The challenge:
no driver behaviour monitoring & truck operator support
In industries relying on heavy vehicles, driver behaviour is a critical factor in ensuring safety for both operators and nearby workers.
A mid-sized logistics firm managing over 200 trucks across England and Wales faced rising concerns over driver and worker safety. Incidents involving unnecessarily risky behaviours—such as distracted driving and improper vehicle handling—had led to accidents and near-misses, increasing liability costs and harming employee morale.
Moreover, truck operators hoped for additional manoeuvre support for operations like reversing, parking, and unloading– all of which can be tricky with workers around. Despite regular safety training sessions, the company struggled to monitor and enforce safe practices across its fleet consistently.
As the issue was getting out of hand, damaging the company’s reputation, its leadership decided to investigate technological solutions to this challenge.
Evaluating available options
#1: Initial solutions involved manual inspections and random audits of in-cabin cameras.
However, this method was reactive and could not address real-time issues.
#2: GPS systems
provided some insights into speeding but could not capture nuanced behaviours like distraction or unsafe manoeuvres.
#3: Advanced technologies like AI-enabled video analysis and sensor integration emerged as potential solutions, promising real-time detection and intervention.
However, alone, they couldn’t deliver the required level of behaviour supervision and truck operator support.
The solution:
smart driver behaviour monitoring & support
The company deployed an integrated driver behaviour monitoring system, also delivering comprehensive, real-time insights into the truck’s surroundings for manoeuvre support.
The solution combines the following elements:
- In-cabin cameras, including dashcams;
- External IoT sensors;
- Cloud-based analytics powered by deep learning.
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The system monitors and analyses driver behaviour in real-time
identifying risks such as mobile phone use, drowsiness, or sudden braking.
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The external sensors help detect when the vehicle gets too close to other vehicles and workers
Once the system identifies the proximity as unsafe, it immediately alerts the driver and provides corrective recommendations.
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The solution also notifies the fleet manager, automatically sending them all necessary incident details
As a result, the trucking company remains on top of all developments and can correctly document and analyse all accidents for future improvements.
Results & plans: further expand driver safety
A01
30% reduction in safety incidents
Within the first six months of implementation, the company saw a 30% reduction in safety incidents and a significantly decreased number of insurance claims.
A02
More confidence in the company's safety protocols
Thanks to smooth and unintrusive driver behaviour monitoring and alerting mechanisms, truck operators gained more confidence in the company’s safety protocols. The system also resulted in safer operations for workers near trucks while supporting manoeuvres in crowded areas.
A03
predictive analytics with historical data for increased risk pre-emption
Building on this implementation’s success, the company plans to further refine its predictive analytics with historical data for increased risk pre-emption. The team also plans to extend monitoring capabilities with external factors like weather and road conditions to further elevate safety standards.
