Enhancing Road Safety And Traffic Management By Leveraging Ai Driven Surveillance, Real-time Monitoring And Automated Violation Detection Using Computer Vision And Iot

• Author(s):

  Shapna Rani E | Eraiarul K | Karthick M | Darwin Shiyam B | Hariharan T

• Keywords:

  Smart Traffic, Computer Vision, Deep Learning, YOLO, CNN, OCR, Traffic Violation.

• Abstract:

  The Smart Traffic Monitoring And Violation Detection System Is An Advanced AI-powered Solution Designed To Revolutionize Traffic Management By Ensuring Real-time Monitoring, Automated Enforcement, And Enhanced Road Safety. Leveraging Computer Vision, Deep Learning, And IoT-based Surveillance, The System Intelligently Detects Violations Such As Helmetless Riding, Signal Jumping, With Exceptional Accuracy. High-resolution Cameras Continuously Capture Live Traffic Feeds, While OCR Technology Extracts Vehicle Number Plate Details For Instant Offender Identification. With YOLOv11 For Object Detection And Convolutional Neural Networks (CNNs) For Number Plate Recognition, The System Achieves Precise And Efficient Violation Detection. Upon Detection, Automated SMS Alerts Are Dispatched To Violators, Providing Fine Details And Enforcement Actions. Integrated With RTO Databases, It Tracks Repeat Offenders, Issuing Escalating Penalties, Including Potential Registration Cancellation For Persistent Violations. By Eliminating Manual Intervention, This System Optimizes Traffic Law Enforcement, Reduces Human Workload, And Ensures Seamless, Technology-driven Compliance. The Fusion Of Real-time AI Processing, Automated Data Retrieval, And Instant Penalty Notification Transforms Traffic Monitoring Into A Smart, Proactive, And Efficient System, Significantly Improving Urban Mobility And Road Discipline While Minimizing Accidents And Fatalities.

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Other Details

• Paper id:

  IJSARTV11I5103439

• Published in:

  Volume: 11 Issue: 5 May 2025

• Publication Date:

  2025-05-02

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