IoT-Enabled Monitoring and Forecasting for Sustainable Adaptive Irrigation System using CatBoost Algorithm

Agriculture is essential for the expansion of sustainable development. It is the backbone of the global economy, and its success is contingent primarily on the availability of water. The growing population in coming decades is probably going to boost this demand. It is a must to use new strategies that optimizes the water quantity required for irrigation in order to meet this sustainable demand. However, only watering is not sufficient for optimal plant growth. For overall plant health monitoring a data monitoring and estimation for approximating the plant growth is required. With the aid of global and local control, crop productivity can be made and adaptive soil moisture (SM) prediction model can control the required water and nutrients to be supplied to it. Developing the perfect model for SM prediction can be difficult, though, because of the many structural features and climatic variables involved. This work presents an internet of things (IoT) database creation facility and soil moisture forecasting facility using CatBoost algorithm. The IoT integrated sensors are used to monitor the parameters needed for optimal plant health and growth whereas the forecasting model is required for an adaptive irrigation system and increase crop yield to sustain an ever-growing economy.