Fuzzy Logic Controller Based Automated Drip Irrigation System Using Field Capacity Measurements

Abstract

At present and more so in the future, irrigated agriculture will take the place of the scarcity of groundwater. Difficulty to provide adequate water supply than expected for irrigation will be the norm. The irrigation management, "production per unit” will shift towards emphasizing maximizing the production per unit of water consumed, the "water productivity". Hence, to find an optimum point of irrigation with the consideration of the quantity of water application, growth and yield of a plant a test was conducted. This smart irrigation system optimizes water usage for agriculture and also To improve agricultural water resources utilization, crop’s automatic, location, time, and appropriate drip irrigation is a good choice. In this study, an automatic control drip irrigation system based on a wireless sensor network and fuzzy control would be introduced. This system uses soil moisture, temperature, humidity, light, pH value, and wind information and sends the drip irrigation instructions via a wireless network. It puts the above six soil factors into the input fuzzy controller, creates a fuzzy control rule base, and finishes crop irrigation time through the fuzzy control. The Humidity sensor’s data helps to predict the rain and harvest the rainwater which helps the agriculture purpose.According the sensor’s data, to identify the best method of predict the rain forecast from logistic regression, KNN classifiers, random forest classifier, and Gradient Boosting Classifier algorithms and Random Forest is the Best method compare to the predict the rain forecast. Weeds are the plants which grow in the wrong place in agricultural land. Focusing on detecting the weeds in the crop using computer vision and Image processing to create the application and then notify the user. Fix the physical system to agricultural land and compare the productivity of the particular plant with the past data