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IoT for Smart Cities
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IoT for Smart Cities

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 (31 August 2019) | Viewed by 43476

Special Issue Editor

Prof. Dr. Carlos Ramos

E-Mail Website
Guest Editor
GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, P-4200-072 Porto, Portugal
Interests: artificial intelligence; decision-support systems; energy markets; machine learning; smart buildings; virtual power players
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

I would like to draw your attention to a Special Issue on the topic of “IoT for Smart Cities” to be published in Applied Sciences (ISSN 2076-3417; CODEN: ASPCC7), an open access journal with high visibility, indexed by Web of Science and SCOPUS.

The increase expected for urban population in the coming years is a big global challenge. According to the United Nations, by 2045 the population in urban areas will surpass 6 million inhabitants. In this context, the governance and management of cities and urban areas is today at the top of the agenda, giving opportunities for research, projects, technology transfer, and innovation. Due to the constraints imposed by increased populations, environmental needs, energy, mobility, health and well-being, aging, safety, employment and many other aspects, cities and urban areas need to be managed in an intelligent way.

Smart Cities use different types of electronic data collection sensors and systems to supply information which is used to manage assets and resources efficiently. This varies from data obtained from raw sensors to information extracted from social networks. It is important to note that all these sources of data and information need to be combined to create useful knowledge for the governance of cities, in order to efficiently manage aspects such as water supply, energy use, waste, and environmental quality, among others. We will be faced with a big data problem, and it is therefore important to use artificial intelligence approaches, such as machine learning, to facilitate real intelligence in the management of cities and urban areas.

The advent of the Internet of Things (IoT) enabled the creation of networks of physical devices, such as vehicles, home appliances, water, electricity, and air quality meters, trash deposits and other items embedded with electronics, software, sensors and actuators which enable these objects to connect and exchange data. Such IoT devices which will be highly prevalent in smart cities, will provide a valuable resource of data to support good decisions and resulting actuations.

This Special Issue is now open to receive papers related to the use of IoT in the context of smart cities. Potential topics, bearing the city and urban context in mind, include:

  • Sensor and Actuator Networks
  • IoT Interoperability
  • IoT Management and Control Platforms
  • IoT and Security & Privacy
  • Distributed Storage and Data Fusion
  • Mobility and Localization Technologies
  • IoT and Personal Data Protection
  • IoT Mining and Analytics
  • AI approaches using IoT
  • IoT for Transportation, Mobility, and Traffic Control
  • IoT for Water Management
  • IoT for Waste Management
  • IoT for Energy Management
  • IoT for Environmental Management
  • IoT for Health, Safety, Well-being, Inclusion and Active Aging
  • IoT in Buildings and Infrastructures
  • IoT for handling Critical and Emergency situations and Disasters
  • Citizen Participation
  • IoT for supporting Policy Development and Governance

Prof. Dr. Carlos Ramos
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 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.

Keywords

  • Active Aging
  • Artificial Intelligence
  • Buildings and Infrastructures
  • Citizen Participation
  • Critical and Emergence Situations
  • Control Platforms
  • Data Fusion
  • Energy Management
  • Environmental Management
  • Governance
  • Health and Well-being
  • Inclusion
  • Internet of Things
  • Interoperability
  • Mining and Analytics
  • Mobility and Localization;
  • Personal Data Protection
  • Policy Development
  • Security & Privacy
  • Sensors and Actuators
  • Transportation, Mobility, and Traffic Control
  • Waste Management
  • Water Management

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Published Papers (7 papers)

