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Proceedings Paper

Fire detection and incidents localization based on public information channels and social media
Author(s): Konstantinos-Georgios Thanos; Katerina Skroumpelou; Konstantinos Rizogiannis; Dimitris M. Kyriazanos; Alkiviadis Astyakopoulos; Stelios C. A. Thomopoulos
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Paper Abstract

In this paper a solution is presented aiming to assist the early detection and localization of a fire incident by exploiting crowdsourcing and unofficial civilian online reports. It consists of two components: (a) the potential fire incident detection and (b) the visualization component. The first component comprises two modules that run in parallel and aim to collect reports posted on public platforms and conclude to potential fire incident locations. It collects the public reports, distinguishes reports that refer to a potential fire incident and store the corresponding information in a structured way. The second module aggregates all these stored reports and conclude to a probable fire location, based on the amount of reports per area, the time and location of these reports. In further the result is entered to a fusion module which combines it with information collected by sensors if available in order to provide a more accurate fire event detection capability. The visualization component is a fully – operational public information channel which provides accurate and up-to-date information about active and past fires, raises awareness about forest fires and the relevant hazards among citizens. The channel has visualization capabilities for presenting in an efficient way information regarding detected fire incidents fire expansion areas, and relevant information such as detecting sensors and reporting origin. The paper concludes with insight to current CONOPS end user with regards to the inclusion of the proposed solution to the current CONOPS of fire detection.

Paper Details

Date Published: 2 May 2017
PDF: 16 pages
Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000T (2 May 2017); doi: 10.1117/12.2266027
Show Author Affiliations
Konstantinos-Georgios Thanos, National Ctr. for Scientific Research Demokritos (Greece)
Katerina Skroumpelou, National Ctr. for Scientific Research Demokritos (Greece)
Konstantinos Rizogiannis, National Ctr. for Scientific Research Demokritos (Greece)
Dimitris M. Kyriazanos, National Ctr. for Scientific Research Demokritos (Greece)
Alkiviadis Astyakopoulos, National Ctr. for Scientific Research Demokritos (Greece)
Stelios C. A. Thomopoulos, National Ctr. for Scientific Research Demokritos (Greece)


Published in SPIE Proceedings Vol. 10200:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI
Ivan Kadar, Editor(s)

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