Next Issue
Volume 3, December
Previous Issue
Volume 3, June
 
 

Smart Cities, Volume 3, Issue 3 (September 2020) – 25 articles

Cover Story (view full-size image): Some pioneering smart cities have gained valuable experience from which both positive and negative lessons can be drawn. Followers can learn from these and join in this emerging trend. Still, the question remains as to whether these cities are truly ready to become smart. In view of the fact that the formulation and implementation of a smart city policy, like any other policy, need to be tailored to the contextual conditions, and would require infrastructures, assessment of the readiness of these cities to participate in this global trend is essential.Therefore, the present study aimed to provide an integrated theoretical framework to measure smart city readiness and, based on that, a Theory of Change that cities can consider when they prepare themselves for their transition to become ‘smart’. View this paper.
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
17 pages, 4941 KiB  
Article
Sustainable City: Energy Usage Prediction Method for Electrified Refuse Collection Vehicles
by Rui Zhao, Tudor Stincescu, Erica E. F. Ballantyne and David A. Stone
Smart Cities 2020, 3(3), 1100-1116; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030054 - 21 Sep 2020
Cited by 5 | Viewed by 3132
Abstract
With the initiative of sustainable smart city space, services and structures (3S), progress towards zero-emission municipal services has advanced the deployment of electric refuse collection vehicles (eRCVs). However, eRCVs are commonly equipped with oversized batteries which not only contribute to the majority of [...] Read more.
With the initiative of sustainable smart city space, services and structures (3S), progress towards zero-emission municipal services has advanced the deployment of electric refuse collection vehicles (eRCVs). However, eRCVs are commonly equipped with oversized batteries which not only contribute to the majority of the weight of the vehicles but also remain a consistent weight, independent of the stage of charge (SoC), thus crucially jeopardising the significance of eRCVs in sustainability and economic strategies. Hence, customising the battery capacity in such a way that minimises its weight while storing ample energy for stalwart serviceability could significantly enhance its sustainability. In this study, taking only addresses as input, through an emergent two-stage data analysis, the energy required to collect refuse from a group of addresses was predicted. Therefore, predictions of the battery capacity requirement for the target location are possible. The theories and techniques presented in this paper were evaluated using real-life data from eRCV trials. For the same group of addresses, predicted results show an averaged error rate of 8.44%, which successfully demonstrates that using the proposed address-driven energy prediction approach, the energy required to collect refuse from a set of addresses can be predicted, which can provide a means to optimise the vehicle’s battery requirement. Full article
(This article belongs to the Section Smart Transportation)
Show Figures

Figure 1

28 pages, 5649 KiB  
Article
Agent-Based Model of a Blockchain Enabled Peer-to-Peer Energy Market: Application for a Neighborhood Trial in Perth, Australia
by Jacob G. Monroe, Paula Hansen, Matthew Sorell and Emily Zechman Berglund
Smart Cities 2020, 3(3), 1072-1099; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030053 - 19 Sep 2020
Cited by 32 | Viewed by 6090
Abstract
The transfer of market power in electric generation from utilities to end-users spurred by the diffusion of distributed energy resources necessitates a new system of settlement in the electricity business that can better manage generation assets at the grid-edge. A new concept in [...] Read more.
The transfer of market power in electric generation from utilities to end-users spurred by the diffusion of distributed energy resources necessitates a new system of settlement in the electricity business that can better manage generation assets at the grid-edge. A new concept in facilitating distributed generation is peer-to-peer energy trading, where households exchange excess power with neighbors at a price they set themselves. However, little is known about the effects of peer-to-peer energy trading on the sociotechnical dynamics of electric power systems. Further, given the novelty of the concept, there are knowledge gaps regarding the impact of alternative electricity market structures and individual decision strategies on neighborhood exchanges and market outcomes. This study develops an empirical agent-based modeling (ABM) framework to simulate peer-to-peer electricity trades in a decentralized residential energy market. The framework is applied for a case study in Perth, Western Australia, where a blockchain-enabled energy trading platform was trialed among 18 households, which acted as prosumers or consumers. The ABM is applied for a set of alternative electricity market structures. Results assess the impact of solar generation forecasting approaches, battery energy storage, and ratio of prosumers to consumers on the dynamics of peer-to-peer energy trading systems. Designing an efficient, equitable, and sustainable future energy system hinges on the recognition of trade-offs on and across, social, technological, economic, and environmental levels. Results demonstrate that the ABM can be applied to manage emerging uncertainties by facilitating the testing and development of management strategies. Full article
Show Figures

