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Home / Technology / AI Cameras to Catch Phone-Using, Unbelted Drivers

AI Cameras to Catch Phone-Using, Unbelted Drivers

12 Dec

•

Summary

  • AI cameras can identify thousands of offenses within hours.
  • PACTS advocates for AI camera rollout nationwide.
  • New tech could deter and better understand risky behavior.
AI Cameras to Catch Phone-Using, Unbelted Drivers

A call for a 'modernised approach' to persistent driving offences, specifically mobile phone misuse and seat belt non-compliance, has been made by the Parliamentary Advisory Council for Transport Safety (PACTS). Their new report recommends a nationwide implementation of roadside AI cameras and in-vehicle monitoring systems to combat these high-risk behaviours, with funding support from Australian firm Acusensus.

Trials of AI cameras have demonstrated their effectiveness in identifying thousands of offenses swiftly, providing a significant deterrent. PACTS argues that the current enforcement relies on sporadic observation, capturing only a fraction of offenders. The proposed technology offers a scalable solution to detect, deter, and better understand non-compliant driving habits.

PACTS also suggests reviewing penalties for these offenses and exploring educational diversionary courses. For commercial fleets, more intrusive technology like telematics and in-vehicle alerts is recommended to ensure drivers are compliant with seat belt and mobile phone regulations.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
PACTS is urging ministers to implement a nationwide rollout of AI cameras and in-vehicle monitoring to tackle mobile phone misuse and seat belt non-compliance.
The AI cameras monitor passing vehicles, identifying drivers using phones or not wearing seat belts. This data is then reviewed by police for penalty enforcement.
Current enforcement methods are insufficient, capturing only a fraction of offenders, while these offences contribute significantly to road collisions and fatalities.

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