Paper
2 May 2017 Sensor data monitoring and decision level fusion scheme for early fire detection
Constantinos Rizogiannis, Konstantinos Georgios Thanos, Alkiviadis Astyakopoulos, Dimitris M. Kyriazanos, Stelios C. A. Thomopoulos
Author Affiliations +
Abstract
The aim of this paper is to present the sensor monitoring and decision level fusion scheme for early fire detection which has been developed in the context of the AF3 Advanced Forest Fire Fighting European FP7 research project, adopted specifically in the OCULUS-Fire control and command system and tested during a firefighting field test in Greece with prescribed real fire, generating early-warning detection alerts and notifications. For this purpose and in order to improve the reliability of the fire detection system, a two-level fusion scheme is developed exploiting a variety of observation solutions from air e.g. UAV infrared cameras, ground e.g. meteorological and atmospheric sensors and ancillary sources e.g. public information channels, citizens smartphone applications and social media. In the first level, a change point detection technique is applied to detect changes in the mean value of each measured parameter by the ground sensors such as temperature, humidity and CO2 and then the Rate-of-Rise of each changed parameter is calculated. In the second level the fire event Basic Probability Assignment (BPA) function is determined for each ground sensor using Fuzzy-logic theory and then the corresponding mass values are combined in a decision level fusion process using Evidential Reasoning theory to estimate the final fire event probability.
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Constantinos Rizogiannis, Konstantinos Georgios Thanos, Alkiviadis Astyakopoulos, Dimitris M. Kyriazanos, and Stelios C. A. Thomopoulos "Sensor data monitoring and decision level fusion scheme for early fire detection", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000S (2 May 2017); https://doi.org/10.1117/12.2266024
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Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Flame detectors

Humidity

Web 2.0 technologies

Monte Carlo methods

Infrared sensors

Infrared cameras

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