Enhancing Agricultural Productivity: Development of a Smart Farming Monitoring System with ESP32 and Fuzzy Logic Control

Abstract

The research describes a novel approach to advancing agricultural productivity by designing and implementing a smart farming monitoring system with fuzzy logic control. The system incorporates a range of sensors, such as temperature and humidity, soil moisture, light intensity, and water level, to continuously assess environmental factors. Experimental testing of the system output has shown 96.5% accuracy and 95.3% efficiency of the developed model in predicting and running the water pump. It has demonstrated the model’s outstanding response speed, with the system detecting the need for alteration within 1 minute of the changed setting, and high reliability, with a 98.7% rate of the water pump’s operation. By comparing to an alternative control design or the existing farmer strategy, it has become evident that fuzzy logic serves as the best approach. Namely, it ensures precision, minimizes input waste, reduces labor expenses, and mitigates the threat of malpractice, which, taken together, makes the system superior. Thus, it is possible to note that fuzzy logic technology has an immense capacity to transform the conventional approach to agricultural management. It allows for the generation of risk-proof and waste-avoiding strategies, thus enabling sustainable performance under the changing environmental pressures. As such, in the future, it is necessary to consider smart farming as a significant direction of further development that can benefit from constant sensor and AI improvement. Such work will result in the development and operations of optimized farming systems.