Development of Hydroponic IoT-based Monitoring System and Automatic Nutrition Control using KNN

Hydroponic farming is limited by inefficient monitoring and maintenance, which can affect plant growth and yield. This paper proposes using IoT technology, specifically a combination of STM32 microcontroller and sensors with 4G connection to cloud, to automate the monitoring and maintenance of hydroponic plants. The system monitors water and air temperature, pH, and TDS, and controls the hydroponics by adding nutrient in the form of AB mix. An automatic decision maker is built using KNN with an accuracy of 92.86% based on Euclidean distance algorithm. This technology could optimize the growth of hydroponic plants, as it provides continuous monitoring and maintenance.