The Fundamentals of 24/7 Vehicle Near-Miss Detection: Enhancing Safety in Real-Time

The Fundamentals of 24/7 Vehicle Near-Miss Detection: Enhancing Safety in Real-Time

Anyone who works in the transportation and storage sector will probably have witnessed a near-miss incident involving a vehicle. This could be a delivery lorry or a forklift truck that comes very close to hitting a person, another vehicle or property. 

As a safety-conscious professional, you will be well aware that in slightly different circumstances the outcome could have been much worse; the person might have been seriously injured or even killed. Property could have been damaged and operations disrupted. 

That’s why most businesses invest in near-miss detection, typically employing safety professionals to manage site activities and encouraging staff to report incidents immediately. Armed with this data, managers can then put mitigation measures in place. 

To foster a truly preventative approach, however, businesses should maintain continuous 24/7 monitoring of their operations so they can capture all near-miss incidents. This is where computer vision-based artificial intelligence (AI) using sensors and machine learning provides solutions that traditional approaches can’t offer.  

‍

How does it work?

Advances in AI monitoring software are such that this innovative safety technology can be connected to CCTV in a warehouse or delivery yard, so that real-time footage on vehicle movements, particularly interactions with pedestrians and other vehicles, is captured and the data analysed.

Driven by machine learning, the software can be trained to identify near misses and also report these ‘close calls’ automatically when they happen. As more data is captured using 24/7 vehicle near-miss detection monitoring, the software can also identify any negative trends or particular behaviours, such as drivers speeding or taking short cuts. 

Sensors can also be attached to vehicles to monitor their proximity to other objects and to send alerts to managers when a driver is speeding or a near miss is detected. 

Sometimes staff may not feel a near miss is important enough to report. Also, the presence of safety professionals may cause individuals to change or moderate their behaviour. The advantage of using AI in safety monitoring is that it operates in the background, providing an accurate and consistent picture of frontline activities. 

‍

What are the benefits?

Near misses are important indicators for businesses that a more serious incident was narrowly avoided, so the value of a more accurate reporting system cannot be overstated. Even the most safety-conscious businesses can benefit from the insights that computer vision-based AI provides.

To start with, the software’s analysis can help identify any gaps in existing risk assessment strategies or safety protocols. Once new or previously unaccounted for hazards and risks are brought to management’s attention, they can then implement enhanced, preventative, measures to better manage them.

Two of the most tangible benefits of acting on these data-driven insights are a reduction in safety incidents and accident prevention.  

However, they are only some of the positive spin-offs. Employee participation is critical to improving safety culture, so when workers see that employers are taking a proactive approach to managing risks, this demonstrates that worker safety is a serious concern. Employees will probably feel more valued as a result and more likely to report near misses because they feel the information will be acted on.

Work activities won’t be disrupted if near misses are avoided and a workforce that feels valued will be more productive. In other words, data-driven insights can also help enhance operational efficiency. 

That’s certainly what leading British retailer Marks and Spencer discovered when it used AI technology and identified a spike in unsafe practices whenever agency staff were employed in its warehouses. Unlike permanent staff, agency workers were not familiar with site safety rules. 

To drive improvements, the retailer updated its induction process for agency staff and implemented enhanced training. One of the headline results was a dramatic 80% reduction in incidents.

‍

Challenges and considerations

One of the biggest concerns businesses cite when they are weighing up whether to implement a computer vision-based AI system is its affordability. They may also worry about its compatibility with their existing software systems.

To answer the first point, it is important to recognise that this workplace safety solution is an investment that will provide better protection for a business over the long-term. Its data-driven insights contribute to operational efficiencies that will improve productivity and consequently increase profit. At the same time, improved vehicle near-miss detection minimises the risk of more serious incidents happening and consequently costly prosecutions. 

The software solutions are also designed to integrate seamlessly with existing systems and providers like Protex AI will support companies to make the transition to autonomous reporting with ease, including how to add customised safety rules. 

‍

Enhanced compliance and reporting

Most businesses aspire to have a strong safety performance and acting promptly on near-miss reports to make the workplace safer is one way they can demonstrate compliance and also meet a key corporate objective. 

The ability to continuously monitor workplace activities, for example, to identify how often potential collisions between pedestrians and vehicles are, can be a game-changer. The data insights can inform decisions, for example, that improve safety around procedures, training and workplace layouts. 

More strategically, businesses that integrate the AI software into their safety strategies will help foster proactive safety management from the top level down, not just minimising the risk of a serious event happening, but also driving operational efficiency.  

‍