Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/331197 
Erscheinungsjahr: 
2025
Quellenangabe: 
[Journal:] Research in Globalization [ISSN:] 2590-051X [Volume:] 10 [Article No.:] 100275 [Year:] 2025 [Pages:] 1-15
Verlag: 
Elsevier, Amsterdam
Zusammenfassung: 
Industry 4.0 has revolutionized modern urbanization and smart cities. However, the relationship between Industry 4.0 technology advances such as Artificial Intelligence (AI) and their impact on the earth, environment, people, and biological ecosystems needs further consideration, particularly during pandemics like COVID-19. This paper proposes a cyber-physical Industry 5.0 framework that is compliant with the Sustainable Development Goals (SDGs) defined by the United Nations (UN) in general and SDG 11 (Sustainable Cities and Communities) in particular. The framework targets three main pillars of SDGs from a technical perspective: global society, economy, and environment. It breaks down the cyber-physical system (CPS) into smaller components, linking them to each of the 17 SDGs and grouping them into broader categories. These components use four leading technologies: blockchain for secure data handling, B5G network function virtualizations, edge-cloud computing for scalable and flexible data processing and AI to deliver insights into the model's data. This paper addresses the challenge of monitoring the indicators of 17 SDGs by utilizing Industry 5.0 advancements. It offers practical validation of the framework through use cases in energy and water management. Results demonstrate how the framework can enhance SDG monitoring's precision, transparency, and scalability while providing stakeholders with helpful information.
Schlagwörter: 
Blockchain
SDGs
IoT
Cyber-physical system
Edge Computing
Explainable AI
Off-chain
Smart City Framework
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article
Erscheint in der Sammlung:

Datei(en):
Datei
Größe
8.35 MB





Publikationen in EconStor sind urheberrechtlich geschützt.