Implementation of YOLOv8 in Object Recognition Systems for Public Area Security in Kebun Raya Bogor - Prihandoko, Prihandoko; Rumapea, Sri Agustina; Fawwaz, Muhamad Faishal (Faculty of Engineering and Informatics, Universitas Multimedia Nusantara, 2025)
Pedestrian areas often serve as centers of high public activity, requiring intelligent monitoring systems to ensure the safety and comfort of their users. The application of computer vision technology, particularly object detection, offers a promising approach for identifying and estimating the number of individuals in open public spaces. This study implements the YOLOv8 algorithm to develop a human detection and crowd counting model within the pedestrian zones of the Bogor Botanical Garden. Data were collected in the form of images and videos from three strategic locations and annotated using Roboflow with a single object class labeled