Mobile Navigation in Emergency Environment Using Wireless Sensor Networks

  • Authors

    • Ms. R.Rajasaranyakumari
    • Mr R.Karthikeyan
    • M Bakyalakshmi
    • R Geethanjali
    • K Priyadharshini
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.19207
  • Group sensing, A* algorithm, google API, optimal route, blockage flexible route.

  • Abstract

    WSN's are used with the ultimate objective of condition checking and are a trademark choice of the system to enable emergency to course services. Even though The course routes picked by the present technique guarantee productive course and gives perfect most secure route by using the min-max rule close by the quantiï¬cation approaches ,however fails to identify the gathering .In the present structure we used an estimation called as SEND which does not revolve around the stop up at a particular zone however, in the proposed structure we use a computation called as CAN i.e blockage adaptable navigation, which bases on the congested locale by swarm recognizing and associates the person to move in an elective way where the hazard level is low and the A* figuring for briefest path. The proposed system moreover has the segment to show no less than two ways which improves the prosperity by empowering the customer to pick the most pleasing path .By coordinating customers following the dive edge of the hazard potential field , The CAN count can along these lines gain guaranteed ground of course and give perfect prosperity.

     

     

  • References

    1. [1] Wang, Jiliang, et al. "Sensor network navigation without locations." IEEE Transactions on Parallel and Distributed systems 24.7 (2013): 1436-1446.

      [2] Chen Wang, Member, IEEE, Hongzhi Lin, Rui Zhang, and Hongbo Jiang, Senior Member,â€SEND: A Situation-Aware Emergency Navigation Algorithm with Sensor Networks “, IEEE Trans. Mobile Comput., vol. 10, no. 5, pp.APRIL2017.

      [3] Wang, Chen, Hongzhi Lin, and Hongbo Jiang. "CANS: Towards congestion-adaptive and small stretch emergency navigation with wireless sensor networks." IEEE Transactionon Mobile Computing 15.5 (2016): 1077-1089.

      [4] S.Bondorf, J. B. Schmitt, "Boosting sensor network calculus by thoroughly bounding cross-traffic", Proc. 34th IEEE Int. Conf. Comput. Commun., pp. 235-243, 2015.

      [5] C. Zhang, J. Luo, L. Xiang, F. Li, J. Lin, Y. He, "Harmonic quorum systems: Data management in 2D/3D wireless sensor networks with holes", Proc. 9th Annu. IEEE Commun. Soc. Conf. Sensor Mesh Ad hoc Commun. Netw., pp. 1-9, 2012.

      [6] Y. Liu, X. Mao, Y. He, K. Liu, W. Gong, J. Wang, "CitySee: Not only a wireless sensor network", IEEE Netw., vol. 27, no. 5, pp. 42-47, Sep./Oct. 2013.

      [7] Xu, Enyang, Zhi Ding, and Soura Dasgupta. "Target tracking and mobile sensor navigation in wireless sensor networks." IEEE Transactions on mobile computing 12.1 (2013): 177-186.

      [8] H. Lin, M. Lu, N. Milosavljevic, J. Gao, L. J. Guibas, "Composable information gradients in wireless sensor networks", Proc. 7th IEEE/ACM Int. Conf. Inf. Process. Sensor Netw., pp. 121-132, 2008.

      [9] Schouten, Theo E., and Egon L. Van den Broek. "Fast Exact Euclidean Distance (FEED): A new class of adaptable distance transforms." IEEE transactions on pattern analysis and machine intelligence 36.11 (2014): 2159-2172.

      [10] Li,Feng,et al. "LBDP: Localized boundary detection and parametrization for 3-D sensor networks." IEEE/ACM Transactions on Networking 22.2 (2014): 567-579.

      [11] S. Lin et al., "Toward stable network performance in wireless sensor networks: A multilevel perspective", ACM Trans. Sensor Netw., vol. 11, no. 3, pp. 42:1-42:26, 2015.

      [12] B. N. Clark, C. J. Colbourn, D. S. Johnson, "Unit disk graphs", Discr. Math., vol. 86, no. 1, pp. 165-177, 1990.

      [13] [13] Braun, Adriana, Bardo EJ Bodmann, and Soraia R. Musse. "Simulating virtual crowds in emergency situations." Proceedings of the ACM symposium on Virtual reality software and technology. ACM, 2005.

      [14] Li, Mo, et al. "Sensor network navigation without locations." INFOCOM 2009, IEEE. IEEE, 2009.

      [15] He, Liang, et al. "Evaluating service disciplines for on-demand mobile data collection in sensor networks." IEEE Transactions on mobile computing 13.4 (2014): 797-810.

      [16] Liu, Yunhao, et al. "CitySee: Not only a wireless sensor network." IEEE Network 27.5 (2013): 42-47.

      [17] Lin, Huijia, et al. "Composable information gradients inwireless sensor networks." Proceedings of the 7th international conference on Information processing in sensor networks. IEEE Computer Society, 2008.

      [18] X.Xu, X. Li, M. Song, "Efficient aggregation scheduling in multihop wireless sensor networks with SINR constraints", IEEE Trans. Mobile Comput., vol. 12, no. 12, pp. 2518-2528, Dec. 2013.

      [19] H. Sorensen, B. L. Shumpert, B. M. Vogt, "Planning for protective action decision making: Evacuate or shelter-in-place", J. Hazardous Mater., vol. 109, no. 1, pp. 1-11, 2004.

      [20] B.E.Saltzman, "Preparation and analysis of calibrated low concentrations of sixteen toxic gases", Anal. Chem., vol. 33, no. 8, pp. 1100-1112, 1961.

  • Downloads

  • How to Cite

    R.Rajasaranyakumari, M., R.Karthikeyan, M., Bakyalakshmi, M., Geethanjali, R., & Priyadharshini, K. (2018). Mobile Navigation in Emergency Environment Using Wireless Sensor Networks. International Journal of Engineering & Technology, 7(3.34), 278-282. https://doi.org/10.14419/ijet.v7i3.34.19207

    Received date: 2018-09-07

    Accepted date: 2018-09-07

    Published date: 2018-09-01