavators, loaders, graders, and articulated haul trucks can weigh tonnes and often operate in close proximity to ground crews going about their daily tasks. Even the most experienced operators face visibility challenges, with blindspots often extending for several meters around large vehicles and workers approaching from unexpected angles. Combine this with dust, noise, adverse weather, and the constant movement of people and materials, and it’s a recipe for potentially life-ending hazards.   The limits of training and human awareness  Most construction safety programs are built around training, procedures, and personal responsibility. These elements are vital parts of the safety picture, but they don’t complete it. Training relies heavily on the assumption that people will always be able to spot danger early enough to respond, and no individual – no matter how experienced or well-trained they may be – can be expected to spot every potential risk and act in time to mediate it. It’s unrealistic, and unfair, to place that kind of burden on individual members of staff.   Human perception has natural limits, particularly in environments filled with noise, dust, movement, and visual obstructions. Operators of heavy machinery rely on mirrors, cameras, and spotters to maintain visibility, but large machines still create blind spots that can conceal pedestrians or obstacles from view. At the same time, workers on the ground are frequently focused on their immediate task, whether guiding materials, securing structures, or preparing equipment. In environments like this where heavy machines and people share the same space, even a brief lapse in awareness can quickly turn into a near miss or a serious incident. The bottom line: no human is capable of eliminating risk on their own.    How AI vision systems are changing the equation  Advances in AI and machine vision are now beginning to introduce a new layer of awareness into industrial environments like construction sites. Using cameras combined with onboard processing, these systems can analyze what is happening around a machine in real time, identifying pedestrians, obstacles, and other hazards that might otherwise go unnoticed. Unlike traditional camera systems that simply display a video feed, AI-powered systems actually interpret the scene, allowing them to recognise risk and alert operators before a dangerous situation develops. In effect, they act as an additional set of eyes that continuously monitor the environment, alleviating much of the burden we place on human shoulders.   Of course, accuracy is critical for these systems to succeed in real-world environments. But trust is important too. Anyone who has spent time around heavy equipment knows that alarms and warnings are only effective when operators trust them. If alerts trigger too frequently without a genuine hazard, workers quickly become desensitized to the noise. The situation is often compared to the classic “boy who cried wolf” story: once people hear too many false alarms, they begin to ignore them. That has shaped the way many industrial AI safety systems are designed. Instead of flagging every possible object in view, effective systems focus on identifying meaningful risks such as pedestrians entering a machine’s path or workers approaching dangerous zones. By minimizing unnecessary alerts, these technologies help ensure that when a warning does occur, operators recognize it as something that genuinely requires attention. And in high-risk environments like construction sites, that balance between awareness and alert fatigue can make the difference between a useful safety system and one that operators simply learn to tune out.   Construction is the new proving ground for industrial AI  As awareness of AI-driven safety technology spreads, construction is emerging as one of the most important testing grounds for its real-world impact. Contractors and project managers are beginning to recognize that the same computer vision systems improving safety in warehouses could also address some of the most persistent risks on job sites. Construction equipment often represents a significant investment, with excavators, loaders, and haul trucks costing hundreds of thousands of dollars and operating in environments where a single incident can halt work, damage machinery, or seriously injure workers. So reducing these risks is not only a safety priority, but an operational one.   Early deployments are already showing how real-time detection can help prevent common construction incidents such as collisions with ground crews, equipment rollovers, and falls near site edges or unstable terrain. Because construction sites are constantly changing, hazards often appear without warning, making them difficult to control through procedures alone. An AI system that continuously monitors the environment can help bridge that gap by identifying risks the moment they emerge, working with operators to ensure safety at all times – even in overstimulated environments where their own senses are impaired.   Redefining safety on modern construction sites  Construction has always required a careful balance between productivity and safety. As projects become larger and machinery more powerful, the margin for error continues to shrink, especially on busy job sites where people and equipment must work side by side. Training, procedures, and experience will always remain central to safe operations, but the complexity of modern construction environments increasingly demands additional layers of awareness. Technologies that can monitor surroundings continuously and identify hazards in real time are now beginning to fill that gap, but trust in the technology matters – adoption will depend as much on understanding the technology as on the technology itself. Contractors are only just beginning to explore how AI-assisted safety systems fit alongside established safety practices, but once site managers see how these tools can help prevent a near miss or highlight a risk before it escalates, without adding to the burden operators already carry, the technology will come into its own.  Eventually, AI-driven awareness systems will become another standard component of responsible site management, empowering crews to navigate the hazards of heavy equipment and dynamic sites more safely. 

As warehouses continue to grow in size and complexity, the ability to make these invisible moments visible will become less of a nice-to-have and more of a foundation for efficient, resilient operations. When organizations talk about “shrinkage” in warehouses and distribution centers, the conversation usually turns quickly to theft. Cameras, access controls, and audit trails are put in place to deter bad actors and tighten security at the perimeter. But in many large logistics environments, some of the most significant losses don’t involve intent at all. They happen quietly, during routine movements, when pallets are dropped in the wrong location, loads are left unscanned, or high-value goods sit idle because no one can say with confidence where they were last placed. These moments rarely trigger alarms, but across thousands of square meters and multiple shifts, they accumulate into real financial loss that is difficult to trace and even harder to recover. It’s not that there’s no effort or accountability on the warehouse floor. Modern operations are fast, complex, and constantly changing, with operators navigating evolving layouts, mixed traffic, and time pressure that leaves little room for manual confirmation at every step. In that environment, visibility gaps understandably become an accepted part of doing business. Inventories exist in systems, but the physical reality between pick-up and placement often goes unrecorded, leaving teams to reconcile discrepancies after the fact. What’s increasingly clear is that this is a visibility problem, not a discipline problem. As vision-based technologies mature, there is an opportunity to address those blind spots directly, capturing the movements that matter, as they happen, without adding friction or slowing the work down. Misplacement is a process problem, not a people problem While it’s tempting to attribute misplaced inventory to individual mistakes, the “blame game” misses the reality of how modern warehouses actually operate. Operators are expected to move quickly, often across unfamiliar or reconfigured spaces, while coordinating with other vehicles, pedestrians, and systems around them. Even the most experienced teams are working within environments that change by the hour, not the week. Under those conditions, relying on training, memory, and habit while expecting procedural perfection is simply unrealistic. What often gets labeled as human error is usually a symptom of systems that cannot see or remember what just happened. And when visibility breaks down at the process level, misplacement becomes inevitable because the environment provides no continuous, objective record of where loads are picked up, carried, and set down. Until that gap is addressed, training and enforcement can only ever reduce, not eliminate, the losses that follow. Why traditional tracking falls short on the warehouse floor Most warehouses already have tracking systems in place, but those systems were designed for static checkpoints rather than continuous movement. Barcode scans, RFID reads, and manual confirmations all depend on operators stopping, aligning, and interacting with a process that sits outside the flow of work. In controlled environments, that can be effective. But on a busy warehouse floor, it introduces friction. When every additional step competes with throughput and safety, compliance inevitably drops. What’s left is a patchwork view of inventory – strong at the edges, weak in the middle – where systems know what was received and what was shipped, but not what happened in between. That “in-between” space is where most misplacement occurs. Loads are moved, set down temporarily, relocated, or staged under pressure, often without a clear trigger that forces a scan or update. Over time, these invisible moments compound. Operators adapt by relying on local knowledge or informal handovers, while supervisors are left reconciling discrepancies after the fact. The issue isn’t that people don’t want to follow process; just that traditional tracking tools were never designed to observe work as it actually happens. Without a way to capture movement and placement passively, warehouses are left managing loss reactively, long after the opportunity to prevent it has passed. Where safety meets operational efficiency Vision-based systems are already proving their value in safety, particularly where vehicles and people operate in close proximity. What’s changing now is how that same capability can be extended beyond hazard and pedestrian detection into broader operational awareness. By understanding where vehicles move, how they interact with their surroundings, and what they are carrying, vision systems can begin to build a contextual picture of work as it unfolds. Importantly, this intelligence lives at the edge, responding in real time without relying on constant connectivity or complex infrastructure. The technology doesn’t need to identify individuals or scrutinize behavior to be useful, it simply needs to observe movement accurately and consistently. Over time, those observations form a kind of “operational memory.” Every pick-up, transport, and placement becomes part of a continuous record that reflects the physical reality of the warehouse, not just what was logged in a system. For operators, this happens quietly in the background, without screens to watch or steps to complete. For supervisors and operations teams, it creates a new layer of visibility into inventory flow that has historically been missing. So instead of searching for what went wrong after a discrepancy appears, teams can understand where goods were last handled, how they moved, and where they were set down, closing the gap between digital records and the real world without adding friction to the job. Reducing shrinkage in warehouses doesn’t require more checkpoints or tighter controls. It just requires better visibility into what is already happening. When systems can see movement as it occurs and retain memories of where loads have been and where they were placed, misplacement stops being an accepted cost of scale. As warehouses continue to grow in size and complexity, the ability to make these invisible moments visible will become less of a nice-to-have and more of a foundation for efficient, resilient operations.

Michael Barnard, Speedshield Technologies, considers how AI safety systems are reshaping high risk worksites, but trust builds only when crews see them in action – catching blind spots, preventing accidents, and proving they are a proactive layer no team can match. AI might be transforming every industry, but out on factory floors, warehouses, and construction sites, it looks nothing like the glossy demos people see online. It shows up as compact hardware bolted onto machines, watching blind spots and reacting faster than any operator could. And yet, even as the technology has matured, the hesitation has not gone away. For many safety managers, the real sticking point is not capability – it is confidence. After decades of relying on training, signage, and manual checks, the idea of a system making split-second safety decisions still feels like a leap of faith, especially for teams who have encountered older systems that raised false alarms or simply got in the way. The tech is ready; earning trust is the part that takes work. In my experience, most of the hesitation around AI comes down to unfamiliarity. People hear the term and immediately picture something complicated, unreliable, or out of their control. But the moment they actually see the system working on their own equipment, everything changes. Those first few minutes of a demo do more than any explanation ever could – operators watch the system pick up a person in a blind spot, trigger the alert or slowdown exactly as it should, and suddenly the scepticism drops away. It goes from “I’m not sure about this AI stuff” to “I want this across my fleet” almost immediately. That is why getting the technology in front of people is the single most powerful trust-builder we have. What reliable AI looks like on the ground When people talk about trusting AI, they are really talking about whether it behaves the same way every time, in the places where mistakes matter most. On the ground, that means recognising a person even if they are partially hidden behind a rack, catching someone stepping into a danger zone, or triggering a clear visual alert, like a bright LED strip, when someone gets too close. Some sites prefer full machine intervention, others start with alerts only, but the key is consistency. Operators quickly pick up on whether a system fires accurately or whether it cries wolf, and once they see it respond correctly in their own daily routines, their whole attitude shifts. Add in capabilities like edge detection or identifying other onsite hazards, and it becomes a tool people rely rather than something they feel forced to work around. Cracking ‘big iron’ in construction and mining Material handling has come a long way, but in construction and mining the conversation is only just beginning. Most crews in those environments have not encountered modern AI safety systems before, so you are often introducing the entire concept from scratch. The upside is that the economics make sense immediately. Adding a multi-camera setup to a machine worth a quarter of a million dollars is a small investment for a big jump in protection. The challenge is getting that first sliver of attention from the right decision-maker and showing, quickly, what the system can actually do. In those industries, once someone sees it work on their own excavator or haul truck, word spreads fast, and that is when adoption really starts to snowball. The leap to proactive protection One of the toughest conversations I have is with companies proud of a spotless safety record who wonder why they should change anything. I always respect that. They have clearly built a strong culture. But they know it only takes one moment of distraction for everything to go wrong. But a system does not get tired or distracted. It can cover the blind spots humans inevitably miss. For a relatively small investment, you get an extra layer of protection that proves its worth the first time it prevents an accident. That shift from reactive thinking to proactive protection is where trust really takes root, and where the biggest safety gains are made.

