Advancing Sustainable Security: AI-Driven Embedded Hardware for Mobile Robotics

Advancing Sustainable Security: AI-Driven Embedded Hardware for Mobile Robotics

연구 분야: Infrastructure

학회: International Conference on Sustainable Development through Machine Learning, AI and IoT

Using AI-driven embedded hardware in mobile robotics, this research proposes a novel way to increase security. YOLO (You Only Look Once) object detection is used by the integrated system, which consists of a Raspberry Pi, an ESP32 microcontroller, and an L298 motor driver, for real-time tracking and identification. Unlike traditional motion detection, our approach prioritizes accurate object recognition to improve security monitoring. Through a Flask-based UI, users may remotely control the robot by utilizing WebSocket communication. The system’s efficacy in decreasing false positives and enhancing total object detection rates is demonstrated by experimental findings, which highlight the combination of artificial intelligence, robotics, and embedded technologies to provide intelligent security solutions.