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Subject: search.filters.subject.YOLOv8

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    Bovitrack:Animal behavior monitoring using Machine learning and IoT
    (Institute of Electrical and Electronics Engineers Inc., 2025) Viraj, H; Wijesekara, S; Tharuka, K; Fernando, S; Jayakody, A; Wijesiri, P
    Analyzing dairy cattle behavior and anomalies is a critical component of precision livestock farming, allowing farmers to remotely monitor animals for health and behavior. In order to accomplish this task better, the use of IoT technology and machine learning algorithms is more appropriate as per the time. The YOLO (you only look once) object recognition algorithm is more suitable for that, and the use of this algorithm allows these processes to be performed automatically and in real time with high accuracy. YOLO's ability to recognize multiple objects in images or videos makes Yolo ideal for cattle detection and tracking.
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    PublicationOpen Access
    AI-Based Smart Traffic Management System for Emergency Vehicles
    (SLIIT City UNI, 2025-07-08) Amarasinghe, D P S V; Benorith, L
    Modern cities' main traffic congestion problem delays emergency vehicles like ambulances and firetrucks and police cars where every second counts. Fixed signal traditional traffic systems lack real-time adaptability, hence delays and risks are raised. This paper suggests an AI-driven smart traffic management system to priorities emergency vehicles and enhance general traffic flow by means of Raspberry Pi, YOLOv8, and OpenCV. Strategically positioned cameras provide video to a Raspberry Pi, which detects emergency vehicles by using OpenCV and YOLOv8. Dynamic control of traffic lights on detection helps to clear the path, so reducing response times and improving safety. The technology also maximizes road use and helps to ease traffic. For cities with limited infrastructure, using reasonably priced, open-source tools are scalable and ideal.