Miller Magazine Issue: 121 January 2020

68 MILLER / JANUARY 2020 “Artificial intelligence and machine learning methodologies have already proven game-changers in many industries. These methodol- ogies could be applied to the grain industry as well and transform the way that managers interact with the silo, receive information on grain condition, and make their decisions. They could improve the accuracy and efficiency of the existing grain management tools but also create new innovative ones.” The Intelligent Silo Effective storage management necessitates maintaining high crop quality and preventing loss. To achieve these goals, one must thor- oughly evaluate factors such as grain temper- ature, moisture content, carbon dioxide con- centrations, weather conditions as well as their interaction and impact on grain in a storage structure. In most cases, silo and storage managers rely on their experience and intuition to man- age grain, which occasionally leads to either costly human errors or overly conservative planning at an unnecessarily high cost. New technologies, both in hardware and software, could transform the passive storage structure to an intelligence one, assisting the storage manager to detect and resolve effi- ciently challenging issues. THE CHALLENGE Artificial intelligence and machine learn- ing methodologies have already proven game-changers in many industries. These methodologies could be applied to the grain industry as well and transform the way that managers interact with the silo, receive infor- mation on grain condition, and make their de- cisions. They could improve the accuracy and efficiency of the existing grain management tools but also create new innovative ones. The transition to an "intelligent" silo should include the following: Dr. Efstathios Kaloudis Centaur Analytics s.kaloudis@centaur.ag