Enhancing Security: A Haar Cascade-based Face Recognition System for PGs and Hostels

This work introduces an innovative security system prototype tailored explicitly for paying guest accommodations or hostels, blending Internet of Things (IoT), artificial intelligence (AI), machine learning algorithms, and web crawling technologies. The core emphasis revolves around facial recognition, precisely distinguishing between known and unknown individuals to manage entry effectively. The system, integrating camera technology, captures visitor images and employs advanced face recognition algorithms for precise face classification. In instances where faces remain unrecognized, the system leverages web crawling to retrieve potential intruder details. Immediate notifications, featuring captured images, are swiftly dispatched to users through email and smartphone alerts, enabling prompt responses. Operated within a wireless infrastructure governed by a Raspberry Pi, this system prioritizes cost-effectiveness and user-friendliness. Rigorously tested across diverse environments encompassing homes, paying guest accommodations, and office spaces, this research establishes a remarkable balance between cutting-edge technology and pragmatic security applications. This solution offers an affordable and efficient security option tailored explicitly for the unique needs of contemporary hostels and paying guest accommodations, ensuring heightened security without exorbitant expenses.