International Journal on Science and Technology

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SMART TRAFFIC MANAGEMENT SYSTEM

Author(s) Drushya S, Anush M P, Sunil B P
Country India
Abstract This project aims to develop an innovative Smart Traffic Management System that combines an Arduino-based platform with an IP camera and object detection algorithms for efficient traffic monitoring and control. The system enhances traffic flow by detecting various vehicle types such as cars, bikes, and trucks, and predicting traffic wait times using real- time vehicle counts. The system's core utilizes the YOLO (You Only Look Once) algorithm, a cutting-edge real-time object detection model, for vehicle identification and classification. The system uses an IP camera installed at traffic intersections to capture live video feeds. These feeds are processed with the YOLO algorithm to identify and classify vehicles in real-time, differentiating between cars, bikes, and trucks. The high speed and accuracy of the YOLO algorithm enable minimal latency, ensuring the traffic data remains current. The Arduino platform is central to processing data from the IP camera and controlling the system's components. After detecting objects, the system counts and categorizes vehicles. This data is used to predict traffic wait times, which are displayed on LED boards at the intersection. These predictions inform drivers of expected wait times, helping to reduce unnecessary idling and improve traffic flow. Additionally, the system uses LED lights to communicate traffic conditions visually. Different colors indicate various levels of congestion, giving drivers an immediate understanding of the traffic situation. For instance, green may signify low congestion, while red indicates heavy traffic, helping drivers make informed decisions. This project integrates computer vision, real-time data processing, and embedded systems to create a comprehensive solution for modern urban traffic management. By utilizing the YOLO algorithm for vehicle detection and traffic prediction, the system aims to enhance traffic efficiency, reduce congestion, and improve the overall driving experience. The use of Arduino and LED components ensures a cost-effective, scalable solution suitable for various urban environments.
Keywords Smart Traffic Management, System Arduino-based platform, IP Camera , Object Detection , YOLO Algorithm , Real-time Processing
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 16, Issue 1, January-March 2025
Published On 2025-02-12
Cite This SMART TRAFFIC MANAGEMENT SYSTEM - Drushya S, Anush M P, Sunil B P - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.1882
DOI https://doi.org/10.71097/IJSAT.v16.i1.1882
Short DOI https://doi.org/g85dkr
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