Smart Cities and Industry 4.0

A special issue of Smart Cities (ISSN 2624-6511).

Deadline for manuscript submissions: 1 June 2024 | Viewed by 2801

Special Issue Editors


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Guest Editor
Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, Aveiro, Portugal
Interests: smart cities; urban logistics; operations management; supply chain; urban planning
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
2. Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal
Interests: industrial management; information systems; human factors; sustainability; Industry 4.0; smart cities; participatory design
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Department of Social, Political and Territorial Sciences, University of Aveiro, Aveiro, Portugal
2. Governance, Competitiveness and Public Policies (GOVCOPP) Research Unit, Aveiro, Portugal
Interests: decision support systems; public policies; data science; regional science; urban planning; demography; housing; education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, smart cities have become more techno-centric and focus has been placed on sustainability and citizen quality of life. Thus, the concept of smart cities has evolved to include citizens as co-creators, and Industry 4.0 has envisioned personalized supply chain models arranged according to consumers’ wishes. Both concepts strive to focus on citizens, impacting transport and manufacturing processes, enhancing social development, and promoting sustainability. While smart cities emerged before Industry 4.0, their influence on one another is intertwined. However,  a greater understanding of this influence is still lacking. Based on the vision promoted by smart cities, citizens will increasingly be empowered by policymakers, whose inclusion and participation will become highly relevant. Furthermore, there is a need to reflect on how the evolution of the smart city concept will impact the development of industry. There is lack of published studies about the influence of smart cities in Industry 4.0, and this is seen as a valuable future focus. It can be addressed from two key directions. The first concerns an improved understanding of the smart city concept and how the evolution of society and its needs, particularly around quality-of-life improvements, may lead industry to adapt and adopt new practices; the second highlights the increasing role of communities and citizens on the instant fulfilment of supply chains and how new urban logistics and manufacturing models may emerge. In summary, a discussion of how the strategies developed by policymakers together with citizens may impact the industry is necessary.

Dr. Diogo Correia
Dr. Leonor Teixeira
Dr. João Lourenço Marques
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com 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. Smart Cities 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 2000 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.

Keywords

  • smart cities
  • Industry 4.0
  • supply chain
  • smart manufacturing
  • urban logistics
  • transportation
  • smart, resilient and sustainable territories
  • urban freight
  • freight management
  • logistics 4.0
  • 3D printing
  • circular economy
  • data science and urban life
  • urban planning
  • strategic planning
  • infrastructure and communication networks
  • community, participation and inclusion

Published Papers (2 papers)

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Research

23 pages, 2546 KiB  
Article
Enhancing Waste-to-Energy and Hydrogen Production through Urban–Industrial Symbiosis: A Multi-Objective Optimisation Model Incorporating a Bayesian Best-Worst Method
by Alessandro Neri, Maria Angela Butturi, Francesco Lolli and Rita Gamberini
Smart Cities 2024, 7(2), 735-757; https://doi.org/10.3390/smartcities7020030 - 28 Feb 2024
Viewed by 1453
Abstract
A surging demand for sustainable energy and the urgency to lower greenhouse gas emissions is driving industrial systems towards more eco-friendly and cost-effective models. Biogas from agricultural and municipal organic waste is gaining momentum as a renewable energy source. Concurrently, the European Hydrogen [...] Read more.
A surging demand for sustainable energy and the urgency to lower greenhouse gas emissions is driving industrial systems towards more eco-friendly and cost-effective models. Biogas from agricultural and municipal organic waste is gaining momentum as a renewable energy source. Concurrently, the European Hydrogen Strategy focuses on green hydrogen for decarbonising the industrial and transportation sectors. This paper presents a multi-objective network design model for urban–industrial symbiosis, incorporating anaerobic digestion, cogeneration, photovoltaic, and hydrogen production technologies. Additionally, a Bayesian best-worst method is used to evaluate the weights of the sustainability aspects by decision-makers, integrating these into the mathematical model. The model optimises industrial plant locations considering economic, environmental, and social parameters, including the net present value, energy consumption, and carbon footprint. The model’s functionalities are demonstrated through a real-world case study based in Emilia Romagna, Italy. It is subject to sensitivity analysis to evaluate how changes in the inputs affect the outcomes and highlights feasible trade-offs through the exploration of the ϵ-constraint. The findings demonstrate that the model substantially boosts energy and hydrogen production. It is not only economically viable but also reduces the carbon footprint associated with fossil fuels and landfilling. Additionally, it contributes to job creation. This research has significant implications, with potential future studies intended to focus on system resilience, plant location optimisation, and sustainability assessment. Full article
(This article belongs to the Special Issue Smart Cities and Industry 4.0)
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22 pages, 6962 KiB  
Article
An Artificial Intelligence and Industrial Internet of Things-Based Framework for Sustainable Hydropower Plant Operations
by Fation T. Fera and Christos Spandonidis
Smart Cities 2024, 7(1), 496-517; https://doi.org/10.3390/smartcities7010020 - 6 Feb 2024
Viewed by 876
Abstract
Hydropower plays a crucial role in supplying electricity to developed nations and is projected to expand its capacity in various developing countries such as Sub-Saharan Africa, Argentina, Colombia, and Turkey. With the increasing demand for sustainable energy and the emphasis on reducing carbon [...] Read more.
Hydropower plays a crucial role in supplying electricity to developed nations and is projected to expand its capacity in various developing countries such as Sub-Saharan Africa, Argentina, Colombia, and Turkey. With the increasing demand for sustainable energy and the emphasis on reducing carbon emissions, the significance of hydropower plants is growing. Nevertheless, numerous challenges arise for these plants due to their aging infrastructure, impacting both their efficiency and structural stability. In order to tackle these issues, the present study has formulated a specialized real-time framework for identifying damage, with a particular focus on detecting corrosion in the conductors of generators within hydropower plants. It should be noted that corrosion processes can be highly complex and nonlinear, making it challenging to develop accurate physics-based models that capture all the nuances. Therefore, the proposed framework leverages autoencoder, an unsupervised, data-driven AI technology with the Mahalanobis distance, to capture the intricacies of corrosion and automate its detection. Rigorous testing shows that it can identify slight variations indicating conductor corrosion with over 80% sensitivity and a 5% false alarm rate for ‘medium’ to ‘high’ severity damage. By detecting and resolving corrosion early, the system reduces disruptions, streamlines maintenance, and mitigates unscheduled repairs’ negative effects on the environment. This enhances energy generation effectiveness, promotes hydroelectric facilities’ long-term viability, and fosters community prosperity. Full article
(This article belongs to the Special Issue Smart Cities and Industry 4.0)
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