A fuzzy logic based decision support system (DSS) for agriculture support system is presented. The primary focus is on the algorithm used to correctly predict how much water should be poured to the agriculture for the optimal growth of the crops. Over-watering as well as under-watering has always been a big problem in farming. The proposed system uses three input parameters; namely field moisture, field humidity and field temperature. However, for predicting the proper amount of water so as to get the optimized best growth of the crop, few more parameters also play a vital role but in this work for simplicity purpose we have taken these three parameters as input. Through decision support system, the meaning of transferred data is translated into linguistic variables that can be understood by non-experts. Mamdani inference engine is used to deduce from the input parameters. Design of the proposed system is given with the fuzzy logic controller and simulation is being done using MATLAB (Matrix Laboratory) for solving the water irrigation issue

Fuzzy logic, Decision Support Systems, Agriculture support, Rule base

[1]. S. J. Yelapure, Dr. R. V. Kulkarni, “Literature Review on Expert System in Agriculture,” International Journal of Computer Science and Information Technologies (IJCSIT), vol. 3, no. 5, 2012.
[2]. Patterson, D.W., “Introduction to Artificial Intelligence and Expert Systems,” Prentice-Hall, New Delhi, 2004.
[3]. S.Saini, Harvinder, Kamal Raj and Sharma A.N., ”Web Based Fuzzy Expert System for Integrated Pest Management in Soybean”, Inter. Journal of Information Technology, vol. 8, no.1, 2002.
[4]. Prasad, G.N.R. and Babu, A.V., “A study on various expert systems in agriculture,” Georgian Electronic Scientific Journal: Computer Science and Telecommunications, vol. 5, no. 4, pp. 81-86, 2006.
[5]. Anna Perini and Angelo Susu, “Developing a Decision Support System for Integrated Production in Agriculture,” Preprint submitted to Environmental Modelling and Software, 10 January 2003.
[6]. D.J. Power, R. Sharda, and F. Burstein, “Decision Support Systems,” Management Information Systems, Published Online, vol. 7, 21 Jan. 2015 DOI: 10.1002/9781118785317.weom070211
[7]. Nam Nguyen, Malcolm Wegener, and Iean Russell, “Decision support systems in Australian agriculture: state of the art and future development,” International Association of Agricultural Economists Conference, Gold Coast, Australia, August 12-18, 2006.
[8]. P.P. Mumba, and E. Kambwiri, “Water Quality of Irrigation Water into and out of an Irrigated Sugar Cane Plantation,” Asian Journal of Water, Environment and Pollution, IOS Press. 2013.
[9]. E Ostrom, WF Lam, and M Lee, “The Performance of Self Governing Irrigation Systems in Nepal,” Human Systems Management, IOS Press, 1994.
Mirschel W, Wenkel K-O, Berg M, Wieland R, Nendel C, Köstner B, Topazh AG, Terleev VV, and Badenko VL, (2016) “A spatial model-based decision support system for evaluating agricultural landscapes under the aspect of climate change,” L. Mueller et al. (Eds), Springer, Cham, pp 519–540 (Chapter 23 of this book).