Figure 1

33 pages, 3620 KiB  
Article
IoT-Enabled Smart Sustainable Cities: Challenges and Approaches
by Laura Belli, Antonio Cilfone, Luca Davoli, Gianluigi Ferrari, Paolo Adorni, Francesco Di Nocera, Alessandro Dall’Olio, Cristina Pellegrini, Marco Mordacci and Enzo Bertolotti
Smart Cities 2020, 3(3), 1039-1071; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030052 - 18 Sep 2020
Cited by 95 | Viewed by 24912
Abstract
The ongoing diffusion of Internet of Things (IoT) technologies is opening new possibilities, and one of the most remarkable applications is associated with the smart city paradigm, which is continuously evolving. In general, it can be defined as the integration of IoT and [...] Read more.
The ongoing diffusion of Internet of Things (IoT) technologies is opening new possibilities, and one of the most remarkable applications is associated with the smart city paradigm, which is continuously evolving. In general, it can be defined as the integration of IoT and Information Communication Technologies (ICT) into city management, with the aim of addressing the exponential growth of urbanization and population, thus significantly increasing people’s quality of life. The smart city paradigm is also strictly connected to sustainability aspects, taking into account, for example, the reduction of environmental impact of urban activities, the optimized management of energy resources, and the design of innovative services and solution for citizens. Abiding by this new paradigm, several cities started a process of strong innovation in different fields (such as mobility and transportation, industry, health, tourism, and education), thanks to significant investments provided by stakeholders and the European Commission (EC). In this paper, we analyze key aspects of an IoT infrastructure for smart cities, outlining the innovations implemented in the city of Parma (Emilia Romagna region, Italy) as a successful example. Special attention is dedicated to the theme of smart urban mobility. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Graphical abstract

17 pages, 1811 KiB  
Perspective
Disruptive Technologies in Smart Cities: A Survey on Current Trends and Challenges
by Laura-Diana Radu
Smart Cities 2020, 3(3), 1022-1038; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030051 - 13 Sep 2020
Cited by 53 | Viewed by 8757
Abstract
This paper aims to explore the most important disruptive technologies in the development of the smart city. Every smart city is a dynamic and complex system that attracts an increasing number of people in search of the benefits of urbanisation. According to the [...] Read more.
This paper aims to explore the most important disruptive technologies in the development of the smart city. Every smart city is a dynamic and complex system that attracts an increasing number of people in search of the benefits of urbanisation. According to the United Nations, 68% of the world population will be living in cities by 2050. This creates challenges related to limited resources and infrastructure (energy, water, transportation system, etc.). To solve these problems, new and emerging technologies are created. Internet of Things, big data, blockchain, artificial intelligence, data analytics, and machine and cognitive learning are just a few examples. They generate changes in key sectors such as health, energy, transportation, education, public safety, etc. Based on a comprehensive literature review, we identified the main disruptive technologies in smart cities. Applications that integrate these technologies help cities to be smarter and offer better living conditions and easier access to products and services for residents. Disruptive technologies are generally considered key drivers in smart city progress. This paper presents these disruptive technologies, their applications in smart cities, the most important challenges and critics. Full article
(This article belongs to the Special Issue Economy and Finance in Smart-Cities)
Show Figures

Graphical abstract

18 pages, 1890 KiB  
Article
A New SDN-Based Routing Protocol for Improving Delay in Smart City Environments
by Lamia EL-Garoui, Samuel Pierre and Steven Chamberland
Smart Cities 2020, 3(3), 1004-1021; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030050 - 09 Sep 2020
Cited by 23 | Viewed by 5233
Abstract
The smart city is an ecosystem that interconnects various devices like sensors, actuators, mobiles, and vehicles. The intelligent and connected transportation system (ICTS) is an essential part of this ecosystem that provides new real-time applications. The emerging applications are based on Internet-of-Things (IoT) [...] Read more.
The smart city is an ecosystem that interconnects various devices like sensors, actuators, mobiles, and vehicles. The intelligent and connected transportation system (ICTS) is an essential part of this ecosystem that provides new real-time applications. The emerging applications are based on Internet-of-Things (IoT) technologies, which bring out new challenges, such as heterogeneity and scalability, and they require innovative communication solutions. The existing routing protocols cannot achieve these requirements due to the surrounding knowledge supported by individual nodes and their neighbors, displaying partial visibility of the network. However, the issue grew ever more arduous to conceive routing protocols to satisfy the ever-changing network requirements due to its dynamic topology and its heterogeneity. Software-Defined Networking (SDN) offers the latest view of the entire network and the control of the network based on the application’s specifications. Nonetheless, one of the main problems that arise when using SDN is minimizing the transmission delay between ubiquitous nodes. In order to meet this constraint, a well-attended and realistic alternative is to adopt the Machine Learning (ML) algorithms as prediction solutions. In this paper, we propose a new routing protocol based on SDN and Naive Bayes solution to improve the delay. Simulation results show that our routing scheme outperforms the comparative ones in terms of end-to-end delay and packet delivery ratio. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Graphical abstract

