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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.

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

  • 会议论文

  • 发表日期：

    2025年

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  • Rishabh Garg,
  • Mehul Chawla,
  • Anupama Bhan,
  • Shubhra Dixit

摘要

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.