Design, development and deployment of a RSSI based wireless network for post disaster management

  • Authors

    • Vivek Kaundal
    • Paawan Sharma
    • Manish Prateek
    • Vinay Chowdary
    2018-03-11
    https://doi.org/10.14419/ijet.v7i2.6.10058
  • Wireless Sensor Network, Post Disaster Management, Real Time Monitoring, RSSI, Zigbee.

  • Abstract

    The wide spectrum of applications of wireless sensor networks in real time monitoring of disaster prone areas makes it very promising and reliable. The present work focuses on communication link establishment for the first 72 hours just after disaster, highlighting the capability of wireless sensor network especially in disaster prone area. The complete network consisting of 8 wireless nodes with integrated Xbee as a sensor to establish a communication link in between the pursuit team and trapped people. The network is deployed in Dunga Valley of Dehradun, Uttarakhand, a seismic zone with a population of more than 1 lakh. The nodes are capable of recognizing the traveler’s location whenever they are passing by the disaster prone areas. The nodes gather RSSI values along with the estimated distances of the traveler (having anchor node) from the pursuit team (having pursuit node). The system has proven its validity by tracking the trapped people in communication deprived area in Dunga Valley by doing mock drill several times. The paper reports the design of wireless network as well as deployment aspects of the nodes in such disaster prone areas.

  • References

    1. [1] Nandy, s., floods in india–disaster and management. convenar moksha, member centre for built environment, 2005.

      [2] Siqueira, i.g., et al., coverage area management for wireless sensor networks. international journal of network management, 2007. 17(1): p. 17-31.https://doi.org/10.1002/nem.604.

      [3] Zussman, g. and a. segall, energy efficient routing in ad hoc disaster recovery networks. ad hoc networks, 2003. 1(4): p. 405-421.https://doi.org/10.1016/S1570-8705(03)00041-6.

      [4] Mazomenos, e., j. reeve, and n. white, an accurate range-only tracking system using wireless sensor networks. procedia chemistry, 2009. 1(1): p. 1199-1202.https://doi.org/10.1016/j.proche.2009.07.299.

      [5] Cheng, g., accurate toa-based uwb localization system in coal mine based on wsn. physics procedia, 2012. 24: p. 534-540.https://doi.org/10.1016/j.phpro.2012.02.078.

      [6] Meng, w., l. xie, and w. xiao, decentralized tdoa sensor pairing in multihop wireless sensor networks. signal processing letters, ieee, 2013. 20(2): p. 181-184.https://doi.org/10.1109/LSP.2013.2237823.

      [7] Dakkak, m., et al., indoor localization method based on rtt and aoa using coordinates clustering. computer networks, 2011. 55(8): p. 1794-1803.https://doi.org/10.1016/j.comnet.2011.01.010.

      [8] Jin, r., et al., an rssi-based localization algorithm for outliers suppression in wireless sensor networks. wireless networks, 2015: p. 1-9.

      [9] Aiello, m., r. de jong, and j. de nes. bluetooth broadcasting: how far can we go? an experimental study. in pervasive computing (jcpc), 2009 joint conferences on. 2009. ieee.

      [10] Gharghan, s.k., et al., accurate wireless sensor localization technique based on hybrid pso-ann algorithm for indoor and outdoor track cycling. ieee sensors journal, 2016. 16(2): p. 529-541.https://doi.org/10.1109/JSEN.2015.2483745.

      [11] Mao, g., b. fidan, and b.d. anderson, wireless sensor network localization techniques. computer networks, 2007. 51(10): p. 2529-2553.https://doi.org/10.1016/j.comnet.2006.11.018.

      [12] Vivek kaundal, p.s., devender saini, manish prateek, location fingerprinting supported unilateral algorithm based on experimental study of localization in disaster prone area international journal of computer science and information security, 2016. 14: p. 162-175.

      [13] Berke, p.r., j. kartez, and d. wenger, recovery after disaster: achieving sustainable development, mitigation and equity. disasters, 1993. 17(2): p. 93-109.https://doi.org/10.1111/j.1467-7717.1993.tb01137.x.

      [14] O'brien, g., et al., climate change and disaster management. disasters, 2006. 30(1): p. 64-80.https://doi.org/10.1111/j.1467-9523.2006.00307.x.

      [15] Bai, y., et al. emergency communication system by heterogeneous wireless networking. in wireless communications, networking and information security (wcnis), 2010 ieee international conference on. 2010. ieee.

      [16] Erdelj, m. and e. natalizio. uav-assisted disaster management: applications and open issues. in computing, networking and communications (icnc), 2016 international conference on. 2016. ieee.

      [17] Ray, n.k. and a.k. turuk, a framework for post-disaster communication using wireless ad hoc networks. integration, the vlsi journal, 2016.

      [18] Minh, q.t., et al., on-the-fly establishment of multihop wireless access networks for disaster recovery. ieee communications magazine, 2014. 52(10): p. 60-66.https://doi.org/10.1109/MCOM.2014.6917403.

      [19] Minh, q.t., et al., on-site configuration of disaster recovery access networks made easy. ad hoc networks, 2016. 40: p. 46-60.https://doi.org/10.1016/j.adhoc.2015.12.008.

      [20] Briante, o., et al., comvivor: an evolutionary communication framework based on survivors’ devices reuse. wireless personal communications, 2015. 85(4): p. 2021-2040.https://doi.org/10.1007/s11277-015-2888-y.

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  • How to Cite

    Kaundal, V., Sharma, P., Prateek, M., & Chowdary, V. (2018). Design, development and deployment of a RSSI based wireless network for post disaster management. International Journal of Engineering & Technology, 7(2.6), 6-11. https://doi.org/10.14419/ijet.v7i2.6.10058

    Received date: 2018-03-11

    Accepted date: 2018-03-11

    Published date: 2018-03-11