2026-06-01T09:44:17Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/366042026-02-03T10:58:21Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Cantizani-Estepa, Juan author Bravo-Arrabal, Juan author Fernández-Lozano, Juan Jesús author Fortes-Rodríguez, Sergio author Barco-Moreno, Raquel author García-Cerezo, Alfonso José author Mandow, Anthony author 2022 In the field of rescue robotics, data collection about the environment and efficient communications are fundamental for the success of search and rescue missions. Digitalization provides new ways of detecting and localizing potential victims via the wireless devices carried by the users. Nowadays, the number of personal Bluetooth low energy wearables in use (smartbands, smartwatches, earbuds … ) increases constantly, being a yet-to-be-exploited personal radio frequency beacon in the case of an emergency, where the user may not be localized and unconscious. In this paper, the results of experimental tests of a Bluetooth low energy based detection system ported by terrestrial and aerial robots are provided, in order to test the feasibility of such system for the localization of the victims in unknown complex disaster areas. The results show that the tested devices can be reliably detected up to 15 meters away when using transmission power values typical of a smartphone, while being able to detect even lightly burdened devices. These results support the idea of developing an algorithm for the delimitation of areas of interest for the search and rescue groups, influencing the routes followed by the robot with the objective of exploring the detected devices area in the search of victims. J. Cantizani-Estepa et al., "Bluetooth Low Energy for Close Detection in Search and Rescue Missions With Robotic Platforms: An Experimental Evaluation," in IEEE Access, vol. 10, pp. 106169-106179, 2022, doi: 10.1109/ACCESS.2022.3204272. https://hdl.handle.net/10630/36604 10.1109/ACCESS.2022.3204272. Robótica Inteligencia artificial Bluetooth Low Energy for Close Detection in Search and Rescue Missions With Robotic Platforms: An Experimental Evaluation