Autonomous Warehouse Survelliance Bot

In recent years, the demand for efficient warehouse management systems has increased significantly. To address this need, we present an innovative solution: an Autonomous Warehouse Surveillance Bot equipped with advanced functionalities for navigation, person detection, and warning system integration. The core components of the system include an Arduino Mega microcontroller, an LSA08 infrared sensor for lane detection, a Nema17 stepper motor for locomotion, and an A4988 stepper motor driver for precise control. The bot utilizes lane detection algorithms to navigate autonomously within the warehouse environment, ensuring efficient and safe movement. Additionally, an IP web camera is employed for real-time person detection. When an unidentified individual is detected, the system cross-references the person’s image with a pre-defined database. If the individual is not recognized, the bot triggers a warning system, alerting relevant personnel to the potential security breach. This research paper provides a comprehensive overview of the design, implementation, and performance evaluation of the Autonomous Warehouse Surveillance Bot. We discuss the hardware architecture, software algorithms, and integration of key components. Furthermore, experimental results demonstrate the effectiveness and reliability of the system in real-world warehouse scenarios. Overall, our solution offers a promising approach to enhancing warehouse security and efficiency through autonomous surveillance technology. By combining navigation, person detection, and warning systems, the Autonomous Warehouse Surveillance Bot represents a significant advancement in warehouse management solutions.