More Alerts, More Problems: Why Industrial Equipment Needs to Grow a Brain
By Nathan McKenzie, CEO, Speedshield Technologies
In industrial settings like construction sites, mines, and warehouses, alerts are seen as inherently valuable. If a vehicle beeps when reversing, that’s a useful indicator to pedestrians. If a sensor warns an operator in their forklift cab about an obstacle in their blind spot, that’s generally useful too. Keep extending that logic, and you will arrive at the conclusion that more alerts generally correlate to better safety. But talk to an operator or anybody who has spent time around heavy industrial equipment, and they’ll tell you a different story. Modern worksites are already filled to the brim with signals and alerts that are constantly competing for attention.
Operators are making hundreds of small judgments throughout a shift, often under pressure and in conditions that can change without warning. They don’t have the luxury of treating every signal with equal importance because doing so would make it impossible to focus on the task in front of them.
Add a sensor system that announces every object it can “see”, regardless of whether that object represents a genuine risk, and the warning itself becomes white noise – the “alarm that cried wolf.” Instead of helping people focus on danger, it becomes yet another potentially dangerous distraction. According to one 2024 study focused on the construction sector, up to 71% of workers suffer from “habituation” (desensitization) when exposed to constant alerts and are likely to engage in a form of rapid-fire triage, subconsciously dismissing alerts because previous identical alerts were false.
This “alert overload” is usually caused by tool sprawl – too many overlapping or uncoordinated monitoring or safety systems, often basic in function and designed to catch everything that might be a hazard instead of being able to assess each potential hazard in its own situational context. A stray traffic cone in an operator’s blind spot doesn’t pose the same risk as an idle pedestrian, and when you’re dealing with hundreds of alerts in a given shift, those distinctions can make a real difference.
This isn’t a failing of detection technology itself, nor is it a failing on the part of operators who are under extreme pressure to maintain 100% awareness during long, busy shifts. In many respects, detection technology is remarkably capable – modern cameras can identify people, vehicles, infrastructure, and equipment with impressive accuracy. The problem is that industrial environments aren’t simply collections of objects. They’re living, changing ecosystems where risk emerges from movement, timing, behavior, and context. Knowing that something exists is useful, but understanding whether it matters in context is what actually improves safety.
The Difference Between Seeing and Understanding
Industrial environments are constantly changing, but not always in ways that are obvious to a camera or sensor system. A construction site that looked perfectly safe at the start of a shift can become significantly more complex a few hours later as work progresses and different trades move through the same space.
Warehouses experience similar fluctuations as inventory levels change, routes become congested, and operational priorities shift throughout the day. The reality is that risk rarely exists as a fixed condition. It emerges from the interaction between people, equipment, and the environment around them, often developing gradually before reaching a point where intervention becomes necessary.
This is where many detection systems begin to struggle. Their primary job is to identify objects, which they often do extremely well, but detecting an object and understanding its significance are two very different challenges. A stationary object that has been safely positioned for hours may generate the same warning as a pedestrian who is about to move into the path of a vehicle. From the system’s perspective, both have entered a predefined detection zone. From a safety perspective, however, they represent entirely different levels of risk.
Human beings instinctively understand this distinction, because we understand context. Experienced operators don’t simply observe their surroundings; they interpret them constantly and make judgment calls. They recognize patterns, anticipate movement, and make countless small predictions about what is likely to happen next. An operator approaching a blind corner isn’t just looking at what is directly in front of them, they’re thinking about what could emerge from behind that corner, what activity is taking place nearby, and whether conditions have changed since they last passed through the area.
This ability to assess context is what allows people to navigate complex environments successfully, but it’s something many safety technologies have historically struggled to replicate. Every detected object is treated as a potential hazard, regardless of whether it presents any realistic danger. That approach may appear cautious on paper, but in practice it contributes directly to the alert overload outlined above.
Why Context Matters More Than Coverage
Industrial safety has become fixated on visibility. The assumption is that if we can expand the field of view, add more cameras, or monitor more of the environment, safety outcomes will naturally improve. Visibility certainly has value, but coverage alone doesn’t solve the problem of interpretation. A system that can see everything but understand nothing is still limited in its ability to help operators make better decisions.
What matters far more is context. A vehicle approaching a work area isn’t necessarily dangerous. A pedestrian walking across a site isn’t necessarily dangerous either. The risk emerges when those two events begin to converge in a way that could result in harm. Likewise, damage to infrastructure often isn’t caused by a single isolated action, but by a series of seemingly routine movements that gradually create unsafe conditions.
These are not scenarios that can be fully understood by analyzing individual objects in isolation. They require an understanding of relationships, behavior, and the broader environment in which those activities are taking place. So, rather than asking systems to identify as many potential hazards as possible, the goal should be to help them distinguish between routine activity and meaningful risk. That requires a deeper understanding of how industrial environments actually function. It means recognizing that the same object can represent very different levels of danger depending on where it is, what is happening around it, and how conditions are changing over time.
I think that’s why the next phase of industrial safety won’t be defined by how many objects a system can detect. It will be defined by how effectively that system can support decision-making in complex, fast-moving environments. In many ways, the industry has already solved the visibility problem. The challenge now is determining how to transform that visibility into meaningful insight.
Nathan McKenzie is the Chief Executive Officer of Speedshield Technologies, where he has spent more than two decades designing and deploying safety systems for industrial environments. He joined the company in 2003 as an engineer, later serving as Engineering Manager and Chief Technology Officer, and played a central role in the development of one of the industry’s first forklift-specific telemetry platforms. A Bachelor of Engineering graduate from Deakin University, Nathan now focuses on advancing practical, operator-centric safety technologies that improve visibility, reduce risk, and work seamlessly on the industrial floor.
Speedshield Technologies is a global leader in industrial connectivity and safety solutions. The company specializes in AI-powered safety cameras, pedestrian detection systems, speed control devices, and telemetry-driven fleet management technologies that help reduce risk, protect operators, and improve productivity across material handling, mining, construction, transportation, and warehousing. Founded in Australia, with subsidiary operations including Speedshield Technologies LLC (USA), Speedshield employs a diverse workforce spanning engineering, software development, manufacturing, and customer support. Its technologies are deployed worldwide by OEMs, dealers, and enterprises to enhance visibility, compliance, and operational safety. Speedshield also maintains a strong commitment to research and development, partnering with universities and industry groups to drive the next generation of safety innovation. Find further information at www.speedshield.com.