MISSING CHILD DETECTION USING MACHINE LEARNING

Abstract

SafeFind AI is an intelligent facial recognition and surveillance system developed to tackle the global issue of missing child detection and recovery. By integrating artificial intelligence, computer vision, and real-time monitoring, it provides a scalable and highly accurate solution that improves recovery efficiency while reducing critical response time. The system employs Haar Cascade classifiers for fast face detection, dlib’s HOG-based models for balanced accuracy and performance, and Convolutional Neural Networks (CNNs) for precise identification under varying lighting and image conditions.Developed on a Flask-based web framework, SafeFind AI seamlessly connects facial recognition modules, database management, and intelligent alert systems through an intuitive interface. Enhanced image preprocessing techniques, including Contrast Limited Adaptive Histogram Equalization (CLAHE) and adaptive optimization, ensure dependable recognition across surveillance footage, mobile images, and social media content.Core functionalities include real-time monitoring, automated alert generation, GIS-based visual mapping, and API integration with law enforcement systems. Strong data security measures such as encryption, role-based access control, and audit logging ensure privacy and compliance.By automating facial matching and reporting processes, SafeFind AI significantly reduces investigator workload while maintaining high accuracy. This ethical, AI-driven innovation enhances global child protection and accelerates recovery operations.