Precision Crop Protection Using Wireless Sensor Network

  • R. RadhaEmail author
  • Amit Kumar Tyagi
  • K. Kathiravan
  • G. Staflin Betzy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 940)


The Wireless Sensor Network (WSN) is a widely developing field which provides many solutions to real-world problems (in various aspects of life). In this paper, monitoring process of the agricultural field by the sensor nodes has been discussed. The sensor node continuously monitors the crop and collects the data, then passes it to the Base station with the help of the Cluster Head (CH). The Cluster head is responsible to collect all the data from the sensor nodes. Collected data passes through multiple cluster heads to reach destination and we create topology among the cluster heads with the help of location information passed by every cluster head along with the data. If more number of shortest paths in the network passes through a cluster head and if it is an Articulation Point (AP) then there is a risk of network partition. So the articulation point must be less in the network, at the same time the between-ness centrality of the cluster head must be more. If cluster head is an articulation point then there will be a huge network failure. To overcome this problem, the cluster head has to be changed dynamically by finding the next between-ness centrality in the cluster region of a network. By using this mechanism, the energy consumption of the network can be reduced, the lifetime of the node can be increased, and the clustering efficiency and throughput is also comparatively increased.


Location aware routing Articulation point Between-ness centrality Cluster head 


  1. 1.
    Abouzar, P., Michelson, D.G., Hamdi, M.: RSSI-based distributed self-localization for wireless sensor networks used in precision agriculture. IEEE (2016). Scholar
  2. 2.
    Ssu, K.-F., Ou, C.-H., Jiau, H.C.: Localization with mobile anchor points in wireless sensor networks. IEEE Trans. Veh. Technol. 54(3), 1187–1197 (2005)CrossRefGoogle Scholar
  3. 3.
    Chen, Y.-C., Deng, D.-J., Chen, Y.-S.: Localization Algorithm for Wireless Sensor Networks. Springer, New York (2014)CrossRefGoogle Scholar
  4. 4.
    Mahlein, A.-K., Oerke, E.-C., Steiner, U., Dehne, H.-W.: Recent advances in sensing plant diseases for precision crop protection. Springer (2011)Google Scholar
  5. 5.
    Han, G., Xu, H., Duong, T.Q., Jiang, J., Hara, T.: Localization algorithms of wireless sensor networks: a survey. Springer (2011)Google Scholar
  6. 6.
    Anisi, M.H., Abdul-Salaam, G., Abdullah, A.H.: A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Springer (2014)Google Scholar
  7. 7.
    Santos, I.M., da Costa, F.G., Cugnasca, C.E., Ueyama, J.: Computational simulation of wireless sensor networks for pesticide drift control. Springer (2014)Google Scholar
  8. 8.
    Qing, L., Zhu, Q., Wang, M.: Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks (2006). Scholar
  9. 9.
    Krishnamachari, B., Iyengar, S.: Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks. IEEE Trans. Comput. 53(3), 241–250 (2004)CrossRefGoogle Scholar
  10. 10.
    Rault, T., Bouabdallah, A., Challal, Y.: Energy efficiency in wireless sensor networks: A top-down survey. Elsevier (2014)Google Scholar
  11. 11.
    Sibley, K.J., Astatkie, T., Brewster, G., Struik, P.C., Adsett, J.F., Pruski, K.: Field-scale validation of an automated soil nitrate extraction and measurement system. Springer (2008)Google Scholar
  12. 12.
    He, T., Huang, C., Blum, B.M., Stankovic, J.A., Abdelzaher, T.: Range-Free Localization Schemes for Large Scale Sensor Networks. ACM, San Diego (2003)CrossRefGoogle Scholar
  13. 13.
    Hong, S.-H., Kim, B.-K., Eom, D.-S.: Localization algorithm in wireless sensor networks with network mobility. IEEE Trans. Consum. Electron. 55(4), 1921–1928 (2009)CrossRefGoogle Scholar
  14. 14.
    Jiang, J.-A., Wang, C.-H., Liao, M.-S., Zheng, X.-Y., Liu, J.-H., Chuang, C.-L., Hung, C.-L., Chen, C.-P.: A wireless sensor network-based monitoring system with dynamic converge cast tree algorithm for precision cultivation management in orchid greenhouses. Springer (2016)Google Scholar
  15. 15.
    Karbasi, A., Oh, S.: Robust localization from incomplete local information. IEEE/ ACM Trans. Networking 21(4), 1131–1144 (2013)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of CSEKoneru Lakshmaiah Education FoundationVaddeswaramIndia
  2. 2.Lingayas VidyapeethFaridabadIndia
  3. 3.Department of Information TechnologyEaswari Engineering CollegeChennaiIndia

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