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Smart Cities of the Future: A Cyber Physical System Perspective

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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 23628

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Prof. Dr. Antonio Puliafito

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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; resource orchestration; 5G/6G system design; system sustainability
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

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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

25 pages, 1830 KiB

Open AccessArticle

Cyber-Physical Systems and Smart Cities in India: Opportunities, Issues, and Challenges

by Md. Onais Ahmad, Mohd Abdul Ahad, M. Afshar Alam, Farheen Siddiqui and Gabriella Casalino

Sensors 2021, 21(22), 7714; https://0-doi-org.brum.beds.ac.uk/10.3390/s21227714 - 19 Nov 2021

Cited by 8 | Viewed by 3420

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 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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15 pages, 2012 KiB

Open AccessArticle

A Methodology for Designing Smart Urban Living Labs from the University for the Cities of the Future

by Nadhiely Martínez-Bello, Mónica José Cruz-Prieto, David Güemes-Castorena and Alberto Mendoza-Domínguez

Sensors 2021, 21(20), 6712; https://0-doi-org.brum.beds.ac.uk/10.3390/s21206712 - 09 Oct 2021

Cited by 7 | Viewed by 2573

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 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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22 pages, 1623 KiB

Open AccessArticle

Testing Off-the-Shelf Optical Wireless LANs for Smart City Environments

by Loreto Pescosolido, Emilio Ancillotti and Andrea Passarella

Sensors 2021, 21(16), 5451; https://0-doi-org.brum.beds.ac.uk/10.3390/s21165451 - 12 Aug 2021

Cited by 1 | Viewed by 1910

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 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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27 pages, 1085 KiB

Open AccessArticle

Fuel Prediction and Reduction in Public Transportation by Sensor Monitoring and Bayesian Networks

by Federico Delussu, Faisal Imran, Christian Mattia and Rosa Meo

Sensors 2021, 21(14), 4733; https://0-doi-org.brum.beds.ac.uk/10.3390/s21144733 - 11 Jul 2021

Cited by 4 | Viewed by 2201

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 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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25 pages, 3718 KiB

Open AccessArticle

Smart Cities of the Future as Cyber Physical Systems: Challenges and Enabling Technologies

by Antonio Puliafito, Giuseppe Tricomi, Anastasios Zafeiropoulos and Symeon Papavassiliou

Sensors 2021, 21(10), 3349; https://0-doi-org.brum.beds.ac.uk/10.3390/s21103349 - 12 May 2021

Cited by 23 | Viewed by 4011

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 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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34 pages, 7033 KiB

Open AccessArticle

An IoE and Big Multimedia Data Approach for Urban Transport System Resilience Management in Smart Cities

by Emanuele Bellini, Pierfrancesco Bellini, Daniele Cenni, Paolo Nesi, Gianni Pantaleo, Irene Paoli and Michela Paolucci

Sensors 2021, 21(2), 435; https://0-doi-org.brum.beds.ac.uk/10.3390/s21020435 - 09 Jan 2021

Cited by 31 | Viewed by 4087

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 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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21 pages, 430 KiB

Open AccessArticle

Error-Robust Distributed Denial of Service Attack Detection Based on an Average Common Feature Extraction Technique

by João Paulo Abreu Maranhão, João Paulo Carvalho Lustosa da Costa, Edison Pignaton de Freitas, Elnaz Javidi and Rafael Timóteo de Sousa Júnior

Sensors 2020, 20(20), 5845; https://0-doi-org.brum.beds.ac.uk/10.3390/s20205845 - 16 Oct 2020

Cited by 10 | Viewed by 3336

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 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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