Industrial manufacturing sites are inherently hazardous environments. With moving machinery, heavy equipment, and high-temperature processes, one small lapse in safety can lead to catastrophic outcomes. Among these risks, worker intrusion into designated danger zones remains one of the most persistent challenges for EHS (Environment, Health & Safety) managers.

At a transmission pipe manufacturing facility in Khobar, Saudi Arabia, this challenge had reached a critical level. The factory, which supplies transmission pipes, was facing repeated risks of workers stepping into the line of fire—areas marked where massive steel pipes were being moved, rotated, or aligned during production.

To address the issue, the factory turned to viAct AI-based intrusion detection system, deploying smart cameras across key areas of the site. What followed was a remarkable transformation in how safety was managed, monitored, and enforced.

In the Khobar transmission pipe manufacturing unit, monitoring practices were rigorous and well-intentioned. The factory had established physical safety barriers around critical areas where large steel pipes were fabricated and transported.

Red boundary lines were painted on the shop floor to designate restricted zones—areas where heavy machinery operated, pipes were in motion, or overhead cranes lifted massive loads. In addition to these markings, traditional surveillance cameras were installed across the shop floor to monitor activities in real time, with safety officers responsible for reviewing the feeds.

Routine safety checks were also a part of the system. Supervisors frequently walked the floor to ensure that no unauthorized workers entered danger zones. Employees were trained to recognize the meaning of the marked boundaries in the line of fire and adhere to safety protocols, such as wearing protective gear and keeping a safe distance during operations.

These practices reflected a strong commitment to safety and were standard across many industrial units worldwide.

Yet, manual intrusion monitoring has always been a weak link:

• Safety officers or supervisors need to continuously monitor the floor, but in a large-scale facility with multiple red zones, blind spots are inevitable.

• Workers, pressed for time, sometimes cut across restricted areas, either to save steps or to perform tasks quickly.

• Improper use of PPE in danger zones adds another layer of risk.

The question arose: Were these measures enough to prevent incidents in a high-risk, fast-moving manufacturing environment? 

The answer, as the company learned, was no! Traditional methods, while important, could not fully eliminate the risk of intrusions into danger zones. What was missing was a system capable of providing constant, automated, and precise detection—something beyond human capacity.

For Khobar’s pipe factory, this translated into:

• Multiple near-miss reports from danger zones every month, where workers unintentionally entered.

• Supervisors spend nearly 20% of their active time just on floor surveillance, reducing focus on other critical safety responsibilities.

• The constant anxiety of potential regulatory penalties in case of a serious incident.

In short, manual monitoring was reactive, inconsistent, and prone to human error, leaving safety gaps in an otherwise modernized production environment.

To address these gaps, the Khobar manufacturing unit turned to viAct’s AI-powered safety monitoring system designed to overcome the limitations of manual surveillance and provide real-time, automated protection. Instead of relying solely on human attention, computer vision algorithms and video analytics AI were trained to detect specific unsafe scenarios on the factory floor.

Here’s how the solution was structured:

In the pipe manufacturing line, long steel pipes vibrate and move when in operation.  Each movement creates a high-risk dynamic zone where workers are not permitted. Traditionally, these zones were outlined with paint or red tape, but visibility alone could not guarantee compliance.

With AI-enabled CCTV for detecting intrusions, the danger zones were digitally mapped by creating a 3-meter restricted zone from each movement. Whenever a worker stepped into the area while pipes were in motion, the system automatically flagged the intrusion. This replaced reactive spot checks with hazardous area access control facilitated by AI, ensuring that no breach was overlooked.

Moving pipes often meant that workers on opposite sides of the production line were simultaneously active, making it impossible for supervisors to track every corner at once. The AI-powered risk zone monitoring system instead scanned multiple factory sections in real time, independent of human limitations.

If a worker moved closer to the active rollers or even crane paths carrying pipes, the system registered the proximity and triggered alerts, both light and sound alerts. Unlike manual observation, which could miss subtle movements, the AI provided consistent coverage with 99% uptime—a critical safeguard where even a few seconds of inattention could lead to life-threatening incidents.

Pipe manufacturing zones are not just hazardous because of moving loads; they also require strict adherence to personal protective equipment (PPE). Helmets, gloves, safety vests, and reinforced boots are mandatory when entering restricted areas.