Work zone fatalities have gone up in the United States, according to the most recent numbers from OSHA (Occupational Safety and Health Admin.) with more than 898 deaths and 40,000 injuries estimated in 2023. This represents a 50% increase in work zone fatalities reported between 2013 and 2023. This is simply unacceptable. Can emerging technologies like AI (artificial intelligence) help? Of course, if implemented correctly. AI-powered safety tools are increasingly being deployed to reduce risk by improving visibility, identifying hazards earlier, and assisting workers and equipment operators with better situational awareness. Unlike traditional safety tools that rely solely on human observation, AI systems can continuously monitor jobsites, analyze patterns, and alert workers to potential dangers before they result in incidents. AI on the Job Consider these cases for AI: Systems can process data from cameras, sensors, and equipment telemetry to detect unsafe behaviors, identify when workers enter restricted zones, or recognize when machinery is operating too close to personnel. Ultimately, these systems can help safety managers analyze trends, such as repeated near-misses or high-risk locations on a jobsite, enabling companies to address hazards proactively rather than reactively. As one specific example, Speedshield Technologies, aims to leverage AI to help prevent injuries and fatalities caused by heavy industrial machinery. Using stereoscopic machine vision and edge-based AI, the technology can give operators realtime, 360-degree awareness of pedestrians, without screens, distractions, or the risk of false alarms. Certainly, this is only one illustration. AI and related technologies are being applied in a variety of ways across the construction industry to improve safety. Some of the most common applications include computer‑vision monitoring, proximity‑detection systems, predictive analytics, wearable technology, and more. None of these are new—we’ve had IoT (Internet of Things) technologies enabling these capabilities for years. What’s changed is that AI is now extracting far deeper, faster, and more actionable insights from the data those IoT systems have been generating all along. And that makes data accuracy more critical than ever—because no matter what data we’re collecting or acting upon, the insights are only as trustworthy as the underlying information. Guidelines for a Safer Jobsite While the technology itself is promising, successful adoption depends on thoughtful implementation and worker engagement. Companies interested in leveraging AI to improve safety should consider several key guidelines. Start with the highest-risk areas: Focus first on hazards that cause the most serious injuries or fatalities, such as struck-by incidents, falls, or heavy equipment interactions. Targeted solutions often deliver the fastest safety improvements. Pilot programs before full deployment: Testing new technology on a limited number of jobsites allows companies to evaluate effectiveness, gather feedback, and adjust accordingly before scaling across operations. Integrate technology with existing safety programs: AI should complement—not replace—established safety procedures, training programs, and jobsite supervision. Provide proper training: Workers and operators must understand how the technology works, what alerts mean, and how to respond. Clear communication helps build trust and ensures the system is used correctly. Focus on usability and reliability: Safety technologies must be practical for real-world construction environments. Systems that generate excessive false alarms or disrupt workflows are less likely to be adopted by crews. Use data responsibly: Companies should be transparent about how safety data is collected and used, ensuring technology supports worker protection rather than creating concerns about surveillance or discipline. Surely, AI will not replace the importance of a strong safety culture—but it can become a powerful tool to support it. By combining advanced technologies with proper training, clear procedures, and worker engagement, construction companies can improve hazard awareness, reduce incidents, and create safer jobsites for everyone involved. As these tools continue to evolve, organizations that proactively explore and implement them will be better positioned to protect and ensure every worker returns home safely at the end of the day.

Today’s workplaces are fast-paced, complex operations. In order to make them safer, we need to design them to be used by real people in real-world conditions. Key Takeaway: Workplace safety, and indeed production plants, have been designed for employees who are consistently operating at the top of their game. The problem? That’s not a relatable, or sustainable, way for employees to operate for hours at a time. Instead, we must acknowledge our human limitations and harness technology to make workplaces safer. In any setting where safety and security are important, humans are regarded as the weakest link. That’s as true for cybersecurity as it is for busy construction sites. But they’re also the most valuable link. For decades, workplace safety programs have been designed around the assumption that humans will make mistakes, and that the solution is to make them “better” — more training, more reminders, more alerts and more rules. When incidents do occur, they are often dissected to find the moment a human being failed. From there, the prescription is usually more of the same. Yet serious industrial accidents remain frequent, even in environments with the strictest safety protocols. We need to ask ourselves why that is. What if the fixation on human error is actually a misdiagnosis? Seen this way, we are focused on treating symptoms rather than addressing the root cause. We are assuming that perfect vigilance is a realistic, sustainable state for anyone working a 10-hour shift in a complex, high-stakes environment. Roughly 40% of the U.S. construction workforce experiences high-level fatigue on a regular basis, according to a 2022 report. It’s tempting to attribute this to long hours or the natural result of physical labor, but what if the current solution is actually part of the problem? Modern industrial sites are noisy, fast-moving and cognitively demanding. Operators have to manage not only the immediate task in front of them but also a stream of peripheral hazards, from sudden pedestrian movements to unpredictable equipment behavior. Fatigue, sensory overload and split-second decision-making are part of the job. Even the most experienced operators cannot maintain peak alertness for every moment of every shift. Expecting them to do so is like asking drivers to keep their eyes on every mirror, every gauge and every inch of the road ahead without blinking for hours at a time. If safety systems are designed with the assumption of perfect human performance, they will fail in the real world. According to a 2024 research paper, repetitive alerts and false alarms are one of the leading causes of distraction and can result in the cry wolf effect, where alerts are simply dismissed as untrustworthy. As further evidence, a 2022 study that focused exclusively on the mining sector found that consistent exposure to noise and audible alerts can induce auditory fatigue and is a contributing factor to at least 20% of site incidents. Safety technology has typically been reactive, meaning we wait for an incident to occur rather than preventing them outright. This is akin to a referee waiting for a foul before blowing his whistle to stop game play. Instead, we need to adopt a more proactive approach. We should treat safety technology as a co-pilot that scans, assesses and acts alongside the humans at the controls—supporting them instead of interrupting them. The Limits of Human Vigilance Even in ideal conditions, the human attention span has limits. Cognitive science shows that our ability to maintain situational awareness fades over time, particularly in repetitive or high-stimulus environments. On an industrial site, those environments are the norm: a mix of moving equipment, unpredictable human behavior, shifting weather and, in many cases, constant background noise. Operators are expected to keep track of their immediate task, their surroundings and the movements of others — all while filtering out irrelevant stimuli and responding instantly to the relevant ones. And that doesn’t even take into account the fact that operators need to be able to hear (with any ear protection and hearing aids or other assisted devices) and comprehend (which is no small feat for workforces that can be dispersed across shifts and locations, multilingual and intergenerational with varied education levels, learning types and any number of learning disorders or mental health disorders). It’s an impossible balancing act, and one that grows harder with every hour on the job. The notion that accidents can be eradicated simply by demanding more focus or discipline from workers overlooks the physiological limits of our attention, and it underestimates the impact of environmental factors that quietly but steadily degrade it. "If safety systems are designed with the assumption of perfect human performance, they will fail in the real world." When Safety is Part of the Problem The prevailing safety model in many industrial settings treats incidents as individual failings. When something goes wrong, the default response is to retrain the operator, tighten procedures or introduce new compliance checks. While well-intentioned, this approach assumes that errors are purely the result of lapses in personal responsibility, and that they can be eliminated through discipline or education alone. In reality, the majority of modern industrial accidents occur in environments where workers are already highly trained and fully aware of the risks. The individuals working on these sites aren’t amateurs; they’re professionals who have completed the necessary training and qualifications to perform their jobs (e.g., OSHA’s 40-hour HAZWOPER training). These individuals are not the problem. Rather, it’s the environment itself—and the passive safety technology that has been deployed. These environments lack a system designed to catch the things human beings inevitably miss while also filtering out false flags. Alarm systems that trigger at the slightest movement or misread harmless objects, such as identifying stray cones as pedestrians, quickly become background noise, leading operators to ignore them or disable them altogether. The very technology designed to protect workers thus becomes part of the problem because it’s not accurate enough. It works on a better safe than sorry principle where anything that could be a risk is flagged, instead of being able to identify risks with certainty. Worse still, some of these legacy safety systems act as a judge and jury by shutting down operations or recording and reporting perceived mistakes. This does nothing but foster distrust between humans and machines, prompting workarounds that further undermine safety. The net effect is a reactive, punitive culture that fails to adapt to the realities of industrial work, leaving operators to shoulder the full burden of hazard detection and accident prevention—often in spite of some safety systems. The Need for Co-pilots, not Overseers I firmly believe that people are employers’ most valuable asset. Rather than treating them as weak links, employers should acknowledge and reaffirm their value by incorporating technology that extends workers’ perception, reduces their cognitive load, and intervenes only when there is a real risk of injury or threat to life. What’s changed in recent years is not the idea of pedestrian detection, but the underlying architecture that finally makes it reliable. Older approaches depended on single-lens (monocular) cameras, ultrasonic sensors, or tags and beacons worn by pedestrians—all of which struggled in the real conditions that define industrial sites. A single camera can’t judge depth, which means distance and speed estimates are guesswork. Tag-based systems only work when every person consistently wears a device. And traditional machine vision setups often need cloud processing, introducing the challenge of latency and making them vulnerable to connectivity gaps. Something called stereoscopic vision removes those constraints. By using a matched pair of industrial-grade cameras, the system can perceive depth the way human eyes do, calculating distance, trajectory and relative movement with precision. That capability can be paired with an on-board neural processing unit (NPU) inside a sealed industrial enclosure, which means all the calculations happen directly on the vehicle. This edge-based design ensures that alerts are based on a real-time interpretation of the environment, rather than a delayed or compressed video that must be sent to the cloud and back. It also eliminates any dependence on external networks, which is critical in warehouses, yards, mines or other work environments where connectivity is often uneven or unreliable. Another major leap is the training data behind modern AI models. Rather than relying on generic datasets, today’s systems are trained on millions of hours of footage from real industrial environments, including variable lighting, dust, steam, reflective surfaces, and the unpredictable ways pedestrians actually move around machinery. This is why current-generation systems succeed where previous ones failed; they can distinguish a pedestrian from a shadow, a cone or a piece of debris as well as detect partial occlusions, such as someone emerging from behind a pallet or crossing between racks. Advances in stereoscopic machine vision, edge-based AI detection, and embedded telematics now make it possible to monitor complex industrial environments without relying solely on human observation. These 3D, real-time systems can identify pedestrians and moving equipment with high accuracy, filter out irrelevant motion and even anticipate collision risks before they become imminent. By processing—and acting on—this information locally at the edge, they avoid the latency of cloud-based systems and ensure alerts or interventions happen in milliseconds, not seconds. When it comes to safety systems, design matters just as much as capability. The most effective safety systems don’t compete with the operator’s focus or demand constant interpretation. Instead, they use intuitive cues (e.g, discreet LEDs, directional audio or targeted vehicle responses) to communicate only what’s necessary—and only when it’s necessary. By minimizing false positives, these systems protect workers’ trust in the system and ensure that every alert has weight. Predictive maintenance features can also be integrated, helping teams address mechanical issues before they escalate into safety hazards. Conclusion Once we shed the myth of the perfect operator, a different picture of the future comes into focus. The operator of tomorrow isn’t someone expected to sustain impossible levels of vigilance. They’re a skilled professional who is supported by systems that recognize the limits of human attention and work to extend it. As stereoscopic vision, edge AI and smarter design become the norm, we move toward workplaces where people aren’t punished for being human; rather, they are protected because of it. Altogether, these advances in technology should create a work environment where confidence replaces anxiety and where attention can be placed on the job rather than the constant fear of missing something. That’s the real benefit here: A future where technology absorbs the cognitive load that used to fall entirely on the operator, and where safety becomes a shared responsibility between human judgement and machine precision. In this way, technology becomes a true co-pilot: scanning the environment continuously, stepping in when human capacity is stretched, and doing so in a way that complements (rather than interrupts) the flow of work.

For a challenge that has been in plain sight for decades, pedestrian detection took an unusually long time to reach the mainstream of industrial safety. Every operator knows the feeling of a near miss. A colleague stepping from behind a pallet, a blind corner, or a reversing vehicle in a noisy yard. These are the daily risks and realities of warehouses, factories, and worksites that have otherwise embraced automation, telemetry, and data-driven performance benchmarking. Yet when it comes to protecting people on the ground, the industry has tended to rely on the same set of tools – training sessions, mirrors, signs, and alarms. These tools are useful, but they work on the assumption that awareness alone can prevent accidents in environments where distraction, fatigue, and constant movement are baked in. That assumption, and a healthy dose of skepticism, has led to the slow uptake of technology that could make a real difference to workers on the ground. Early attempts to bring machine vision into safety systems were simply not fit for the conditions they faced. Monocular cameras couldn’t judge distance or depth. Thermal imaging was blinded by sunlight, dust, or steam. And beacon-based systems depended on perfect human behavior, such as remembering to charge, wear, and carry the right devices during every shift. Each of these solutions chipped away at confidence instead of building it. Companies wanted to innovate, but either they couldn’t fully trust the technology of the time, or it placed too much of the safety burden on workers themselves. For safety to be taken seriously by the people it’s meant to protect, it has to work every single time, without creating additional distractions or expecting workers to shoulder more responsibility than they already do. The slow uptake of pedestrian detection hasn’t been due to a lack of willingness, but due to a lack trust in the technology that underpins it. The illusion of “good enough” safety Stepping back a decade or so, industrial sites believed they already had safety covered. If a site had clear signage, well-documented procedures, and a few audible alarms, it was considered well managed. The emphasis was on training and awareness, making sure every operator understood the risks and followed the rules. But awareness isn’t the same as assurance. Even the most diligent workers experience fatigue and lapses in concentration, and the more crowded and noisy a site becomes, the harder it is to maintain perfect vigilance. Alarms blur into background noise. Mirrors get obscured. Corners stay blind. Despite its best intentions to innovate, the industry left much of the safety burden firmly with the people at the controls, and that’s a heavy weight to carry. This “old school” mindset made the industry slow to accept new approaches. Every additional system was seen as an intrusion rather than an improvement – another alert, another screen, another distraction, and more for operators to keep track of. The irony is that many early technologies reinforced that fear by adding noise without adding certainty, which may even make sites less safe. Operators quickly learned to tune out devices that constantly triggered false alerts, and adoption slowed and even regressed. Safety culture, in many ways, had been built around the idea that risk was inevitable and that accidents could be reduced, but never fully prevented. What was missing was a new generation of technology that could quietly extend human awareness without demanding constant attention. Trust and technology  Trust is the make-or-break factor when it comes to safety technology. When a system triggers false alarms or misses genuine hazards, it only has to happen a few times before it gets written off and ignored. That has been the pattern for much of the past decade – bursts of enthusiasm followed by frustration and, eventually, abandonment. Pedestrian detection needed a way to see the environment the same way humans do, in three dimensions, in real time, and without dependency on perfect lighting or connectivity. It wasn’t until stereoscopic vision and edge-based AI matured that this became possible. Only then could detection systems move from lab demonstrations to something capable of earning trust in the mud, heat, and noise of everyday operations. The only thing that’s changed is that the technology has caught up and is now able to reach that high bar for trust. The new generation of pedestrian detection systems runs on the edge, not in the cloud, which means decisions can be made instantly, without waiting on servers that can be hundreds of miles away. AI models work directly on-device through industrial-grade neural processing units, allowing systems to detect, classify, and respond in fractions of a second. Combined with stereoscopic vision, these systems can see the world in detail, measuring distance, movement, and human form with the same kind of spatial awareness an operator has. It’s this combination of edge-based AI and stereoscopic precision that has finally bridged the gap between promise and delivery. The design of such systems is just as important as the technology built into them. Pedestrian detection technology has matured into something built for industrial reality – sealed and passively cooled to survive heat, vibration, dust, and rain. The AI models behind these systems are trained on millions of hours of real industrial footage, even annotated by engineers who understand what a forklift looks like in low light or how visibility changes in fog. That “human-in-the-loop” approach gives the AI fine-grained accuracy, distinguishing people from objects without a false positive in sight. And unlike older systems that constantly shouted for attention, modern designs stay silent until it matters, using clear visual and voice cues that fit naturally into the operator’s workflow. Pedestrian detection used to be a technology that demanded constant attention. Now, that attention is earned. Instead of being just another safety layer or something else to keep track of, it’s a built-in co-pilot with complete spatial awareness that only triggers alerts when it really matters. That builds trust, and that trust saves lives.

