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An ontology model to represent aquaponics 4.0 system’s knowledge
- Source :
- Information Processing in Agriculture. 9:514-532
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
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.
- Subjects :
- 2. Zero hunger
0209 industrial biotechnology
G500
D400
020206 networking & telecommunications
Forestry
02 engineering and technology
H700
15. Life on land
Aquatic Science
D700
Computer Science Applications
020901 industrial engineering & automation
13. Climate action
0202 electrical engineering, electronic engineering, information engineering
Animal Science and Zoology
14. Life underwater
Agronomy and Crop Science
Subjects
Details
- ISSN :
- 22143173
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Information Processing in Agriculture
- Accession number :
- edsair.doi.dedup.....e7647a8fbebdc45602145bd47405132a