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http://dx.doi.org/10.6109/jkiice.2019.23.10.1248

Emergency Rescue Guidance Scheme Using Wireless Sensor Networks  

Joo, Yang-Ick (Division of Electronics and Electrical Information Engineering, Korea Maritime & Ocean University)
Abstract
Using current evacuation methods, a crew describes the physical location of an accident and guides evacuation using alarms and emergency guide lights. However, in case of an accident on a large and complex building, an intelligent and effective emergency evacuation system is required to ensure the safety of evacuees. Therefore, several studies have been performed on intelligent path finding and emergency evacuation algorithms which are centralized guidance methods using gathered data from distributed sensor nodes. However, another important aspect is effective rescue guidance in an emergency situation. So far, there has been no consideration on the efficient rescue guidance scheme. Therefore, this paper proposes the genetic algorithm based emergency rescue guidance method using distributed wireless sensor networks. Performance evaluation using a computer simulation shows that the proposed scheme guarantees efficient path finding. The fitness converges to the minimum value in reasonable time. The density of each exit node is remarkably decreased as well.
Keywords
Rescue; Sensor Network; Genetic Algorithm; Emergency Situation;
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1 S. H. Ok, J. H. Ahn, S. H. Kang, and B. I. Moon, "A combined heuristic algorithm for preference-based shortest path search," Journal of The Institute of Electronics Engineers of Korea, vol. 47, no. 8, pp. 74-84, 2010 (in Korean).
2 M. B. Kang, G. Park, S. H. Yim, and Y. I. Joo, "Design of optimal evacuation route guidance system for accidents on board the ship," in Proceedings of the 40th KOSME Spring Conference, pp. 158, 2016 (in Korean).
3 M. B. Kang, and Y. I. Joo, "Intelligent evacuation systems for accidents aboard a ship," Journal of the Korean Society of Marine Engineering, vol. 40, no. 9, pp. 824-829, 2016 (in Korean).   DOI
4 Y. K. Kim, B. S. Yun, and S. B. Lee, Meta-Heuristic, YoungJi, 1997 (in Korean).
5 K. B. Kim, "Combining A* and genetic algorithm for efficient path search," Journal of the Korea Institute of Information and Communication Engineering, vol. 22, no. 7, pp. 943-948, Jul. 2018 (in Korean).   DOI
6 J. K. Ahn, S. Y. Kang, and M. O. So, "PD controller based on genetic algorithms for depth control of an autonomous underwater vehicle," Journal of the Korean Society of Marine Engineering, vol. 42, no. 1, pp. 24-30, Jan. 2018(in Korean).
7 S. Ghosh, and R. J. Gagnon, "A comprehensive literature reivew and anlysis of the design, balancing and scheduling of assembly systems," International Journal of Production Research, vol. 27, no. 4, pp. 637-670, 1989.   DOI
8 D. E. Goldberg, and R. Lingle, "Alleles, Loci, and the TSP," in Proceedings of the 1st International Conference on Genetic Altorithms, Lawrence Erlbaum Associates, Hillsdale, NJ, pp. 154-159, 1985.
9 M. Herdy, "Application of the evolution strategy to discrete optimization problems," in Proceedings of the 1st International Conference on Parallel Problem Solving from Nature, Springer-Verlag, Lecture Notes in Computer Science 496, pp. 188-192, 1991.
10 M. H. Cho, and Y. I. Joo, "A base study on emergency rescue guidance scheme using genetic algorithm," in Proceedings of the 43rd KOSME Spring Conference, pp. 273, 2019 (in Korean)