Next-generation detection technology and human-first design are turning safety into a performance advantage, giving operators greater confidence and improving workflow efficiency. It may sound like an obvious question to ask, but what is safety exactly? For the longest time, industrial leaders have treated safety as something to prove rather than something to use. Most industrial environments still operate on the assumption that compliance is a regulatory exercise. They document the training, tick the box, and keep the auditors happy. But when you spend enough time on factory floors, distribution centers, mines, and yards, you see the real story. People are not unsafe because they don’t know the rules; they’re unsafe because the environments around them are dynamic, noisy, and full of variables they can’t always anticipate. The companies that are pulling ahead now are the ones recognizing that safety isn’t just a bar to pass. When it’s built intelligently into daily operations, it becomes a way to stabilize the entire workforce and optimize productivity. But before that can happen, a simple truth must be acknowledged. Operators do better work when they feel their environment is working with them, not against them. The moment safety stops being a series of interruptions and starts becoming a source of confidence, everything changes – cycle times, spatial awareness, operator focus, even the speed at which equipment can be safely run. Leaders are beginning to understand that safety, when designed as a strategic enabler, reduces the hesitations and compensations that slowly eat away at productivity. It opens the door to cultural change, operational consistency, and a workplace where people can focus fully on their craft. The trust dividend I’ve seen it countless times. When operators know they have support that reacts faster than they ever could, their entire posture on the job changes. Most incidents don’t happen because someone was reckless; they happen because humans can only track so many moving parts at once. A well-designed detection system fills those perceptual gaps without second-guessing the operator’s skill. It becomes a silent partner, extending its awareness into blind spots, behind racks, around corners, and across constantly shifting pedestrian traffic. That frees operators from the mental overhead of constantly compensating for uncertainty. They can commit to their maneuvers with clarity instead of constantly bracing for a surprise or worrying that they’ve taken their eye off something. The knock-on effect is huge because when operators trust the system, they move with greater precision and fewer hesitations. They waste less time inching around blind spots or second-checking pedestrian zones. In environments where accuracy is high and false positives are rare, we’ve seen teams run equipment at the speed it was designed for, not at the speed they feel forced to adopt out of caution. The confidence comes from knowing the system is watching over them, not watching them – a subtle but important distinction that matters more than most safety vendors realize. The technology supports the operator’s judgement instead of undermining it, and that trust becomes a performance advantage in its own right. Next generation safety tech The reason safety systems are finally becoming true enablers (and not just compliance hardware bolted onto a machine) is that the underlying technology has caught up with the complexity of industrial environments. Earlier systems struggled because they were built on compromises. Monocular cameras could recognize shapes but couldn’t reliably judge depth or separation. Thermal imaging promised visibility through dust or steam but was easily confused by heat sources, reflections, or environmental interference. Beacon-based approaches put the burden on people to remember tags, keep batteries charged, or move in rigidly defined patterns. Each of these solutions added friction, noise, or failure points, and operators learned quickly that they couldn’t rely on them when conditions got difficult. The latest generation takes a completely different approach: true three-dimensional perception and real-time decision-making at the edge. Stereoscopic vision paired with dedicated NPUs means the system doesn’t guess at distance – it actually measures it, in millimeters, continuously. Inference happens on-device in milliseconds, so there’s no dependency on networks, cloud latency, or environmental variability. And because the models are trained specifically for pedestrian detection rather than broad object classification, they’re selective by design. They focus on the single signal that matters most: a human being in harm’s way. That precision, combined with “ruggedized” hardware built for vibration, shock, dust, and temperature extremes, is what finally makes these systems dependable in the environments where they can have the most impact. Human-first interfaces Most legacy safety systems assume that human attention is an infinite resource. They rely on loud alarms, intrusive screens, or constant notifications that pull operators out of the task at hand. Over time, that noise trains people to ignore the very signals meant to protect them. The newest safety platforms work because they’re designed around how operators actually perceive their environment. Directional LED cues mapped to proximity and movement allow workers to interpret risk through peripheral vision, the same way they read brake lights or forklift mast lights subconsciously. The signal is immediate, precise, and doesn’t demand a shift of focus. In other words, it guides action without interrupting it. This human-first design philosophy also tackles the biggest historical barrier to adoption – the “boy who cried wolf” effect or alert fatigue. By reducing false positives through more accurate detection and tighter algorithms, the system only speaks up when there is something that genuinely needs attention. That’s why operators accept it. It’s not a constant critic looking over their shoulder. Instead, it’s a calm, reliable companion that steps in only when risk is present. Over time, it blends into the background like any other tool. It complements human judgment, reinforcing awareness in a way that becomes part of the natural flow of work rather than an external layer being clumsily pushed on top of it. When safety systems are built to be fast, accurate, and intuitive, they become part of how high-performing operations run. Leaders who adopt intelligent detection early often see the benefits compound in the form of fewer near misses, smoother traffic flow, greater operator confidence, and a culture where people trust the tools around them. Instead of slowing work down, safety becomes the mechanism that keeps it predictable. It reduces liability, stabilizes planning, and gives frontline teams the confidence to operate equipment at its fullest capability. Most importantly, it reframes compliance from a target that needs to be hit to an operational baseline that can propel businesses forward and empower those with their boots on the ground.

Every year, the World Day of Remembrance for Road Traffic Victims invites the world to pause and reflect on the lives lost and the families changed forever by preventable accidents. While much of the focus falls on public highways, the same dangers persist in industrial work zones, where people and heavy vehicles still operate side by side. According to the US Bureau of Transportation data, 898 people lost their lives in work zones in 2023, including 240 fatalities caused by vehicle strikes. These incidents represent a pattern of risk that continues to play out on factory floors, in distribution warehouses, and on construction sites every day. We honored these victims by remembering them at the weekend, but we should also do everything in our power to protect those who continue to work in harm’s way.  Industrial safety has always been defined by hindsight. Incidents prompted investigations, investigations led to retraining, and new procedures emerged only after something had gone wrong. But the hyperconnected, data-rich environment we now inhabit is opening the door to foresight. Across industries, advances in AI and machine vision are reshaping the way sites handle potential collisions. The concept of AI-based pedestrian detection isn’t new, but until recently the technology was prone to misreadings and false alarms that for many workers ended up being more of a hindrance than a help when it came to safety and productivity. Newer iterations of that technology can detect pedestrians accurately, even in busy, low-visibility environments filled with glare, dust, or steam. Using stereoscopic vision and edge-based processing, they can judge depth and distance with human-like precision, ensuring that what’s detected as a person actually is a person, not a traffic cone, a shadow, or a reflection.  This level of reliability is rebuilding trust in safety technology. Instead of operators being overwhelmed by false alarms, they can trust the system to raise the flag only when there is legitimate risk of an incident occurring. When combined with telemetry and analytics, the data gathered from every one of these detections becomes another layer of insight, allowing the system to anticipate patterns, near misses, and operational risks before they escalate. Hindsight is 20/20 The prevailing logic of industrial safety is grounded in reaction. Most safety measures, such as training programs, signage, and process reviews, are introduced only after a near miss or a serious incident has already taken place. It assumes that identifying what went wrong once is enough to prevent it from happening again. But in industrial environments where people and machines interact, often in dusty, low-visibility conditions, every single variable matters – lighting conditions, operator fatigue, shifting terrain, the difference between loaded and unloaded vehicle weight. Even the most rigorous safety protocols can be undone by a moment of operator distraction or a blind spot no one anticipated. To be clear, operators themselves aren’t to blame for these incidents. In many cases, they are overwhelmed by signs, alerts, screens, and flashing lights – not to mention the intensity of the environment itself. The problem is that, until now, safety protocols have simply depended too much on “the human in the room,” mounting pressure on them in an already stressful work setting. False alarms only add to that pressure, leading to frustration when work is constantly interrupted.  But the real problem with hindsight is that it can’t account for what it never actually sees. Near misses go unreported, risky behaviors become reinforced, and valuable lessons are lost in the gaps between shifts or sites. Predictive safety turns that cycle on its head. By collecting and analyzing data continuously, such as on vehicle movements, proximity alerts, and operator response times, AI-enabled systems make it possible to see the invisible precursors to an incident. Instead of reacting to a collision, they reveal the moments that could have led to one, giving organizations the chance to intervene early and change outcomes in real time. Human-like machine vision Just like humans, predictive safety in AI begins with vision – machines that can see, interpret, and respond to the world around them in real time. The latest generation of AI-driven detection systems combines stereoscopic cameras with edge-based neural processing, enabling equipment to perceive depth and distance the way a human eye would. Unlike earlier monocular or thermal systems, which struggled with glare, dust, or reflective surfaces, these advanced vision systems maintain clarity in almost any condition. They can distinguish a person walking through a haze of exhaust from the background noise of moving machinery, or identify a worker partially obscured by a load or barrier. At the heart of this capability is the neural processing unit (NPU) embedded directly within the device. Processing occurs on the edge, milliseconds after a frame is captured, rather than being sent to the cloud for interpretation. This on-device processing makes a real difference, particularly in environments where even a half-second delay can mean the difference between a near miss and a fatality. The models powering these systems are trained on millions of hours of real-world industrial footage, often selected and annotated by workers in the field rather than dreamed up in a lab. As a result, they’ve learned to recognize human shapes through dust clouds, differentiate a reflective vest from a warning cone, and ignore the visual noise that would trigger false alerts in less mature systems. This level of environmental awareness is rebuilding trust in a technology that was once written off for being too inaccurate and raising too many false flags. And what once allowed for a single intervention is now giving way to a broader feedback loop that helps sites understand why risks emerge in the first place. As the world pauses to remember those lost to preventable vehicle-related incidents each November, it’s also a moment to look ahead to a future where technology helps ensure that such incidents never happen again. 

