Managing Irrigation in Indian Agriculture Using Fuzzy Logic – A Decision Support System

  • Authors

    • N Suruthi
    • R Saranya
    • S Subashini
    • P Shanthi
    • A Umamakeswari
    2018-04-25
    https://doi.org/10.14419/ijet.v7i2.24.12075
  • Irrigation Decision Support System, Sensors, Fuzzy Logic, Adaptive Neuro Fuzzy Inference Systems.
  • Supplementation of water for irrigation in needed in south India due to uncertainty of monsoon rainfall. This paper proposes a support system to manage the irrigation system based on the information provided by humidity, temperature, soil moisture and weather information. The temperature, humidity and soil moisture data were collected by sensors. The proposed ANFIS based system consists of N inputs and a single output which determines the irrigation time needed for the crop. The experimentation is carried out using real time data collected from the region of VALLAM, located near THANJAVUR. The result helps in determining the time for irrigation which helps in increasing the yield of the crop.

     

     
  • References

    1. [1] Khelifa B, Amel D, Amel B, Mohamed C, Tarek B, “Smart irrigation using internet of thingsâ€, InFuture Generation Communication Technology (FGCT), Fourth International Conference on 2015.

      [2] Baranwal T, Pateriya PK, “Development of IoT based smart security and monitoring devices for agricultureâ€, InCloud System and Big Data Engineering (Confluence), 6th International Conference 2016.

      [3] Arvindan AN, Keerthika D, “Experimental investigation of remote control via Android smart phone of arduino-based automated irrigation system using moisture sensorâ€, InElectrical Energy Systems (ICEES), 3rd International Conference on 2016.

      [4] Nikolidakis SA, Kandris D, Vergados DD, Douligeris C, “Energy efficient automated control of irrigation in agriculture by using wireless sensor networksâ€, Computers and Electronics in Agriculture, 2015.

      [5] Putjaika N, Phusae S, Chen-Im A, Phunchongharn P, Akkarajitsakul K, â€A control system in an intelligent farming by using arduino technologyâ€, Fifth ICT International 2016.

      [6] Giusti E, Marsili-Libelli S, “A Fuzzy Decision Support System for irrigation and water conservation in agricultureâ€, Environmental Modelling & Software. 2015.

      [7] Ojha T, Misra S, Raghuwanshi NS, “Wireless sensor networks for agriculture: The state-of-the-art in practice and future challengesâ€, Computers and Electronics in Agriculture. 2015.

      [8] Navarro-Hellín H, Martínez-del-Rincon J, Domingo-Miguel R, Soto-Valles F, Torres-Sánchez R, “A decision support system for managing irrigation in agricultureâ€, Computers and Electronics in Agriculture, 2016.

      [9] M. Rajesh, Manikanthan, “ANNOYED REALM OUTLOOK TAXONOMY USING TWIN TRANSFER LEARNINGâ€, International Journal of Pure and Applied Mathematics, ISSN NO:1314-3395, Vol-116, No. 21, Oct 2017.

      [10] S.V.Manikanthan, Padmapriya.T, “RECENT TRENDS IN M2M COMMUNICATIONS IN 4G NETWORKS AND EVOLUTION TOWARDS 5Gâ€, International Journal of Pure and Applied Mathematics, Vol. 115, No. 8, pp: 623-630, 2017.

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  • How to Cite

    Suruthi, N., Saranya, R., Subashini, S., Shanthi, P., & Umamakeswari, A. (2018). Managing Irrigation in Indian Agriculture Using Fuzzy Logic – A Decision Support System. International Journal of Engineering & Technology, 7(2.24), 321-325. https://doi.org/10.14419/ijet.v7i2.24.12075