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Research

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15 pages, 866 KiB  
Article
Emotion-Driven System for Data Center Management
by Alberto Corredera, Marta Romero and Jose M. Moya
Appl. Sci. 2019, 9(19), 4073; https://doi.org/10.3390/app9194073 - 29 Sep 2019
Cited by 1 | Viewed by 2709
Abstract
Complex Information Systems and infrastructures, like Smart Cities, must be efficiently operated, minimizing inefficiencies and maximizing productivity. Traditional approaches are focused on improving the systems, automating processes and services, leaving aside human and emotions considerations. To achieve this efficient operation, we attempted to [...] Read more.
Complex Information Systems and infrastructures, like Smart Cities, must be efficiently operated, minimizing inefficiencies and maximizing productivity. Traditional approaches are focused on improving the systems, automating processes and services, leaving aside human and emotions considerations. To achieve this efficient operation, we attempted to cover both sides. We found new ways to capture the information coming from the workforce, in our case, the operations management team, and, merged this information with the data from the IoT sensors from the systems, enabling a holistic view of the entire operations occurring in real-time. In a Data Center environment, we have developed a set of tools for capturing the emotional data in order to detect potential biases caused by the specific mood of the person inside the operations team. We used Artificial Intelligence algorithms for finding the patterns that will help us to manage the system in the future. We compared and verified our findings with the existing references from other disciplines, e.g., Psychology. In this article, we expose some methods to be developed in future studies for supervising and increasing productivity in Data Centers, as a useful example for Smart Cities. Our research focuses on monitoring the mood and the emotional status of the personnel responsible for operating the system. We use this emotional data as an input for measurement. Full article
(This article belongs to the Special Issue IoT for Smart Cities)
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16 pages, 6721 KiB  
Article
Flooding Message Mitigation of Wireless Content Centric Networking for Last-Mile Smart-Grid
by Jaebeom Kim, Byung-Seok Park and Yong-up Park
Appl. Sci. 2019, 9(19), 3978; https://doi.org/10.3390/app9193978 - 23 Sep 2019
Cited by 3 | Viewed by 2376
Abstract
In view of Smart-Grid architecture, wireless Last-Mile Network (LMN) devices as smart meters and intelligent home control machines are normally installed in harsh and lossy communication environment. In order to improve communication reliability of LMN, we proposed Wireless Topology Aware Content Centric Networking [...] Read more.
In view of Smart-Grid architecture, wireless Last-Mile Network (LMN) devices as smart meters and intelligent home control machines are normally installed in harsh and lossy communication environment. In order to improve communication reliability of LMN, we proposed Wireless Topology Aware Content Centric Networking (TOP-CCN) protocol. TOP-CCN reduces channel access overhead of traditional Content Centric Networking and supports efficient multicast message transmission by using Multiple Point Relay (MPR), and Publisher MPR (PMPR). In addition, TOP-CCN LMN provides simple multi-hop forwarding scheme that can reduce the traditional routing control message overhead in multi-hop wireless LMN environment. The simulation result shows TOP-CCN can improve the service provisioning time and reliability compared to traditional IP based network model in LMN. Full article
(This article belongs to the Special Issue IoT for Smart Cities)
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21 pages, 1336 KiB  
Article
Beyond Stochastic Gradient Descent for Matrix Completion Based Indoor Localization
by Wafa Njima, Rafik Zayani, Iness Ahriz, Michel Terre and Ridha Bouallegue
Appl. Sci. 2019, 9(12), 2414; https://doi.org/10.3390/app9122414 - 13 Jun 2019
Cited by 12 | Viewed by 3646
Abstract
In this paper, we propose a high accuracy fingerprint-based localization scheme for the Internet of Things (IoT). The proposed scheme employs mathematical concepts based on sparse representation and matrix completion theories. Specifically, the proposed indoor localization scheme is formulated as a simple optimization [...] Read more.
In this paper, we propose a high accuracy fingerprint-based localization scheme for the Internet of Things (IoT). The proposed scheme employs mathematical concepts based on sparse representation and matrix completion theories. Specifically, the proposed indoor localization scheme is formulated as a simple optimization problem which enables efficient and reliable algorithm implementations. Many approaches, like Nesterov accelerated gradient (Nesterov), Adaptative Moment Estimation (Adam), Adadelta, Root Mean Square Propagation (RMSProp) and Adaptative gradient (Adagrad), have been implemented and compared in terms of localization accuracy and complexity. Simulation results demonstrate that Adam outperforms all other algorithms in terms of localization accuracy and computational complexity. Full article