Advanced safety systems are meant to prevent accidents on construction sites — but when misapplied or overloaded with false alarms, they can dull worker awareness and create new hazards. Busy constructions sites are a gauntlet. In any given shift, workers may have to navigate between excavators swinging loads, delivery trucks reversing into tight spaces and forklifts moving heavy pallet loads back and forth. In these high stakes environments, safety systems are deployed with the very best of intentions – preventing collisions, protecting pedestrians and keeping projects firmly on track. But even the most advanced safety features can become part of the problem if they’re misunderstood, misapplied or overcompensating for a lack of accuracy with frequent false alarms. A warning that arrives too late, or an alert that sounds too often for the wrong reasons, can dull a worker’s instincts rather than sharpen them. The result is a dangerous paradox, where technology designed to make construction safer can, under the wrong conditions, introduce new points of failure risk. According to the US Bureau of Labor Statistics, in 2023 there were 5,283 fatal work injuries across all US industries, of which 1,075 occurred in construction. That means about one in five workplace deaths happened in the construction sector, with “struck-by” and “caught-in/between” incidents ranking among the deadliest hazards. Many of these events occurred in settings where safety protocols were in place, but where human factors – distraction, over-familiarity or a lack of trust in safety technology – tipped the balance. On the ground, this translates into a reality that many construction managers now quietly acknowledge: no matter how sophisticated the systems are, there is no substitute for situational awareness, consistent operator engagement and technology designed with the real-world messiness of a construction site in mind. In mining, a very similar environment plagued by many of the same incidents, a university-backed research paper revealed that constant exposure to audible alerts was one of the main contributors to mental fatigue. In some of these cases, response times slowed by up to 20 percent. As unusual as it might sound, simply adding more alerts and more layers of safety isn’t the answer. We need to look at how those alerts and layers operate and ensure they’re supporting workers, rather than burdening them. The ‘Smart’ Warehouse Problem The construction industry has been quick to borrow digital safety concepts from other industrial settings, particularly “smart” warehouses where automation, sensors and tracking systems have become standard. On paper, these tools promise a safer, more controlled environment, but while these systems can work in the regimented and repetitive workflows of a warehouse, they can falter on the more unpredictable construction site. Building projects are constantly changing, with shifting layouts, temporary access routes, and equipment moving between zones, creating blind spots that static or overly rigid safety systems fail to cover. The danger lies in the false sense of security such systems can create. Site managers and operators may assume that a sensor network or geofenced zone is catching every risk, when those systems may only be monitoring the conditions, they were programmed to anticipate. A proximity sensor that works flawlessly in a flat, indoor environment may misinterpret scaffolding, machinery or debris as a hazard or fail to detect a worker partially obscured by materials. Over time, this mismatch between perceived and actual coverage can erode vigilance or trust, leaving workers and supervisors exposed. Outdated Safety Protocols Many construction sites still operate under safety protocols that were designed decades ago, long before the advent of real-time hazard reporting, wearable sensors or AI-driven monitoring systems. While the fundamentals, such as lockout/tagout procedures and equipment spotters, remain essential, they often fail to address the pace and complexity of modern sites. A job site today may involve dozens of subcontractors, overlapping work zones and heavy machinery working alongside foot traffic in tight spaces. Without up-to-date protocols that reflect these realities, there’s a risk that safety plans will become little more than paperwork. Digitizing hazard reporting, sequencing activities more intelligently, and linking safety plans directly to live operational data can dramatically improve their effectiveness. But on many sites, reporting still happens at the end of a shift, meaning hazards go unaddressed for hours or even days. Similarly, generic safety checklists often fail to capture the unique risk profile of each project phase, leaving workers to make judgment calls without clear, site-specific guidance. When Alarms Become White Noise Safety alerts are meant to be an unmistakable signal that something is dangerously wrong. But if systems sound too often for minor or non-existent issues, they become white noise – ignored at best and distractions at worst. Over time, operators learn to tune out these false positives, treating them as an annoyance rather than a prompt for action. It’s not that these systems are poorly configured, it’s that they lack the precision to be able only raise the alarm when there is a real and imminent threat to life. But technology like machine vision and AI-based detection have come on leaps and bounds, virtually eliminating this problem for those ready to implement it. Why Smart Tech Needs Dumb Interfaces While AI-powered monitoring can perform extraordinary feats in the background, from distinguishing human movement from machine motion to predicting collision trajectories, the way those insights are delivered to workers matters just as much as the accuracy of the data. A well-trained model loses its value if its alerts are buried or require an operator to interpret multiple data points before acting. In the seconds it takes to decipher a complex interface, a hazard can already have turned into an incident. The most reliable systems remove ambiguity entirely. Instead of demanding a worker’s attention with a flood of visual data, they use clear cues – a flashing LED that can be seen from any angle, a distinctive audio signal, a spoken alert that names the hazard. On a busy site where noise is constant, lines of sight are often blocked, and attention is constantly divided, these more clear alerts can cut through the chaos more effectively than the most advanced display. Simplicity isn’t a compromise here – it’s potentially life-saving. Less is More If construction safety is to keep pace with the scale and speed of modern projects, the goal shouldn’t be to add more alarms, more dashboards or more layers of protocol. The goal should always be to create systems that workers instinctively trust and act on. Every alert and process should carry the weight of credibility, so that when it activates there’s no doubt in anybody’s mind that it matters. Stop building safety systems for safety’s sake and start building them for the specific environments and personnel they’re meant to protect.

It’s no secret that Canada’s mining industry is one of the largest in the world, producing more than 60 different metals and minerals including potash, uranium, aluminum and nickel. As of 2025, the sector accounts for roughly 700,000 jobs and more than a fifth of the country’s exports. But it’s also one of the riskiest industries, with a fatal injury rate six times that of all other private industries. Machinery and transportation equipment are among the leading causes of both fatal and non-fatal injuries, with companies potentially facing hundreds of thousands of dollars in claims and payouts. Any impact on the safety and wellbeing of those working in mining or mining-adjacent sectors is a tragedy, particularly when such incidents can be avoided, and in recent years the number of injuries and fatalities has fallen due to increased regulation in the sector. But regulation is only the start. With innovations in artificial intelligence (AI) and embedded technology, more can be done. The next challenge is making that innovation practical for the people who rely on it. Without thoughtful design, even advanced technology can become a distraction rather than protection. Too many systems work against workers rather than for them, sounding false alarms or disrupting their workflow with repetitive sirens and buzzers that erode their concentration. According to one academic research paper that focused exclusively on the mining sector, consistent exposure to repetitive audible alerts is one of the primary contributors to mental fatigue. So, at what point do these safety systems begin to undermine safety itself? And at what point does ‘the boy who cried wolf’ – in this case, countless false alerts – start to get taken less seriously? The alarm that cried wolf Let’s make one thing abundantly clear – this isn’t about blaming workers for lapses in concentration or choosing to ignore alarms. In mining, false positives are everywhere: a cone mistaken for a person, a shadow across uneven ground, or a mechanical arm shifting position. Each of these can trigger alarms designed to jolt an operator into action. But when those alerts happen dozens of times an hour, they lose all meaning. In an industry where seconds can be the difference between a close call and catastrophe, that erosion of trust and urgency is a risk in and of itself. This is why many miners end up silencing alerts altogether or switching off sensors. Not out of carelessness, but because they have a job to do. In already stimulus-heavy environments filled with vibration, radio chatter, and visual clutter, an unreliable system quickly becomes more of a hindrance than a help. The responsibility doesn’t lie with workers who disengage. It actually lies with safety technologies that fail to distinguish between nuisance and necessity. Without precision, alarms are little more than background noise, and once trust is gone, regaining it is almost impossible. Outpaced protocols For all the digital transformation sweeping the mining sector, many safety protocols remain rooted reactive standards. Paper checklists, generic proximity rules, and rigid zone delineations are still common practice, often treated as a box-ticking exercise rather than a living layer of protection. These approaches falter in environments where heavy mobile equipment moves unpredictably, conditions change by the minute, and the lines between ‘safe’ and ‘unsafe’ zones blur constantly. Struck-by and caught-in / between accidents continue to be leading causes of fatalities in mining, with haul trucks, loaders, and light vehicles representing some of the most persistent dangers. Too often, the underlying belief is that installed technology will ‘catch everything,’ creating complacency in protocols that no longer reflect the realities of modern operations. This gap becomes most visible in incident investigations, where outdated procedures collide with outdated tools. A proximity system designed for a warehouse floor struggles on a steep, rutted ramp. A checklist signed at the start of a shift doesn’t account for dynamic pedestrian movement throughout the day. And a detection model calibrated to flag any moving object will inevitably drown operators in false alerts. The problem often overlooked is that the safety processes put in place are simply mismatched to the environment. When rules, training, and technology aren’t designed for the realities of high-risk mining conditions, they create vulnerability gaps rather than closing them. So, if modernization is long overdue, how should it look? Complex technology, simple operation Operators are already juggling multiple screens, radios, gauges, and controls, and the last thing they need is another interface demanding constant attention. Not all risks are the same, and people are a company’s most valuable asset. Many safety systems are overly complex, flooding operators with constant alerts. Instead, the focus should be on practical solutions that target the most serious hazards and support workers in staying safe and effective. If an alarm triggers, it triggers for a reason – a light that flashes when a pedestrian is nearby, or a voice prompt that cuts through noise only when it truly matters. Operators don’t need more sophisticated interfaces; they just need simple signals that get it right. Take stereoscopic machine vision or edge-based AI as an example. The technology behind it is cutting-edge. It analyzes depth, posture, and movement patterns in milliseconds, and is able to distinguish a human from another object with incredible accuracy – far more than a basic proximity sensor. But the output is deliberately stripped down. Instead of overloading operators with endless data points, it stays silent until there’s an immediate collision risk, then delivers a single, unmistakable cue. This simplified interface is what makes it usable in the chaos of mining. Workers don’t have to interpret a busy screen or sift through alerts; they just need to know when to act. In practice, the systems that win trust are the ones that keep their intelligence hidden in the background, surfacing only when lives are on the line.

Speedshield’s new Optix platform enhances AiVA’s pedestrian detection with real-time analytics for access equipment safety. Speedshield has expanded its AiVA safety ecosystem with the release of Optix, a digital platform designed to improve visibility and predictive safety for operators, fleet managers and site supervisors. Optix connects every AiVA-equipped asset to a centralized analytics dashboard, providing real-time data on equipment movement, pedestrian detection events and operator activity. The system converts this information into visual insights that can help identify safety risks and guide corrective actions before incidents occur. “Optix gives our customers the visibility they’ve been asking for,” said Neeti Kulhar, product manager at Speedshield. “Every AiVA unit already captures a wealth of contextual data, such as distances, detection events and equipment state. Optix takes that information and turns it into a clear, interactive picture of what’s happening on the ground, allowing managers to pinpoint risk areas, validate safety interventions and continuously improve for better safety outcomes.” The Optix platform features a critical events dashboard and analytics interface that displays near-miss patterns, time-based trends and environmental factors contributing to risk. For organizations managing multiple sites, the platform also provides GPS tracking, equipment transfer tools and video playback of event data. The launch aligns with industry-wide efforts to reduce accidents involving mobile and lifting equipment. According to U.S. reports from 2020 to 2024, workplace injuries involving heavy machinery continue to result in significant downtime, averaging 80 lost workdays per incident. “We’ve known for some time that industrial safety doesn’t stop at detection,” Kulhar said. “With Optix, we’re helping customers move from awareness to understanding. We want to empower both teams on the ground and those in the office to make smarter decisions, reduce false alarms and ultimately prevent the kinds of critical events that cost lives and livelihoods.” Optix will be rolled out to Speedshield customers beginning in October, with general availability set for November 2025.

Safety is a moving target in the construction industry. Roughly 100 years ago, safety simply wasn’t a priority in the construction industry—but all of that began to change in the 1970s when OSHA (Occupational Safety and Health Admin.) entered the equation and businesses quickly began to realize an unsafe jobsite could potentially cost a lot of money. Worker deaths in America are down from about 38 worker deaths a day in 1970 to 15 a day in 2019—so some progress, but there is still work to be done. But one death is still one too many. In the past decade or so, we have seen a new wave emerge as it relates to safety in construction. The rise of new technologies brings new opportunities. The Rise of Technologies The evolution of safety technology in the construction industry looks a little like this: handwritten safety forms and filing cabinets to digital data collection systems and checklist. The next wave will most certainly include AI (artificial intelligence). Much like we are hearing that AI will aid in curing cancer, AI will most likely come to the aid to help prevent construction deaths on the jobsite. The value here is teams can automate safety tasks, do realtime incident reporting, complete digital checklists, and quickly communicate safety concerns. Teams can also use technology for vehicles and equipment to monitor incidents related to machinery. Here’s an example: Speedshield offers Optix, which is a cloud-based digital platform that gives users a view of every AiVA-equipped asset. The platform’s analytics present near-miss data with contextual insights and visualizations, highlighting not only the frequency of incidents, but the conditions in which they occur, such as problem vehicles, times of day, or operator activity levels. While this is only one instance there are a host of other emerging technologies that demonstrate how AI is rising to the rescue when it comes to safety in the construction. But there are still many challenges the industry will face. Challenges Still Lie Ahead Many workers still don’t believe businesses value safety as a matter of great importance. A recent report from Brady found 57% of employees across all industries believe their company prioritizes profits over safety. More than half lack full trust in leadership, 61% say their employers are unprepared for an active shooter, and one in three feel unsafe due to coworkers. The truth is most workers don’t feel safe at work—in any industry, and I would suspect the numbers are probably even higher when we look specifically at construction. Safety is a key value for many workers and often they want to know that it is a core value for their employer as well. This is why embedding safety into the fabric of the culture of a construction company is so critical. What Comes Next What steps can we then take to improve safety across the company, attract more workers, and ensure everyone gets home safely to their families every night? It starts with culture, and that culture often begins at the top. From there, safety must be embedded into all layers of the culture to thrive in the construction industry. Key to this is trust. Safety programs and training are also essential. These have been central to the construction industry for decades and they are beginning to pay off. OSHA suggests for every dollar spent on safety programs, construction companies save about $4 to $6. Start training early and make sure the programs are ongoing, because as we know processes, technologies, and equipment are constantly changing. Leverage technology to the fullest. As I mentioned earlier, technology is evolving rapidly. There is a huge opportunity to use the new technology to create a safer jobsite. From PPE (personal protective equipment), to mobile technology, to AI, there is so much to explore these days. Without a clear safety mission, a company risks more than compliance—it risks losing its talent because employees feel sidelines, trust erodes, and performance weakens. Employees cannot thrive in an environment ruled by fear. When safety is a priority, people thrive, feel protected, and empowered. How can we continue to ensure safety in the construction industry? What ways are you shining a light on safety?

