A Deep Dive into Traffic Sign and Lane Monitoring Systems

A Deep Dive into Traffic Sign and Lane Monitoring Systems

Dr. Vinod Desai Associate Professor,

Computer Science and Engineering Sai Vidya Institute of Technology Bengaluru, Karnataka, India vinod.desai@saividya.ac.in

Sowmya H N Assistant Professor,

Computer Science and Engineering Sai Vidya Institute of Technology Bengaluru, Karnataka, India sowmya.hn@saividya.ac.in

Suprit U

Computer Science and Engineering Sai Vidya Institute of Technology Bengaluru, Karnataka, India supritu.22cs@saividya.ac.in

Kushaal A Kumar Computer Science and Engineering Sai Vidya Institute of Technology

Bengaluru, Karnataka, India kushaalakumar.22cs@saividya.ac.in

Chandana U

Computer Science and Engineering Sai Vidya Institute of Technology Bengaluru, Karnataka, India chandanau.22cs@saividya.ac.in

Bhoomika C

Computer Science and Engineering Sai Vidya Institute of Technology Bengaluru, Karnataka, India bhoomikac.22cs@saividya.ac.in

Abstract — This project focuses on developing an IoT and AI-based Driver Assistance System to enhance road safety through the real-time identification and monitoring of vehicles, obstacles, and hazards. The system includes continuous lane positioning, traffic sign recognition, and potential hazard identification using IoT sensors and AI algorithms. A significant improvement is the provision of real-time notifications, enabling the driver to minimize the risk of accidents by responding to identifiable dangers with minimal distraction. The system employs computer vision for lane detection, utilizes YOLOv5 for traffic sign detection, and incorporates Arduino-controlled sensors for obstacle detection. This adaptive solution aligns with smart-city agendas, facilitating data-oriented road safety solutions and integrating easily into existing traffic management systems. Future upgrades may include enhancements in security features and expanded functionality.