Automated Detection and Identification of Missing Person Using AI

Abstract: Every year, millions of people, including children and adults, go missing due to a range of causes such as abduction, natural disasters, accidents, and voluntary disappearances. The issue of missing persons is a significant and growing problem that affects individuals, families, and entire communities around the world. The Missing Person Finder project depicts the idea of automating the process of locating missing individuals by combining web technologies, computer vision, and deep-learning. The web portal built using Python Flask, allows families and law enforcement to upload details and photos of missing persons. The system processes CCTV footage with OpenCV to extract frames, which are analyzed by a deep learning face recognition model to identify potential matches. Notifications are sent to relevant parties when a match is found, enabling prompt action. By automating video analysis, the system significantly reduces the time and effort required for manual reviews, improving search efficiency and accuracy. Public engagement is encouraged through the portal, where users can view missing person profiles and report sightings. Integration with national or regional databases broadens the search network, enhancing the chances of finding matches. This innovative tool offers a comprehensive approach to addressing the critical issue of missing persons, benefiting families, law enforcement, and the wider community. Keywords: Deep Learning, Image & Video Processing, Web Portal, Facial Recognition