As industries such as construction and mining strive to prevent costly on-site incidents and strengthen operator awareness, Speedshield – a global industrial connectivity and safety solutions provider – is expanding its AI-powered ecosystem with the launch of Optix, a cloud-based digital platform designed to give operators, fleet managers, and safety leaders a 360-degree view of every AiVA-equipped asset. Optix serves as the digital command center for AiVA, Speedshield’s advanced pedestrian detection system, translating millions of real-time data points into actionable intelligence. From tracking near misses and high-risk time periods to identifying trends in operator behaviour, the platform enables faster, data-driven interventions that can help prevent accidents before they occur. Optix will include features such as a critical events dashboard, which captures critical events and near-miss insights, as well as a new analytics interface, and app guest access for quick demonstrations and third-party installations. “Optix gives our customers the visibility they’ve been asking for,” commented Neeti Kulhar, product manager, Speedshield. “Every AiVA unit already captures a wealth of contextual data, such as distances, detection events, and equipment state. Optix takes that information and turns it into a clear, interactive picture of what’s happening on the ground, allowing managers to pinpoint risk areas, validate safety interventions, and continuously improve for better safety outcomes.” The platform’s analytics present near-miss data with contextual insights and visualizations, highlighting not only the frequency of incidents but the conditions in which they occur, such as problem vehicles, times of day, or operator activity levels. For enterprise and multi-site customers, company and site-level management tools enable seamless user access control, equipment transfers, GPS tracking, and on-demand event video playback. By linking AiVA’s stereoscopic vision and real-time detection capabilities with centralized, cloud-based analytics, Optix closes the loop between detection, documentation, and decision-making, transforming safety from a reactive process into a predictive data-driven discipline. “We’ve known for some time that industrial safety doesn’t stop at detection,” Kulhar added. “With Optix, we’re helping customers move from awareness to understanding. We want to empower both teams on the ground and those in the office to make smarter decisions, reduce false alarms, and ultimately prevent the kinds of critical events that cost lives and livelihoods.” Optix will be rolled out to all Speedshield customers beginning this month, with general availability, including in Canada, scheduled for November.

In the fast-paced and often hazardous environments of construction, mining, and logistics, preventing accidents before they occur has become the holy grail of safety management. Speedshield Technologies, a recognised global leader in industrial connectivity and safety innovation, is taking a bold step in that direction with the launch of its new digital platform, Optix. This cloud-based command hub integrates seamlessly with AiVA, the company’s advanced AI-powered pedestrian detection system, transforming streams of raw data into real-time, actionable safety insights. Optix acts as the digital nerve centre for AiVA-equipped assets, giving fleet managers, site supervisors, and safety officers a live panoramic view of what’s happening across their operations. Through its smart analytics, Optix not only identifies near misses and high-risk periods but also detects behavioural trends and environmental factors that may heighten risk. The platform’s ultimate goal is simple yet transformative: to shift industrial safety from a reactive stance to a predictive, data-driven discipline. Turning data into foresight Speedshield’s Product Manager, Neeti Kulhar, described Optix as a direct response to customer demand for deeper visibility and proactive tools: “Optix gives our customers the visibility they’ve been asking for. Every AiVA unit already captures a wealth of contextual data, such as distances, detection events, and equipment state. Optix takes that information and turns it into a clear, interactive picture of what’s happening on the ground, allowing managers to pinpoint risk areas, validate safety interventions, and continuously improve for better safety outcomes.” This integration of AI-driven sensing with intuitive data visualisation allows users to anticipate and address risks before they escalate. Optix’s Critical Events Dashboard consolidates near-miss events, equipment status, and contextual conditions into a central interface. Users can quickly identify when and where risks peak, whether due to specific vehicles, certain operators, or environmental factors like poor visibility or congested zones. Deep analytics and enterprise scalability At its core, Optix is built to serve both single-site operations and large-scale enterprise customers. The system’s analytics not only display near-miss frequencies but also highlight contextual insights, pinpointing the root causes behind risky situations. For companies managing multiple sites, Optix offers advanced tools for cross-site management, user permissions, and asset transfers. Key features include: Critical Events Dashboard: Captures and categorises near misses, providing detailed analytics on conditions and timing. GPS Tracking: Allows real-time monitoring of AiVA-equipped vehicles and equipment. On-demand video playback: Enables instant review of recorded safety events for analysis and training. App guest access: Offers quick demonstrations or limited external access for third-party installations. The scalable architecture of Optix ensures that both small operators and global enterprises can benefit from the same depth of safety intelligence, tailored to their operational footprint. A growing need for proactive safety The timing of Speedshield’s Optix launch could not be more pressing. According to U.S. labour statistics, over 1.2 million workplace injury claims were filed between 2020 and 2024, with construction and manufacturing sectors among the most affected. Vehicle-related incidents, in particular, continue to dominate the list of workplace hazards, costing businesses an average of 80 lost workdays per case. These numbers highlight the urgent need for solutions that go beyond traditional safety measures. Optix bridges that gap by linking AiVA’s stereoscopic vision and on-board detection algorithms with a centralised cloud intelligence platform. This closed-loop approach ensures that every detection event contributes to a growing reservoir of insights, helping companies understand not only what happened but why it happened, and how to prevent it in future. Kulhar emphasised the company’s vision: “We’ve known for some time that industrial safety doesn’t stop at detection. With Optix, we’re helping customers move from awareness to understanding. We want to empower both teams on the ground and those in the office to make smarter decisions, reduce false alarms, and ultimately prevent the kinds of critical events that cost lives and livelihoods.” From awareness to anticipation By combining edge intelligence with cloud analytics, Optix introduces a new paradigm for safety management. Instead of waiting for accidents to trigger investigations, companies can now rely on predictive insights to pre-empt incidents. The platform’s advanced algorithms continuously analyse data patterns to flag emerging risks, enabling timely interventions. The ability to visualise high-risk zones and operator behaviours gives managers the confidence to refine safety protocols and provide targeted training. Moreover, because Optix centralises every data point, from detection events to video logs, it serves as a powerful tool for compliance documentation, insurance reporting, and internal auditing. Designed for real-world impact Speedshield’s approach to digital safety isn’t confined to laboratories or prototypes. Its technologies are already deployed in some of the most demanding environments across mining sites, construction zones, logistics depots, and manufacturing plants. The introduction of Optix simply amplifies that capability, creating a more connected and responsive ecosystem. Optix will be rolled out to existing Speedshield customers this month, with general availability scheduled for November 2025. Its integration-ready design also allows for smooth deployment across legacy AiVA systems, reducing downtime and accelerating adoption. A global commitment to safer operations Founded in Australia, Speedshield Technologies has built a strong global presence with subsidiaries including Speedshield Technologies LLC (USA). Its workforce spans engineering, software development, manufacturing, and customer support, with a shared mission to enhance industrial safety through technology. From AI-powered cameras and telemetry systems to speed control and fleet analytics, Speedshield’s portfolio reflects its relentless pursuit of innovation. The company also maintains robust research partnerships with universities and industry consortia, driving continuous development in machine vision, autonomous systems, and industrial AI. Looking ahead to a safer tomorrow Optix represents more than a product release; it signals a shift in how industrial safety will be managed in the years ahead. By turning detection data into predictive intelligence, Speedshield is helping companies make safety decisions that are not only reactive but also preventative and strategic. As global industries continue to digitise and automate, platforms like Optix will play an increasingly pivotal role in keeping people safe while maintaining productivity and efficiency. Through its AI-powered insights, Speedshield is redefining what it means to stay one step ahead of danger, making safety not just a priority but a built-in advantage.

Speedshield, a global leader in industrial connectivity and safety solutions, has expanded its AI ecosystem with Optix, a cloud-based digital platform that gives operators, fleet managers and safety leaders a 360-degree view of every AiVA-equipped asset. Speedshield launched a new online platform that helps construction and mining companies prevent workplace accidents by analyzing data from their safety cameras in real time. The system spots dangerous patterns and close calls, giving managers clear insights they can use to fix problems before someone gets hurt. Speedshield Technologies develops AI-powered safety cameras, pedestrian detection systems, speed control devices and telemetry-driven fleet management solutions for material handling, mining, construction, transportation and warehousing. Founded in Australia and operating internationally, including Speedshield Technologies LLC (USA), the company deploys its technologies through OEMs, dealers and enterprises and collaborates with universities and industry groups on research and development. Optix acts as the digital command center for AiVA, Speedshield’s pedestrian detection system, converting millions of live data points into actionable intelligence. The platform tracks near misses and high-risk time periods, identifies operator-behavior trends, and enables faster, data-driven interventions aimed at preventing accidents. Optix will include a critical events dashboard that captures critical events and near-miss insights, a new analytics interface, and app guest access for demonstrations and third-party installs. Neeti Kulhar, product manager at Speedshield, commented: "Optix gives our customers the visibility they’ve been asking for. Every AiVA unit already captures a wealth of contextual data, such as distances, detection events, and equipment state. Optix takes that information and turns it into a clear, interactive picture of what’s happening on the ground, allowing managers to pinpoint risk areas, validate safety interventions, and continuously improve for better safety outcomes.” Speedshield will roll out Optix to all customers beginning this month, with general availability set for November 2025.

As inventory grows and SKU counts increase, many warehouses feel pressure before they run out of space. The real challenge often shows up in the aisles, at the rack, and around staging areas where congestion slows operations. The right narrow aisle solution can increase storage density, enhance manneweuverability, and keep goods moving smoothly. Instead of expanding your footprint, many facilities can unlock capacity by rethinking equipment, racking, and traffic flow. At Papé Material Handling, this broader approach connects layout planning, operator-focused technology, lift trucks, racking, automation, and fleet management to keep warehouse operations running efficiently and safely. Safety and Productivity Go Hand in Hand With tighter spaces, control, visibility, training, and maintenance become even more important. In a narrow aisle environment, small inefficiencies can quickly lead to product damage or increase the risk of injury. That’s why productivity and safety need to be addressed together. Operator-assist technologies and warehouse solutions can help create a more controlled and confident working environment, while fleet management tools improve maintenance visibility, support compliance, and reduce avoidable costs over time. Papé Material Handling offers comprehensive warehouse safety tools matched with the right equipment, including advanced AI pedestrian detection, Advanced Dynamic Stability (ADS) for forklifts, and safety accessories like strobe lights and backup alarms. Why Narrow Aisle Solutions Matter in Modern Warehouses When space becomes limited, narrow aisle solutions play a bigger role in maintaining productivity. The biggest advantage of narrow aisle forklifts is how well they align equipment with layout. When designed correctly, warehouses can increase pallet positions, make better use of vertical space, and create more streamlined travel paths for operators In practice, narrow aisle strategies help warehouses: Increase storage capacity without adding square footage Improve maneuverability in tight spaces Enable faster, more consistent pallet handling Reduce wasted travel within the warehouse Those gains matter most in buildings where space is already under pressure and every aisle decision affects throughput. Signs It May Be Time to Upgrade Your Narrow Aisle Strategy Some common signs it may be time to adjust your approach include: Aisles feel congested during peak activity Operators struggle with lift height or maneuverability Available pallet positions are running low Rack contact or product damage is increasing The current fleet no longer aligns with storage needs Layout changes, new racking, or automation are already being considered A well-designed warehouse layout plays a key role in maximizing space and maintaining safety. Papé Material Handling offers complimentary Warehouse Planning Services to analyze your operation, recommend layout improvements, and support long-term efficiency and safety. Once you’re ready to refine your narrow aisle strategy, choosing the right equipment becomes critical.The key is matching the truck to the load, not just the aisle width. A narrow aisle strategy is most effective when equipment aligns with how materials are stored and moved within the facility. Reach Trucks: A Go-To Solution for High-Density Storage For many warehouse teams, reach trucks are a practical starting point for a narrow aisle strategy. They are built for tall racking, tighter aisles, and improved pallet placement and retrieval, making them a strong fit for high-density storage environments. Current reach truck offerings from Hyster and Yale focus on operator productivity, ergonomic design, and durability. This supports both day-to-day throughput and long-term uptime in demanding warehouse settings. Beyond Reach Trucks: When Specialized Equipment Makes More Sense Some operations need a solution that goes beyond a standard reach truck. Facilities handling long, bulky, or irregular materials often require a different kind of maneuverability. In these cases, multi-directional equipment can offer a clear advantage. Combilift multi-directional forklifts are designed to travel forward, backward, and sideways, allowing operators to move long loads through narrow aisles with greater control. This makes them well suited for handling materials like lumber, pipe, and other lengthy items while improving space utilization. Combilift units can be a strong fit for operations preparing for growth or looking to improve space utilization. Build a Smarter Warehouse With the Right Equipment Partner Narrow aisle equipment can help unlock more storage capacity and improve daily efficiency without expanding the building footprint. The best results come from pairing the right reach trucks or specialized forklifts with thoughtful layout planning, safety-focused technology, and strong fleet support. At Papé Material Handling, this broader approach connects equipment decisions with warehouse layout, storage systems, and overall facility optimization. With a focus on safety, damage reduction, maintenance visibility, and operating efficiency, the goal is to help operations make better use of tight spaces and build a smarter, more adaptable warehouse for the work ahead.

