Regardless of the extensive research conducted on large-scale evacuations, the instrumentation of these processes still represents an open issue for first response organizations. Self-evacuation of civilians that follows evacuation plans has shown to be feasible as early response to several natural disasters; however, the typical lack of interaction capability of the evacuees with first response organizations and emergency managers jeopardizes the effectiveness of these processes. This article proposes an IoT-based infrastructure that supports self-evacuation of civilians in mass processes, allowing people to participate as information providers and consumers. This infrastructure is the backbone of an ambient intelligence system used as a bridge between evacuees, first response units, and the emergency operation center managing the process. Depending on the people location and the status of the area, the system implements breadcrumbs that guide people to shelters and safe places. The proposed infrastructure includes (1) an architecture that captures the core design aspects of the solution and makes it reusable for other researchers, (2) an implementation of the system based on Raspberry Pi 3 devices with LoRa radio connectivity, (3) a mobile application that allows evacuees to interact with the evacuation system, and (4) a simplified algorithm to support the deployment of the IoT-based infrastructure into an urban area. The solution was evaluated using real measurements and simulations, and the obtained results are highly encouraging.
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This work was partially funded by the Spanish Government under contract PID2019-106774RB-C21, the Spanish State Research Agency (AEI) under contracts PCI2019-111850-2 and PCI2019-111851-2 and the Generalitat de Catalunya as Consolidated Research Group 2017-SGR-990.
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Finochietto, J.M., Micheletto, M., Eggly, G.M. et al. An IoT-based infrastructure to enhance self-evacuations in natural hazardous events. Pers Ubiquit Comput (2021). https://doi.org/10.1007/s00779-020-01506-z
- IoT-Based infrastructure
- Ambient intelligence system
- Large-scale self-evacuations
- Participation of civilians
- Human sensors
- Natural disasters