DESIGN OF A MULTI-SENSOR LORA-CONNECTED ROBOT FOR HUMAN DETECTION AND NAVIGATION USING ARDUINO AND ESP32-CAM

Abstract

The growing demand for smart home technologies has increased interest in multifunctional robotic systems that support health monitoring, navigation, and cleaning. This study presents the design and development of a semi-autonomous, LoRa-connected robot capable of human detection, environmental monitoring, and vacuum-assisted cleaning. By integrating multiple sensors and enabling wireless control, the system offers a practical solution for home assistance and remote health tracking. The robot was developed using the Experimental Prototyping Methodology. Key components include the YDLIDAR X3 for 360-degree obstacle detection, the MLX90614 infrared sensor for non-contact temperature measurement, the MAX30102 for heart rate and pulse monitoring, and the BME280 for sensing ambient temperature, humidity, and pressure. Real-time video streaming and facial recognition are provided by the ESP32-CAM module. A mini vacuum motor enables cleaning, while two gear motors control movement via a DBH-12 H-Bridge. The system is managed by an Arduino Mega 2560 integrated with an ESP8266 Wi-Fi module. User control is facilitated through a Nextion 3.5-inch touchscreen and the Blynk mobile application. LoRa technology enhances data transmission range and reliability. Testing demonstrated that all sensors performed reliably and produced accurate readings. The LiDAR enabled smooth and effective obstacle avoidance, while the ESP32-CAM delivered stable video streams and successful human detection. Health monitoring sensors recorded consistent pulse and temperature data. The cleaning system functioned as intended, collecting light debris during operation. LoRa connectivity ensured the successful transmission of sensor data over long distances, and user inputs through the touchscreen and Blynk app were responsive and accurate. The robot successfully integrates core functions—navigation, health monitoring, and cleaning—into a cohesive, semi-autonomous platform. The environmental and physiological data collected support practical applications in smart homes, particularly for elderly care, safety, and comfort optimization. With its modular structure and wireless capabilities, the prototype lays the groundwork for the development of more advanced domestic robotics systems in future implementations.