Improvements in telecommunications and digitalization directly improve the efficacy of a wide variety of processes. Recently, detection systems have received considerable attention because of the importance of tracking infected people contacts during SARS-CoV-2 pandemic. Such implementations can be useful in the task of finding potential victims in the context of emergency response, especially in situations where GPS is not available or inspection by imaging is not practical. Radio signals come into play, and specifically from devices that transmit periodically and with low power consumption. With the rise of Internet of Things over the last years, the number of wearable devices that support BLE, such as smartbands, smartwatches or smartphones, has been increasing constantly, as well as the number of users that carry them. Those devices can provide considerable assistance in locating injured or unconscious people. This work presents a system for detecting victims by means of a terrestrial search and rescue (SAR) robot. A real implementation of a close detection robotic platform based on BLE for SAR interventions is laid out. To estimate the distance between a robotic agent and potential victims within an experimental area, a Log-distance path loss model is presented. The proposed scheme has been tested in realistic scenarios during SAR exercises.This work was partially funded by the Spanish project RTI2018-093421-B-I00. It has been also performed in the framework of the Horizon 2020 project LOCUS (ICT-871249) receiving funds from the European Union. This work has been also partially funded by Junta de Andalucía and ERDF projects: Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Proyecto de Excelencia PENTA, P18-FR-4647; postdoctoral grant (Ref., DOC 01154, “selección de personal investigador doctor convocado mediante Resolución de 21 de mayo de 2020”, PAIDI 2020) and the I Plan Propio de Investigación, Transferencia y Divulgación Científica of the University of Málaga.
The authors want to thank the collaboration of the Chair for Safety, Emergencies and Disasters of the University of Malaga, led by Prof. Jesús Miranda, as well as Javier Serón Barba for his support during the experiments.
Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
