IOT Based Missing Person Detection System

This paper presents the design and implementation of an Internet of Things (IoT)-based Missing Person Detection System aimed at improving the efficiency and accuracy of locating missing individuals in real-time. The proposed system integrates a Raspberry Pi 3B+ with a Pi camera module, GPS technology, and face recognition algorithms to continuously monitor and identify individuals in public and crowded environments. The captured images are processed using image processing techniques to detect and recognize human faces, which are then compared with a prestored database of missing persons. Upon successful identification, the system instantly generates alerts and transmits location details to concerned authorities and family members through IoTenabled communication channels, ensuring rapid response and action. Additionally, the system incorporates geo-fencing capabilities and can be extended with mobile application integration for enhanced accessibility and user interaction. The proposed solution is cost-effective, portable, and scalable, making it suitable for deployment in various real-world scenarios such as railway stations, malls, and public gatherings. By leveraging IoT and automation, the system significantly reduces manual search efforts, increases recovery rates, and enhances public safety. Furthermore, the model can be improved with advanced artificial intelligence and deep learning techniques to achieve higher accuracy and broader surveillance coverage in future implementations.