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A Survey of Explainable Artificial Intelligence for Smart Cities
Air University, Pakistan;Lebanese American University, Lebanon.ORCID iD: 0000-0002-0570-1813
Air University, Pakistan.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Symbiosis International Deemed University, India.ORCID iD: 0000-0002-4507-1844
Vellore Institute of Technology, India.ORCID iD: 0000-0003-4209-2495
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2023 (English)In: Electronics, E-ISSN 2079-9292, Vol. 12, no 4, article id 1020Article in journal (Refereed) Published
Sustainable development
SDG 11: Make cities and human settlements inclusive, safe, resilient, and sustainable
Abstract [en]

The emergence of Explainable Artificial Intelligence (XAI) has enhanced the lives of humans and envisioned the concept of smart cities using informed actions, enhanced user interpretations and explanations, and firm decision-making processes. The XAI systems can unbox the potential of black-box AI models and describe them explicitly. The study comprehensively surveys the current and future developments in XAI technologies for smart cities. It also highlights the societal, industrial, and technological trends that initiate the drive towards XAI for smart cities. It presents the key to enabling XAI technologies for smart cities in detail. The paper also discusses the concept of XAI for smart cities, various XAI technology use cases, challenges, applications, possible alternative solutions, and current and future research enhancements. Research projects and activities, including standardization efforts toward developing XAI for smart cities, are outlined in detail. The lessons learned from state-of-the-art research are summarized, and various technical challenges are discussed to shed new light on future research possibilities. The presented study on XAI for smart cities is a first-of-its-kind, rigorous, and detailed study to assist future researchers in implementing XAI-driven systems, architectures, and applications for smart cities

Place, publisher, year, edition, pages
MDPI, 2023. Vol. 12, no 4, article id 1020
National Category
Information Systems
Research subject
Computer and Information Sciences Computer Science, Information Systems; Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-119565DOI: 10.3390/electronics12041020ISI: 000944989500001Scopus ID: 2-s2.0-85148854883OAI: oai:DiVA.org:lnu-119565DiVA, id: diva2:1739596
Available from: 2023-02-27 Created: 2023-02-27 Last updated: 2023-04-20Bibliographically approved

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Pandya, Sharnil

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Javed, Abdul RehmanPandya, SharnilMaddikunta, Praveen Kumar ReddyAlazab, MamounGadekallu, Thippa Reddy
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