The proposed system is to develop a density-based dynamic traffic system where certain signal timing varies intelligently depending on the quantity of traffic at each intersection. Because traffic congestion could be a big problem in most cities across the globe, it is time to change from a manual or fixed-timed system to one that may make decisions. The present traffic signal system operates on a fixed schedule, which can be wasteful if one lane is active while the others do not seem to be. A framework for an intelligent system has been designed to deal with the difficulty. Because higher traffic density on one side of the junction frequently needs additional green signal timing than the standard given time, a system is proposed wherein the fundamental measure of green and red light is assigned in support of the density of traffic existing at that time. Proximity infrared sensors (PIR) are commonly employed. Once the density has been determined, the microcontroller is employed to allocate the green light's glowing duration. The sensors on the road's edges detect the presence of automobiles and communicate this information to the microcontroller, which determines how long a lane will remain open or when the signal light’s timing is adjusted. The framework's method was developed in later stages. This framework is employed to implement traffic congestion control, ambulance clearance, and stolen vehicle detection.


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    Title :

    Smart Traffic, Ambulance Clearance, and Stolen Vehicle Detection


    Additional title:

    Lecture Notes on Data Engineering and Communications Technologies




    Publication date :

    2022-01-17


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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