Design and Implementation of an Autonomous Reconnaissance Vehicle Integrating Embedded Systems, IoT Sensor Fusion, and Wireless Data Transmission

This paper presents the design, development, and evaluation of a Reconnaissance Automatic Control Vehicle (RACV) — an autonomous mobile robotic platform integrating embedded control systems, environmental sensor fusion, computer vision, and wireless IoT data transmission for real-time environmental monitoring and reconnaissance. The system architecture employs a Raspberry Pi 4 Model B as the central processing unit, supported by an STM32 microcontroller for motor control and an ESP32 microcontroller for environmental data acquisition and wireless communication. Navigation capabilities include line following via a 4-channel infrared sensor module with PID-based closed-loop control, and obstacle detection and avoidance using ultrasonic sensor feedback. Environmental monitoring is achieved through the integration of a DHT11 temperature and humidity sensor and an MQ-2 gas sensor, with data transmitted in real-time to a remote web dashboard over Wi-Fi using HTTP protocol and JSON data formatting. Performance evaluation demonstrated high navigation accuracy with minimal line deviation, consistent obstacle avoidance across varied terrain conditions, reliable sensor readings with low noise impact, and efficient real-time data transmission with minimal packet loss. The results validate the feasibility of integrating autonomous navigation, multi-sensor environmental monitoring, and IoT communication in a single low-cost embedded platform — with implications for applications in disaster response, agricultural monitoring, industrial surveillance, and environmental analysis.