Road Accident Prevention using AIRAVAT: Artificial Intelligence-based Real-time Advanced Vehicle Administration Technology
Keywords:
Artificial Intelligence, Real-Time Vehicle Administration, Traffic Control, Accident DetectionAbstract
In the modern era of advanced technology, many urban areas are equipped with surveillance cameras linked to traffic management systems. Several road accidents result in severe damage to vehicles, and property as well as human injury sometimes leading to death. Road accidents are the eighth major cause of death among the young generation and have affected millions of people every year. Thus, the topic has gathered widespread attention for research wide attention to the topic for research. The study aims to reduce the accidents caused by driving conditions such as health, speed, control issues, or drowsiness and vehicle conditions. Additionally, it pursues to enhance the overall efficiency and safety of transportation systems. Utilizing advanced computer vision techniques can enhance the performance of the systems for automatic detection of accidents. The study proposed a framework - Artificial Intelligence-based Real-time Advanced Vehicle Administration Technology (AIRAVAT). It is based on the registration of drivers across the road network and vehicle authentication for safe and secure journeys. The administration system ensures the vehicle’s condition and also monitors the driver’s condition using advanced AI techniques. It sends alerts to drivers in case signs of drowsiness are detected. The centralized control system facilitates mobile apps with easier access from any location. The proposed system provides valuable insights for reducing road accidents and consequently saves human lives from injuries and fatalities. Ultimately, the proposed project establishes a roadmap for reducing accidents through real-time traffic control.
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