Scholarlink

This project presents an integrated road safety and monitoring system that combines pedestrian tracking, pothole detection, and traffic sign recognition into a cohesive, real-time solution. Leveraging video feeds from vehicle-mounted or roadside cameras, the system processes each frame through three specialized detection modules. The pedestrian tracking module uses the YOLOv8n model, along with tracking algorithms, to identify and track pedestrians continuously, triggering audio alerts based on proximity and movement speed for enhanced safety. Simultaneously, the pothole detection module, powered by the YOLOv4 model, detects potholes with high accuracy, logging GPS coordinates and issuing alerts to aid in infrastructure maintenance. The traffic sign detection module classifies signs using a pre-trained model and displays the identified signs in a user-friendly interface, allowing users to make informed driving decisions. Together, these subsystems form a comprehensive solution that not only enhances situational awareness for drivers but also provides valuable data for roadway maintenance, ensuring safer and more efficient transportation.

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Smart Road Safety: A Real-Time Framework for Pedestrian, Pothole, and Traffic Sign Detection and Driver Alerting

  • 会议论文

  • 发表日期：

    2026年

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  • Tejashree Yelicherla,
  • Janaki Kandasamy,
  • V. Sai Ujwal,
  • Naga Dheeraj Mukkara

摘要

This project presents an integrated road safety and monitoring system that combines pedestrian tracking, pothole detection, and traffic sign recognition into a cohesive, real-time solution. Leveraging video feeds from vehicle-mounted or roadside cameras, the system processes each frame through three specialized detection modules. The pedestrian tracking module uses the YOLOv8n model, along with tracking algorithms, to identify and track pedestrians continuously, triggering audio alerts based on proximity and movement speed for enhanced safety. Simultaneously, the pothole detection module, powered by the YOLOv4 model, detects potholes with high accuracy, logging GPS coordinates and issuing alerts to aid in infrastructure maintenance. The traffic sign detection module classifies signs using a pre-trained model and displays the identified signs in a user-friendly interface, allowing users to make informed driving decisions. Together, these subsystems form a comprehensive solution that not only enhances situational awareness for drivers but also provides valuable data for roadway maintenance, ensuring safer and more efficient transportation.