26 pages, 1125 KiB  
Article
Replicating Smart Cities: The City-to-City Learning Programme in the Replicate EC-H2020-SCC Project
by Igor Calzada
Smart Cities 2020, 3(3), 978-1003; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030049 - 08 Sep 2020
Cited by 23 | Viewed by 6363
Abstract
This article addresses the problem of replication among smart cities in the European Commission’s Horizon 2020: Smart Cities and Communities (EC-H2020-SCC) framework programme. This article initially sets the general policy context by conducting a benchmarking about the explicit replication strategies followed by each [...] Read more.
This article addresses the problem of replication among smart cities in the European Commission’s Horizon 2020: Smart Cities and Communities (EC-H2020-SCC) framework programme. This article initially sets the general policy context by conducting a benchmarking about the explicit replication strategies followed by each of the 17 ongoing EC-H2020-SCC lighthouse projects. This article aims to shed light on the following research question: Why might replication not be happening among smart cities as a unidirectional, hierarchical, mechanistic, solutionist, and technocratic process? Particularly, in asking so, it focuses on the EC-H2020-SCC Replicate project by examining in depth the fieldwork action research process implemented during 2019 through a knowledge exchange webinar series with participant stakeholders from six European cities—three lighthouse cities (St. Sebastian, Florence, and Bristol) and three follower-fellow cities (Essen, Lausanne, and Nilüfer). This process resulted in a City-to-City Learning Programme that reformulated the issue of replication by experimenting an alternative and an enhanced policy approach. Thus, stemming from the evidence-based policy outcomes of the City-to-City Learning Programme, this article reveals that a replication policy approach from the social innovation lenses might be enabled as a multidirectional, radial, dynamic, iterative, and democratic learning process, overcoming the given unidirectional, hierarchical, mechanistic, solutionist, and technocratic approach. Full article
(This article belongs to the Special Issue Revisiting the Smart City Concept)
Show Figures

Figure 1

26 pages, 11166 KiB  
Article
Complexity in the Built Environment: Wayfinding Difficulties in the Modular Design of Qatar University’s Most Iconic Building
by Mark David Major, Heba O. Tannous, Doha Elsaman, Lolwa Al-Mohannadi, Meera Al-Khulifi and Shaikha Al-Thani
Smart Cities 2020, 3(3), 952-977; https://doi.org/10.3390/smartcities3030048 - 01 Sep 2020
Cited by 4 | Viewed by 3496
Abstract
Constructed in the 1980s, the BCR Corridors complex is the most iconic building at Qatar University (QU). However, it is also notorious for way-finding difficulties. The problem appears to derive from the repetitive similarity of individual parts in its modular design. Elevators, stairwells, [...] Read more.
Constructed in the 1980s, the BCR Corridors complex is the most iconic building at Qatar University (QU). However, it is also notorious for way-finding difficulties. The problem appears to derive from the repetitive similarity of individual parts in its modular design. Elevators, stairwells, screens, and temporary installations also create impediments to user readability and visibility. Collectively, this tends to complicate its relationship to the immediate context of the university campus. Recently, researchers at QU conducted a post-occupancy evaluation (PoE) of the BCR Corridors. It included (1) direct observation of movement flows and static occupation of space in common areas, (2) room use and photographic surveys, and (3) computer modeling of the spatial layout using space syntax. Space syntax is an international research program of academics and practitioners studying the role of built space in society from the single building to entire cities. The purpose of the PoE study was to understand observed patterns of movement and space use with reference to the problems for way-finding in the BCR Corridors. Based on this, researchers developed proposals for design alterations to enable easier use of the complex. The findings of the study support the above hypothesis about navigation problems in the building. Full article
(This article belongs to the Section Smart Buildings)
Show Figures

