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Special Issue "Smart Cities of the Future: A Cyber Physical System Perspective"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 7850

Special Issue Editors

Prof. Dr. Antonio Puliafito
E-Mail Website
Guest Editor
Department of Engineering, University of Messina, 98122 Messina, Italy
Interests: cloud; IoT; smart cities; embedded systems; cyberphysical systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Symeon Papavassiliou
E-Mail Website
Guest Editor
School of Electrical and Computer Engineering, National Technical University of Athens, Iroon Polytechniou 9, 15780 Athens, Greece
Interests: complex networks; wireless systems; ad hoc and sensor networks; software-defined radios and software-defined networks; online social networks; network modeling and optimization; network economics; cyber physical systems; Internet of Things; future internet research experimentation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) integrates networked sensors such as WSNs and, more in general, physical objects (i.e., things) in a ubiquitous cyberspace by interconnecting these systems to the Internet at large, making them also available over the Web. At the same time, the evolution and combination of 5G with IoT have pushed researchers and industries to be looking at the technological transformation to move towards an environment, where multiple devices will be able to connect, share information, interpret, and deliver a seamless experience for users.

The integration of the physical world with the cyber one is commonly refered to as a cyberphysical system (CPS), where cyber interactions, physical perceptions, and social connections are combined into a ubiquitous hyperspace that remarkably enriches and broadens the interactions and connections among human-to-human, human-to-object, and object-to-object. When also strenthening the focus of social interactions and humann in the loop considerations, cyberphsyical social systems (CPSS) are also emerging, as an extension of the broader class of CPSs.

Based on the significant development of high variety of rich-soured IoT sensing devices, cyberphysical–social sensing and computing technologies, together with some advanced networking and communications technologies, we can obtain an integrated set of data, information, and knowledge from the physical world, human society, as well as the virtual world.

A smart city represents an improvement of today’s cities—both functionally and structurally—that strategically utilizes many smart factors, such as Information and Communications Technology (ICT), to increase the city’s sustainable growth and strengthen city functions, while ensuring citizens’ quality of life and health. Cities can be viewed as a microcosm of “objects” with which citizens interact daily and represent an extremely interesting example of cyberphysical systems, where a continuous monitoring of a city’s status occurs through sensors and processors applied within the real-world infrastructure.

Each object in the City can be both the collector and distributor of information regarding mobility, energy consumption, air pollution, as well as potentially offering cultural and tourist information. As a consequence, cyber and real worlds are strongly linked in a smart city. New services can be deployed when needed and evaluation mechanisms are set up to assess the health and success of a smart city. In particular, the objectives of creating ICT-enabled smart city environments aim to: improve city services; optimize decision-making; create smart urban infrastructures; orchestrate cyber and physical resources; address challenging urban issues such as environmental pollution, transportation management, energy usage and public health; optimize use and benefit of next generation (5G and beyond) communication; capitalize on social networks and their analysis; support Tactile Internet applications; inspire urban citizens to improve their quality of life; etc.

However, large-scale deployment of cyberphysical–social systems will face a series of challenges and issues (e.g., energy efficiency requirements, architecture, protocol stack design, implementation, security), which requires more smart sensing and computing methods, advanced networking, and communications technologies to provide more pervasive cyberphysical–social services for people.

This Special Issue is soliciting conceptual, theoretical, and experimental contributions, discussing and treating challenges, state-of-the-art, and solutions to a set of currently unresolved key questions related to CPSs and smart cities. The authors from both academia and industry are welcome to contribute and demonstrate the latest research results with the design, implementation, deployment, operation, and evaluation of smart sensing and computing models, networking methodologies, and communications tools and platforms for CPS, as well as describe and present relevant services and applications.

