Towards automated greenhouse: A state of the art review on greenhouse monitoring methods and technologies based on internet of things

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作者
Li, Haixia [1 ,2 ,3 ]
Guo, Yu [1 ,2 ,3 ]
Zhao, Huajian [1 ,2 ,3 ]
Wang, Yang [1 ,2 ,3 ]
Chow, David [4 ]
机构
[1] College of Information and Electrical Engineering, China Agricultural University, Beijing,100083, China
[2] National Innovation Center for Digital Fishery, China Agricultural University, Beijing,100083, China
[3] Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing,100083, China
[4] School of Architecture, University of Liverpool, Liverpool,L69 7ZN, United Kingdom
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摘要
As a controllable environment, greenhouse has less resource consumption and emission than field crop production and reduced greenhouse gas emissions from agricultural production. Besides, the greenhouse with an intelligent monitoring system has better energy-saving and emission reduction effects. Simultaneously, the intelligent monitoring system can predict the extreme greenhouse environment in advance, reduce diseases and insect pests, reduce the use of pesticides and fertilizers, and provide high-quality food. Researchers are becoming more and more interested in greenhouse monitoring systems, and how to put them into production correctly and effectively is a major challenge. This paper aims to review the intelligent greenhouse monitoring system systematically, serve the data transmission and server processing subsystems by identifying, listing and further explaining the greenhouse environmental parameters and studying the overall design of the greenhouse monitoring system. According to the characteristics of each component of the system, the paper makes a comparative study and obtains its development trend, summarizes the current popular technology and the future development trend of the intelligent monitoring system, and provides support for the research of greenhouse monitoring system. It was found that multi-parameter monitoring is beneficial to achieve effective greenhouse control, and wireless technology has gradually replaced wired mode for data transmission in the environment both inside and outside the greenhouse. Notably, deep learning, big data, and other advanced technologies used in greenhouse monitoring are considered valuable developments, further refine unmanned greenhouse management, and further improve greenhouse construction's energy utilization. © 2021 Elsevier B.V.
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