Figure 1

24 pages, 2609 KiB  
Article
BlendSPS: A BLockchain-ENabled Decentralized Smart Public Safety System
by Ronghua Xu, Seyed Yahya Nikouei, Deeraj Nagothu, Alem Fitwi and Yu Chen
Smart Cities 2020, 3(3), 928-951; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030047 - 01 Sep 2020
Cited by 31 | Viewed by 3167
Abstract
Due to the recent advancements in the Internet of Things (IoT) and Edge-Fog-Cloud Computing technologies, the Smart Public Safety (SPS) system has become a more realistic solution for seamless public safety services that are enabled by integrating machine learning (ML) into heterogeneous edge [...] Read more.
Due to the recent advancements in the Internet of Things (IoT) and Edge-Fog-Cloud Computing technologies, the Smart Public Safety (SPS) system has become a more realistic solution for seamless public safety services that are enabled by integrating machine learning (ML) into heterogeneous edge computing networks. While SPS facilitates convenient exchanges of surveillance data streams among device owners and third-party applications, the existing monolithic service-oriented architecture (SOA) is unable to provide scalable and extensible services in a large-scale heterogeneous network environment. Moreover, traditional security solutions rely on a centralized trusted third-party authority, which not only can be a performance bottleneck or the single point of failure, but it also incurs privacy concerns on improperly use of private information. Inspired by blockchain and microservices technologies, this paper proposed a BLockchain-ENabled Decentralized Smart Public Safety (BlendSPS) system. Leveraging the hybrid blockchain fabric, a microservices based security mechanism is implemented to enable decentralized security architecture, and it supports immutability, auditability, and traceability for secure data sharing and operations among participants of the SPS system. An extensive experimental study verified the feasibility of the proposed BlendSPS that possesses security and privacy proprieties with limited overhead on IoT based edge networks. Full article
Show Figures

Graphical abstract

34 pages, 3611 KiB  
Review
Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review
by Gabriela Ahmadi-Assalemi, Haider Al-Khateeb, Gregory Epiphaniou and Carsten Maple
Smart Cities 2020, 3(3), 894-927; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030046 - 13 Aug 2020
Cited by 24 | Viewed by 8258
Abstract
The world is experiencing a rapid growth of smart cities accelerated by Industry 4.0, including the Internet of Things (IoT), and enhanced by the application of emerging innovative technologies which in turn create highly fragile and complex cyber–physical–natural ecosystems. This paper systematically identifies [...] Read more.
The world is experiencing a rapid growth of smart cities accelerated by Industry 4.0, including the Internet of Things (IoT), and enhanced by the application of emerging innovative technologies which in turn create highly fragile and complex cyber–physical–natural ecosystems. This paper systematically identifies peer-reviewed literature and explicitly investigates empirical primary studies that address cyber resilience and digital forensic incident response (DFIR) aspects of cyber–physical systems (CPSs) in smart cities. Our findings show that CPSs addressing cyber resilience and support for modern DFIR are a recent paradigm. Most of the primary studies are focused on a subset of the incident response process, the “detection and analysis” phase whilst attempts to address other parts of the DFIR process remain limited. Further analysis shows that research focused on smart healthcare and smart citizen were addressed only by a small number of primary studies. Additionally, our findings identify a lack of available real CPS-generated datasets limiting the experiments to mostly testbed type environments or in some cases authors relied on simulation software. Therefore, contributing this systematic literature review (SLR), we used a search protocol providing an evidence-based summary of the key themes and main focus domains investigating cyber resilience and DFIR addressed by CPS frameworks and systems. This SLR also provides scientific evidence of the gaps in the literature for possible future directions for research within the CPS cybersecurity realm. In total, 600 papers were surveyed from which 52 primary studies were included and analysed. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Figure 1

21 pages, 7318 KiB  
Article
A Procedure for Complete Census Estimation of Rooftop Photovoltaic Potential in Urban Areas
by Andrea Pinna and Luca Massidda
Smart Cities 2020, 3(3), 873-893; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030045 - 12 Aug 2020
Cited by 11 | Viewed by 3586
Abstract
Rooftop photovoltaic solar systems can be an essential tool to support the energy transition of Europe. The assessment of solar power generation potential in urban areas, necessary for smart grid planning, requires the processing of data of different types, such as building cadastral [...] Read more.
Rooftop photovoltaic solar systems can be an essential tool to support the energy transition of Europe. The assessment of solar power generation potential in urban areas, necessary for smart grid planning, requires the processing of data of different types, such as building cadastral information, a detailed description of available roof areas, and solar irradiation data. We introduce an algorithm for the fast calculation of the building’s shadows and a procedure for the integration of solar irradiation in time. We therefore develop a methodology that allows a fast evaluation with minimal computational resources, and we apply it to an urban scenario of a medium-sized European city obtaining an estimate of the complete census PV power generation potential, with a spatial resolution of 1 m. We validate the results by comparison with a reference procedure, obtaining minimal deviation with a much lower demand for computational resources. Full article
(This article belongs to the Section Energy and ICT)
Show Figures

