An ontology model to represent aquaponics 4.0 system’s knowledge

Abbasi, Rabiya, Martinez Rodriguez, Pablo and Ahmad, Rafiq (2021) An ontology model to represent aquaponics 4.0 system’s knowledge. Information Processing in Agriculture. ISSN 2214-3173 (In Press)

[img]
Preview
Text (Proof)
1-s2.0-S2214317321000937-main.pdf - Other
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (6MB) | Preview
Official URL: https://doi.org/10.1016/j.inpa.2021.12.001

Abstract

Aquaponics, one of the vertical farming methods, is a combination of aquaculture and hydroponics. To enhance the production capabilities of the aquaponics system and maximize crop yield on a commercial level, integration of Industry 4.0 technologies is needed. Industry 4.0 is a strategic initiative characterized by the fusion of emerging technologies such as big data and analytics, internet of things, robotics, cloud computing, and artificial intelligence. The realization of aquaponics 4.0, however, requires an efficient flow and integration of data due to the presence of complex biological processes. A key challenge in this essence is to deal with the semantic heterogeneity of multiple data resources. An ontology that is regarded as one of the normative tools solves the semantic interoperation problem by describing, extracting, and sharing the domains’ knowledge. In the field of agriculture, several ontologies are developed for the soil-based farming methods, but so far, no attempt has been made to represent the knowledge of the aquaponics 4.0 system in the form of an ontology model. Therefore, this study proposes a unified ontology model, AquaONT, to represent and store the essential knowledge of an aquaponics 4.0 system. This ontology provides a mechanism for sharing and reusing the aquaponics 4.0 system’s knowledge to solve the semantic interoperation problem. AquaONT is built from indoor vertical farming terminologies and is validated and implemented by considering experimental test cases related to environmental parameters, design configuration, and product quality. The proposed ontology model will help vertical farm practitioners with more transparent decision-making regarding crop production, product quality, and facility layout of the aquaponics farm. For future work, a decision support system will be developed using this ontology model and artificial intelligence techniques for autonomous data-driven decisions.

Item Type: Article
Additional Information: Funding information: The authors acknowledge the financial support of this work by the Natural Sciences and Engineering Research Council of Canada (NSERC) (Grant File No. ALLRP 545537-19 and RGPIN-2017-04516).
Uncontrolled Keywords: Aquaponics 4.0, Industry 4.0, Ontology modeling, Knowledge modeling, Decision support system
Subjects: D400 Agriculture
D700 Agricultural Sciences
G500 Information Systems
H700 Production and Manufacturing Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: John Coen
Date Deposited: 15 Dec 2021 14:53
Last Modified: 15 Dec 2021 15:00
URI: http://nrl.northumbria.ac.uk/id/eprint/47989

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics