Customized Evacuation Pathfinding through WSN-Based Monitoring in Fire Scenarios 


Vol. 41,  No. 11, pp. 1661-1670, Nov.  2016


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  Abstract

In this paper, we present a risk prediction system and customized evacuation pathfinding algorithm in fire scenarios. For the risk prediction, we apply a multi-level clustering mechanism using collected temperature at sensor nodes throughout the network in order to predict the temperature at the time that users actually evacuate. Based on the predicted temperature and its reliability, we suggest an evacuation pathfinding algorithm that finds a suitable evacuation path from a user’s current location to the safest exit. Simulation results based on FDS(Fire Dynamics Simulator) of NIST for a wireless sensor network consisting of 47 stationary nodes for 1436.41 seconds show that our proposed prediction system achieves a higher accuracy by a factor of 1.48. Particularly for nodes in the most reliable group, it improves the accuracy by a factor of up to 4.21. Also, the customized evacuation pathfinding based on our prediction algorithm performs closely with that of the ground-truth temperature in terms of the ratio of safe nodes on the selected path, while outperforming the shortest-path evacuation with a factor of up to 12% in terms of a safety measure.

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  Cite this article

[IEEE Style]

J. Yoon, Y. Jin, S. Park, H. Lee, "Customized Evacuation Pathfinding through WSN-Based Monitoring in Fire Scenarios," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 11, pp. 1661-1670, 2016. DOI: .

[ACM Style]

JinYi Yoon, YeonJin Jin, So-Yeon Park, and HyungJune Lee. 2016. Customized Evacuation Pathfinding through WSN-Based Monitoring in Fire Scenarios. The Journal of Korean Institute of Communications and Information Sciences, 41, 11, (2016), 1661-1670. DOI: .

[KICS Style]

JinYi Yoon, YeonJin Jin, So-Yeon Park, HyungJune Lee, "Customized Evacuation Pathfinding through WSN-Based Monitoring in Fire Scenarios," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 11, pp. 1661-1670, 11. 2016.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880