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Abstract: Manual procedures and disjointed data frequently impede down the tracking and recovery of missing persons. By using a PyQT5-based GUI for case registration and safe data storage in a PostgreSQL database, this solution enhances identification. Through a mobile app, members of the public can anonymously share photographs. By comparing user-submitted photos with stored face encodings, the AdaBoost KNN algorithm improves matching accuracy. The process of finding missing people is greatly accelerated by automating case registration and image matching. By overcoming the shortcomings of conventional approaches in missing person investigations, this system expedites the recovery of missing persons, boosts efficiency, enhances public involvement, and protects privacy.