Prediction of Crop and Intrusions Using WSN

  • S. Sangeetha
  • M. K. Dharani
  • B. Gayathri Devi
  • R. Dhivya
  • P. Sathya
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 44)


Nowadays, the major problem in the agriculture sector is stumpy crop production due to less number of workers in the farm and animal intrusion. The main objective is to improve the sustainable agriculture by enhancing the technology using wireless sensor technology. It uses Micro Electro Magnetic System which is used to measure temperature, humidity and moisture. The characteristic data obtained from the Wireless Sensor Network will be compared with the pre-defined data set in the Knowledge Base where historical data’s are stored. The corresponding decisions from the Knowledge Base are sent to the respective land owner’s mobile through SMS using radio frequency which has less power consumption. The sensors are co-ordinated using the GPS and are connected to the base station in an ad hoc network using WLAN. Another common issue is animal intrusion, especially in the places like Mettupalayam, Coimbatore, and Pollachi where elephants are destroying the crops. To protect the crops and common people, Seismic sensors are used to detect the footfalls of elephants in hilly areas. This sensor uses geophone to record the footfalls of elephants and immediately alert message is sent to the people.


WSN-Wireless sensor network MEMS-Micro electro magnetic system SMS-Short message service WLAN-Wireless local area network GPS-Global positioning system 


  1. 1.
    Othman, M.F., Shazali, K.: Wireless sensor network applications: a study in environment monitoring system. International Symposium on Robotics and Intelligent Sensors, Procedia Engineering 41, 1204–1210 (2012)Google Scholar
  2. 2.
    Nengfu, X., Wensheng, W.: Ontology and acquiring of agriculture knowledge. Agric. Netw. Inf. 8, 13–14 (2007)Google Scholar
  3. 3.
    Keshtgari, M., Deljoo, A.: A wireless sensor network solution for precision agriculture based on zigbee technology. Sci. Res. J. Wirel. Sensor Netw. 4, 25–30 (2012)Google Scholar
  4. 4.
    de Leona, M.R.C., Jalaob, E.R.L.: A prediction model framework for crop yield prediction. In: Asia Pacific Industrial Engineering and Management System (2013)Google Scholar
  5. 5.
    Kays, R., et al.: Tracking animal location and activity with an automated radio telemetry system in a tropical rainforest. Comput. J. 54(12), 1931–1948 (2011)CrossRefGoogle Scholar
  6. 6.
    Zviedris, R., Elsts, A., Strazdins, G.: LynxNet: wild animal monitoring using sensor. Networks 2009, 170–173 (2010)Google Scholar
  7. 7.
    Hons, M., Stewart, R., Lawton, D., Bertram, M.: Ground motion through geophones and MEMS accelerometers: sensor comparison in theory, modelling and field data. Society of Exploration Geophysicists, University of Calgary, CREWES Project (2007)Google Scholar
  8. 8.
    Song, G., Wang, M., Ying, X., Yang, R., Zhang, B.: Study on precision agriculture knowledge presentation with ontology. In: AASRI Conference on Modelling, Identification and Control, AASRI Procedia, vol. 3, pp. 732–738 (2012)Google Scholar
  9. 9.
    Ping, Q., Yelu, Z.: Study and Application of Agricultural Ontology. China Agricultural Science and Technology Publishing House, Beijing (2006)Google Scholar
  10. 10.
    Stathakis, D., Savin, I., Nègre T.: Neuro-fuzzy modeling for crop yield prediction. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 34, Part XXXGoogle Scholar
  11. 11.
    Klir, G.J.: Fuzzy sets and fuzzy logic theory and applicationsGoogle Scholar
  12. 12.
    El-kader, S.M.A., El-Basioni, B.M.M.: Precision farming solution in Egypt using the wireless sensor network technology. Egypt. Inform. J. 14, 221–233 (2013)Google Scholar
  13. 13.
    Jiang, X., Zhou, G., Liu, Y., Wang, Y.: Wireless sensor networks for forest environmental monitoring, pp. 2–5 (2010)Google Scholar
  14. 14.
    Majone, B., Viani, F., Filippi, E., Bellin, A., Massa, A., Toller, G., Robol, F., Salucci, M.: Wireless sensor network deployment for monitoring soil moisture dynamics at the field scale. Procedia Environ. Sci. 19, 426–435 (2013)CrossRefGoogle Scholar
  15. 15.
    Wood, J.D., O’Connell-Rodwell, C.E., Klemperer, S.: Using seismic sensors to detect elephants and other large mammals: a potential census technique. J. Appl. Ecol. 42, 587–594 (2005)CrossRefGoogle Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • S. Sangeetha
    • 1
  • M. K. Dharani
    • 1
  • B. Gayathri Devi
    • 1
  • R. Dhivya
    • 1
  • P. Sathya
    • 1
  1. 1.Department of Computer Science and EngineeringAvinashilingam University for WomenCoimbatoreIndia

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