Situational awareness in smart environments: socio-mobile and sensor data fusion for emergency response to disasters

System architecture Experimental results AViReS Laboratory University of Udine, Italy Conferenza del Dottorato di Ricerca in Ingegneria Industriale e dell’Informazione | 26 Giugno 2014 | Udine, Italia Traditional situational awareness services in disaster management are mainly focused on the institutional warning response and not fully exploit the active participation of citizens involved. This work presents an Advanced SYstem for Emergency Management (ASyEM) which fuses the potentiality offered by mobile social data and bottom-up communication with smart sensors. The proposed architecture model is organized into four different layers: 1) sensor, 2) local transmission, 3) network and 4) management. ASyEM is able to capture and aggregate two different kind of data: a) user generated content (UGC) produced by citizens during or immediately after the disaster and shared online through socio-mobile applications and b) data acquired by smart sensors distributed on the environment (i.e., intelligent cameras, microphones, acoustic arrays, etc.). Data are selected, analysed, processed and integrated in order to increase the reliability and the efficiency of whole situational awareness services, localize the critical areas and obtain in this way some relevant information for emergency response and completion of search and rescue operations. The logical architecture of ASyEM (Figure 1) is constituted by four layers: 1) sensor, 2) local transmission, 3) network and 4) management. In particular, at the sensor layer, input data are acquired from different kind of sensors and, at the local transmission layer, data are pre-processed (e.g., compressed, etc.), collected and passed to the network layer who is in charge of sending them to a remote control centre. Finally, at the management layer, all sensor data are processed, fused and used to generate a situational awareness and suggest to the operators a planning of the emergency responses to be activated. Data Fusion Module UCG Analysis Audio and Video Analysis 0 10 20 30 40 50 60 70 80 Hearthquake Shake Collapse Magnitude Percentage of keywords 84% 11% 5% Percentage of success Success Failure No classification Test scenario UCG Analysis results Several experiments have been carried out to evaluate ASyEM in the context of an emergency situation caused by an earthquake. Tests have been classified into two main groups: 1) tests performed during the event and 2) tests performed after the event. The first set of tests would demonstrate the capability of ASyEM to autonomously detect an earthquake event. Some audio and video data recorded during the 2009 L’Aquila earthquake were used as input of the system. Instead, the second test set makes use of UGC from different social platforms (therefore after the event) to confirm the disaster event and locating its consequences on a top view map of the area. The results emerged from our test scenario are promising. Taken together, the data generated by environmental sensors (optical and infrared cameras, microphones, etc.) and the data generated by citizens via socio-mobile applications were able to provide an accurate visualization of the disaster Work in collaboration with Manuela Farinosi, Department of Human Sciences, University of Udine – [email protected] G. L. Foresti, M. Farinosi, M. Vernier, (2014) "Situational awareness services in smart environments: socio-mobile and sensor data fusion for emergency response to disasters, Journal of Ambient Intelligence and Humanized Computing", Journal of Ambient Intelligence and Humanized Computing, pp 1 -19