Development of AI Modeling for Implementation of Agricultural Product Price Information Prediction System

Abstract

As smart farm is currently designated as one of the government's seven key tasks, it is an industry that is important in agriculture and has a lot of potential for development. It is very important to manage and utilize the data generated by these smart farms. In addition, it is essential to make smart farm big data information a new growth engine for agriculture and an industry that creates added value. However, the technology that can use agricultural data is still lacking, and the direction of the data utilization is still ambiguous. Therefore, in this paper, big data analysis necessary for predicting market price information on agricultural product prices among smart farm support factors was performed. To this end, supervised learning, regression analysis, and classification were performed, and finally, a study was conducted to develop a predictive model. Through this, it is possible to prepare a basis for discovering services such as production environment and price compared to grade quality by synthesizing it with data produced in the future smart farm.