ZoneWatch-A Deep Learning Approach to Vehicle Zone Recognition and Speed Management

Registration ID: IJNRD_218584

Published ID: IJNRD2404589

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C.SURYA, T.JEEVA, V.KANIMOZHI, M.NANDHINI, K.SOFIYA

Artificial intelligence, Convolutional neural network, microcontroller, traffic monitoring, segmentation, vehicles, zone recognition.

This study has been undertaken to focuses on leveraging deep learning approaches, specifically Convolutional Neural Networks (CNN), to enhance the efficiency of a vehicle zone recognition system tailored for critical areas such as schools, hospitals, and accident-prone zones. The proposed system aims to integrate artificial intelligence (AI) with a microcontroller to regulate vehicle speed dynamically. By implementing CNN algorithms, the model enhances the accuracy and robustness of object recognition within designated zones, contributing to improved safety measures. The incorporation of a microcontroller ensures real-time control of vehicle speed, facilitating a responsive and adaptive system that prioritizes safety in sensitive areas. This study not only addresses the technical aspects of deep learning but also explores the practical implications of deploying an AI-enhanced system for improved traffic management and overall public safety.

Published Paper   E-Certificate

C.SURYA, T.JEEVA, V.KANIMOZHI, M.NANDHINI, & K.SOFIYA (April-2024). ZoneWatch-A Deep Learning Approach to Vehicle Zone Recognition and Speed Management. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), f736-f741. https://ijnrd.org/papers/IJNRD2404589.pdf

Volume 9 Issue 4, April-2024

Pages : f736-f741

Paper Reg. ID: IJNRD_218584

Published Paper Id: IJNRD2404589

Downloads: 000122254

Research Area: Computer Science & Technology 

Author Type: Indian Author

Country: perambalur, Tamilnadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404589.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404589

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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Call For Paper - Volume 10 | Issue 12 | December 2025

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