| Autor: |
Gabriel M. Eggly, José Mariano Finochietto, Matias Micheletto, Roger Pueyo Centelles, Rodrigo Santos, Sergio F. Ochoa, Roc Meseguer, Javier Orozco |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Proceedings, Vol 31, Iss 1, p 38 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2504-3900 |
| DOI: |
10.3390/proceedings2019031038 |
| Popis: |
The response to natural disasters usually requires evacuation procedures that should be followed in a quick and orderly fashion. While census data provide information on the population distribution during sleeping hours, the evacuation procedure may arrive at any moment of the day, even when people are not at home; e.g., in their daily activities. This particular situation causes preparedness plans based on census information to become minimally effective; therefore, more dynamic and context-aware strategies are required to properly address these evacuation processes. In this paper, an evacuation supporting system, based on IoT-networked devices, is proposed to guide people to safe places or shelters once the alert of an extreme event has been issued. The system is interactive and support crowd-sensing; this allows people to upload information on the state of the routes and the shelters, thus keep an updated status of the evacuation routes. The contribution of the paper is twofold. On one side, an evolutionary algorithm is proposed to provide coverage in a breadcrumb deployment of information posts called witness units. On the other, an application based on geographical information system is presented as an intermediary between the witness units and the users; this application guides people towards safe places or shelters. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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