The Building Innovation Awards 2025 brought together the most influential minds in digital construction for an unforgettable night of celebration, innovation, and inspiration. Held at Birmingham’s National Conference Centre & Motorbike Museum alongside UK Construction Week, this year’s sold-out ceremony welcomed 450 leaders, innovators and pioneers from across the UK’s digital construction and built environment sectors. From digital transformation and modern methods of construction (MMC) to sustainability and AI-driven design, the evening showcased the groundbreaking technologies and collaborative approaches shaping the future of the UK’s built environment. Honouring digital construction excellence The Building Innovation Awards have become a benchmark for excellence in construction technology, digital engineering, and sustainable building practices. This year’s event was a true reflection of how far the industry has come, and where it’s heading next. The 2025 ceremony shone a spotlight on trailblazers across the spectrum of construction innovation: Digital disruptors pushing the boundaries of BIM and data-driven design. Offsite and modular construction pioneers redefining project delivery. Sustainability champions driving carbon reduction and circular economy practices. Tech innovators revolutionising workflows with AI, robotics, and automation. The Awards’ partnership with UK Construction Week added even more momentum, creating a unique platform that connected the nation’s construction technology community with live demonstrations, networking, and thought leadership across the week. Adding to the night’s success, the event also raised an impressive £4,103.68 for the Anthony Nolan Trust, reflecting the industry’s commitment to positive social impact alongside technical innovation. The digital construction leaders of 2025 The winners of the Building Innovation Awards 2025 represent the best and brightest in digital construction, from visionary startups to established industry giants. Their work exemplifies how technology, creativity, and collaboration are transforming the built environment. Category Winners: Best Energy Efficiency Innovation: Water Filled Glass Most Sustainable Building Project: Paradise SE11 – B&K Structures Most Innovative Build Process using MMC: Harcourt Technologies Ltd Best Use of Remote Monitoring Technology: VIS Systems Ltd Most Innovative Contech Startup: Invictus Robotics Best Use of Data on a Construction Project: Sir Robert McAlpine Best Use of Advanced Materials: B&K Structures Best Use of Visualisation Technology: Nemetschek dTwin Best Digital Transformation: 40 Charter Street – Revizto with Canary Wharf Group, KPF, AECOM, Disperse and Dome Consulting Best Carbon Reduction Innovation or Practice: Galliford Try, Manchester University, Cemex, Sika & Northumbrian Water Smart Building Project of the Year: Worship Square – HB Reavis UK Best Health & Safety Innovation: Speedshield Technologies Best Approach to Company Culture & Wellbeing: Premier Modular Best Asset Management Innovation: Kier Construction Limited Best Retrofit Innovation or Project: Retrofit Eaves Insulator – ARC Building Solutions Ltd Most Innovative Urban Regeneration Project: Bargate House, Southampton – Stelling Properties Most Innovative Affordable Housing Project: Grange Close – Harcourt Technologies Ltd Most Innovative Partnership: Amrize & Meta Best Use of Automation or AI: Robotiz3d Technology Ltd Professional Services Partner of the Year: Trowers & Hamlins Most Innovative SME: Biohm Most Innovative Supplier: AeroBarrier Most Innovative Contractor: HB Reavis Construction Most Innovative New Product (Hardware): Geberit FlowFit – Geberit Most Innovative New Product (Digital): Minoro – Grimshaw Digital Construction Team of the Year: One Creative Environments Ltd Best Technology Partner: Morta Technology Ltd Innovator of the Year 2025: Dr Matyas Gutai – Water Filled Glass Building Innovation of the Year 2025: Robotiz3d Technology Ltd Celebrating a connected and collaborative future As digital construction continues to evolve, the Building Innovation Awards 2025 underscored a critical message: innovation thrives through collaboration. The event demonstrated how data integration, digital twins, robotics, AI, and sustainable materials are converging to create smarter, greener, and more efficient buildings. The winners’ achievements reflect the UK construction industry’s rapid progress in embracing digital transformation, advancing sustainability, and redefining how projects are conceived, built, and maintained.

Murray Cox is principal engineer at Speedshield Technologies, where he seamlessly connects cutting-edge research with real-world industrial mobile equipment and applications. He is passionate about pushing the boundaries of AI-driven vision and spatial sensing to revolutionise workplace safety and operational efficiency across industries. When it comes to safety in warehouses and worksites, what could be more important than visibility? Cameras mounted on forklifts and other industrial vehicles have become the new standard, giving operators and managers a clearer line of sight into busy, often dust-filled environments.  But as anyone who has spent time on a warehouse floor knows, seeing isn’t always the same as understanding.  A camera can record what’s in front of a forklift, but it can’t always interpret what that means for the machine, its operator, or the people moving around it.  That’s why the next wave of “machine vision” isn’t about sharper images or higher resolutions. It’s actually about equipping machines with the intelligence to see things the way we do – with context and situational awareness.  By combining cameras with radar, LIDAR, temperature sensors, and accelerometers, the humble forklift is able to graduate from nuts-and-bolts machinery to an intelligent workplace companion that empowers operators to act with safety and confidence.  In many ways, this multi-sensory approach mirrors how humans navigate the world: sight is important, but we also rely on hearing, touch, and spatial awareness to make safe decisions.  The rise of multi-sensory safety systems Multi-sensory systems are already changing how vehicles interact with their surroundings. Radar and LIDAR, for instance, can detect objects and people even in poor visibility – conditions where cameras might struggle due to low light, glare, or dust.  Temperature sensors can provide early warning of overheating components or nearby fire risks, while accelerometers can sense changes in speed, tilt, or impact that may indicate instability. Together, these inputs create a web of awareness that exceeds anything a single lens can capture.  For operators, this means an extra layer of protection in high-risk situations. A forklift navigating a crowded aisle can now distinguish between a pedestrian stepping out from behind a pallet and a shadow cast by overhead lighting.  On a slippery surface, sensors can recognise traction loss and adjust behaviour before the operator even reacts. It also reduces the likelihood of false alarms – a major pain point in the industry that can cause endless distractions and sow mistrust in safety systems.  AI and edge processing: The brains behind the sensors Collecting data from multiple sensors is only half the challenge; making sense of it in real time is where the real breakthroughs lie. In a busy warehouse, milliseconds matter.  A forklift approaching a blind intersection can’t afford a delay while raw data is sent to the cloud and back for analysis.  That’s why the next generation of safety systems is leaning heavily on edge computing – processing information directly on the machine itself.  And artificial intelligence is the layer that brings this capability to life.  Models trained on millions of hours of operational footage and sensor data can help machines recognise complex patterns, from spotting signs of unsafe operator behaviour to predicting the likelihood of a collision.

Speedshield was demonstrating its AiVA pedestrian detection system, which can be retrofitted onto any vehicle to prevent accidents between people and machinery on the work site. With the ability to be fitted to everything from small plant up to mining machinery, the radar system alerts when pedestrians are in proximity and can even intervene to slow or stop the machine. “We apply this most often to forklifts, because they tend to operate in the busiest areas in terms of pedestrians and machinery working in close proximity to each other,” Speedshield integration support officer Scott Baker says.“From there, we’ve moved into earthmoving equipment, telehandlers, graders, wheel loaders and even container handlers. At the mining level we’ve worked with BHP where we covered all of their material handling equipment and drill rigs. We’re looking at some underground mining solutions for them as well.” Designed and built in Melbourne, a single camera provides 90-degree coverage, with a detection range of 12m. Alerts sound if a pedestrian is detected at the 6m and 3m mark. Additional cameras can be mounted to provide full 360-degree coverage. “One of the key features is the dual lens camera,” Speedshield business development manager Ashley Dobson says. “This means we can capture people in different stances. So, if they are crouched, or have had a fall, the dual lens camera is able to pick that up.” All of the data is recorded and accessible through a web platform to provide the business with insights into near miss incidents. “This means we can look at the stats of how many people encroach into a defined parameter and how often these offenses occur, which means further safety measures can be put in place,” Baker says. “And it isn’t just large companies that use this – we fitted one to a Bobcat being used by a landscaper who often works in confined areas constructing playgrounds. This gives an operator essentially a pair of eyes in the back of their head for that extra peace of mind."

Speedshield Technologies – a global provider of industrial connectivity and safety solutions – is accelerating its US expansion with the appointment of Michael Barnard as Vice President of Sales.   Barnard joins the company at a time of accelerating demand for AI-powered safety systems and brings more than a decade of experience in construction equipment, territory development, and customer relationship building.  In his new role, Barnard will oversee Speedshield Technologies’ go-to-market strategy across North America, with a focus on expanding adoption of the company’s flagship AiVA system beyond material handling and into sectors such as construction, mining, agriculture and forestry.   AiVA, Speedshield’s advanced pedestrian detection platform, uses stereoscopic vision and on-board AI to identify human forms in real time – even in low-light or high-risk operating conditions. Built for scalability and rapid deployment, the system is already in use across thousands of assets throughout major industrial fleets.   “What drew me to Speedshield was the mission. This is a technology that quite literally saves lives,” Barnard said in a news release.   “When you spend years working around heavy equipment, you understand how easily a split-second mistake or lapse in attention can lead to tragedy. And the high volume of false alarms in legacy systems erodes trust to the point where workers and operators become overwhelmed and unable to do their jobs safely and effectively.”  “We now have a system that can detect pedestrians with near-perfect accuracy, virtually eliminating the risk of false alarms,” Barnard said. “My goal is to make sure this technology gets into the hands of the people who need it most.” 

National Tradesmen Day, Sept. 19, serves as a reminder of the vital role tradespeople play in lifting, access and other industrial sectors. While machinery continues to evolve, workers remain central to safe and efficient operations. In a message marking the day, Terry J. Ryals, director at Speedshield, urged the industry to ensure safety technology enhances rather than undermines worker performance. When Safety Technology Becomes the Enemy National Tradesmen Day is a chance to recognize and celebrate the people who keep the wheels of industry turning. Those with dirty boots on the ground, those co-ordinating and overseeing projects, and those operating heavy equipment and complex machinery, usually in environments where there’s zero margin for error. Tradespeople are valuable because of the experience they bring to their roles day after day, but they also have an uncanny ability to adapt, improvise, and keep things moving safely and efficiently in challenging conditions. That combination of skill, knowledge, and human awareness is something no machine can replace. Yet, at the same time, the sheer scale and power of modern industrial equipment means that tradespeople are beginning to face levels of risk that can catch even the most practiced worker off-guard. There are more than 40,000 manufacturers of industrial machinery in the US alone, each doing what they can to minimize risk and keep tradespeople safe. Often, that means layering on more alert systems – buzzers, sirens, and flashing lights. And while technologies like pedestrian detection are fitted to these machines, they often flag so many false alerts that work begins to slow, and tradespeople lose trust in the very systems designed to keep them and their colleagues safe. Over the years we’ve seen ‘alert fatigue’ creep in, where tradespeople become so overwhelmed by the number of audible alerts and false alarms that it becomes almost impossible to maintain full concentration and situational awareness. The role of technologists like us is to listen closely to these challenges and create safety solutions that work with tradespeople rather than against them. Rather than layer on more alerts, we need to ensure that the alerts that do sound are timely and accurate. Technology should be used to take the heavy burden of vigilance away from workers rather than trying to catch them out – whether that’s through pedestrian detection, telemetry, or predictive maintenance that spots issues before they become hazards.  Tradespeople will remain central to everything from building infrastructure to keeping global logistics flowing. This National Tradesmen Day, it’s worth remembering that the future of industry depends not just on innovation in machines, but in the safety, wellbeing, and expertise of the people who operate them. Terry J Ryals, Director, Speedshield Ryals’ comments point to a key issue for the lifting industry: the risk of overloading workers with alarms and warnings that may desensitize them to real dangers. He stressed that the future of industrial safety lies in precision — providing timely, accurate alerts and using tools like telemetry and predictive maintenance to reduce hazards before they appear.

