AI keeps an eye on road safety for fleet managers

May 04, 2020 //By Derek Bryan
road safety
The use of dash cam technology is on the rise, and for good reason. Last year, Scotland Yard revealed the extent to which its use has increased for the investigation of road incidents, with an average of 640 pieces of dash cam footage uploaded to its online portal each month.

For fleet-based businesses, dash cam technology can be instrumental in reducing impact of a road traffic incident on the bottom line. Survey data from Verizon Connect shows that small to medium-sized fleet operated businesses in the UK already spend £6,000 on average on repairs each year due to traffic accidents, making the ability to submit accurate insurance claims a financial imperative.

While dash cams have improved in quality over the last few years – improving video quality with higher resolution lenses or live streaming via 4G – the recent development of AI integration stands to transform their functionality, with specific benefits for fleet-based businesses.


Bridging the gap between analysing video and taking action

According to official figures from the Department of Transport, light commercial vehicles alone travelled more than 60 billion miles in the UK last year. Many businesses own or run vehicles that spend large amounts of time on the road, and as a result have to wade through hours of footage when an incident occurs to access the necessary data. To exacerbate this issue, the time elapsed between a vehicle becoming unroadworthy due to an accident and a claim being compiled can have an impact on meeting service level agreements (SLAs) and ultimately, the business’ bottom line.

As in its many different applications, AI helps close this gap between data collection, analysis and insight. AI-integrated dash cam solutions can automatically classify driving events by severity and reduce the data analysis burden on fleet managers by alerting them to events that require immediate attention. They do this by reviewing footage and matching it with captured data indicating abnormal driving behaviours - such as harsh braking, hard cornering or rapid acceleration - as soon as an event occurs.

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