Citation

Hassan, Ali H. and Ahmed, Elsadig Musa and Hussien, Jamal M. and Sulaiman, Riza bin and Abdulhak, Mansoor and Kahtan, Hasan (2025) A cyber physical sustainable smart city framework toward society 5.0: Explainable AI for enhanced SDGs monitoring. Research in Globalization, 10. p. 100275. ISSN 2590051X

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Smart City Framework, SDGs, Explainable AI, Edge Computing, Blockchain, Off-chain, IoT, Cyber-physical system
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD2321-4730.9 Industry
Divisions:	Faculty of Business (FOB)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	06 Mar 2025 00:23
Last Modified:	06 Mar 2025 00:23
URII:	http://shdl.mmu.edu.my/id/eprint/13567

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