Urban public transport buses traverse almost every major road in a city every day. Modern buses are increasingly equipped with multiple cameras covering the front, rear, sides, and passenger cabin. However, these cameras are primarily used for recording incidents and are not leveraged as intelligent sensing systems. At the same time, city authorities rely on fixed CCTV cameras, manual inspections and citizen complaints to detect road defects, traffic congestion,missing infrastructure and uns
Develop an AI-powered onboard and centralized software system that transforms public transport buses into mobile urban sensing units.
Urban public transport buses traverse almost every major road in a city every day Modern buses are increasingly equipped with multiple cameras covering the front, rear, sides, and passenger cabin However, these cameras are primarily used for recording incidents and are not leveraged as intelligent sensing systems
Develop an AI-powered onboard and centralized software system that transforms public transport buses into mobile urban sensing units. The onboard software shall analyse video streams from multiple bus-mounted cameras to detect road defects such as potholes, damaged roads, missing road dividers, missing zebra crossings, damaged or missing traffic signboards,waterlogging and other road hazards. It shall estimate vehicle density through vehicle detection, classification and counting, identify traffic bottlenecks, and detect vulnerable pedestrian situations such as school children crossing roads. During incidents such as hit-and-run or rash driving, the system should detect and track the offending vehicle, extract the registration number with a confidence score, timestamp and GPS location, a