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Ontology-Based IoT Middleware Approach for Smart Livestock Farming toward Agriculture 4.0: A Case Study for Controlling Thermal Environment in a Pig Facility

Title: Ontology-Based IoT Middleware Approach for Smart Livestock Farming toward Agriculture 4.0: A Case Study for Controlling Thermal Environment in a Pig Facility
Authors: Eleni Symeonaki; Konstantinos G. Arvanitis; Dimitrios Piromalis; Dimitrios Tseles; Athanasios T. Balafoutis
Source: Agronomy, Vol 12, Iss 3, p 750 (2022)
Publisher Information: MDPI AG, 2022.
Publication Year: 2022
Collection: LCC:Agriculture
Subject Terms: agriculture 4.0; integrated farm management; smart livestock farming; internet of things; middleware; context-awareness; Agriculture
Description: Integrated farm management (IFM) is promoted as a whole farm approach toward Agriculture 4.0, incorporating smart farming technologies for attempting to limit livestock production’s negative impacts on the environment while increasing productivity with regard to the economic viability of rural communities. The Internet of Things (IoT) may serve as an enabler to ensure key properties—such as interconnectivity, scalability, agility, and interoperability—in IFM systems so that they could provide object-based services while adapting to dynamic changes. This paper focuses on the problem of facilitating the management, processing, and sharing of the vast and heterogeneous data points generated in livestock facilities by introducing distributed IoT middleware as the core of a responsive and adaptive service-oriented IFM system, specifically targeted to enable smart livestock farming in view of its unique requirements. The proposed IoT middleware encompasses the context-awareness approach via the integration of a flexible ontology-based structure for modeling and reasoning. The IoT middleware was assessed in actual conditions on the grounds of a case study for smart control of the thermal environment in a medium-sized pig farming facility. As derived from the obtained evaluation results, the system appears to perform quite satisfactorily in terms of computational performance as well as ontology coherence, consistency, and efficiency.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2073-4395
Relation: https://www.mdpi.com/2073-4395/12/3/750; https://doaj.org/toc/2073-4395
DOI: 10.3390/agronomy12030750
Access URL: https://doaj.org/article/2cd83bc9fc104d64a52b71bc12eb3b3f
Accession Number: edsdoj.2cd83bc9fc104d64a52b71bc12eb3b3f
Database: Directory of Open Access Journals