Design and simulation of an intelligent irrigation system using fuzzy logic - Peter Kibazo; Wanzala Jimmy Nabende; Michael Robson Atim (Discover Electronics)
Abstract Farmers in developing countries employ various irrigation methods ranging from traditional techniques such as the use of irrigation cans to modern pressurized systems while irrigating short-seasoned crops that require continuous water supply especially during the dry season. Inspite of being cheap and easy to use, farmers find it challenging to optimize farming costs through the application of the neccessary amount of water onto the crops, leading to crop water logging and hence roting. Due to the growing demand for agricultural products, there was need to develop an irrigation system that considers the amount of moisture in the soil, air temperature and light intensity, which are important parameters in plants’ growth. This dissertation therefore presents the design, simulation and implementation of an intelligent irrigation system, utilizing multiple sensors and a fuzzy logic controller to optimize water usage while ensuring high farming yields. The system design integrates light, temperature, and soil moisture sensors to monitor environmental conditions and soil moisture content in real-time. The operation of the irrigation system is governed by a set of one hundred twenty five (125) fuzzy rules that process the inputs from these sensors, determining the appropriate irrigation duration based on the prevailing light intensity, ambient temperature, and soil moisture levels. The fuzzy logic controller employs a combination of membership functions and rule-based inference to handle the relationships between the environmental parameters and the irrigation needs of the soil. By continuously analyzing the data from the sensors, the system dynamically adjusts the water output, ensuring optimal soil moisture levels while minimizing water wastage. Additionally, the system is equipped to send notifications in form of calls to a smartphone connected to the GSM network in case of critical conditions or system malfunctions. Experimental results demonstrate the ability of the intelligent irrigation system to dynamically adjust the amount of water being pumped into the garden basing on the prevailing soil moisture, temperature and light intensity.