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智能鱼菜共生系统中水培种植床的数字孪生

Digital Twinning of Hydroponic Grow Beds in Intelligent Aquaponic Systems.

作者信息

Reyes Yanes Abraham, Abbasi Rabiya, Martinez Pablo, Ahmad Rafiq

机构信息

Aquaponics 4.0 Learning Factory (AllFactory), Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 2G8, Canada.

Department of Mechanical and Construction Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.

出版信息

Sensors (Basel). 2022 Sep 28;22(19):7393. doi: 10.3390/s22197393.

Abstract

The use of automation, Internet-of-Things (IoT), and smart technologies is being rapidly introduced into the development of agriculture. Technologies such as sensing, remote monitoring, and predictive tools have been used with the purpose of enhancing agriculture processes, aquaponics among them, and improving the quality of the products. Digital twinning enables the testing and implementing of improvements in the physical component through the implementation of computational tools in a 'twin' virtual environment. This paper presents a framework for the development of a digital twin for an aquaponic system. This framework is validated by developing a digital twin for the grow beds of an aquaponics system for real-time monitoring parameters, namely pH, electroconductivity, water temperature, relative humidity, air temperature, and light intensity, and supports the use of artificial intelligent techniques to, for example, predict the growth rate and fresh weight of the growing crops. The digital twin presented is based on IoT technology, databases, a centralized control of the system, and a virtual interface that allows users to have feedback control of the system while visualizing the state of the aquaponic system in real time.

摘要

自动化、物联网(IoT)和智能技术正在迅速应用于农业发展中。传感、远程监测和预测工具等技术已被用于加强农业生产过程,其中包括鱼菜共生,并提高产品质量。数字孪生通过在“孪生”虚拟环境中实施计算工具,实现对物理组件改进的测试和实施。本文提出了一个用于鱼菜共生系统数字孪生开发的框架。通过为鱼菜共生系统的种植床开发数字孪生以实时监测pH值、电导率、水温、相对湿度、气温和光照强度等参数,对该框架进行了验证,并支持使用人工智能技术,例如预测生长作物的生长速率和鲜重。所呈现的数字孪生基于物联网技术、数据库、系统的集中控制以及一个虚拟界面,该界面允许用户在实时可视化鱼菜共生系统状态的同时对系统进行反馈控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70b4/9570900/31cf79f7dfc2/sensors-22-07393-g001.jpg

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