Topics of interest include but are not limited to the following:

  • Multifunctional IoT sensing devices
  • Networked smart cyberphysical–social sensing system and platform
  • Modeling of CPS
  • Energy-efficient cyberphysical–social sensing architectures
  • Green computing and sustainable computing for IoT and CPS
  • Cloud computing, fog computing, and edge computing
  • Routing protocols, data dissemination, and offloading algorithms
  • Community detection and network evolution analysis for CPS
  • Localization and node mobility models
  • Construction technology of dynamics of social groups
  • Methods for data collection, convergence, and storage
  • Schemes of data mining, processing, and analysis
  • Techniques of data visualization
  • Quality of experience and quality of service in CPS
  • Social network analysis and social influence analysis
  • Crowdsourcing, crowdsensing, participatory sensing
  • Low-power, distributed data processing in sensor applications
  • Smart worlds, smart cities, and smart healthcare
  • Security, privacy, and trust for the IoT
  • Energy-harvesting communications and networks
  • Machine learning/deep learning/artificial intelligent approaches
  • Applications and testbeds of CPS

Both review articles and original research papers relating to sensors and smart cities are solicited. There is particular interest in papers with advances towards practical experiences and services overcoming the adoption barriers for sensors and smart cities.

Prof. Dr. Antonio Puliafito
Prof. Dr. Symeon Papavassiliou
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. Sensors 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.

Keywords

  • cloud
  • IoT
  • smart cities
  • embedded systems
  • wireless systems
  • cyberphysical systems
  • online social networks
  • software-defined networks
  • network modeling and optimization
  • network economics
  • data management
  • Artificial Intelligence

Published Papers (7 papers)

