• Mr.Dhanushprashath.P
• Dr. Swati Sah

Unresolved traffic is one of the main contributors to the India' declining productivity, which affects both its citizens and many industrial sectors. The nation has made several attempts to control traffic, involving the construction of highways, the extension of roads, and the execution of several traffic plans. The answer to the drawbacks of conventional traffic signal systems is being researched as one of the research directions. Existing research on traffic light systems has led to the development of intelligent transportation systems (ITS), which normally rely on real-time data on traffic density to function but are only implemented with a certain level of control. This work focused on a technique for developing traffic signaling systems that may prioritize congested lanes based on real-time data on traffic density, coupled with automatic and human control, and implemented in a mobile Android-based application. The system collected traffic images from CCTV cameras positioned in each of the intersection's lanes and delivered them to the Raspberry Pi 3 microcontroller for use in determining traffic density using image processing. To control how traffic lights operated, it used an Android mobile app store and a traffic monitoring system. The system was evaluated, and the average vehicle detection rate for daylight and nighttime, respectively, was 92.83% and 85.77%. Additionally, during daylight and nighttime testing, an overall system dependability of 92.82% and 85.77% were achieved based on the Android GUI, lane prioritization, and traffic light response. Future development included connecting the traffic light system to the Internet of Things (IoT) for a more extensive, networked application.

computer vision, image processing, Intelligent transportation systems, and mobile Android- based applications

"Computer Vision Based Intelligent Traffic Light System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 2, page no.d794-d801, February-2023, Available :http://www.jetir.org/papers/JETIR2302398.pdf

"Computer Vision Based Intelligent Traffic Light System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 2, page no. ppd794-d801, February-2023, Available at : http://www.jetir.org/papers/JETIR2302398.pdf