DOI: 10.17798/bitlisfen.1840155 ISSN: 2147-3129

Bluetooth Low Energy (BLE) based Internet of Things (IoT) Application for Life Detection under Debris

Özlem Şeker, Cennet Akçakaya, Nurullah Akarslan
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Earthquakes represent a major global hazard due to their unpredictable nature and destructive consequences. The rapid and reliable detection of individuals trapped under collapsed structures is a decisive factor that directly influences the effectiveness of search and rescue operations. However, conventional manual search techniques often fall short, particularly in time-critical situations. This study presents a multi-sensor network based on ESP32 microcontrollers that communicates via the Bluetooth Low Energy (BLE) protocol and operates entirely without internet infrastructure, together with an integrated mobile application. The proposed system aggregates data from an infrared (IR) thermal camera, accelerometer, vibration sensor, and passive infrared (PIR) motion detectors through multi-hop BLE Mesh routing, forwards these data to a Raspberry Pi gateway using the Message Queuing Telemetry Transport (MQTT) protocol, and displays them to search and rescue teams in real time via the mobile interface. When a living subject is detected, the mobile application highlights the corresponding area, assisting team navigation and providing real-time vital-signal analyses through its user interface. The developed prototype was evaluated under three representative scenarios, that are unobstructed, partially obstructed, and node-failure conditions. Results showed that sensor fusion produced clear increases in temperature, vibration, and acceleration magnitudes during live tests, while non-live scenarios exhibited a completely static profile. Centroid-based analysis of normalized sensor features demonstrated that the feature-space energy in live cases was approximately 35–50% higher compared to non-live conditions. Regarding communication performance, the BLE Mesh topology remained stable; time-to-live (TTL) values consistently ranged between 6 and 7 hops, and the sustained data transmission rate of 1.5–2.1 kB/s in live scenarios confirmed the robustness of the MQTT communication chain. The findings indicate that the proposed Internet of Things (IoT) based framework can accurately detect living individuals in confined and complex environments following an earthquake, while reliably delivering critical information to search and rescue teams through the mobile application. Furthermore, its infrastructure-independent operation suggests that the system can be readily adapted to other disaster contexts, including floods, landslides, mining accidents, and confined-space emergencies following explosions.

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