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A Survey on Efficient Internet of Things Based Techniques for Efficient Irrigation and Water Usage

  • Ruthesh ChandranEmail author
  • P. Rekha
  • Balaji Hariharan
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 98)

Abstract

India is the second populous country in the world. The major occupation of Indian people is agriculture but majority of Indian crops will be dependent on the monsoon. With the decrease in rainfall, farmers have to use other alternate means of freshwater for the crops. This increase in demand and unsupervised usage of the available freshwater has led to water shortage. To address this issue an efficient water management and prediction techniques need to be implemented by using the ever-augmenting technologies like (IoT), which has progressed in recent years as an effective and cost-efficient substitute to conventional computing techniques. The need to design a dependable assessment and innovative mechanism needs to be designed. - A system that is capable to calculate, monitor and predict an efficient usage pattern to reduce water wastage and avoid subsequent crop loss. This paper surveys the techniques and areas that have to be considered for developing an IoT based agriculture system.

Keywords

Efficiency IoT Agriculture Water usage Irrigation 

Notes

Acknowledgement

We would like to express our immense gratitude to our beloved Chancellor Sri. Mata Amritanandamayi Devi (AMMA) for providing the motivation and inspiration for doing this research work. The authors would like to thank everyone who was instrumental in doing this research work.

References

  1. 1.
    Divya, P., Sonkiya, S., Das, P., Manjusha, V.V., Ramesh, M.V.: Cawis: context aware wireless irrigation system. In: 2014 International Conference on Computer, Communications, and Control Technology (I4CT), pp. 310–315. IEEE, September 2014Google Scholar
  2. 2.
    Rajalakshmi, P., Devi Mahalakshmi, S.: IOT based crop-field monitoring and irrigation automation. In: 2016 10th International Conference on Intelligent Systems and Control (ISCO), pp. 1–6. IEEE (2016)Google Scholar
  3. 3.
    Kumar, V.V., Ramasamy, R., Janarthanan, S., Babu, M.V.: Implementation of IOT in smart irrigation system using arduino processor. Int. J. Civ. Eng. Technol. 8(10), 1304–1314 (2017)Google Scholar
  4. 4.
    Malhotra, A., Saini, S., Kale, V.V.: Automated irrigation system with weather forecast integration. Int. J. Eng. Technol. Manag. Appl. Sci. 5(6), 179–184 (2017)Google Scholar
  5. 5.
    Shekhar, Y., Dagur, E., Mishra, S., Sankaranarayanan, S.: Intelligent IoT based automated irrigation system. Int. J. Appl. Eng. Res. 12(18), 7306–7320 (2017)Google Scholar
  6. 6.
    Khan, M.A., Islam, Z., Hafeez, M.: Irrigation water demand forecasting: a data pre-processing and data mining approach based on spatio-temporal data. In: Proceedings of the Ninth Australasian Data Mining Conference, vol. 121, pp. 183–194. Australian Computer Society, Inc. (2011)Google Scholar
  7. 7.
    Gutiérrez, J., Villa-Medina, J.F., Nieto-Garibay, A., Porta-Gándara, M.Á.: Automated irrigation system using a wireless sensor network and GPRS module. IEEE Trans. Instrum. Meas. 63(1), 166–176 (2013)CrossRefGoogle Scholar
  8. 8.
    Gumaste, S.S., Kadam, A.J.: Future weather prediction using genetic algorithm and FFT for smart farming. In: 2016 International Conference on Computing Communication Control and automation (ICCUBEA), pp. 1–6. IEEE (2016)Google Scholar
  9. 9.
    Rekha, P., Rangan, V.P., Ramesh, M.V., Nibi, K.V.: High yield groundnut agronomy: an IoT based precision farming framework. In: IEEE Global Humanitarian Technology Conference(GHTC), pp. 1–5. IEEE 2017 (2017)Google Scholar
  10. 10.
    Krupakar, H., Jayakumar, A.: A review of ıntelligent practices for irrigation prediction. arXiv preprint arXiv:1612.02893 (2016)
  11. 11.
    Prabha, R., Sinitambirivoutin, E., Passelaigue, F., Ramesh, M.V.: Design and development of an IoT based smart irrigation and fertilization system for chilli farming. In: 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), pp. 1–7. IEEE (2018)Google Scholar
  12. 12.
    Krishnan, R., Ramesh, M.: A low cost remote cardiac monitoring framework for rural regions. In: Proceedings of the 5th EAI International Conference on Wireless Mobile Communication and Healthcare, pp. 231–236. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) (2015)Google Scholar
  13. 13.
    Pathinarupothi, R.K., Alangot, B., Ramesh, M.V., Achuthan, K., Rangan, P.V.: H-plane: intelligent data management for mobile healthcare applications. In: International Conference on Mobile Web and Information Systems, pp. 283–294. Springer, Cham (2016)Google Scholar
  14. 14.
    Rajkumar, M.N., Abinaya, S., Kumar, V.V.: Intelligent irrigation system—an IOT based approach. In: 2017 International Conference on Innovations in Green Energy and Healthcare Technologies (IGEHT), pp. 1–5. IEEE (2017)Google Scholar
  15. 15.
    Saraf, S.B., Gawali, D.H.: IoT based smart irrigation monitoring and controlling system. In: 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp. 815–819. IEEE (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Amrita Center for Wireless Networks & Applications (AmritaWNA), Amrita School of Engineering, AmritapuriAmrita Vishwa VidyapeethamCoimbatoreIndia

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