TY - JOUR
T1 - Digital Twinning of Hydroponic Grow Beds in Intelligent Aquaponic Systems
AU - Reyes-Yanes, Abraham
AU - Abbasi, Rabiya
AU - Martinez, Pablo
AU - Ahmad, Rafiq
N1 - Funding information: The authors acknowledge the financial support of this work from the Council on Science and Technology (CONACYT) (File No. 2018-000039 01EXTF-00050) and the Transportes Pitic Scholarship. In addition, the authors acknowledge the financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC) (Grant File No. ALLRP 545537-19 and RGPIN- 2017-04516).
PY - 2022/9/28
Y1 - 2022/9/28
N2 - 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.
AB - 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.
KW - digital twin
KW - IoT
KW - precision farming
KW - aquaponics farm 4.0
U2 - 10.3390/s22197393
DO - 10.3390/s22197393
M3 - Article
SN - 1424-8220
VL - 22
JO - Sensors
JF - Sensors
IS - 19
M1 - 7393
ER -