Advanced Transportation Safety Using Real-Time GIS-Based Alarming System for Animal-Prone Zones and Pothole Areas

The transportation system undergoes severe impacts due to potholes and the presence of stray animals on the roads resulting in accidents and fatal injuries. The utilization of intelligent transportation systems would reduce accidents and impart safety to the overall transportation network. This research aims to impart transportation safety through a real-time alert warning system for avoiding accidents due to potholes and the presence of stray animals. The study incorporates real-time detection of transportation entities like vehicles, animals, and pedestrians through a YOLO v3 computer vision algorithm processed on the GPU environment for a higher frame rate. The potholes and animal hotspots are mapped to form a geospatial database on which the buffer tool of geographic information system (GIS) is applied. The buffer zone was implemented on the geospatial layer to alert the driver in real-time, while the vehicle approaches the buffer zone. The system yields high precision of 0.976 mean average precision (mAP) score of entity detection and the real-time alert warning alerts the driver to ensure transportation safety while avoiding any possible accidents or fatal crashes.