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@article{186110,
        author = {Bhagyashri Babasaheb Fulari and Sarika Devidas Gadhe and Aditi Subhash Khamkar and Pratima Bhagwan Devikar and Nikhil Deshpande},
        title = {AI-Powered Lost Child Detection System using Facial Recognition and Behavior Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1863-1865},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186110},
        abstract = {The growing number of incidents involving missing children emphasizes how urgently intelligent and automated solutions are needed to facilitate prompt recovery and identification. Finding missing children using manual methods takes a lot of effort and is frequently unreliable, especially in busy public places. The creation of an AI-powered lost child detection system that combines facial recognition and behavioral emotion analysis to improve detection accuracy and response time is suggested in this research as a solution to this problem. The suggested system automatically detects and recognizes children's faces in real time using surveillance camera feeds, then compares them with a centralized database of missing children. By identifying anguish or terror, emotion recognition helps authorities prioritize high-risk cases. After a successful identification, the system also seeks to instantly notify administrators, parents, and law enforcement. This study describes the architecture, data flow, and module interactions with an emphasis on the design and methodology phase. The AI model will be implemented, trained, and its performance assessed in real-world situations in subsequent work.},
        keywords = {AI, Computer Vision, Facial Recognition, Lost Child Detection, Emotion Analysis, Deep Learning, CNN, YOLO},
        month = {November},
        }