Markov Chain Model Used in Agricultural Yield Predictions Utilizing on Indian Agriculture

A new problem is how to adjust farming operations to shifting climatic conditions while using cutting edge agricultural technologies and novel seed varieties. IoT offers a fresh method for adjusting to future problems as a result. Historically, agricultural production was significantly influenced by the weather. The current climate catastrophe has dramatically changed this norm, though. Older seed kinds still generate superior yields when cared for correctly, whereas newer seed varieties have evolved in response to certain climatic and moisture requirements. In this study, we set out to train the machinery to recognize significant developmental stages in the life cycle of the crop, so that it can advise the farmer on how to best care for the machine depending on the circumstances under which the crop thrives. Instead of striving to create a system with predetermined thresholds, this improved agricultural initiative seeks to protect the environment while also meeting the crop's shifting needs throughout the course of its whole life cycle. Depending onwhere the crop is in its lifecycle and how long it is expected to last, the farmer may search for new approaches. Any device having an internet connection and the capability to attach sensorsmay be utilized to carry out all of these procedures.