RT Journal Article
T1 Victim Detection and Localization in Emergencies
A1 Álvarez-Merino, Carlos Simón
A1 Khatib, Emil Jatib
A1 Qiang Luo-Chen, Hao
A1 Barco-Moreno, Raquel
K1 Localización
AB Detecting and locating victims in emergency scenarios comprise one of the most powerful tools to save lives. Fast actions are crucial for victims because time is running against them. Radio devices are currently omnipresent within the physical proximity of most people and allow locating buried victims in catastrophic scenarios. In this work, we present the benefits of using WiFi Fine Time Measurement (FTM), Ultra-Wide Band (UWB), and fusion technologies to locate victims under rubble. Integrating WiFi FTM and UWB in a drone may cover vast areas in a short time. Moreover, the detection capacity of WiFi and UWB for finding individuals is also compared. These findings are then used to propose a method for detecting and locating victims in disaster scenarios.
PB IOAP-MPDI
YR 2022
FD 2022-11-02
LK https://hdl.handle.net/10630/25879
UL https://hdl.handle.net/10630/25879
LA eng
NO Álvarez-Merino, C.S.; Khatib, E.J.; Luo-Chen, H.Q.; Barco, R. Victim Detection and Localization in Emergencies. Sensors 2022, 22, 8433. https://doi.org/10.3390/s22218433
NO This work was performed in the framework of the Horizon 2020 project LOCUS (Grant Agreement Number 871249), receiving funds from the European Union. This work was also partially funded by Junta de Andalucia (Project PY18-4647:PENTA).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026