Safebot-Intelligent Patrol System for Realtime Safety Monitoring

Public safety in urban and semi-urban environments continues to face significant challenges due to limited surveillance coverage, slow emergency response, and inefficient monitoring mechanisms. Existing security systems largely rely on fixed cameras and manual supervision, which often delay the detection of suspicious activities or potential threats. To overcome these limitations, this paper presents SafeBot, an autonomous patrol robot designed to deliver intelligent, real-time safety monitoring. SafeBot integrates Artificial Intelligence (Al), Internet of Things (IOT) technology, GPS-based location tracking, and sensor-driven navigation to enhance situational awareness and responsiveness. The system employs deep learning—based emotion recognition models capable of identifying emotional states such as fear, stress, and distress, enabling early recognition of emergency situations. Accurate location tracking is achieved through GPS modules, while 10T connectivity facilitates automatic email alerts to relevant authorities during critical events. Obstacle detection sensors support safe and autonomous navigation, and solar-powered components ensure continuous and energy-efficient operation. The proposed system demonstrates improved response time, enhanced monitoring capability, and reliable performance across various environments, including educational campuses, office premises, and public spaces.