Intelligent irrigation system using ML and IoT

Abstract

To realize IoT promise in commercial-scale applications, integrated Internet of Things (IoT) platforms are required. The key challenge is to make the solution flexible enough to fulfill the demands of specific applications. A platform which is IoT-based which is used for smart irrigation with a adaptable design is created so that it allows developers to quickly link IoT and machine learning (ML) components to create application solutions. The design allows for a variety of customized analytical methods for precision irrigation, allowing for the advancement of machine learning techniques. Impacts on many stakeholders may be predicted, including IoT specialists, who would benefit from easier system setup, and farmers, who will benefit from lower costs and safer crop yields. The typical irrigation procedure necessitates a large quantity of use of precious water, which results in waste of water. An intelligent irrigation system is in desperate need to decrease the wastage of water during this tiresome process. Using Machine learning (ML) and the Internet of Things (IoT),it is possible to develop an intelligent system that can accomplish this operation automatically and with minimum human intervention. An system which is enables using IoT and trained using ML is highly recommended and is suggested in this paper for optimum water consumption with minimal farmer interaction. In agriculture, IoT sensors are used to capture exact field and environmental data. The data being collected is transferred and kept in a cloud-based server that uses machine learning to evaluate the data and provide irrigation recommendations.