Intelligent Automated Irrigation System Based on Soil Sensors and Weather Forecast Data

Abstract

There are lots of factors that support the economic development of the country. Agriculture plays a very crucial role in the process of economic development of any country. In this scenario, farmers are principle person which contributes to National Income as well as they are the important source of food supply to the entire nation, irrespective of the developed, undeveloped, or developing nation. Farmers face various problems related to insufficient capital amount, soil erosion, seeds, lack of automation, and irrigation of soil. In this paper, we propose a novel concept of an automatic irrigation system called AGRIDUINO, which will target to solve the problem of lack of automation and irrigation of soil. In the traditional method, farmers have to do manual irrigation of multiple agriculture fields, situated in various geographical areas. In this case, there is a chance of giving excess or less water to plants. A huge amount of water is also wasted. Our Proposed system AGRIDUINO efficiently handles this scenario. The Proposed System efficiently detects water content of the soil (soil moisture), weather, temperature, and forecasting of rain, and based on these parameters our Decision Tree algorithm will predict, whether to make water motor ON or OFF for watering the plants. We present propitious results by applying our proposed technique.