Evidence map›Paper›PMID 36236490›Full record

ArticleSensors (Basel, Switzerland)2022

Digital Twinning of Hydroponic Grow Beds in Intelligent Aquaponic Systems.

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

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Digital Twins in Agriculture: Orchestration and Applications.Journal of agricultural and food chemistry · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Abraham Reyes YanesAquaponics 4.0 Learning Factory (AllFactory), Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 2G8, Canada.
Rabiya AbbasiAquaponics 4.0 Learning Factory (AllFactory), Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 2G8, Canada.ORCID 0000-0001-9917-3830
Pablo MartinezDepartment of Mechanical and Construction Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.ORCID 0000-0003-3397-9617
Rafiq AhmadAquaponics 4.0 Learning Factory (AllFactory), Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 2G8, Canada.ORCID 0000-0001-9353-3380

Funding

Consejo Nacional de Ciencia y Tecnología 2018-000039-01EXTF-00050Natural Sciences and Engineering Research Council ALLRP 545537-19Natural Sciences and Engineering Research Council RGPIN-2017-04516
6 · The paper itself

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.

Indexed as

AgricultureCrops, AgriculturalArtificial IntelligenceHydroponicsWaterWateraquaponics farm 4.0digital twinIoTprecision farming

Identifiers

PMID36236490
PMCPMC9570900

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.