Graphical abstract

20 pages, 980 KiB  
Article
Blockchain as a Driver for Smart City Development: Application Fields and a Comprehensive Research Agenda
by Horst Treiblmaier, Abderahman Rejeb and Andreas Strebinger
Smart Cities 2020, 3(3), 853-872; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030044 - 07 Aug 2020
Cited by 61 | Viewed by 10436
Abstract
The term “Smart City” denotes a comprehensive concept to alleviate pending problems of modern urban areas which have developed into an important work field for practitioners and scholars alike. However, the question remains as to how cities can become “smart”. The application of [...] Read more.
The term “Smart City” denotes a comprehensive concept to alleviate pending problems of modern urban areas which have developed into an important work field for practitioners and scholars alike. However, the question remains as to how cities can become “smart”. The application of information technology is generally considered a key driver in the “smartization” of cities. Detailed frameworks and procedures are therefore needed to guide, operationalize, and measure the implementation process as well as the impact of the respective technologies. In this paper, we discuss blockchain technology, a novel driver of technological transformation that comprises a multitude of underlying technologies and protocols, and its potential impact on smart cities. We specifically address the question of how blockchain technology may benefit the development of urban areas. Based on a comprehensive literature review, we present a framework and research propositions. We identify nine application fields of blockchain technology in the smartization of cities: (1) healthcare, (2) logistics and supply chains, (3) mobility, (4) energy, (5) administration and services, (6) e-voting, (7) factory, (8) home and (9) education. We discuss current developments in these fields, illustrate how they are affected by blockchain technology and derive propositions to guide future research endeavors. Full article
Show Figures

Figure 1

11 pages, 426 KiB  
Letter
Deep Learning with Loss Ensembles for Solar Power Prediction in Smart Cities
by Moein Hajiabadi, Mahdi Farhadi, Vahide Babaiyan and Abouzar Estebsari
Smart Cities 2020, 3(3), 842-852; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030043 - 07 Aug 2020
Cited by 10 | Viewed by 2743
Abstract
The demand for renewable energy generation, especially photovoltaic (PV) power generation, has been growing over the past few years. However, the amount of generated energy by PV systems is highly dependent on weather conditions. Therefore, accurate forecasting of generated PV power is of [...] Read more.
The demand for renewable energy generation, especially photovoltaic (PV) power generation, has been growing over the past few years. However, the amount of generated energy by PV systems is highly dependent on weather conditions. Therefore, accurate forecasting of generated PV power is of importance for large-scale deployment of PV systems. Recently, machine learning (ML) methods have been widely used for PV power generation forecasting. A variety of these techniques, including artificial neural networks (ANNs), ridge regression, K-nearest neighbour (kNN) regression, decision trees, support vector regressions (SVRs) have been applied for this purpose and achieved good performance. In this paper, we briefly review the most recent ML techniques for PV energy generation forecasting and propose a new regression technique to automatically predict a PV system’s output based on historical input parameters. More specifically, the proposed loss function is a combination of three well-known loss functions: Correntropy, Absolute and Square Loss which encourages robustness and generalization jointly. We then integrate the proposed objective function into a Deep Learning model to predict a PV system’s output. By doing so, both the coefficients of loss functions and weight parameters of the ANN are learned jointly via back propagation. We investigate the effectiveness of the proposed method through comprehensive experiments on real data recorded by a real PV system. The experimental results confirm that our method outperforms the state-of-the-art ML methods for PV energy generation forecasting. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Graphical abstract

24 pages, 9193 KiB  
Article
Predicting Venue Popularity Using Crowd-Sourced and Passive Sensor Data
by Stanislav Timokhin, Mohammad Sadrani and Constantinos Antoniou
Smart Cities 2020, 3(3), 818-841; https://doi.org/10.3390/smartcities3030042 - 06 Aug 2020
Cited by 7 | Viewed by 3283
Abstract
Efficient and reliable mobility pattern identification is essential for transport planning research. In order to infer mobility patterns, however, a large amount of spatiotemporal data is needed, which is not always available. Hence, location-based social networks (LBSNs) have received considerable attention as a [...] Read more.
Efficient and reliable mobility pattern identification is essential for transport planning research. In order to infer mobility patterns, however, a large amount of spatiotemporal data is needed, which is not always available. Hence, location-based social networks (LBSNs) have received considerable attention as a potential data provider. The aim of this study is to investigate the possibility of using several different auxiliary information sources for venue popularity modeling and provide an alternative venue popularity measuring approach. Initially, data from widely used services, such as Google Maps, Yelp and OpenStreetMap (OSM), are used to model venue popularity. To estimate hourly venue occupancy, two different classes of model are used, including linear regression with lasso regularization and gradient boosted regression (GBR). The predictions are made based on venue-related parameters (e.g., rating, comments) and locational properties (e.g., stores, hotels, attractions). Results show that the prediction can be improved using GBR with a logarithmic transformation of the dependent variables. To investigate the quality of social media-based models by obtaining WiFi-based ground truth data, a microcontroller setup is developed to measure the actual number of people attending venues using WiFi presence detection, demonstrating that the similarity between the results of WiFi data collection and Google “Popular Times” is relatively promising. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Figure 1

