Enhancing Wireless Surveillance Robot with Real-Time Feedback with AI & IOT Integration

This paper presents the design and implementation of an advanced wireless surveillance robot equipped with real-time feedback capabilities. The system utilizes a combination of hardware components such as Arduino Mega, ESP32-CAM, and sensors, along with software applications including Arduino IDE, Anaconda, and Telegram, to achieve its functionality. The robot is capable of capturing high-resolution images, providing live video feedback, detecting faces using machine learning algorithms, and sending alerts in case of emergencies. The integration of IoT technologies enables remote monitoring and control of the robot's movements and functions via web-based interfaces. The paper discusses the hardware setup, software requirements, design, and implementation steps involved in building the surveillance robot. Furthermore, simulation outputs and experimental results demonstrate the effectiveness and performance of the system in real-world scenarios. Finally, the paper concludes with suggestions for future enhancements, including AI integration for object detection, improved navigation using GPS and compass, and additional features for remote control via Telegram bot. This research paper provides insights into the design, implementation, and performance evaluation of an advanced wireless surveillance robot. It serves as a valuable resource for researchers, engineers, and enthusiasts interested in exploring the potential of IoT-based surveillance systems for various applications, including security, monitoring, and remote sensing.