Fuzzy Logic Inference-Based Automated Water Irrigation System

Usha Patel, Parita Rajiv Oza, Riya Revdiwala, Utsav Mukeshchandra Haveliwala, Smita Agrawal and Preeti Kathiria
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Usha Patel: Institute of Technology, Nirma University, India
Parita Rajiv Oza: Institute of Technology, Nirma University, India
Riya Revdiwala: Institute of Technology, Nirma University, India
Utsav Mukeshchandra Haveliwala: Institute of Technology, Nirma University, India
Smita Agrawal: Institute of Technology, Nirma University, India
Preeti Kathiria: Institute of Technology, Nirma University, India

International Journal of Ambient Computing and Intelligence (IJACI), 2022, vol. 13, issue 1, 1-15

Abstract: To fulfill the food interest of consistently expanding populace of our planet, it is important to do essential in the field of agribusiness. Traditional techniques for water systems like trench, wells, and precipitation are tedious and occasional. With the help of an automated water irrigation system the water, energy, and time can be moderated. This paper presents fuzzy rule logic inference-based automated water system framework. The soil moisture, weather forecast, crop status, and water-tank level are taken as input parameters. Soil moisture and water tank level can be recorded by utilizing sensors. The fuzzy logic-based system uses eighty-one rules to identify the amount of time to irrigate the fields. The emphasis is to solve agricultural problems by employing symbolic logic and to develop a system using computer science and mathematical logic. The use of such an automated system will decline costs, water prerequisite, and give power streamlining, with expanded proficiency.

Date: 2022
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