CVEH: A Dynamic Framework To Profile Vehicle Movements To Mitigate Hit And Run Cases Using Crowdsourcing

TL;DR

CVEH is a crowdsourcing-based framework designed for developing countries to profile vehicle movements and assist law enforcement in mitigating hit-and-run incidents through vehicle-to-infrastructure communication.

Contribution

It introduces a novel, resource-efficient vehicle profiling framework using crowdsourcing and V2I communication suitable for resource-limited settings.

Findings

Framework effectively profiles vehicle movements in simulations.

Engages citizens and law enforcement for improved security.

Operates on Android smartphones with positive evaluation results.

Abstract

In developed countries like the USA, Germany, and the UK, the security forces used highly sophisticated equipment, fast vehicles, drones, and helicopters to catch offenders' vehicles. Whereas, in developing countries with limited resources such schemes cannot be utilized due to management cost and other constraints. In this paper, we proposed a framework called CVEH that enables developing countries to profile the offender vehicle movements through crowdsourcing technique and act as an early warning system to the law forcing agencies. It also engages citizens to play their role in improving security conditions. The proposed CVEH framework allows Vehicle-to-Infrastructure (V2I) communication to monitor the movement of the offender's vehicle and shared its information with the Command and Control (CC) centre. The CC centre projects the path and engages nearly located law enforcement agencies. CVEH is developed and evaluated on android smartphones. Simulations conducted for this study exhibit the effectiveness of our framework.