Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{205028,
        author = {Mr Swapnil Memane and Mrs Dhage T.S. and Dr Bere S.S.},
        title = {SMART CCTV SURVEILLANCE USING IOT, AI & WEB TECHNOLOGY},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {4811-4822},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205028},
        abstract = {This project proposes an intelligent CCTV surveillance system that combines IoT, AI, and web technologies to allow for monitoring in real time and the identification of anomalous activity.The system employs the YOLO (You Only Look Once) deep learning model to accurately identify objects in video streams obtained from CCTV cameras. Before analysis, the video frames undergo pre-processing steps such as noise reduction, grayscale transformation, and resizing to improve detection efficiency. YOLO allows the simultaneous recognition of multiple objects with high speed and precision, facilitating the timely identification of suspicious or unauthorized behaviors. When any When an abnormality is found, the system immediately notifies authorized personnel by email, SMS, or audio alerts. Testing demonstrates that the system achieves a detection accuracy of 98.3%, making it highly effective for smart city surveillance, industrial security, and public safety applications. By integrating computer vision, AI, and IoT, the system minimizes human intervention while enabling proactive security management.},
        keywords = {Smart CCTV Surveillance, YOLO, Object Detection, Real-time Monitoring, Anomaly Detection, AI-based Security, IoT-enabled Alert System},
        month = {June},
        }