JEDDAH: King Abdulaziz University has completed an innovative research project that uses artificial intelligence to monitor violations of emergency lanes on highways in real time.
The project was carried out by a student-led team under the supervision of Department of Geomatics faculty members Kamel Faisal, Abdullah Al-Attas, Muhannad Abu-Hashem and Mahmud Al-Koffash, the Saudi Press Agency reported.
The project employs the YOLO algorithm. YOLO, which stands for You Only Look Once, is a real-time object detection algorithm known for its speed and efficiency.
The algorithm works detecting objects directly from an input image, as opposed to older methods which required multiple passes. This approach significantly speeds up the detection process.
The system uses the Raspberry Pi device, a cost-effective mini computer that employs advanced vision techniques.
According to Saudi Press Agency, the project is highly efficient, making it well-suited for smart city applications, traffic authorities and government agencies.
It has the potential to contribute to improving emergency response times and saving lives by ensuring emergency lanes remain unobstructed.
The model was trained using custom image datasets, with specific video Regions of Interest defined to identify any violations by vehicles.
Geomatics, the academic field behind the project, focuses on the science and technology of digital geographic data.
This includes urban surveying, spatial information systems, and is also referred to as “geospatial data science” or “digital surveying engineering.”
It encompasses the collection, processing, analysis, visualization, and mapping of all types of geographic information, as well as the measurement and management of geospatial data.
Ƶ currently utilizes a number of AI technologies to manage the country’s road traffic and improve safety.
The Sawaher system is a national platform designed to analyze streams of images and videos from public roads and provide real-time insights.
Another system, the Smart C platform, uses data to help decision-making in infrastructure projects.