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Research

Article
Cyber-Physical Systems and Smart Cities in India: Opportunities, Issues, and Challenges
Sensors 2021, 21(22), 7714; https://doi.org/10.3390/s21227714 - 19 Nov 2021
Viewed by 535
Abstract
A large section of the population around the globe is migrating towards urban settlements. Nations are working toward smart city projects to provide a better wellbeing for the inhabitants. Cyber-physical systems are at the core of the smart city setups. They are used [...] Read more.
A large section of the population around the globe is migrating towards urban settlements. Nations are working toward smart city projects to provide a better wellbeing for the inhabitants. Cyber-physical systems are at the core of the smart city setups. They are used in almost every system component within a smart city ecosystem. This paper attempts to discuss the key components and issues involved in transforming conventional cities into smart cities with a special focus on cyber-physical systems in the Indian context. The paper primarily focuses on the infrastructural facilities and technical knowhow to smartly convert classical cities that were built haphazardly due to overpopulation and ill planning into smart cities. It further discusses cyber-physical systems as a core component of smart city setups, highlighting the related security issues. The opportunities for businesses, governments, inhabitants, and other stakeholders in a smart city ecosystem in the Indian context are also discussed. Finally, it highlights the issues and challenges concerning technical, financial, and other social and infrastructural bottlenecks in the way of realizing smart city concepts along with future research directions. Full article
(This article belongs to the Special Issue Smart Cities of the Future: A Cyber Physical System Perspective)
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Article
A Methodology for Designing Smart Urban Living Labs from the University for the Cities of the Future
Sensors 2021, 21(20), 6712; https://doi.org/10.3390/s21206712 - 09 Oct 2021
Viewed by 810
Abstract
Cities have high demand and limited availability of water and energy, so it is necessary to have adequate technologies to make efficient use of these resources and to be able to generate them. This research focuses on developing and executing a methodology for [...] Read more.
Cities have high demand and limited availability of water and energy, so it is necessary to have adequate technologies to make efficient use of these resources and to be able to generate them. This research focuses on developing and executing a methodology for an urban living lab vocation identification for a new water and energy self-sufficient university building. The methods employed were constructing a technological roadmap to identify global trends and select the technologies and practices to be implemented in the building. Among the chosen technologies were those for capturing and using rain and residual water, the generation of solar energy, and water and energy generation and consumption monitoring. This building works as a living laboratory since the operation and monitoring generate knowledge and innovation through students and research groups that develop projects. The insights gained from this study may help other efforts to avoid pitfalls and better design smart living labs and off-grid buildings. Full article
(This article belongs to the Special Issue Smart Cities of the Future: A Cyber Physical System Perspective)
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Article
Testing Off-the-Shelf Optical Wireless LANs for Smart City Environments
Sensors 2021, 21(16), 5451; https://doi.org/10.3390/s21165451 - 12 Aug 2021
Viewed by 632
Abstract
Optical wireless LANs (OWLs) constitute an emerging networking paradigm for indoor scenarios’ fit to different smart cities’ fields of applications. Commercial products employing this technology have been made available on the market in recent years. In this work, we investigate, through a set [...] Read more.
Optical wireless LANs (OWLs) constitute an emerging networking paradigm for indoor scenarios’ fit to different smart cities’ fields of applications. Commercial products employing this technology have been made available on the market in recent years. In this work, we investigate, through a set of indoor communication experiments based on commercially available products, how different environmental and usage modes affect the performance of the system, addressing the presence of multiple users, the position and mobility of the mobile devices, the handover among adjacent cells and the effect of background lighting. Our finding shows that the system is quite robust with respect to the variation of operational conditions. We show that, in most conditions, the links can reliably sustain a stable throughput, achieving at least 50% of the throughput achieved with using the maximum light intensity of the transmitting lamp, while they are affected in a very mild way by factors like position and height of the mobile device, and virtually unaffected by variations in the background light. Full article
(This article belongs to the Special Issue Smart Cities of the Future: A Cyber Physical System Perspective)
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Article
Fuel Prediction and Reduction in Public Transportation by Sensor Monitoring and Bayesian Networks
Sensors 2021, 21(14), 4733; https://doi.org/10.3390/s21144733 - 11 Jul 2021
Cited by 2 | Viewed by 782
Abstract
We exploit the use of a controller area network (CAN-bus) to monitor sensors on the buses of local public transportation in a big European city. The aim is to advise fleet managers and policymakers on how to reduce fuel consumption so that air [...] Read more.
We exploit the use of a controller area network (CAN-bus) to monitor sensors on the buses of local public transportation in a big European city. The aim is to advise fleet managers and policymakers on how to reduce fuel consumption so that air pollution is controlled and public services are improved. We deploy heuristic algorithms and exhaustive ones to generate Bayesian networks among the monitored variables. The aim is to describe the relevant relationships between the variables, to discover and confirm the possible cause–effect relationships, to predict the fuel consumption dependent on the contextual conditions of traffic, and to enable an intervention analysis to be conducted on the variables so that our goals are achieved. We propose a validation technique using Bayesian networks based on Granger causality: it relies upon observations of the time series formed by successive values of the variables in time. We use the same method based on Granger causality to rank the Bayesian networks obtained as well. A comparison of the Bayesian networks discovered against the ground truth is proposed in a synthetic data set, specifically generated for this study: the results confirm the validity of the Bayesian networks that agree on most of the existing relationships. Full article
(This article belongs to the Special Issue Smart Cities of the Future: A Cyber Physical System Perspective)
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Article
Smart Cities of the Future as Cyber Physical Systems: Challenges and Enabling Technologies