12 pages, 732 KiB  
Letter
Model Predictive Control of a Road Junction
by Francesco Liberati
Smart Cities 2020, 3(3), 806-817; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030041 - 05 Aug 2020
Cited by 7 | Viewed by 2397
Abstract
This paper presents a model predictive control (MPC) approach for optimally managing the traffic light (TL) signals at a road junction. The objective is to improve queue balancing compared to traditional control strategies where TL signals are periodic. The resulting MPC optimization problem [...] Read more.
This paper presents a model predictive control (MPC) approach for optimally managing the traffic light (TL) signals at a road junction. The objective is to improve queue balancing compared to traditional control strategies where TL signals are periodic. The resulting MPC optimization problem is of quadratic mixed-integer nature. The proposed approach is validated via simulations based on a real scenario. Full article
(This article belongs to the Section Smart Urban Infrastructures)
Show Figures

Figure 1

13 pages, 2291 KiB  
Article
Smart Facility Management: Future Healthcare Organization through Indoor Positioning Systems in the Light of Enterprise BIM
by Tor Åsmund Evjen, Seyed Reza Hosseini Raviz, Sobah Abbas Petersen and John Krogstie
Smart Cities 2020, 3(3), 793-805; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030040 - 01 Aug 2020
Cited by 16 | Viewed by 5182
Abstract
Synthesizing the Internet of Things (IoT) with building information modeling (BIM) can improve the performance of the data collection. In this regard, BIM endeavors to enable real-time monitoring conditions of buildings. This paper is focused on the indoor positioning system (IPS) as a [...] Read more.
Synthesizing the Internet of Things (IoT) with building information modeling (BIM) can improve the performance of the data collection. In this regard, BIM endeavors to enable real-time monitoring conditions of buildings. This paper is focused on the indoor positioning system (IPS) as a key enabling technology for IoT applications, which uses smart and non-smart mobile devices (object tags and beacons) with the aim of positioning and objects tracking that lead to a smart approach in the field of facility management (FM). Hence, we have surveyed the joint use of IPS and BIM in FM based on the concept of enterprise BIM (EBIM). EBIM forms the basis for the future strategic real estate management using virtual models and open standards. As a result, we gained the ability to collect positioning data continuously, save them in a BIM database, and present them on two-dimensional (2D) maps. This is a part of an ongoing study that aims to use data collection effectively for FM as an organizational function in large and complex buildings. Hence, for this purpose, we have considered St. Olavs Hospital, one of the biggest healthcare centers in Norway, as a case study. The effectiveness of data collection by IoT devices installed in buildings and how the combination of BIM and IoT technology can support a holistic view of the status of the buildings, which subsequently can enhance data usage efficiency and FM development, will be demonstrated. Full article
(This article belongs to the Special Issue mHealth in Smart Cities)
Show Figures

Graphical abstract

26 pages, 2829 KiB  
Review
Advanced Machine Learning in Point Spectroscopy, RGB- and Hyperspectral-Imaging for Automatic Discriminations of Crops and Weeds: A Review
by Wen-Hao Su
Smart Cities 2020, 3(3), 767-792; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030039 - 01 Aug 2020
Cited by 59 | Viewed by 7983
Abstract
Crop productivity is readily reduced by competition from weeds. It is particularly important to control weeds early to prevent yield losses. Limited herbicide choices and increasing costs of weed management are threatening the profitability of crops. Smart agriculture can use intelligent technology to [...] Read more.
Crop productivity is readily reduced by competition from weeds. It is particularly important to control weeds early to prevent yield losses. Limited herbicide choices and increasing costs of weed management are threatening the profitability of crops. Smart agriculture can use intelligent technology to accurately measure the distribution of weeds in the field and perform weed control tasks in selected areas, which cannot only improve the effectiveness of pesticides, but also increase the economic benefits of agricultural products. The most important thing for an automatic system to remove weeds within crop rows is to utilize reliable sensing technology to achieve accurate differentiation of weeds and crops at specific locations in the field. In recent years, there have been many significant achievements involving the differentiation of crops and weeds. These studies are related to the development of rapid and non-destructive sensors, as well as the analysis methods for the data obtained. This paper presents a review of the use of three sensing methods including spectroscopy, color imaging, and hyperspectral imaging in the discrimination of crops and weeds. Several algorithms of machine learning have been employed for data analysis such as convolutional neural network (CNN), artificial neural network (ANN), and support vector machine (SVM). Successful applications include the weed detection in grain crops (such as maize, wheat, and soybean), vegetable crops (such as tomato, lettuce, and radish), and fiber crops (such as cotton) with unsupervised or supervised learning. This review gives a brief introduction into proposed sensing and machine learning methods, then provides an overview of instructive examples of these techniques for weed/crop discrimination. The discussion describes the recent progress made in the development of automated technology for accurate plant identification as well as the challenges and future prospects. It is believed that this review is of great significance to those who study automatic plant care in crops using intelligent technology. Full article
(This article belongs to the Special Issue Sustainable Agricultures and Food Production in Smart Cities)
Show Figures

