In the Internet of Things (IoT) era, autonomous mobile robots have been widely utilized across various domains, including security surveillance, hazardous environment detection, warehouse logistics, and automated distribution systems. They have crucial roles in enhancing operational efficiency, reducing human intervention, and improving safety. However, one of the primary challenges of autonomous mobile robots is their reliance on built-in batteries, which deplete rapidly during continuous operation, causing system downtime and interrupting critical tasks such as real-time and security tracking. This research proposes a home security system that employs radio frequency identification (RFID) technology in conjunction with computer vision (CV) to address the current issue and incorporates smart navigation to ensure the system operates stably at all times. The system leverages RFID technology for precise contact with the charging station (97% success rate), while CV enhances real-time monitoring and threat detection. Additionally, an innovative self-charging mechanism allows the robot to independently proceed to a charging station when battery levels fall below a certain threshold. A co-design approach enhanced the interaction between hardware and software components, resulting in highly accurate object detection (98%) and efficient energy management (7%).