Sensors 2021, 21(10), 3349; https://doi.org/10.3390/s21103349 - 12 May 2021
Cited by 6 | Viewed by 1133
Abstract
A smart city represents an improvement of today’s cities, both functionally and structurally, that strategically utilizes several smart factors, capitalizing on Information and Communications Technology (ICT) to increase the city’s sustainable growth and strengthen the city’s functions, while ensuring the citizens’ enhanced quality [...] Read more.
A smart city represents an improvement of today’s cities, both functionally and structurally, that strategically utilizes several smart factors, capitalizing on Information and Communications Technology (ICT) to increase the city’s sustainable growth and strengthen the city’s functions, while ensuring the citizens’ enhanced quality of life and health. Cities can be viewed as a microcosm of interconnected “objects” with which citizens interact daily, which represents an extremely interesting example of a cyber physical system (CPS), where the continuous monitoring of a city’s status occurs through sensors and processors applied within the real-world infrastructure. Each object in a city can be both the collector and distributor of information regarding mobility, energy consumption, air pollution as well as potentially offering cultural and tourist information. As a consequence, the cyber and real worlds are strongly linked and interdependent in a smart city. New services can be deployed when needed, and evaluation mechanisms can be set up to assess the health and success of a smart city. In particular, the objectives of creating ICT-enabled smart city environments target (but are not limited to) improved city services; optimized decision-making; the creation of smart urban infrastructures; the orchestration of cyber and physical resources; addressing challenging urban issues, such as environmental pollution, transportation management, energy usage and public health; the optimization of the use and benefits of next generation (5G and beyond) communication; the capitalization of social networks and their analysis; support for tactile internet applications; and the inspiration of urban citizens to improve their quality of life. However, the large scale deployment of cyber-physical-social systems faces a series of challenges and issues (e.g., energy efficiency requirements, architecture, protocol stack design, implementation, and security), which requires more smart sensing and computing methods as well as advanced networking and communications technologies to provide more pervasive cyber-physical-social services. In this paper, we discuss the challenges, the state-of-the-art, and the solutions to a set of currently unresolved key questions related to CPSs and smart cities. Full article
(This article belongs to the Special Issue Smart Cities of the Future: A Cyber Physical System Perspective)
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Article
An IoE and Big Multimedia Data Approach for Urban Transport System Resilience Management in Smart Cities
Sensors 2021, 21(2), 435; https://doi.org/10.3390/s21020435 - 09 Jan 2021
Cited by 13 | Viewed by 1585
Abstract
Today, the complexity of urban systems combined with existing and emerging threats constrains administrations to consider smart technologies and related huge amounts of data generated as a means to take timely and informed decisions. The smart city needs to be prepared for both [...] Read more.
Today, the complexity of urban systems combined with existing and emerging threats constrains administrations to consider smart technologies and related huge amounts of data generated as a means to take timely and informed decisions. The smart city needs to be prepared for both expected and unexpected situations, and the possibility to mitigate the effect of the uncertainty behind the causes of disruptions through the analysis of all the possible data generated by the city open new possibility for resilience operationalization. This article aims at introducing a new conceptualization for resilience and presenting an innovative full stack solution to exploit Internet of Everything (IoE) and big multimedia data in smart cities to manage resilience of urban transport systems (UTS), which is one of the most critical infrastructures of the city. The approach is based on a novel data driven approach to resilience engineering and functional resonance analysis method (FRAM), to understand and model an UTS in the context of smart cities and to support evidence driven decision making. The paper proposes an architecture taking into account: (a) different kinds of available data generated in the smart city, (b) big data collection and semantic aggregation and enrichment; (c) data sense-making process composed by analytics of different data sources like social media, communication networks, IoT, user behavior; (d) tools for knowledge driven decisions able to combine different information generated by analytics, experience, and structural information of the city into a comprehensive and evidence driven decision model. The solution has been applied in Florence metropolitan city in the context of RESOLUTE H2020 research project of the European Commission. Full article
(This article belongs to the Special Issue Smart Cities of the Future: A Cyber Physical System Perspective)
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Article
Error-Robust Distributed Denial of Service Attack Detection Based on an Average Common Feature Extraction Technique
Sensors 2020, 20(20), 5845; https://doi.org/10.3390/s20205845 - 16 Oct 2020
Cited by 6 | Viewed by 1113
Abstract
In recent years, advanced threats against Cyber–Physical Systems (CPSs), such as Distributed Denial of Service (DDoS) attacks, are increasing. Furthermore, traditional machine learning-based intrusion detection systems (IDSs) often fail to efficiently detect such attacks when corrupted datasets are used for IDS training. To [...] Read more.
In recent years, advanced threats against Cyber–Physical Systems (CPSs), such as Distributed Denial of Service (DDoS) attacks, are increasing. Furthermore, traditional machine learning-based intrusion detection systems (IDSs) often fail to efficiently detect such attacks when corrupted datasets are used for IDS training. To face these challenges, this paper proposes a novel error-robust multidimensional technique for DDoS attack detection. By applying the well-known Higher Order Singular Value Decomposition (HOSVD), initially, the average value of the common features among instances is filtered out from the dataset. Next, the filtered data are forwarded to machine learning classification algorithms in which traffic information is classified as a legitimate or a DDoS attack. In terms of results, the proposed scheme outperforms traditional low-rank approximation techniques, presenting an accuracy of 98.94%, detection rate of 97.70% and false alarm rate of 4.35% for a dataset corruption level of 30% with a random forest algorithm applied for classification. In addition, for error-free conditions, it is found that the proposed approach outperforms other related works, showing accuracy, detection rate and false alarm rate of 99.87%, 99.86% and 0.16%, respectively, for the gradient boosting classifier. Full article
(This article belongs to the Special Issue Smart Cities of the Future: A Cyber Physical System Perspective)
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