Intelligent Algorithm for Optimizing Hydroponic Solution in IoT-Integrated Agriculture Systems

This research presents an intelligent control system for managing the nutrient solution in a hydroponic environment. The system utilizes a combination of Fuzzy Logic and a Genetic Algorithm (GA) to optimize nutrient delivery for plants. A Mamdani Fuzzy Inference System (FIS) grades the overall quality of the nutrient solution based on factors like pH and Electrical Conductivity (EC). The GA then optimizes the volumes of different nutrients and water to be added to the reservoir, considering the desired solution quality and plant growth stage. The system also features an Internet of Things (IoT) architecture with various sensors monitoring crucial parameters like pH, EC, temperature and humidity. Real-time data is transmitted to the cloud and a user-friendly web application allows for remote monitoring and control. The system’s efficacy is demonstrated through experiments showcasing its ability to maintain desired pH, EC and solution level throughout various plant growth phases. The proposed methodology offers a comprehensive solution to address the challenges of modern farming, ensuring efficient resource utilization and enhanced crop yields in urban environments.