WINTERVILLE, N.C. – The cost of on-site incidents in the US involving heavy machinery is rising sharply. Between 2020 and 2024, US businesses recorded around 1.2 million workplace injury claims, with employees missing an average of 80 workdays per incident. Construction, manufacturing, and other high-risk sectors are among the hardest hit, with vehicle-related accidents accounting for the majority of claims.Against this backdrop, Speedshield Technologies – a global leader in industrial connectivity and safety solutions – is accelerating its US expansion with the appointment of Michael Barnard as Vice President of Sales. Barnard joins the company at a time of accelerating demand for AI-powered safety systems, and brings more than a decade of experience in construction equipment, territory development, and customer relationship building.In his new role, Barnard will oversee Speedshield Technologies’ go-to-market strategy across North America, with a focus on expanding adoption of the company’s flagship AiVA system beyond material handling and into sectors such as construction, mining, agriculture and forestry. AiVA, Speedshield’s advanced pedestrian detection platform, uses stereoscopic vision and on-board AI to identify human forms in real time – even in low-light or high-risk operating conditions. Built for scalability and rapid deployment, the system is already in use across thousands of assets throughout major industrial fleets.“What drew me to Speedshield was the mission. This is a technology that quite literally saves lives,” said Barnard. “When you spend years working around heavy equipment, you understand how easily a split-second mistake or lapse in attention can lead to tragedy. And the high volume of false alarms in legacy systems erodes trust to the point where workers and operators become overwhelmed and unable to do their jobs safely and effectively.”Barnard continued “We now have a system that can detect pedestrians with near-perfect accuracy, virtually eliminating the risk of false alarms. My goal is to make sure this technology gets into the hands of the people who need it most.”Barnard’s appointment reflects Speedshield Technologies’ growing commitment to the US market, where industrial safety remains a critical concern across sectors such as construction, mining, and logistics. From 2019 to 2023, construction recorded the highest fatality rate at 14.6 per 100,000 workers, followed by mining at 12.9, manufacturing at 9.3, and wholesale trade at 8.6. With workplace incidents involving heavy machinery still a leading cause of injury and fatality, Speedshield sees significant opportunity to deliver a more intelligent, less intrusive safety solution tailored to American worksites.Barnard joins Speedshield from H&E Equipment Services, where he was responsible for revitalizing underperforming sales territories across rural markets and growing a customer base from the ground up. He plans to apply the same relationship-driven approach at Speedshield, drawing on his extensive industry network and direct experience with the environments in which AiVA is designed to perform. Multiple adoptions by major construction companies are demonstrating exceptional performance results and strong interest across uses in other vertical applications.As the company looks to diversify its market presence, Barnard’s arrival signals a more confident push into sectors that have traditionally lagged in advanced safety technologies. “We’ve seen enormous success in material handling,” Barnard added. “Now we’re targeting environments where incident rates are even higher, and because AiVA can be retrofitted to existing equipment, it’s a low-cost, low-disruption way of bringing cutting-edge safety to existing fleets.”Commenting on the appointment, Speedshield [spokesperson] said: “Michael brings a deep understanding of the challenges faced on worksites and a rare ability to connect that understanding with practical solutions on the ground. His experience with machine equipment, his passion for safety, and his drive to build lasting partnerships make him the ideal person to lead our next phase of growth. We’re thrilled to welcome him to the team.”Barnard and his team are preparing for a busy slate of industry events, including the NSC Safety Congress & Expo in Denver this September and CONEXPO-CON/AGG in Las Vegas next March – two of the world’s largest gatherings of safety and construction professionals. At each, Speedshield Technologies will showcase AiVA’s real-time detection capabilities, including demonstrations of its low-light performance and ability to identify pedestrians even when prone or crouched – conditions in which traditional systems typically fail.“Once people see what AiVA can do, it speaks for itself, “Barnard concluded. “But we’ve got to get out there, show it in action, and make the case that safety systems don’t have to be disruptive or frustrating. They just have to work seamlessly as part of the environment.”

Mining is getting smarter. From autonomous haul trucks to real-time fleet management systems, digital transformation is reshaping how mine sites operate. But Mining is getting smarter. From autonomous haul trucks to real-time fleet management systems, digital transformation is reshaping how mine sites operate. But despite this wave of automation, some of the industry’s most serious safety risks remain stubbornly present. “Struck-by” and “caught-in/between” incidents continue to account for a significant share of mining injuries and fatalities, particularly those involving heavy mobile equipment. While new technologies and processes have raised the floor on safety, they haven’t eliminated blind spots altogether.  Lack of data or intelligence isn’t a problem, but applying it effectively remains a stubborn roadblock. We have alert systems, but they tend to overwhelm operators rather than support them. According to one university-backed research paper, consistent exposure to audible alerts is one of the primary contributors to mental fatigue in the industry, impacting miners’ performance and their ability to do their jobs safely. Where safety automation does exist, it’s often designed in a way that disrupts workers rather than support them, and technologies like video monitoring tend to be too primitive to cope with such a busy environment. All of these shortcomings conspire to allow risk to hide in plain sight, and a solution is long overdue.   The limits of traditional safety systems  Mining is such a unique environment that few traditional safety systems were designed to deal with the pace and pressure that come with it. Machine vision exists, but object detection tools are often so generic that they are unable to distinguish between a person and a piece of equipment with the reliability required in such fast-moving, high-risk zones. Meanwhile, alert systems tend to overcompensate, issuing frequent warnings that don’t always reflect real danger. Over time, this can train operators to dismiss or mute alerts altogether, creating a dangerous gap between what the system sees and what the worker perceives. This isn’t a worker problem, but a systemic one.   This “alert fatigue” is particularly acute in mining environments, where dust, vibration, poor lighting, and constantly shifting activity make precision more difficult to achieve. A well-intentioned alert that triggers needlessly, especially during peak work cycles, can break concentration, delay progress, or be seen as a nuisance. And when alerts are ignored or overridden, the entire safety net starts to unravel. Mining needs safety technology that reacts, but it also needs safety technology that understands the environment it’s working in.  Why visual intelligence needs simple, rugged design  In theory, AI can make split-second decisions with superhuman accuracy. Advances in machine vision can allow AI to distinguish between humans and other objects with overwhelming accuracy. But in mining, theory doesn’t count for much unless the system can survive the real world. That means hardware that holds up in dust-choked air, on vibrating machines, in low-light tunnels and open pits alike. It also means software that doesn’t rely on remote servers or constant connectivity. Decisions need to happen at the edge – on the vehicle, in the moment, and without latency or dependency on external infrastructure.  Equally important is how the system communicates with the operator. In a cab already filled with gauges, radios, and movement, a new screen or complex dashboard might seem helpful on the surface but could unintentionally become a hazard in and of itself. What works best in mining tends to be simple: clear visual cues like LED indicators, or voice alerts – used sparingly – that cut through background noise without overwhelming the operator. When systems stay quiet until something truly demands attention, workers are more likely to trust what they hear.  Lessons from the pit  AI safety systems are already being used across a growing number of mining operations, often as fully embedded tools on everything from underground loaders to light vehicles. But rather than rely on off-the-shelf object recognition models, which can easily mistake a shadow or a cone for a person, they’re trained specifically to detect pedestrians using stereoscopic vision and edge-based neural processing. That narrows the focus to what truly matters, making the system and any alerts it produces more impactful and trustworthy.   This is important, because false alerts are perhaps one of the biggest hazards of all. One false alert and workers will continue, but two or three false alerts in quick succession will lead most workers to power down the safety system. Again, it’s important to note that this isn’t about blaming workers themselves – it’s about designing technology and safety protocols that support them rather than hinder them.   In a mining environment, safety should never be the sole responsibility of operators and “boots on the ground” – it should be built into the working environment as standard. 

In high-risk industrial environments, safety technologies are often deployed with the best of intentions. They are designed to protect pedestrians near heavy equipment, reduce collisions, and support workplace EHS protocols. But a system that triggers alerts too frequently or inaccurately can steadily become its own kind of hazard. False positives, where an alarm is activated by inanimate objects, erratic sensor behaviour, or misunderstood movements, not only disrupt workflow – they erode trust between humans and the machines they interact with every single day.  And when trust in a safety system begins to break down, workers may begin to tune it out entirely. The result is a subtle but serious risk: over time, critical warnings lose their urgency, and near-misses become inevitabilities. A 2024 article published in the research journal Automation in Construction points out that reaction times to audible alerts got slower over time as operators became accustomed to them. In some cases, operators exposed to the same alarm repeatedly showed an 18 per cent increase in their reaction time, and they reported lower trust in alarms that triggered unnecessarily or without any clear relevance. To be clear, this isn’t carelessness on the part of operators. It’s simply human nature. In noisy, stimulus-rich worksites, operators are already managing sensory overload from machines, radios, environmental hazards, and task demands. When yet another system adds to that noise, especially one that often triggers inaccurately, it can push workers toward disengagement. Some may mute the alert. Others might cover the sensor. Most will simply learn to ignore it. And while it’s easy to write this off as negligence, the real issue is systemic. Safety systems that fail to prioritize accuracy and relevance unintentionally invite the very behaviours they were meant to prevent. Safety technology should support workers rather than hinder them. Blanket detection is not a blanket solution For years, proximity detection systems have operated on a simple premise: if something enters a defined zone, trigger an alert. While effective in theory, the approach in practice often produces a stream of alerts triggered by irrelevant stimuli – pallets being moved, shadows cast across a detection field, or harmless obstructions like cones or trolleys. These systems operate on binary logic: something is either in or out of bounds. But on a busy worksite, not everything that moves is a threat. The result is a flood of false positives that interrupt workflow, frustrate operators, and invite a “boy who cried wolf” effect where alarms are simply ignored. Because when every beep or flash demands equal attention, none of them feel urgent. That’s why modern safety thinking is shifting away from maximum sensitivity toward maximum specificity. Instead of detecting anything, new AI-powered systems are being engineered to detect the right thing, at the right time, and with the right level of urgency. Precision means being able to distinguish between a person and a post, or between someone walking past a machine and someone about to step into its path. Without that nuance, alerts become meaningless white noise, and it’s something the industry has been grappling with for decades. Specificity over sensitivity We need systems that go beyond simply detecting movement and instead interpret it. And thanks to breakthroughs in stereoscopic machine vision, real-time AI inference, and edge-based processing, that’s now a possibility, allowing systems to understand what’s in front of them with remarkable granularity. Stereoscopic vision allows the system to perceive depth, enabling it to distinguish between a human walking behind a forklift and a stack of boxes on the same plane. AI models trained on millions of hours of industrial footage can identify human forms through pose estimation, movement patterns, and body segmentation, which is crucial for environments where visibility is limited or occlusion is common. This technology can elevate equipment to being a contextual rationalizer rather than a mere detector. By calculating distance, direction, and velocity, a precision system can determine whether an interaction is likely to lead to a collision. More importantly, because these systems run on edge hardware, they don’t rely on external connectivity or cloud processing. Everything happens in real time, within milliseconds, which all count when operating around fast-moving equipment. The goal is to alert only when there’s an actual threat to human safety, not when a shadow passes or a machine pivots harmlessly. This is the difference between a safety system being a constant distraction or a safety system being a trusted layer of protection. Rebuilding trust between humans and machines The trust boundary has moved. The real measure of a safety system’s effectiveness isn’t whether or not it can trigger an alert, but whether or not it should. When systems cry wolf too often, workers become frustrated and fatigued and almost conditioned to ignore the noise. This creates a negative feedback loop where trust breaks down and safety systems are seen as a thorn in the side of productive workers. As an industry, this is where we currently stand. But the difference now is that we have the means to restore that trust, and it starts with technology and context. Designing systems that align with how humans operate and incorporating those systems into new and existing equipment. When alerts are rare, timely, and meaningful, they regain trust. And that trust between human and machine is the ultimate key to site safety. Read the full article online at OHS Canada.

