Sensor Network Based Emergency Response and Navigation Support Architecture
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33104
Sensor Network Based Emergency Response and Navigation Support Architecture

Authors: Dilusha Weeraddana, Ashanie Gunathillake, Samiru Gayan

Abstract:

In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment. 

Keywords: Emergency response, Firefighters, Navigation, Wireless sensor network.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1086853

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2005

References:


[1] Y.Yanning, “Opportunities for WSN for facilitating fire emergency response,” in IEEE International Conference on Information and Automation for Sustainability, pp. 81–86, 2010.
[2] M. R. J. A. A. V. G. K.Lorincz, J.David and M.Welsh, “Sensor networks for emergency response: Challenges and opportunities,” Pervasive Computing, 3(4), pp. 16–23, 2004.
[3] K. M. L. Yang, R. Prassana, “On-site information systems design for emergency first responders,” Journal of Information Technology Theory and Application (JITTA), pp. 5–27, 2010.
[4] X. P. L.Shen, A.Zhan and G.Chen, “Efficient emergency rescue navigation with wireless sensor networks,” in Journal of Information Science and Engineering, vol. 27, 2011.
[5] S.Gamwarige and E.C.Kulasekere, “An energy efficient distributed clustering algorithm for ad-hoc deployed wireless sensor networks in building monitoring applications,” Electronic Journal of Structural Engineering (eJSE) Special Issue: Sensor Network on Building Monitoring: from Theory to Real Application, pp. 11–27, 2009.
[6] P. R. Y. L. Yang, Y., “Opportunities for WSN for facilitating fire emergency response,” Proceedings of ICIAfS 10, pp. 81–86, 2010.
[7] T. R. A. Meissner, T. Luckenbach, T. Kirste, and H.Kirchner, “A design challenges for an integrated disaster management communication and information system,” Proceedings of the 1st IEEE Workshop on Disaster Recovery Networks (DIREN 2002), June 2002.
[8] Y. C. Tseng, M. S. Pan, and Y. Y. Tsai, “Wireless sensor networks for emergency navigation,” Computer, vol. 39, no. 7, pp. 55–62, 2006.
[9] C. P. Waltenegus Dargie, Fundamentals of Wireless Sensor Networks. John Wiley & Sons Ltd, 2010.
[10] W. W. Ji and Z. Liu, “An improvement of dv-hop algorithm in wireless sensor networks,” in Wireless Communications, Networking and Mobile Computing, 2006. WiCOM 2006.International Conference on, pp. 1–4, 2006.
[11] A. C. W. Heinzelman and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS ’00), January 2000.
[12] I. M. G. Smaragdakis and A. Bestavros, “Sep: A stable election protocol for clustered heterogeneous wireless sensor networks,” Proceedings of the International Workshop on SANPA, (Boston), pp. 1–11, August 2004.
[13] O. Younis and S. Fahmy, “Heed: A hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks,” IEEE Transactions on Mobile Computing, vol. 3, pp. 366–379, October-December 2004.
[14] W. Zheng, S. Zhang, Y. Ouyang, F. Makedon, and J. Ford, “Node clustering based on link delay in p2p networks,” In 2005 ACM Symposium on Applied Computing, 2005.
[15] H. L. R.K. Ganti, P. Jayachandran and T. . Abdelzaher, “Datalink streaming in wireless sensor networks,” 4th international conference on Embedded networked sensor systems, pp. 209–222, 2006.
[16] S. Blackman and R. Popoli, Design and Analyis of Modern Tracking Systems. Norwood, MA: Artech House, 1999.
[17] Q. Guo, J. Dai, and J. Wang, “Study on fire detection model based on fuzzy neural network,” in Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on, pp. 1–4, 2010
[18] S. B. M. Chammem and N. Boudriga, “Smart navigation for firefighters in hazardous environments: A ban-based approach,” ICPCA-SWS, pp. 82–96, 2013.
[19] E. N. H. Koohi and M. Fathi, “Employing sensor network to guide firefighters in dangerous area,” International Journal of Engineering, vol. 32, pp. 191–202, 2010.
[20] S. Acharya and M. Kam, “Evidence combination for hard and soft sensor data fusion,” in Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on, pp. 1–8, 2011.
[21] K. Premaratne, M. Murthi, J. Zhang, M. Scheutz, and P. Bauer, “A dempster-shafer theoretic conditional approach to evidence updating for fusion of hard and soft data,” in Information Fusion, 2009. FUSION ’09. 12th International Conference on, pp. 2122–2129, 2009.