Paper Title
SmartFlow: Real time Traffic Flow Optimization and Management System Using Reinforcement Techniques.
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Registration ID: IJNRD_324575
Published ID: IJNRD2605167
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Abstract
This AI-Based traffic monitoring system is designed to stimulate intelligent traffic analysis using computer vision and deep learning techniques. The system utilizes the YOLOv8 algorithm to detect and count vehicles from traffic images in real time. Input images are processed using OpenCV to enhance resolution and improve clarity through cubic interpolation, ensuring accurate object detection. The system identifies different vehicle classes such as cars, buses, truck, and motorcycles, and highlights them using bounding boxes. The boxes help to separate and identify every vehicle as a unique vehicle. After detection, the total vehicle count is calculated and displayed dynamically on the screen with graphical overlay. The processed output is also saved as high- definition image for further analysis. This AI –based approach helps estimate traffic density, security, inspection, supports congestion monitoring, and can be integrated with automated traffic signal control system. Along with the signal control the timings of the signal can be customized. Along with the use in the main roads it can also be implemented by malls and other public places in order to make commute easy and smooth. This system also analyses the lane-wise traffic conditions and wait time, and improves the traffic flow efficiency. hence provides a better approach for reducing wait time, and improves the traffic flow efficiency.
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How To Cite (APA)
Mathumitha.V, Aanchal Sharma, Udhaya.P, & Yalpi Nithish Kumar (May-2026). SmartFlow: Real time Traffic Flow Optimization and Management System Using Reinforcement Techniques. . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(5), b526-b535. https://ijnrd.org/papers/IJNRD2605167.pdf
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Volume 11 Issue 5, May-2026
Pages : b526-b535
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Paper Reg. ID: IJNRD_324575
Published Paper Id: IJNRD2605167
Research Area: Other area not in list
Author Type: Indian Author
Country: Chennai 600073/Chengalpattu, Tamil Nadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2605167.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2605167
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