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An ontology model to represent aquaponics 4.0 system’s knowledge

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摘要 Aquaponics,one of the vertical farming methods,is a combination of aquaculture and hydroponics.To enhance the production capabilities of the aquaponics system and maxi-mize 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 inte-gration 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 rep-resent and store the essential knowledge of an aquaponics 4.0 system.This ontology pro-vides 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 termi-nologies 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.
机构地区 Aquaponics
出处 《Information Processing in Agriculture》 EI 2022年第4期514-532,共19页 农业信息处理(英文)
基金 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).
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