(This article belongs to the Special Issue IoT for Smart Cities)
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15 pages, 1327 KiB  
Article
DiRPL: A RPL-Based Resource and Service Discovery Algorithm for 6LoWPANs
by Luca Davoli, Mattia Antonini and Gianluigi Ferrari
Appl. Sci. 2019, 9(1), 33; https://doi.org/10.3390/app9010033 - 22 Dec 2018
Cited by 7 | Viewed by 4958
Abstract
The Internet of Things (IoT) will bring together billions of devices, denoted as Smart Objects (SOs), in an Internet-like architecture. Typically, SOs are embedded devices with severe constraints in terms of processing capabilities, available memory (RAM/ROM), and energy consumption. SOs tend to be [...] Read more.
The Internet of Things (IoT) will bring together billions of devices, denoted as Smart Objects (SOs), in an Internet-like architecture. Typically, SOs are embedded devices with severe constraints in terms of processing capabilities, available memory (RAM/ROM), and energy consumption. SOs tend to be deployed in environments in which the human intervention is not suitable or needs to be minimized (e.g., smart city maintenance). They must adapt to the surrounding environment by self-configuring: to this end, several mechanisms have been proposed (e.g., UPnP, ZeroConf, etc.). In this paper, we focus on IEEE 802.15.4 networks with IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) adaptation layer, where IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is the routing protocol of choice. In this context, we propose a lightweight RPL-based mechanism to Resource Discovery (RD) and Service Discovery (SD), denoted as DiRPL. In particular, DiRPL exploits the RPL handshake to detect new nodes in the network; resources are then simply discovered with a Constrained Application Protocol (CoAP) request and can thus be published in a local resource directory. A very attractive feature of the proposed DiRPL approach is that it builds on well-defined and well-known standard protocols. The performance of the proposed system is investigated with WisMote nodes deployed inside the Cooja simulator, running the Contiki operating system. Practical application scenarios to large-scale smart city monitoring, such as smart lighting and large-scale water consumption monitoring, are investigated. Full article
(This article belongs to the Special Issue IoT for Smart Cities)
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27 pages, 2208 KiB  
Article
Characterizing Situations of Dock Overload in Bicycle Sharing Stations
by Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, Giuseppe Ricupero and Elena Baralis
Appl. Sci. 2018, 8(12), 2521; https://doi.org/10.3390/app8122521 - 6 Dec 2018
Cited by 4 | Viewed by 2859
Abstract
Bicycle sharing systems are becoming increasingly popular in cities around the world as they are an inexpensive and sustainable means of transportation. Promoting the use of these systems substantially improves the quality of life in cities by reducing pollutant emissions and traffic congestion. [...] Read more.
Bicycle sharing systems are becoming increasingly popular in cities around the world as they are an inexpensive and sustainable means of transportation. Promoting the use of these systems substantially improves the quality of life in cities by reducing pollutant emissions and traffic congestion. In these systems, bikes are made available for shared use to individuals on a short-term basis. They allow people to borrow a bike in one dock and return it to any other station with free docks belonging to the same system. The occupancy level of the stations can be constantly monitored. However, to achieve a satisfactory user experience, all the stations in the system must be neither overloaded nor empty when the user needs to access the station. The aim of this paper is to analyze occupancy level data acquired from real systems to determine situations of dock overload in multiple stations which could lead to service disruption. The proposed methodology relies on a pattern mining approach. A new pattern type called Occupancy Monitoring Pattern is proposed here to detect situations of dock overload in multiple stations. Since stations are geo-referenced and their occupancy levels are periodically monitored, occupancy patterns can be filtered and evaluated by taking into consideration both the spatial and temporal correlation of the acquired measurements. The results achieved on real data highlight the potential of the proposed methodology in supporting domain experts in their maintenance activities, such as periodic re-balancing of the occupancy levels of the stations, as well as in improving user experience by suggesting alternative stations in the nearby area. Full article
(This article belongs to the Special Issue IoT for Smart Cities)
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Review

