An IoT Based Agricultural Management Approach Using Machine Learning

Agriculture is India's most crucial and vital occupation since it balances the human population's need for food and the supply of essential raw materials for numerous industries. Growing water concerns and the necessity for suitable farm management approaches is a pressing issue that must be addressed with the utmost care. This study proposes an automated watering system for farmers. Internet of Things (IoT) based solution is presented as a cost-effective and precise solution for the farm. To make irrigation management more accessible and effective, a monitoring system is created which focuses on mud attrition, extra-irrigation, and crop-oriented processing. Due to the circumstance that the river is a limited supply, it is essential to reduce the amount that is wasted. The disseminated wireless sensor system will be built to provide coverage for the entire farm, with various sensor modules providing data to a central server. Crop and weather data will be used to anticipate irrigation patterns using machine learning (ML) techniques. In this study, a long-term solution to irrigation is presented. The visualization process necessitates the use of a dedicated server or network storage. Crop water needs are not available in an organized form. How well a model predicts depends on how much data it has access to. There are hyper-parameters and kernel types that influence SVR accuracy.