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Special Issue "Smart Cities"

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

Deadline for manuscript submissions: closed (30 November 2018)

Special Issue Editor

Guest Editor
Prof. Dr. Bart Braem

imec-IDLab-University of Antwerp, Middelheimlaan 1, B-2020 Antwerpen, Belgium
Website | E-Mail
Interests: smart cities; Internet of Things networks; network research infrastructure

Special Issue Information

Dear Colleagues,

Throughout history, cities have been at the heart of societies around the world. With their dense populations, in cities, both societal and technical challenges are typically experienced at a larger scale, with a greater impact. With the accelerating uptake of Internet of Things technologies, the IoT is now coming to cities around the world. Smart cities are arising as a new paradigm for modern cities. In a smart city, Internet of Things technology supports the city government, the (local) economy, and helps citizens to live a better life in the city of tomorrow.

To realize this highly-ambitious goal, in smart cities, Internet of Things application domains, such as smart mobility, smart sustainability, and smart grid, all have to be intelligently combined to create synergies, taking into account the needs of citizens, municipalities, and economies. As a result, smart city infrastructure has to support a very broad range of applications, each with different, possibly contradicting demands to the underlying infrastructure, including sensors, networks, and data platforms.

This Special Issue expects innovative work to explore new frontiers and challenges in the field of smart cities, including the mentioned sensors, network technologies, and data platforms, as well as large-scale deployments and innovative use cases of smart city technology.

The particular topics of interest include, but are not limited to:

  • Smart city architectures and frameworks
  • Software defined network integration with smart cities
  • Smart cities cloud and edge computing
  • Low-power smart city sensors
  • Fault-tolerance in smart cities
  • Smart city network orchestration
  • Computational intelligence for smart cities
  • Scalable smart city big data analytics
  • Deep learning algorithms for smart cities
  • Human-centric services and applications for smart cities
Prof. Dr. Bart Braem
Guest Editor

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 papers will be 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 1800 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
  • Cyber-physical systems
  • IoT
  • Artificial intelligence
  • Big data

Published Papers (10 papers)

