The demand for creative solutions to handle traffic incidents and speed up emergency response times is higher than ever at a time when road safety is of the utmost importance. Conventional traffic control systems frequently rely on manual reporting, which causes inefficiencies and delays that can worsen traffic risks and jeopardize safety. To close this gap, we suggest a real-time system that combines cameras, sensors, and artificial intelligence (AI) algorithms to transform traffic incident detection and response. This state-of-the-art system instantly notifies emergency services of traffic events in real-time, automating the process of improving road safety and streamlining emergency response procedures. Through the elimination of human reporting delays, this technology fixes existing inefficiencies and enhances traffic management as a whole. The technology foundation consists of smartphone applications for real-time updates, AI-driven incident detection, continuous monitoring, and linked car technologies. To reduce dangers related to driver weariness and stress and to provide early warnings, this system also includes driver stress level detection using computer vision. In the end, this system hopes to establish a new benchmark for proactive incident avoidance and traffic management, encouraging safer driving behaviors and more effective emergency response.


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    Title :

    AI-Powered Traffic Solutions for Preventing and Detecting Incidents for Safer Roads


    Contributors:


    Publication date :

    2024-10-08


    Size :

    516144 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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