Finding Abductors Using AI

Abstract

This project presents a comprehensive backend system designed to assist in the identification and tracking of missing persons and abductors using deep learning and web technologies. The system leverages a Convolutional Neural Network (CNN) model to perform image recognition on uploaded photographs of missing individuals or suspects, enabling automated matching against a stored database of profiles. The backend is built with Flask and integrates PostgreSQL for robust data storage, including user details, case reports, and image records. Authentication mechanisms secure access for general users, victim families, and authorized police personnel. The system supports image uploads, real-time prediction, and retrieval of matched records, enhancing law enforcement's ability to verify cases quickly and accurately. This solution aims to streamline the investigative process, improve data management, and facilitate collaboration between affected families and police authorities.