IoT-Based Sensor Technologies for Object Detection in Low-Visibility Environments: Development and Validation of a Functional Prototype

In emergency scenarios where visibility is compromised, rapid and accurate object detection becomes critical. This study addresses this challenge by proposing an IoT-enabled robotic solution capable of operating in low-visibility environments, with a focus on supporting search and rescue missions through autonomous sensing and real-time data communication. This research presents the development and implementation of an IoT-based sensorized system designed to detect objects in low-visibility environments. The system aims to enhance search and rescue operations by identifying potential human presence in areas with limited access due to smoke, darkness, or hazardous conditions. The platform integrates distance sensors, a thermal camera (AMG8833), a PIR motion sensor, and wireless communication through the Arduino MKR1000 and ESP32-CAM boards. The mobile robot is equipped with obstacle avoidance, person detection, and IoT communication modules, allowing data to be sent to the cloud via ThingSpeak and enabling remote commands through TalkBack. A structured methodology was followed, including technology selection, hardware/software design, and testing under various lighting and opacity conditions. Experimental results showed the effectiveness of the system in identifying obstacles and detecting heat signatures representing human bodies, with optimal performance observed at a 15 cm detection threshold. The system demonstrated robust operation in simulated rescue environments, providing real-time data transmission and remote-control capabilities.