COMMUNITY-DRIVEN TRAFFIC LAW ENFORCEMENT WITH A REWARD MECHANISM

Abstract

India continues to face alarming road fatality rates due to non-compliance with traffic regulations. Despite the presence of CCTV surveillance and manual policing, the scale of violations outpaces enforcement capacity. The proposed work introduces a community-driven framework where citizens act as real- time contributors to traffic law enforcement through a mobile application. The application enables users to capture and submit photographic or video evidence of violations such as helmetless riding, triple-seating, and signal jumping. Each report is automatically tagged with GPS coordinates, date, and time before being uploaded to a secure cloud repository. Traffic au- thorities access a web- based dashboard to verify the reports and reward legitimate submissions through a point-based incentive mechanism redeemable as mobile recharges or digital coupons. The collected data feeds into an analytics engine that generates violation heatmaps and temporal statistics to identify high-risk zones. This work combines crowdsourcing, cloud computing, and artificial intelligence to deliver a sustainable, scalable, and cost- efficient solution. By turning citizens into active partners rather than passive observers, the system enhances account- ability, promotes behavioural change, and supports data-driven policy-making for safer roads across urban and semi-urban environments.