A Structure of Intelligent Smart Farm Control with Correlated Interface using Edge Computing
AUTHORS
Hee-Dong Park,Professor, Department of Smart IT, Joongbu University, #305 Dongheon-ro, Dugyang-gu, Goyang, Gyeonggi-do, Korea
ABSTRACT
Most Internet of Things (IoT) devices used in recent smart farm systems have limitations in data analysis, processing, and storage capabilities due to their limited computing capacity compared to increasing requirements for smart farming. In addition, massive data sent by devices to the cloud via Internet will result in network congestion and a processing burden on the cloud. A structure of intelligent control analysis for smart farm systems is proposed in this paper, which is based on the two-stage control system for efficient and intelligent management using correlation analysis with edge computing. This structure can reduce the burden on the cloud server and enables standalone management in case of communication failure. It could support advanced functions that can provide processing capability using various greenhouse-related parameters with the help of lightweight Artificial Intelligence (AI) and big data. Management and operation of large-scale smart farm systems can be possible using a network interface with intermediate data from the lower conditional control stage and information from the upper cloud server. Our proposed structure using edge computing will be referenced as an architecture framework for smart farm standardization in the future, with a scalable structure that can be connected and extended to other correlation control stages of edge nodes.
KEYWORDS
Smart farm, Edge computing, Intelligent control, Layered structure, Internet of Things, Correlation control, Conditional control