Realistic acoustic sensor network deployment and radio coverage in terrain profile using 3d modeling

  • Authors

    • Gajendra Sharma
    • Manish Kumar
    • Shekhar Verma
    2018-02-09
    https://doi.org/10.14419/ijet.v7i1.8.9443
  • AWSN, DTMP, 3D Modelling, Coverage, Terrain.

  • Abstract

    Acoustic sensing can be done by deploying a wireless sensor network in the area of interest. To detect anthrophonic events such as, deforestation along with monitoring the vehicle movement on the muddy road for smuggling intension. In the present time, anthrophonic event classification on the basis of wireless acoustic sensor node remain unanswered. This work explores speedy improvement in wireless acoustic sensor node that classify acoustic event applications. Wireless acoustic sensor node deployment strategy in outside surroundings is proposed. Most of the studies on sensor network in term of deployment consider on flat surfaces. The deployment of wireless sensor network in unequal surface like a forest was rarely reported. The aim is to maximize the quality of coverage of a wireless sensor on a forest surface. A probabilistic sensing model and line of sight algorithm are utilized for this purpose.

  • References

    1. [1] Köpke, A., Swigulski, M., Wessel, K., Willkomm, D., Haneveld, P.T., Parker, T.E., Visser, O.W., Lichte, H.S. and Valentin, S., 2008, March. Simulating wireless and mobile networks in OMNeT++ the MiXiM vision. In Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (p. 71). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).

      [2] Hefeeda, M. and Bagheri, M., 2009. Forest Fire Modeling and Early Detection using Wireless Sensor Networks. Ad Hoc & Sensor Wireless Networks, 7(3-4), pp.169-224.

      [3] Buratti, C., Conti, A., Dardari, D. and Verdone, R., 2009. An overview on wireless sensor networks technology and evolu-tion. Sensors, 9(9), pp.6869-6896. https://doi.org/10.3390/s90906869.

      [4] Ioannis, K., Dimitriou, T. and Freiling, F.C., 2007, April. To-wards intrusion detection in wireless sensor networks. In Proc. of the 13th European Wireless Conference (pp. 1-10).

      [5] Golovin, D., Faulkner, M. and Krause, A., 2010, April. Online distributed sensor selection. In Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks (pp. 220-231). ACM. https://doi.org/10.1145/1791212.1791239.

      [6] Gabrys, J., 2012. Sensing an experimental forest: processing environments and distributing relations. Computational Culture, 2, p.online.

      [7] Strübe, M., Lukas, F., Li, B. and Kapitza, R., 2014, September. DrySim: simulation-aided deployment-specific tailoring of mote-class WSN software. In Proceedings of the 17th ACM in-ternational conference on Modeling, analysis and simulation of wireless and mobile systems (pp. 3-11). ACM. https://doi.org/10.1145/2641798.2641838.

      [8] Kivelä, I. and Hakala, I., 2015. Area-based environmental noise measurements with a wireless sensor network.

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  • How to Cite

    Sharma, G., Kumar, M., & Verma, S. (2018). Realistic acoustic sensor network deployment and radio coverage in terrain profile using 3d modeling. International Journal of Engineering & Technology, 7(1.8), 15-19. https://doi.org/10.14419/ijet.v7i1.8.9443

    Received date: 2018-02-09

    Accepted date: 2018-02-09

    Published date: 2018-02-09