Crop yield forecasting is becoming more essential in the present environment, when food security must be maintained despite climate, population, and climate change concerns. Machine learning and Deep learning isare useful decision-making tools for predicting agricultural yields, as well as for deciding what crops to plant and what to do throughout the crop’s growth season. To aid agricultural production prediction studies, number of artificial intelligence methods have been used. Agriculture plays a significant role in the economic sector. The automation in agriculture is the main concern and the emerging subject across the world. The population is increasing tremendously and with this increase the demand of food and employment is also increasing. The traditional methods which were used by the farmers were not sufficient and enough to fulfill these requirements. Thus, new automated methods were introduced. These new methods satisfied the food requirements and also provided employment opportunities to billions of people. In this paper, an overview of various techniques and tools based on AI is discussed.

Agriculture AI