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39 pages, 6085 KiB  
Review
A Comprehensive Study of the Use of LoRa in the Development of Smart Cities
by Roberto Omar Andrade and Sang Guun Yoo
Appl. Sci. 2019, 9(22), 4753; https://doi.org/10.3390/app9224753 - 7 Nov 2019
Cited by 81 | Viewed by 7311
Abstract
The New Urban Agenda (Agenda 2030) adopted at the United Nations Conference related to Sustainable Urban Development (Habitat III) in the year 2016 has the goal of prompting cities to achieve the identified Sustainable Development Goals by the year 2030. In this context, [...] Read more.
The New Urban Agenda (Agenda 2030) adopted at the United Nations Conference related to Sustainable Urban Development (Habitat III) in the year 2016 has the goal of prompting cities to achieve the identified Sustainable Development Goals by the year 2030. In this context, cities can experiment strategies of circular economy for the optimization of resources, waste reduction, reuse, and recycling. The data generated by the components of an Internet of Things (IoT) ecosystem can contribute in two relevant ways to a smart city model: (1) by the generation of a circular economy and (2) by the creation of intelligence to improve the decision-making processes by citizens or city managers. In this context, it is in our interest to understand the most relevant axes of the research related to IoT, particularly those based on the LoRa technology. LoRa has attracted the interest of researchers because it is an open standard and contributes to the development of sustainable smart cities, since they are linked to the concepts of a circular economy. Additionally, the intention of this work is to identify the technological or practical barriers that hamper the development of solutions, find possible future trends that could exist in the context of smart cities and IoT, and understand how they could be exploited by the industry and academy. Full article
(This article belongs to the Special Issue IoT for Smart Cities)
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34 pages, 1184 KiB  
Review
Smart Parking: A Literature Review from the Technological Perspective
by Jhonattan J. Barriga, Juan Sulca, José Luis León, Alejandro Ulloa, Diego Portero, Roberto Andrade and Sang Guun Yoo
Appl. Sci. 2019, 9(21), 4569; https://doi.org/10.3390/app9214569 - 28 Oct 2019
Cited by 96 | Viewed by 18648
Abstract
The development and high growth of the Internet of Things (IoT) have improved quality of life and strengthened different areas in society. Many cities worldwide are looking forward to becoming smart. One of the most popular use cases in smart cities is the [...] Read more.
The development and high growth of the Internet of Things (IoT) have improved quality of life and strengthened different areas in society. Many cities worldwide are looking forward to becoming smart. One of the most popular use cases in smart cities is the implementation of smart parking solutions, as they allow people to optimize time, reduce fuel consumption, and carbon dioxide emissions. Smart parking solutions have a defined architecture with particular components (sensors, communication protocols, and software solutions). Although there are only three components that compose a smart parking solution, it is important to mention that each component has many types that can be used in the deployment of these solutions. This paper identifies the most used types of every component and highlights usage trends in the established analysis period. It provides a complementary perspective and represents a very useful source of information. The scientific community could use this information to decide regarding the selection of types of components to implement a smart parking solution. For this purpose, herein we review several works related to smart parking solutions deployment. To achieve this goal, a semi-cyclic adaptation of the action research methodology combined with a systematic review is used to select papers related to the subject of study. The most relevant papers were reviewed to identify subcategories for each component; these classifications are presented in tables to mark the relevance of each paper accordingly. Trends of usage in terms of sensors, protocols and software solutions are analyzed and discussed in every section. In addition to the trends of usage, this paper determines a guide of complementary features from the type of components that should be considered when implementing a smart parking solution. Full article
(This article belongs to the Special Issue IoT for Smart Cities)
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