Project Abstract

Road accidents are a significant menace to public safety, often caused by irresponsible driving. Existing enforcement techniques are not without their drawbacks, and technological advancements present novel approaches to encourage road safety. This void is intended to be filled by Road Sense Assist through a novel, community-driven strategy. The app will empower users to report hazardous driving and leverage AI for accident prevention. The initiative concentrates on developing a mobile app that allows users to readily record and submit video evidence of traffic violations. It will use AI algorithms to analyze footage in real-time, alerting vehicles to potential collisions. In the event of a catastrophe, the app will automatically contact emergency services and reveal the user’s location. I anticipate that Road Sense Assist will increase the reporting of hazardous driving behaviors, fostering community responsibility for road safety. The AI-powered features have the potential to reduce collision rates and enhance emergency response times. Road Sense Assist will provide a valuable model for integrating technology and community involvement in enhancing road safety. It has the potential to reduce accidents, save lives, and demonstrate a transition towards proactive, collaborative traffic management.

Keywords: Human Computer Interaction, Artificial Intelligence, Facilitating Pervasive Community Policing on the Road

 Conference Details

Session: Presentation Stream 24 at Presentation Slot 9

Location: College 017 at Wednesday 8th 09:00 – 12:30

Markers: Fabio Caraffini, Nader Al Khatib (GTA)

Course: MSc Advanced Computer Science, Masters PG

Future Plans: I’m looking for an industry placement