Smart Agriculture Water System Using Crop Water Stress Index and Weather Prediction

Abstract

Water is essential for crops to grow well. However, overwatered or underwatered plants hinder growth and produce less fruit than plants with sufficient watering. Using the Internet of Things (IoT), agriculture can be controlled to achieve the best condition for plants to grow. The research aims to develop a watering system based on Crop Water Stress Index (CWSI), soil moisture content, and weather prediction. By evaluating CWSI and soil moisture content, the research makes a smart watering system that efficiently monitors water concentration in a plant. However, there is a flaw in the watering system that water from the rain makes the plant overwatered. So, using weather prediction can delay irrigation to save water and produce a better stress index result. Next, the research compares the watering system using four pots: (1) weather prediction, CWSI, and soil moisture watering system; (2) CWSI and soil moisture watering syste;, (3) soil moisture watering system; (4) manual irrigation watering system to get the best watering system by water consumption and CWSI. The results show a significant difference by using CWSI. It gets a 42.7754% smaller CWSI value by using CWSI value in making watering decisions. By adding weather prediction, the research saves water consumption by 21.9% compared to CWSI and soil moisture watering systems. These results show that weather prediction and CWSI are vital for IoT plant watering systems.