Designing an intelligent irrigation system with fuzzy logic to improve the agriculture industry in Iran
Subject Areas : International Journal of Industrial Mathematics
سیده معصومه حسینی عباس آبادی
1
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پرستو حاتمی
2
1 - master Ghiasuddin Jamshid Kashani
2 - Faculty member and professor of Ghiasuddin Jamshid Kashani University of Qazvin, Iran
Keywords: Smart agriculture, Smart irrigation, IoT, Fuzzy logic, Dry / wet Sensor, Temperature sensor.,
Abstract :
Agriculture has always been one of the most important and basic human needs. Population increase, dietary changes, resource constraints and climate change are all problems that force farmers to produce more using fewer resources. According to the research undertaken in this area, the rate of water loss in Iran's agricultural industry is 28 to 30 percent, while this amount is equal to 9 to 12 percent in the world. Hence, this study focused on designing an intelligent irrigation system to improve the irrigation system in the agricultural industry of Iran, as well as examining the challenges of farmers in the field of water scarcity, costs related to intelligent irrigation systems and land flooding. For this purpose, fuzzy logic based on SPSS software was used to perform normalization operations and linear regression to determine the correlation coefficient as well as the coefficient of determination between the two characteristics of soil moisture and soil temperature and the relationship between the two with air temperature. In addition, MATLAB software has been used to design the intelligent irrigation system module. As a result, the removal of the soil temperature sensor identified as one of the useful ways to reduce the challenges of farmers, which not only can eliminate the possibility of disconnection between the soil temperature sensor and the network, but also can decrease the costs associated with the purchase and Maintenance. The use of meteorological information in addition to the information of soil moisture and air temperature sensors in the design of module inputs can prevent flooding and damage to agricultural products and conserves water significantly. The results of this study can help farmers to overcome the related challenges due to use intelligent irrigation systems.