Fuzzy system design for automatic irrigation of agricultural fields

• Intelligent systems in the irrigation lead to better scheduling according to climatic and regional conditions. • The use of remote sensing in agricultural lands is less expensive than sensor-based hardware equipment. • Fuzzy systems based on remote sensing have more accuracy in calculating the water consumption. One of the main challenges in arid and semi-arid regions is the lack of water for various purposes such as industrial and agricultural applications. The problem is even more significant in traditional agriculture. The geographical location, climatic conditions, average annual rainfall, vegetation, air pollution and turbidity, and canopy of plants are important and lead to different water consumption in plants. Therefore, proper water consumption in agriculture in most countries leads to food security and a better supply of crops. In this research, we propose a fuzzy system that has eight inputs and seven outputs. Inputs include soil moisture, relative humidity, air temperature, wind speed, soil permeability, daily rainfall, vegetation, and air pollution. The Fuzzy outputs are the reference and water stress evapotranspiration, water pump condition, duration of water pump operation, the volume of water requirements for crops, irrigation efficiency, and water losses. The main feature of the fuzzy system is the prediction of water consumption in different climates with high accuracy. To prove high efficiency and accuracy, we have performed many analyzes in various geographical locations. The geographical locations are tropical, semi-mountainous, and mountainous areas. In addition, we have performed three different analyses in four periods using our fuzzy system. In the first and second modes are used the average daily and hourly data, respectively. Finally, in the third mode, some data of the second method, such as the impacts of air pollution, soil moisture, vegetation, and water infiltration rate in the soil, are not considered because most of the proposed approaches do not consider the factors. The results show that the second mode is more efficient, and in some farms saves about 70% in water consumption. In addition, the results show that the water consumption in autumn and winter is lower than in spring and summer. The fuzzy system has high efficiency on all crops in different climates and can prevent water stress or waterlogging. It irrigates as much water as the plants need and prevents water loss. One of the main factors in increasing the accuracy of the fuzzy system is the use of vegetation level, soil moisture, air pollution, soil type, and plant canopy. The research results show that the proposed system can be used in different climates and significantly reduce water consumption in agricultural lands. Regression, correlation coefficient, and RMSE analysis have been used to validate the fuzzy system.