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Research

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Open AccessArticle The Campus as a Smart City: University of Málaga Environmental, Learning, and Research Approaches
Sensors 2019, 19(6), 1349; https://doi.org/10.3390/s19061349
Received: 23 February 2019 / Revised: 5 March 2019 / Accepted: 11 March 2019 / Published: 18 March 2019
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Abstract
For the past few years, the concept of the Internet of Things (IoT) has been a recurrent view of the technological environment where nearly every object is expected to be connected to the network. This infrastructure will progressively allow one to monitor and [...] Read more.
For the past few years, the concept of the Internet of Things (IoT) has been a recurrent view of the technological environment where nearly every object is expected to be connected to the network. This infrastructure will progressively allow one to monitor and efficiently manage the environment. Until recent years, the IoT applications have been constrained by the limited computational capacity and especially by efficient communications, but the emergence of new communication technologies allows us to overcome most of these issues. This situation paves the way for the fulfillment of the Smart-City concept, where the cities become a fully efficient, monitored, and managed environment able to sustain the increasing needs of its citizens and achieve environmental goals and challenges. However, many Smart-City approaches still require testing and study for their full development and adoption. To facilitate this, the university of Málaga made the commitment to investigate and innovate the concept of Smart-Campus. The goal is to transform university campuses into “small” smart cities able to support efficient management of their area as well as innovative educational and research activities, which would be key factors to the proper development of the smart-cities of the future. This paper presents the University of Málaga long-term commitment to the development of its Smart-Campus in the fields of its infrastructure, management, research support, and learning activities. In this way, the adopted IoT and telecommunication architecture is presented, detailing the schemes and initiatives defined for its use in learning activities. This approach is then assessed, establishing the principles for its general application. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle A Regulatory View on Smart City Services
Sensors 2019, 19(2), 415; https://doi.org/10.3390/s19020415
Received: 12 December 2018 / Revised: 7 January 2019 / Accepted: 14 January 2019 / Published: 21 January 2019
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Abstract
Even though various commercial Smart City solutions are widely available on the market, we are still witnessing their rather limited adoption, where solutions are typically bound to specific verticals or remain in pilot stages. In this paper we argue that the lack of [...] Read more.
Even though various commercial Smart City solutions are widely available on the market, we are still witnessing their rather limited adoption, where solutions are typically bound to specific verticals or remain in pilot stages. In this paper we argue that the lack of a Smart City regulatory framework is one of the major obstacles for a wider adoption of Smart City services in practice. Such framework should be accompanied by examples of good practice which stress the necessity of adopting interoperable Smart City services. Development and deployment of Smart City services can incur significant costs to cities, service providers and sensor manufacturers, and thus it is vital to adjust national legislation to ensure legal certainty to all stakeholders, and at the same time to protect interests of the citizens and the state. Additionally, due to a vast number of heterogeneous devices and Smart City services, both existing and future, their interoperability becomes vital for service replicability and massive deployment leading to digital transformation of future cities. The paper provides a classification of technical and regulatory characteristics of IoT services for Smart Cities which are mapped to corresponding roles in the IoT value chain. Four example use cases are chosen—Smart Parking, Smart Metering, Smart Street Lighting and Mobile Crowd Sensing—to showcase the legal implications relevant to each service. Based on the analysis, we propose a set of recommendations for each role in the value chain related to regulatory requirements of the aforementioned Smart City services. The analysis and recommendations serve as examples of good practice in hope that they will facilitate a wider adoption and longevity of IoT-based Smart City services. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle Sii-Mobility: An IoT/IoE Architecture to Enhance Smart City Mobility and Transportation Services
Sensors 2019, 19(1), 1; https://doi.org/10.3390/s19010001
Received: 29 October 2018 / Revised: 20 November 2018 / Accepted: 15 December 2018 / Published: 20 December 2018
Cited by 1 | PDF Full-text (8863 KB) | HTML Full-text | XML Full-text
Abstract
The new Internet of Things/Everything (IoT/IoE) paradigm and architecture allows one to rethink the way Smart City infrastructures are designed and managed, but on the other hand, a number of problems have to be solved. In terms of mobility the cities that embrace [...] Read more.
The new Internet of Things/Everything (IoT/IoE) paradigm and architecture allows one to rethink the way Smart City infrastructures are designed and managed, but on the other hand, a number of problems have to be solved. In terms of mobility the cities that embrace the sensoring era can take advantage of this disruptive technology to improve the quality of life of their citizens, also thanks to the rationalization in the use of their resources. In Sii-Mobility, a national smart city project on mobility and transportation, a flexible platform has been designed and here, in this paper, is presented. It permits one to set up heterogeneous and complex scenarios that integrate sensors/actuators as IoT/IoE in an overall Big Data, Machine Learning and Data Analytics scenario. A detailed and complex case-study has been presented to validate the solution in the context of a system that dynamically reverse the traveling direction of a road segment, with all the safety conditions in place. This case study composes several building blocks of the IoT platform, which demonstrate that a flexible and dynamic set-up is possible, supporting security, safety, local, cloud and mixed solutions. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle A Low-Cost Open Hardware System for Collecting Traffic Data Using Wi-Fi Signal Strength
Sensors 2018, 18(11), 3623; https://doi.org/10.3390/s18113623
Received: 28 August 2018 / Revised: 18 October 2018 / Accepted: 22 October 2018 / Published: 25 October 2018
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Abstract
Road traffic and its impacts affect various aspects of wellbeing with safety, congestion and pollution being of significant concern in cities. Although there have been a large number of works done in the field of traffic data collection, there are several barriers which [...] Read more.
Road traffic and its impacts affect various aspects of wellbeing with safety, congestion and pollution being of significant concern in cities. Although there have been a large number of works done in the field of traffic data collection, there are several barriers which restrict the collection of traffic data at higher resolution in the cities. Installation and maintenance costs can act as a disincentive to use existing methods (e.g., loop detectors, video analysis) at a large scale and hence limit their deployment to only a few roads of the city. This paper presents an approach for vehicle counting using a low cost, simple and easily installable system. In the proposed system, vehicles (i.e., bicycles, cars, trucks) are counted by means of variations in the WiFi signals. Experiments with the developed hardware in two different scenarios—low traffic (i.e., 400 objects) and heavy traffic roads (i.e., 1000 objects)—demonstrate its ability to detect cars and trucks. The system can be used to provide estimates of vehicle numbers for streets not covered by official traffic monitoring techniques in future smart cities. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle Difficulties and Challenges of Anomaly Detection in Smart Cities: A Laboratory Analysis
