Deep Learning Based Traffic Surveillance for Managing Unusual Events with Edge Computing
Navaneetha M, Shanthi M. B · 2024
A Robust Traffic Surveillance System is crucial in challenging terrains with limited medical assistance. By leveraging Geospatial, Temporal, Social contexts and storing relevant data with metadata, the proposed system monitors traffic effectively. It alerts authorities about potential disasters or threats, and in case of an attack, quickly analyzes factors leading up to it, enabling appropriate action. This involves studying object detection methods, exploring Deep Learning for Video Analytics, and developing an Edge-based model for Traffic Vision. The system is evaluated on Real-Time Traffic videos for accuracy and effectiveness.