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Applying UAVs for indoor emergency risk evaluation
This study deals with the adoption of UAVs in the case of indoor fires. UAVs map the indoor space before the rescue team arrival in order to minimize the risk of exposure to firefighters, maximize the effectiveness of their intervention and provide information to the evacuees. We develop a framework in which first we compute the drone trajectory that minimizes the number of sacrificed detection points; next, we derive the value of risk associated with each monitored point, evaluated through the main dangerous products of a fire (i.e. smoke, temperature and carbon monoxide). After that, we match the pedestrian path with the environment risk analysis and finally, the lowest risk pedestrian paths are generated both for evacuees and rescue operators, respectively toward the exits and the ignition point(s). Preliminary results are shown for a real-case indoor space, simulated using a synthetic environment generator.
Applying UAVs for indoor emergency risk evaluation
This study deals with the adoption of UAVs in the case of indoor fires. UAVs map the indoor space before the rescue team arrival in order to minimize the risk of exposure to firefighters, maximize the effectiveness of their intervention and provide information to the evacuees. We develop a framework in which first we compute the drone trajectory that minimizes the number of sacrificed detection points; next, we derive the value of risk associated with each monitored point, evaluated through the main dangerous products of a fire (i.e. smoke, temperature and carbon monoxide). After that, we match the pedestrian path with the environment risk analysis and finally, the lowest risk pedestrian paths are generated both for evacuees and rescue operators, respectively toward the exits and the ignition point(s). Preliminary results are shown for a real-case indoor space, simulated using a synthetic environment generator.
Applying UAVs for indoor emergency risk evaluation
Mannini, Livia (Autor:in) / Nigro, Marialisa (Autor:in) / Sama, Marcella (Autor:in)
14.06.2023
954836 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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