AI-enabled smart surveillance system for secure monitoring and authentication

The proposed Smart Surveillance System presents a novel, hardware-integrated prototype demonstration aimed The proposed Smart Surveillance System presents a groundbreaking hardware-integrated prototype that decisively validates the effectiveness of a dual-branch anti-spoofing model on the low-power edge device, Raspberry Pi 3B+. This prototype goes beyond algorithmic performance research, showcasing a fully functional proof of concept. In contrast to existing surveillance solutions that typically rely on centralized cloud processing or basic recognition systems, our system employs an advanced dual-branch model that utilizes both spatial and frequency-domain features. This approach enables real-time anti-spoofing with an impressive error rate of less than 2%. What truly sets our system apart is its seamless end-to-end integration of cloud-based authentication, edge-level inference for rapid response, and an interactive live video conferencing feature. This configuration empowers immediate verification and action during potential spoofing events. With IoT-enabled devices, our system ensures effortless communication for live streaming, automated alerts, and scalable cloud data management. Coupled with edge computing, it guarantees real-time decision-making with minimal latency. Experimental results confirm its high accuracy in distinguishing genuine users from spoofing attempts, positioning our solution as a lightweight, proactive, and user-interactive surveillance option that is perfectly suited for homes, enterprises, and public infrastructures.