文献类型: 外文期刊
作者: Liu, Jiayao 1 ; Wang, Linfeng 1 ; Wang, Yunsheng 2 ; Xu, Shipu 2 ; Liu, Yong 2 ;
作者机构: 1.Shanghai Inst Technol, Sch Railway Transportat, Shanghai 201418, Peoples R China
2.Shanghai Acad Agr Sci, Shanghai 201803, Peoples R China
关键词: digital twin; internet of things; plant factory; smart farm
期刊名称:SUSTAINABILITY ( 影响因子:3.9; 五年影响因子:4.0 )
ISSN:
年卷期: 2023 年 15 卷 6 期
页码:
收录情况: SCI
摘要: A digital twin (DT) system is a virtual system that can provide a comprehensive description of a real physical system. The DT system continuously receives data from physical sensors and user input information and provides information feedback to the physical system. It is an emerging technology that utilizes an advanced Internet of Things (IoT) to connect different objects, which is in high demand in various industries and its research literature is growing exponentially. Traditional physical systems provide data support for the monitoring of physical objects such as buildings through digital modeling techniques, data acquisition tools, human computer interfaces, and building information models (BIM). However, DT can offer much more than data presentation. DT uses the received data to perform operations such as analysis, prediction, and simulation, and finally transmits the analysis results to the physical system as feedback. Compared with other physical systems, DT has the characteristics of bidirectional data exchange and real-time autonomous management. The plant factory control system based on digital twin technology continuously measures the power consumption of electrical equipment through the sensors of the physical system and makes the corresponding virtual color-coded gradient map based on the obtained data. The darker the virtual device is, the more power it currently requires, and just based on the shade of color gives the user a very intuitive idea of the current power usage of the electronic device. There has been extensive research on digital twin technology, but there are few studies on implementing plant factories based on digital twin technology. This paper proposes the idea of combining digital twin technology with plant factories to provide research directions for future smart agriculture. It proves that smart agricultural production with sustainability can also benefit from this idea.
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