Level of Automation Assessment for Controlled-Environment Hydroponic Agriculture via Fuzzy MCDM Method

Abstract

The increasing world population and urbanization rates, and inevitable climate change tendencies have threatened food security. Integrating emerging technologies such as robotics, artificial intelligence (AI), and the Internet of Things (IoT) into agriculture through automation is crucial to sustainably meet global food demand by efficiently utilizing available arable land and natural resources. Although Controlled Environment Agriculture (CEA), where every ecological component may be monitored, controlled, and processes are executed with higher-level automation, is an emerging solution for urban areas; establishing automation levels for energy management has been identified as one of the major challenges in developing an efficient and viable CEA system. In this study, three levels of automation, manual, semi-automation, and full automation, were evaluated for controlled-environment hydroponic agriculture (CEHA). In this regard, 15 criteria were determined, and TODIM (an acronym in Portuguese-TOmada de Decis a~ o Iterativa Multicritério) method was applied to incorporate risk factors in the decision-making process. In order to cope with the vagueness in data collection, fuzzy sets were integrated into the method. As a result of the application, the semi-automation alternative showed the best performance with respect to the evaluation criteria.