THE USE OF IOT IN WATER UTILIZATION STRATEGIES FOR SMART IRRIGATION SYSTEMS BASED ON MACHINE LEARNING - Junaidi, Junaidi (Universitas Royal, 2024)
Abstract: Water irrigation is a crucial aspect of agriculture that often becomes the primary concern for farmers, especially because suboptimal management can lead to decreased crop yields and reduced income. So far, farmers have been practicing irrigation manually, where plants are watered twice a day, in the morning and evening, based on weather conditions without considering soil temperature or moisture levels. Based on the observations conducted, it was found that excessive water application increases water accumulation, resulting in nutrient loss from the soil and even root diseases. The objective of this study is to develop a system utilizing an ESP32 microcontroller and sensors to detect soil moisture, with a machine learning-based K-Nearest Neighbor (KNN) model, enabling farmers to remotely monitor and control their crops using an Android device. The testing results showed that with input data of 32°C temperature, 40% soil moisture, and 60% air humidity, the system produced a nearest distance of 0.000 and 0.541 from the closest k-nearest neighbors, with a status label of