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Internet of Things and Artificial Intelligence as Enablers for Circular Economy

Mboli, Julius S.
Publication Date
2023
End of Embargo
Supervisor
Not named
Keywords
Circular economy, Circular supply chain management, Decision support systems, Industry 4.0 technologies, Internet of Things (IoT), Artificial Intelligence (AI), Semantic technology, Zero waste, Recycling, Remanufacturing
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Creative Commons License
The University of Bradford theses are licenced under a Creative Commons Licence.
Peer-Reviewed
Open Access status
Accepted for publication
Institution
University of Bradford
Department
Department of Computer Science. Faculty of Engineering and Informatics
Awarded
2023
Embargo end date
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Theses
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PhD Thesis
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Abstract
The traditional linear economy, using a take-make-dispose model is resourceintense and comes with adverse environmental impacts. Circular economy (CE) is regenerative and restorative by design and intention and is recommended as the business model for efficient use of resources. Despite the push for businesses and organisations to switch from linear to CE, there are several barriers/challenges that need solving such as business models and the criticism of CE projects often being small scale. Technology can be an enabler toward scaling up CE; however, the prime challenge is to identify technologies that can allow predicting, tracking and proactive monitoring of product's residual value, that can potentially motivate businesses to pursue circularity decisions. In this thesis, an Internet of Things (IoT)-enabled decision support system (DSS) for CE business model is proposed. The aim is to effectively enable tracking, monitoring, and analysis of products in real time with focus on residual value. The business model is implemented using an ontological model. This model is complemented by a semantic DSS. The semantic ontological model, first of its kind, is evaluated for technical compliance, quality of modelling and domain coverage, for final reengineering and re-evaluations. The DSS and the ontological model is applied in a real-world use case and demonstrate viability and applicability of the approach to businesses and sustainability via Sustainable Development Goals (SDGs) lens. The results of the comparison of this novel model to the linear economy is promising with the novel model proving more profitable and resource efficient.
URI
http://hdl.handle.net/10454/20048
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Type
Thesis
Qualification name
PhD
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