Mohammed Faizan, Malika R, Prof. Mallikarjuna M, Praveen Kumar, C Sai Sahithya Reddy


  It has been noted by experience that traffic signals in the city, Bengaluru, have been broken at will by the ones whose safety and convenience is the primary objective of these traffic signals. This has caused accidents incidentally, thereby leading to loss of life and property and causing huge traffic disturbance. Moreover, inefficient management can lead to traffic snarls in cities of developing countries like India. Manual discernment of traffic violations is a daunting task with many of the violations going unrecognized. An automated traffic management system, is therefore, an efficient alternative. The project at hand will aid to control these issues and further avoid these accidents by means of automated fine system. The system has a cognitive computer vision, a convolution neural network, supported by strong network of IOT devices and is called the Traffic Violation Administrator (TVA). In order to reduce this congestion and set up a functional system of traffic management and to minimize emergency vehicles waiting time, the TVA, which uses image processing and a scheduling algorithm, automatically manages the duration of traffic signals based on the number of vehicles, length of the queue and the average lane speed. The management of signals to prioritize emergency vehicles such as ambulances or fire brigades is by ensuring green signals in their specified routes with aid of GPS and maps. This project is aimed to be developed for the Traffic monitoring agencies in various parts of the country to replace the traditional monitoring with increased efficiency.



automated traffic management system, computer vision, internet of things,

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