The AI-powered danger zone monitoring system layered PPE detection onto intrusion monitoring. If a worker had to step into a danger zone for maintenance, inspection, or equipment alignment, the AI verified their compliance with safety gear. A worker entering without a helmet or vest was flagged immediately, allowing supervisors to intervene before exposure to moving pipes caused harm.

The speed of pipe movement left no margin for delayed responses. To counter this, the AI in the danger zone transmitted instant alerts to both the floor supervisors’ and the central control room dashboards.

For example, if a worker breached a restricted area just as a pipe was being rolled to the next section, the supervisor could act within seconds—either by halting pipe movement or guiding the worker out. This real-time intervention mechanism converted near-miss events into predictive insights, reducing the probability of accidents.

Every intrusion attempt or PPE violation was time-stamped, logged, and categorized. Over weeks of operation, this data provided a clear picture of safety behavior inside the factory.

• Repeated breaches were traced back to specific shifts, often coinciding with peak workload hours.

• Data revealed “hotspots” where pipes frequently moved and workers tended to shortcut across marked zones.

• EHS Managers could identify whether the issue was training-related (workers ignoring boundaries) or process-related (zones overlapping with routine workflows).

By analyzing these patterns, the factory not only prevented accidents in real time but also improved long-term safety planning, redesigning workflows around data-driven insights.

The impact of the AI-powered system was evident in the pipe manufacturing unit’s line of fire within 8 weeks of deployment.

• Intrusion Incidents Reduced by 97%: Within the first quarter, human entry into risk zones dropped drastically. By six months, worker intrusions were reported down to zero, thanks to instant alerts and better compliance.

• PPE Compliance Improved by 85%: Workers became more aware of their responsibilities, knowing that non-compliance would be detected immediately. This led to a cultural shift in workplace safety.

• Supervisor Efficiency Increased by 60%: Instead of focusing on constant monitoring, supervisors could redirect their attention to process optimization and preventive maintenance, supported by AI’s real-time insights.

• Zero Lost-Time Injuries (LTIs): Perhaps the most significant achievement was a full quarter with zero LTIs related to danger zone intrusions—a first in the factory’s history.

According to the plant’s safety committee, the system did not just reduce risks but also helped build trust among workers, as they felt more secure knowing that an intelligent monitoring layer was always active.

The Khobar transmission pipe factory’s journey from manual monitoring to AI-powered intrusion prevention in manufacturing demonstrates how technology can bridge the gaps in traditional safety systems.

By embracing AI video analytics, computer vision, and real-time PPE monitoring, the factory not only secured its workforce but also optimized operations. Worker intrusions fell to zero, PPE compliance soared, and supervisors could finally focus on higher-value tasks instead of constant red zone policing.

As industries across the globe evolve with the challenges of keeping humans safe in increasingly automated environments, the Khobar case study offers a replicable model:

• Trust AI for vigilance where humans are prone to fatigue and oversight.

• Use data-driven insights to reshape safety training and culture.

• Transform workplace safety from a reactive process into a proactive shield.

The future of manufacturing safety is not about choosing between humans and technology—it’s about creating a collaboration where AI safeguards humans, and humans use the insights to build safer, smarter factories.

The best benefits of deploying an AI-based system occurs in the following ways –

• Sends mobile alerts with live camera feeds.

• Issues sound or light alarms on the shop floor.

• Provides a central dashboard view of all risk zones.

• Reduces supervisor workload by automating 24/7 surveillance.

Yes. AI-powered risk zone monitoring like viAct’s has 100+ AI modules which are  already used in construction sites, oil & gas sites like drilling rig floors, logistics & warehouses, and mining sites. It works anywhere human intrusion into unsafe zones is a risk.

No. While they are highly beneficial in large-scale operations, even small and medium enterprises  can deploy AI-based safety systems using their existing CCTV infrastructure, making them cost-effective and scalable.

No—they support supervisors by handling repetitive monitoring. AI helps them by:

• Logging every intrusion event

• Providing video evidence for investigations

• Highlighting high-risk workers or shifts

• Freeing supervisors to focus on training and audits

No. While the Khobar transmission pipe factory serves as a strong example, the system is being adopted globally across different industries and geographies. It is available in other In the Middle East countries like Saudi Arabia, UAE, and Qatar. Further, its deployment is there in Hong Kong, Malaysia, and Singapore along with major European and North American regions.

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