Sensor Network Based Emergency Response and Navigation Support Architecture
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.
<p>[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.</p>
<p>[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.</p>
@article{"International Journal of Electrical, Electronic and Communication Sciences:64960", author = "Dilusha Weeraddana and Ashanie Gunathillake and Samiru Gayan", title = "Sensor Network Based Emergency Response and Navigation Support Architecture", 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.", volume = "7", number = "7", pages = "955-6", }