In warehouses where people and machines operate in close quarters, pedestrian safety is a critical concern. At the recent PMH Forklift Safety event in Seattle, attendees witnessed firsthand how technology is stepping up to protect workers. One standout innovation was the Hyster Pedestrian Awareness Camera System, presented by TJ Ryals of Speedshield Technologies. This wireless forklift system represents a major leap forward in accident prevention with its smarter, more human-aware approach to pedestrian detection. Designed to retrofit easily into existing fleets and requiring only very limited training, the system is positioned to redefine warehouse safety standards throughout the industry. Beyond Object Detection: Smarter Vision for Safer Operations While previous safety systems have focused on detecting all nearby objects, the Pedestrian Awareness Camera System goes further. It’s purpose-built to recognize pedestrians specifically, ignoring inanimate obstacles to minimize false starts. It uses stereoscopic vision (with two lenses, mimicking human vision) combined with AI-trained modeling to detect people, even when they are partially obscured or crouching low. “We’ve trained the AI model to understand what a pedestrian is,” Ryals explains. “A hand’s connected to an arm, an arm’s connected to a body…We don’t have to see a full body to alert and let you know that a pedestrian is within proximity of the equipment.” Further, this ability to detect occluded figures—those not fully visible—is essential in fast-paced and dynamic environments like a busy warehouse where workers may be crouching, reaching, or moving between equipment. A Retrofittable Safety Upgrade for Mixed Fleets One of the biggest challenges of warehouse operations is the wide diversity of equipment in use—new, old, large, small. The Hyster system solves that with a flexible, retrofittable design. Whether your fleet is brand new or has aging units, this camera system can be installed quickly and effectively across the board. “This can be retrofitted in the field, which is really neat because very few operations have all brand new fleets,” says Ryals. “It installs in well under an hour, and I can usually train someone to use it in about five minutes.” The system runs on existing power sources—so no additional inverter needed—and supports plug-and-play setup using the strobe light connector. WIth built-in inertial measurement unit (IMU) sensors, it knows when the forklift is in motion and only activates alerts when necessary, reducing noise and helping operators trust the system’s accuracy. Visual + Audible Alerts Without Screen Distractions Instead of relying on small onboard screens, the system uses a remote-mounted operator interface to provide peripheral alerts. This approach avoids the risky behavior of operators diverting attention from their current task to interpret on-screen information. “There’s very little context you can get out of someone 16 feet away on a five-inch screen,” says Ryals. “We’ve already done the complex part—we told you a pedestrian is there. You just need to stay focused and keep your eyes on the task.” The alert system combines audio and visual cues to communicate risk without overwhelming operators. It’s fully configurable, including voice or tonal outputs, volume settings up to 100 dB, and proximity zones. Typically, alerts are spaced every 7–8 seconds to maintain operator awareness without creating alert fatigue. Designed for Contextual Awareness, Not Mere Alarms The system isn’t merely about detecting pedestrians, however; it’s about understanding context. Whether someone is walking toward a forklift or crouching to grab a package, the AI has been trained to distinguish normal operating behavior from potentially dangerous proximity. The camera unit processes data locally (edge computing), so nothing is sent to the cloud—a major benefit for facilities with union environments or GDPR compliance concerns. And while pedestrian awareness is currently the primary focus, Speedshield hints at future capabilities like near-miss analytics and zone monitoring, offering even deeper operational insights. “There’s going to be future capability to show how many people came into the zone, how long they were there, what proximity range they were in,” Ryals explains. “That gives the safety manager additional KPI data to change operational flows.” Compatibility and Scalability The Hyster Pedestrian Awareness Camera System can support up to eight cameras on a single vehicle, although standard forklifts typically only require one to four. For more complex equipment like container handlers, the additional coverage ensures full 360-degree visibility. Whether operating indoors under fluorescent lighting or outside near garage doors, the system is built with industrial sensors rated IP67, meaning they’re dust-tight and water-resistant. That makes it an ideal solution for facilities with varied environments. Safety Through Consistency By standardizing safety systems across all equipment—regardless of age or manufacturer—warehouses can achieve consistency in training and operation. The result is a safer workplace not just because of the improved equipment, but also because the operators develop trust in the tools at their disposal.  “Safety comes from consistency,” explains Ryals. “Having the same safety solution on all of your equipment adds value.” A System That Gets Smarter Over Time Each camera is a fully self-contained processing unit, and updates to the AI model are easily applied by scanning a QR code on the device. Speedshield typically releases updates every three to six months, ensuring that customers benefit from ongoing improvements without needing to overhaul their hardware. Final Thoughts: Safety That’s Simple, Smart, and Scalable The Hyster Pedestrian Camera System is more than just a forklift camera system—it’s a forklift collision avoidance system purpose-built for real-world warehouses. With retrofit capability, intuitive setup, and smart AI-driven pedestrian detection, it tackles some of the biggest pain points in forklift safety today. For purchasing managers, safety officers, and fleet supervisors looking to improve worker protection and reduce incident rates, this system offers a compelling path forward. As Ryals puts it with a touch of humor and insight, “You can replace parts, not body parts.”

Artificial intelligence is headline-grabbing technology. It can write novels, create photorealistic images, crunch data to make incredibly accurate predictions, and even have a conversation with you. But for all the stories about driverless vehicles and humanoid robots, some of the most meaningful applications of AI are happening in places far from the spotlight. In warehouses, factories, construction sites, and ports, AI is quietly reshaping how we keep people safe, prevent accidents, and respond to risk in real time. AI Appreciation Day is a chance to reflect on this quieter, but no less vital, form of digital intelligence. At Speedshield, we recognize the smartest use of AI may not be to do solely with automation or optimization – but safety. It protects people where visibility is low, reaction times are critical, and every second counts. That belief drives our work at the intersection of machine vision, edge processing, and pedestrian safety, where AI can quite literally save lives. Where Artificial Intelligence Meets Safety Industrial environments are among the least predictable environments it’s possible to work in. They’re filled with moving vehicles, blind corners, shifting loads, and the full spectrum of human behavior. In these settings, even a momentary lapse in awareness can lead to serious injury or worse. Despite advances in training, signage, and manual safety protocols, pedestrian-vehicle interactions remain one of the most persistent and dangerous risks on job sites. This is where AI is making a critical difference. Unlike static safety measures or operator-dependent interventions, AI systems can observe, analyze, and act in real time – without delay, distraction, or fatigue. By continuously monitoring for threats and responding proactively, AI enables a level of situational awareness that even the most diligent and well-trained workers lack. We’ve built our AiVA system around this very principle: real intelligence, applied to real-world risks, with the singular goal of keeping people safe. In the spirit of AI appreciation day, let’s explore more about AI’s role within AiVA. AiVA in Action: Putting AI to Work At the heart of Speedshield’s safety innovation is AiVA – an AI-powered pedestrian detection system purpose-built for the realities of industrial environments. It doesn’t just watch. It sees, understands, predicts, and acts. Here’s how AiVA puts artificial intelligence to work where it matters most: Seeing in 3D: Machine Vision with Depth and Precision Traditional camera systems, especially monocular or thermal-based solutions, can struggle in industrial settings where lighting conditions vary, and visual clutter is common. AiVA overcomes these limitations with stereoscopic machine vision: two cameras working together to perceive depth and distinguish between people, equipment, and static objects. Forget motion detection, this is 3D spatial awareness, and it’s essential in high-traffic environments where a stray pallet or forklift arm might trigger a false alarm in less sophisticated systems. By understanding shape, distance, and context, AiVA filters out the noise and focuses only on what matters: keeping us safe. Thinking on the Edge: Real-Time Processing Without Delay Of course, speed matters in safety. But not only for the reasons you might think. AiVA is built with dedicated on-board neural processors that aren’t reliant on cloud infrastructure or external connectivity. This edge-based design enables the system to process visual data, run AI inference models, and trigger alerts within milliseconds. By eliminating the “lag” associated with cloud-based connectivity, AiVA delivers ultra-low-latency detection and response, even in network-constrained environments like ports, mines, warehouses, or remote construction sites. That means faster decisions, fewer delays, and more lives protected. Acting with Clarity: Contextual Alerts and Automated Interventions When a potential pedestrian collision is detected, AiVA doesn’t overwhelm operators with abstract warnings or screen-based prompts. Instead, it uses clear, contextual indicators like directional LED lights and audible alerts to guide behavior without distraction. The system can also trigger automated responses, such as slowing or halting vehicle movement when a pedestrian enters a defined danger zone. This approach is rooted in Speedshield’s core philosophy: technology should assist, not interrupt. By embedding intelligence into intuitive cues, AiVA enhances operator awareness without adding cognitive load. Learning from the Field: Data That Drives Better Decisions While all of this is happening, AiVA also captures a stream of anonymized safety data that helps identify risk patterns, recurring hazards, and high-exposure areas across a facility. Over time, this data becomes a powerful tool for EHS teams looking to move beyond reactive incident response and toward proactive risk mitigation. Whether it’s analyzing near-miss events, pinpointing blind spots, or validating the impact of a new traffic management layout, AiVA equips safety leaders with evidence-based insights to guide continuous improvement. In this way, AI becomes more than an idle watchdog that barks for attention, but more of a feedback loop that makes the entire operation smarter and safer over time. Why It Matters: The Human Side of Industrial AI Behind every detection event, every alert, and every automatic slowdown is a human life potentially spared. In industries like construction, mining, and material handling, where workers share space with heavy equipment, pedestrian incidents remain one of the leading causes of serious injury and death. According to the Occupational Safety and Health Administration (OSHA), the construction industry alone accounts for roughly 1 in 5 worker deaths in the US each year, many of them vehicle related.  In sectors like this, AI isn’t a nice-to-have enhancement; it’s a non-negotiable layer of protection. Optimization, automation, and compliance are all important uses of AI, but we’re aiming to build technology that can step in and help when human senses inevitably fall short. Whether it's a fatigued operator at the end of a double shift, a new seasonal hire unfamiliar with site layouts, or a pedestrian crossing into a blind spot, AiVA is there to assist – invisibly, intelligently, and instantly. This AI Appreciation Day, instead of focusing on the AI use-cases that generate headlines, let’s take a moment to reflect on the AI use-cases that prevent them. We’re proud to build AI that works quietly in the background, protecting people, empowering operators, and making each shift safer than the last. Read the full article here.

Artificial Intelligence Appreciation Day marks a moment to reflect on the transformative effect artificial intelligence is having across industries worldwide. Far from being a futuristic novelty, AI is rapidly embedding itself into the bedrock of sectors ranging from cybersecurity and logistics to construction and customer experience, increasingly serving as an essential layer of intelligence, safety, and efficiency. In cybersecurity, the integration of AI is seen as not merely beneficial but fundamental. Sanjay Katkar, Joint Managing Director of Quick Heal, highlighted the growing importance of AI-driven security solutions in today's volatile digital environment. "AI Appreciation Day is a timely reminder of the transformational role artificial intelligence plays in securing our connected world. As we navigate an increasingly uncertain digital world, AI-powered cybersecurity has become essential in enabling stronger, more adaptive defenses. The global AI cybersecurity market is projected to reach $93.75 billion by 2030, growing at a remarkable CAGR of 24.4 percent, a reflection of the trust being placed in AI to keep pace with emerging digital threats. "At Quick Heal Technologies Limited, we recognised the potential of AI a few decades ago and have built our entire innovation strategy around it. As the only cybersecurity company from India to be part of the United States Artificial Intelligence Safety Institute Consortium, we deeply understand its responsible use. For us, AI is not just an enabler, it is a foundational capability we are continuously investing in and refining. "At the heart of this strategy is GoDeep.AI, our patented malware hunting engine that powers both Quick Heal and Seqrite solutions. Using deep learning and behavioral analytics, it identifies and neutralizes threats in real time enabling a stronger, faster defense against today's evolving threat landscape. "Our recent innovations build on this momentum as well. Launched last year, AntiFraud.AI, India's first comprehensive fraud prevention solution, reflects our commitment to safeguarding citizens in a rapidly evolving digital financial landscape where fraud is becoming more sophisticated by the day." On the enterprise side, Seqrite Intelligent Assistant (SIA), brings AI to the center of security operations with conversational threat intelligence that simplifies and accelerates decision-making for security teams. "Through every product and breakthrough, we remain focused on reimagining cybersecurity through the lens of responsible AI making security simpler, sharper, and more effective for every user we serve." The expansion of AI is also fundamentally reshaping customer engagement. Harsha Solanki, Vice President and General Manager Asia at Infobip, observed the transition from AI as a "support tool" to one that acts as an "autonomous agent driving the future of customer experience." With platforms such as Infobip's Customer Experience Orchestration Platform, brands now have the ability to deliver highly personalised, context-aware, and proactive conversations throughout the entire customer journey. Initiatives like these are helping companies build stronger, trust-based relationships with consumers through seamless, anticipatory engagement. AI's impact on logistics and supply chain management is dramatic and quantifiable. Dhruvil Sanghvi, CEO and Founder of LogiNext, noted that over 78% of businesses globally are now utilising AI, nearly doubling in two years. The wider AI market is expected to swell to a staggering USD $1.85 trillion by 2030. In logistics specifically, AI-driven technologies are optimising route planning, forecasting demand, and managing autonomous vehicles, all leading to "increased efficiency, lower costs, and enhanced overall reliability." The AI logistics market is forecasted to surge from USD $18.01 billion in 2024 to USD $549 billion by 2033, underscoring AI's vital role in powering smarter, more resilient supply chains. The accelerating pace of AI's adoption brings with it new security challenges. According to Parag Khurana, Country Manager for Barracuda Networks in India, "The ease of using generative AI to create and enhance content is having a far-reaching impact on people's lives," but it is also facilitating more sophisticated cyber threats. Khurana pointed out that attackers leveraging AI require only one successful breach, while cyber defenders must be vigilant without a single lapse. This dynamic has spurred calls for the development and deployment of advanced, multimodal AI security capable of detecting and neutralising threats regardless of their format or origin. Beyond the digital realm, AI is also quietly revolutionising safety in high-risk industrial environments. A spokesperson from Speedshield explained that warehouses, factories, and construction sites pose inherent dangers due to unpredictable vehicle and pedestrian movements. AI, through real-time monitoring and intervention, is providing a non-negotiable layer of protection that significantly reduces the risk of accidents and fatalities. Their AiVA system exemplifies how AI can "observe, analyse, and act without delay, distraction, or fatigue" to save lives where manual protocols may fall short. The construction and infrastructure sectors are also seeing significant AI-driven evolution. Balaji Sreenivasan, CEO of Aurigo Software, illustrated how AI is bridging the gap between long-term planning and execution in construction, enabling the simulation of future demand, the assessment of scenarios, and the prevention of project risk. "If the race to AI is one of progress, then it's also a race to modernise the infrastructure that will support it," Sreenivasan remarked, emphasising AI's pivotal role in shaping not just buildings and roads but the very systems that underpin modern industry. As AI embeds itself deeper into the operational fabric of business and industry, its role is expanding from a technological enhancement to an indispensable foundation for security, efficiency, safety, and innovation. On AI Appreciation Day, the message across sectors is clear: artificial intelligence is no longer merely a tool of the future - it is a force actively shaping the present and, inevitably, the world to come. Read the full article online at IT Brief Australia