Figure 1

9 pages, 627 KiB  
Editorial
CITIES: Ibero-American Research Network for Sustainable, Efficient, and Integrated Smart Cities
by Sergio Nesmachnow and Luis Hernández-Callejo
Smart Cities 2020, 3(3), 758-766; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030038 - 31 Jul 2020
Cited by 5 | Viewed by 2744
Abstract
This article describes CITIES, the Ibero-American research network for integrated, sustainable, and efficient smart cities. General/specific goals of the network are commented, and participant members are introduced. The main activities developed within the network are described, including research, education, outreach, and dissemination. Finally, [...] Read more.
This article describes CITIES, the Ibero-American research network for integrated, sustainable, and efficient smart cities. General/specific goals of the network are commented, and participant members are introduced. The main activities developed within the network are described, including research, education, outreach, and dissemination. Finally, some key aspects of the current and future work are presented. Full article
(This article belongs to the Special Issue Mobility and IoT for the Smart Cities)
Show Figures

Figure 1

22 pages, 21229 KiB  
Article
Gamified Participatory Sensing in Tourism: An Experimental Study of the Effects on Tourist Behavior and Satisfaction
by Shogo Kawanaka, Yuki Matsuda, Hirohiko Suwa, Manato Fujimoto, Yutaka Arakawa and Keiichi Yasumoto
Smart Cities 2020, 3(3), 736-757; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030037 - 16 Jul 2020
Cited by 10 | Viewed by 4454
Abstract
In the tourism sector, user-generated information and communication among tourists are perceived to be more effective and reliable contents. In addition, the collection of dynamic tourism information with high spatio-temporal resolution is required to provide comfortable tourism in response to the changing tourism [...] Read more.
In the tourism sector, user-generated information and communication among tourists are perceived to be more effective and reliable contents. In addition, the collection of dynamic tourism information with high spatio-temporal resolution is required to provide comfortable tourism in response to the changing tourism style with the advancement of information technology. Participatory sensing, which can collect various types of information is a useful method by which to collect these contents. However, continuous participation of users is essential in participatory sensing, and it is one of the most important points to stimulate participation motivation. In the tourism situation, we also need to pay attention to the total tourist satisfaction of participants. In this paper, we adopt gamification, i.e., the implementation of game design elements in real-world contexts for non-gaming purposes, for participatory sensing as an incentive mechanism to motivate participants with active participation and collect the necessary information efficiently. Within the framework, where points are given when completing the requested sensing task (=mission), two sensing missions with different burdens; Area Mission and Check-in Mission, and three different types of rewarding mechanisms; Fixed, Variable and Dynamic Variable, are designed as a gamification mechanism. We implemented these elements in the proposed participatory sensing platform application and conducted an experimental case study with 33 participants at an actual tourist spot: Kyoto, Japan. Then, we investigate the effects on tourist behavior and satisfaction by analyzing collected sensor data, mission logs, and post-survey answers. As a result, we can conclude the following: (1) the tourist behavior is changed due to the proposed gamification design and the necessary information was collected efficiently; (2) the participants tend to prioritize Check-in Mission over the sightseeing, which can induce a behavior change but might impact sightseeing enjoyment. Full article
Show Figures

