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@article{205897,
        author = {Yash Thakare and Isha Mohite and Sakshi More and Kalyani Pawar and Prof. Priti Malkhede},
        title = {Developing Smart Surveillance System using YOLOv8 and Deep SORT for Real-Time Crowd Monitoring and Behavioral Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {8879-8891},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205897},
        abstract = {Public safety in crowded areas has become an important concern due to increasing population and urbanization. Traditional surveillance systems rely on manual monitoring, which is often inefficient and error-prone. This research proposes a Smart Surveillance System using YOLOv8 and Deep SORT for real-time crowd monitoring, person tracking, and suspicious behavior detection [3], [5]. The system uses YOLOv8 for accurate object detection and Deep SORT for multi-object tracking across video frames [3], [5]. It can monitor crowd movement and identify abnormal activities such as fighting, running, and loitering.},
        keywords = {Smart Surveillance System, YOLOv8, Deep SORT, Crowd Monitoring Object Detection, Behavioral Analysis, Missing Person Detection, Deep Learning, Computer Vision.},
        month = {June},
        }