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Smart Cities Research in Gulf Cooperation Council Countries

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (27 March 2023) | Viewed by 2168

Special Issue Editor

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Guest Editor
1. School of Business, Deree—The American College of Greece, 6 Gravias Street, GR-153 42 Aghia Paraskevi Athens, Greece
2. College of Engineering, Effat University, Jeddah, Saudi Arabia
Interests: cognitive computing; artificial intelligence; data science; bioinformatics; innovation; big data research; data mining; emerging technologies; information systems; technology driven innovation; knowledge management
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Special Issue Information

Dear Colleagues,

Smart cities research provides a unique testbed for progressive, multi-disciplinary business, engineering, computer engineering and architectural research worldwide. The strategy blueprints in the Gulf Cooperation Council countries promote the Smart Cities Vision as it embedded in the pillars of the Vibrant Societies with Sustainable Social Inclusive Economic Growth. Technology driven innovation, empowering communities, and entrepreneurship in novel methods is a bold direction for the realization and application of the Smart Cities Vision to take.

We are inviting multidisciplinary research related to four significant pillars and topics:

Pillar 1. Foundations of smart cities research:

  • Smart cities as a multi- and inter-disciplinary domain of research;
  • Theoretical approaches to smart cities value approach;
  • Progressive research on new research frameworks on smart cities research.

Pillar 2. Novel theoretical models, frameworks, and approaches for the integration of smart cities research in sustainable development: 

  • Multidisciplinary scientific models for the adoption and utilization of smart cities towards sustainable economic development and growth;
  • Integration of computer-engineering algorithms in smart cities value proposition;
  • New business models for the delivery of value adding smart cities services;
  • Use of research methods for new contributions in the body of knowledge of smart cities research.

Pillar 3. Digital transformation in all aspects of value chain of smart cities:

  • Adoption of artificial intelligence and machine learning for value adding smart cities services;
  • Exploitation of cloud computing, Internet of Everything research and augmented reality in the context of smart cities;
  • NEOM as a test bed for next generation smart cities;
  • Digital transformation of citizenship and government in the context of smart cities.

Pillar 4. Next generation smart cities research:

  • Emerging models of next generation smart cities;
  • Megacities in Gulf Cooperation Council countries context;
  • Leadership and strategy for smart cities design, implementation, and leadership.

Pillar 5: Case studies and indicative smart cities projects in GCCC: dissemination of key outcomes.

You may choose our Joint Special Issue in Sustainability.

Prof. Dr. Miltiadis D. Lytras
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • smart cities
  • sustainable development
  • artificial intelligence
  • megacities
  • gulf cooperation council countries
  • megacities
  • business models

Published Papers (1 paper)

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15 pages, 1301 KiB  
Simultaneous Classification and Regression for Zakat Under-Reporting Detection
by Mohamed Maher Ben Ismail and Nasser AlSadhan
Appl. Sci. 2023, 13(9), 5244; - 22 Apr 2023
Viewed by 1685
Tax revenue represents an essential budget source for most countries around the world. Accordingly, the modernization of relevant technological infrastructure has become a key factor of tax administration strategy for improving tax collection efficiency. In particular, the fiscal consolidation of the Kingdom of [...] Read more.
Tax revenue represents an essential budget source for most countries around the world. Accordingly, the modernization of relevant technological infrastructure has become a key factor of tax administration strategy for improving tax collection efficiency. In particular, the fiscal consolidation of the Kingdom of Saudi Arabia has been supported by considerable development in tax policy and administration, aimed at raising more taxes from non-oil activities. In fact, non-Saudi investors are liable for income tax in Saudi Arabia. On the other hand, Saudi citizen investors (and citizens of the GCC countries) are liable for Zakat, an Islamic assessment. Typically, taxpayers are in charge of preparing and accurately reporting their Zakat declaration. This allows tax authorities to overview and audit their business activities. However, despite administration efforts to increase taxpayer compliance, considerable revenue remains at under-reporting risk. In this paper, we introduce a novel intelligent approach to support tax authority efforts in detecting under-reporting among Zakat payer declarations. In particular, the proposed solution aims at improving detection accuracy and determining the fraud cases that correspond to a higher revenue at risk. Specifically, we formulate Zakat under-reporting detection as a supervised machine learning task through the design of a deep neural network that performs simultaneous classification and regression tasks. In particular, the proposed network contains an input layer, five hidden layers, and two output layers for classification and regression. Zakat declarations are mapped into the predefined “under-reporting” or “actual declaration” classes. Moreover, the revenue at risk caused by the predicted fraud cases is learned by the designed model. This allows the proposed approach to prioritize the auditing of specific Zakat payers based on the corresponding predicted revenue at risk. A real dataset including 51,919 Zakat declarations was used to validate and assess the designed model. Further, the Synthetic Minority Oversampling Technique (SMOTE) boosted the proposed model performance in terms of classification and prioritization. Full article
(This article belongs to the Special Issue Smart Cities Research in Gulf Cooperation Council Countries)
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