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@article{173812,
        author = {Divya Mahale and Sulakshana Malwade},
        title = {Fall And Gesture Detection Using Smart Sentinel},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {1629-1637},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173812},
        abstract = {Smart Sentinel is an AI-powered activity detection system based on computer vision technology to monitor homes, workplaces, and community areas. By processing the video feeds, the system identifies incidents such as health emergencies requiring immediate attention. It mainly relies on fall detection and gesture recognition for assessing incident severity. 
Once a fall is detected, the system waits for some time to ensure the fall needs attention before it sends out notifications to authorities. If the subject is okay, then they can gesture thumbs up to let Smart Sentinel know all is okay and no help is needed. This combination of fall detection and gesture detections can dramatically reduce false positives and make the system more dependable. 
With enhancements in computer vision technology, it is now feasible to build fall detection and gesture detection models with adequate accuracy. The system is useful in addressing needs in security, health monitoring, and community assistance domains.},
        keywords = {Artificial Intelligence, Machine Learning, Activity Detection, Fall Detection and Gesture Detection},
        month = {March},
        }