AI-Powered System to Monitor Emergency Lane Violations in Real Time

King Abdulaziz University has successfully developed an innovative AI-driven system designed to monitor violations of emergency lanes on highways in real time.

This advanced project leverages the Raspberry Pi device and employs sophisticated computer vision techniques.

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Key Features of the System

Technology and Methodology

• Detection Algorithm: The system utilizes the YOLO (You Only Look Once) algorithm to detect vehicles encroaching on designated emergency lanes.
• Custom Dataset: The model is trained on a customized dataset of images, enhancing its accuracy in identifying violations.

Cost-Effective Solution

• The system is designed to be low-cost and highly efficient, making it suitable for integration into:
  • Smart city infrastructures
  • Traffic management agencies
  • Government authorities

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Objectives and Benefits

• Improving Emergency Response: By ensuring unobstructed emergency lanes, the project aims to improve response times during emergencies, ultimately saving lives.
• Innovative Traffic Management: This system represents a step forward in leveraging technology for better traffic management and public safety on highways.

The implementation of this AI-powered monitoring system reflects a commitment to enhancing road safety and efficiency in emergency response.

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