A Research Survey on Traffic Management, Accident Detection and Emergency Notification Systems to Improve Society Health

The rapid growth of urbanization coupled with the rise in number of vehicles on roads have resulted in various issues, including traffic congestion, emergency vehicle delays, and delayed medical assistance to accident victims. To tackle these problems, we propose an Intelligent Traffic Management and Accident Detection System with Emergency Notifications using Artificial Intelligence (AI), implemented in a software-based, simulated, controlled environment. Our system employs a combination of computer vision, image processing, and machine learning techniques to collect data from strategically placed cameras along the roads and a camera mounted on top of signals. The captured image frames are sent to a central server located at the intersection, where the system's logic processes them in real-time to dynamically adjust signal timings based on the traffic density. In addition, our system provides priority for emergency first-responder vehicles to ensure their swift and safe passage through traffic. The proposed system also includes an accident detection system that classifies accidents based on their severity. If the severity exceeds a predefined threshold value, the system detects the location of the accident and sends an alert to the nearest hospital, allowing medical assistance to reach the accident site promptly. Our system aims to offer an efficient and effective solution to the challenges posed by increasing traffic. By incorporating AI, we can provide an advanced traffic management system that can optimize traffic flow and prioritize emergency vehicle movements, ensuring the safety and well-being of all commuters and accident victims.