Sensors 2018, 18(10), 3198; https://doi.org/10.3390/s18103198
Received: 19 July 2018 / Revised: 13 September 2018 / Accepted: 18 September 2018 / Published: 21 September 2018
Cited by 1 | PDF Full-text (9354 KB) | HTML Full-text | XML Full-text
Abstract
Smart cities work with large volumes of data from sensor networks and other sources. To prevent data from being compromised by attacks or errors, smart city IT administrators need to apply attack detection techniques to evaluate possible incidents as quickly as possible. Machine [...] Read more.
Smart cities work with large volumes of data from sensor networks and other sources. To prevent data from being compromised by attacks or errors, smart city IT administrators need to apply attack detection techniques to evaluate possible incidents as quickly as possible. Machine learning has proven to be effective in many fields and, in the context of wireless sensor networks (WSNs), it has proven adequate to detect attacks. However, a smart city poses a much more complex scenario than a WSN, and it has to be evaluated whether these techniques are equally valid and effective. In this work, we evaluate two machine learning algorithms (support vector machines (SVM) and isolation forests) to detect anomalies in a laboratory that reproduces a real smart city use case with heterogeneous devices, algorithms, protocols, and network configurations. The experience has allowed us to show that, although these techniques are of great value for smart cities, additional considerations must be taken into account to effectively detect attacks. Thus, through this empiric analysis, we point out broader challenges and difficulties of using machine learning in this context, both for the technical complexity of the systems, and for the technical difficulty of configuring and implementing them in such environments. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle Managing Pervasive Sensing Campaigns via an Experimentation-as-a-Service Platform for Smart Cities
Sensors 2018, 18(7), 2125; https://doi.org/10.3390/s18072125
Received: 25 April 2018 / Revised: 28 June 2018 / Accepted: 29 June 2018 / Published: 2 July 2018
Cited by 2 | PDF Full-text (4384 KB) | HTML Full-text | XML Full-text
Abstract
The adoption of technologies like the IoT in urban environments, together with the intensive use of smartphones, is driving transformation towards smart cities. Under this perspective, Experimentation-as-a-Service within OrganiCity aims to create an experimental facility with technologies, services, and applications that simplify innovation [...] Read more.
The adoption of technologies like the IoT in urban environments, together with the intensive use of smartphones, is driving transformation towards smart cities. Under this perspective, Experimentation-as-a-Service within OrganiCity aims to create an experimental facility with technologies, services, and applications that simplify innovation within urban ecosystems. We discuss here tools that facilitate experimentation, implementing ways to organize, execute, and administer experimentation campaigns in a smart city context. We discuss the benefits of our framework, presenting some preliminary results. This is the first time such tools are paired with large-scale smart city infrastructures, enabling both city-scale experimentation and cross-site experimentation. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle Do Monetary Incentives Influence Users’ Behavior in Participatory Sensing?
Sensors 2018, 18(5), 1426; https://doi.org/10.3390/s18051426
Received: 20 March 2018 / Revised: 28 April 2018 / Accepted: 3 May 2018 / Published: 4 May 2018
Cited by 2 | PDF Full-text (1381 KB) | HTML Full-text | XML Full-text
Abstract
Participatory sensing combines the powerful sensing capabilities of current mobile devices with the mobility and intelligence of human beings, and as such has to potential to collect various types of information at a high spatial and temporal resolution. Success, however, entirely relies on [...] Read more.
Participatory sensing combines the powerful sensing capabilities of current mobile devices with the mobility and intelligence of human beings, and as such has to potential to collect various types of information at a high spatial and temporal resolution. Success, however, entirely relies on the willingness and motivation of the users to carry out sensing tasks, and thus it is essential to incentivize the users’ active participation. In this article, we first present an open, generic participatory sensing framework (Citizense) which aims to make participatory sensing more accessible, flexible and transparent. Within the context of this framework we adopt three monetary incentive mechanisms which prioritize the fairness for the users while maintaining their simplicity and portability: fixed micro-payment, variable micro-payment and lottery. This incentive-enabled framework is then deployed on a large scale, real-world case study, where 230 participants were exposed to 44 different sensing campaigns. By randomly distributing incentive mechanisms among participants and a subset of campaigns, we study the behaviors of the overall population as well as the behaviors of different subgroups divided by demographic information with respect to the various incentive mechanisms. As a result of our study, we can conclude that (1) in general, monetary incentives work to improve participation rate; (2) for the overall population, a general descending order in terms of effectiveness of the incentive mechanisms can be established: fixed micro-payment first, then lottery-style payout and finally variable micro-payment. These two conclusions hold for all the demographic subgroups, even though different different internal distances between the incentive mechanisms are observed for different subgroups. Finally, a negative correlation between age and participation rate was found: older participants contribute less compared to their younger peers. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context
Sensors 2018, 18(4), 1282; https://doi.org/10.3390/s18041282
Received: 23 February 2018 / Revised: 3 April 2018 / Accepted: 17 April 2018 / Published: 21 April 2018
Cited by 7 | PDF Full-text (2917 KB) | HTML Full-text | XML Full-text
Abstract
This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is [...] Read more.
This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented. Full article
(This article belongs to the Special Issue Smart Cities)
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Open AccessArticle Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities
Sensors 2018, 18(4), 965; https://doi.org/10.3390/s18040965
Received: 15 February 2018 / Revised: 16 March 2018 / Accepted: 21 March 2018 / Published: 24 March 2018
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Abstract
In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes (Ad-Hoc) and neighborhood proximity (Top-K). Such a computation can be used for ZIP code-based target marketing as one of the [...] Read more.
In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes (Ad-Hoc) and neighborhood proximity (Top-K). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space. Full article
(This article belongs to the Special Issue Smart Cities)
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Review

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Open AccessReview Visualization of Urban Mobility Data from Intelligent Transportation Systems
Sensors 2019, 19(2), 332; https://doi.org/10.3390/s19020332
Received: 11 December 2018 / Revised: 2 January 2019 / Accepted: 10 January 2019 / Published: 15 January 2019
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Abstract
Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners [...] Read more.
Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings. Full article
(This article belongs to the Special Issue Smart Cities)
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