Prediction of Crops Driven by Machine Learning


  • A. T. Barge
  • R.R. Shinde
  • P.D. Poteka
  • A.A. Pathan


Agriculture has made its own way to make every living being healthy, survive in this universe. In India, we all realize that agriculture is the foundation of the country. Smart things (IoT) have brought modification in each and every area/field of common man’s life by making everything intelligent and smart. The factors that have impacted the crop significantly yield water, UV, pesticides. This paper is for or shows that a machine learning model proposed to illustrate the use of neural network. This system will help the farmer to decide which crop is suitable for a current season. By using previous data (dataset), machine will learn and predict from the dataset which crop is suitable for the environment of that time. This paper will help the farmer to make decision quickly without taking any risks. The use of Internet of Things (IoT) along with sensors network in farming renew the traditional way of farming. Different types of sensors are used to monitor and collect information about the yield condition. In this paper, the concept of smart crop prediction is explained and the use of various advanced technologies towards the agriculture domain is highlighted. The use of sensors in the domain of agriculture is not new but because of change in weather, soil, water, and land conditions, method of analysis and solutions are needed on which various communities of researchers are working and proposing solutions. That need of different ways for farming can be helpful in making solution for various conditions.