Predicting yield of crop type and water requirement for a given plot of land using machine learning techniques

Nitin Padriya, Nimisha Patel


Internet of things (IoT) smart technology enables new digital agriculture. Technology has become necessary to address today's challenges, and many sectors are automating their processes with the newest technologies. By maximizing fertiliser use to boost plant efficiency, smart agriculture, which is based on IoT technology, intends to assist producers and farmers in reducing waste while improving output. With IoT-based smart farming, farmers may better manage their animals, develop crops, save costs, and conserve resources. Climate monitoring, drought detection, agriculture and production, pollution distribution, and many more applications rely on the weather forecast. The accuracy of the forecast is determined by prior weather conditions across broad areas and over long periods. Machine learning algorithms can help us to build a model with proper accuracy. As a result, increasing the output on the limited acreage is important. IoT smart farming is a high-tech method that allows people to cultivate crops cleanly and sustainably. In agriculture, it is the use of current information and communication technologies.


Climate; Internet of things; Machine learning; Precision agriculture; Regression problem

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International Journal of Reconfigurable and Embedded Systems (IJRES)
p-ISSN 2089-4864, e-ISSN 2722-2608
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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