Figure 1

31 pages, 2358 KiB  
Article
From a Comprehensive Pool to a Project-Specific List of Key Performance Indicators for Monitoring the Positive Energy Transition of Smart Cities—An Experience-Based Approach
by Komninos Angelakoglou, Konstantinos Kourtzanidis, Paraskevi Giourka, Vasilis Apostolopoulos, Nikos Nikolopoulos and Julia Kantorovitch
Smart Cities 2020, 3(3), 705-735; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030036 - 14 Jul 2020
Cited by 18 | Viewed by 6154
Abstract
As cities grow rapidly and energy needs increase, shaping an effective energy transition is a top priority towards urban sustainability and smart development. This study attempts to answer three key research questions that can help city authorities, planners and interested agents simplify and [...] Read more.
As cities grow rapidly and energy needs increase, shaping an effective energy transition is a top priority towards urban sustainability and smart development. This study attempts to answer three key research questions that can help city authorities, planners and interested agents simplify and increase the transparency of Key Performance Indicators (KPIs) selection for smart city and communities (SCC) projects focusing on energy transition and creation of Positive Energy Districts (PEDs): Question 1: “What resources are available for extracting such KPIs?”; Question 2: “Which of those KPIs are the most suitable for assessing the energy transition of smart city projects and PED-related developments?” and Question 3: “How can a project-specific shortlist of KPIs be developed?”. Answering these questions can also serve as a major first step towards a “universal” KPI selection procedure. In line with this purpose, an experiential approach is presented, capitalizing on knowledge and lessons learned from an ongoing smart city project in Europe (POCITYF) that focuses on PED deployment. Under this framework, a) a review of smart city KPI frameworks has been conducted, resulting in a pool of 258 indicators that can potentially be adopted by smart city projects; b) eight key dimensions of evaluations were extracted, setting a holistic performance framework relevant to SCCs; c) a detailed evaluation process including pre-determined criteria and city-needs feedback was applied to shortlist the KPI pool, leading to a ready-to-be-used, project-specific list of 63 KPIs and d) KPIs were sorted and analyzed in different granularity levels to further facilitate the monitoring procedure. The experiential procedure presented in this study can be easily adapted to the needs of every smart city project, serving as a recommendation guide. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Figure 1

29 pages, 1294 KiB  
Article
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities
by Negar Noori, Martin de Jong and Thomas Hoppe
Smart Cities 2020, 3(3), 676-704; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030035 - 10 Jul 2020
Cited by 24 | Viewed by 7021
Abstract
This paper introduces an indicator system to measure and assess smart city readiness. Analyzing smart city initiatives in Iran as case studies, the theoretical framework we present reflects on how cities explore the possibility of becoming smart, and prepare themselves to begin implementing [...] Read more.
This paper introduces an indicator system to measure and assess smart city readiness. Analyzing smart city initiatives in Iran as case studies, the theoretical framework we present reflects on how cities explore the possibility of becoming smart, and prepare themselves to begin implementing the transition towards becoming a smart city. This theoretical framework is then applied to four Iranian cities aspiring to become smart and that already possess credible smart city brands. The findings reveal that the most significant difficulty in Iran is associated with the political context. The changing urban governance model is the most important factor in Iranian smart cities’ readiness. Utilization of open data policies and data sharing, as well as making reforms in government structures are all considered a sine qua non to gain momentum. Based on the results of our empirical analysis a Theory of Change is developed to address the cities’ technological, socio-economic, and political readiness vis-à-vis the desired transition. The framework for measuring smart city readiness and the Theory of Change provide practical guidelines to developing systematic roadmaps for developing and implementing smart city policies. Full article
Show Figures

Figure 1

19 pages, 5038 KiB  
Article
Big Data Analytics in Australian Local Government
by Richard B. Watson and Peter J. Ryan
Smart Cities 2020, 3(3), 657-675; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030034 - 09 Jul 2020
Cited by 6 | Viewed by 6181
Abstract
Australian governments at all three levels—local (council), state, and federal—are beginning to exploit the massive amounts of data they collect through sensors and recording systems. Their aim is to enable Australian communities to benefit from “smart city” initiatives by providing greater efficiencies in [...] Read more.
Australian governments at all three levels—local (council), state, and federal—are beginning to exploit the massive amounts of data they collect through sensors and recording systems. Their aim is to enable Australian communities to benefit from “smart city” initiatives by providing greater efficiencies in their operations and strategic planning. Increasing numbers of datasets are being made freely available to the public. These so-called big data are amenable to data science analysis techniques including machine learning. While there are many cases of data use at the federal and state level, local councils are not taking full advantage of their data for a variety of reasons. This paper reviews the status of open datasets of Australian local governments and reports progress being made in several student and other projects to develop open data web services using machine learning for smart cities. Full article
Show Figures

Figure 1

15 pages, 5132 KiB  
Article
Power Supply Solution for Ultrahigh Speed Hyperloop Trains
by Marcos Lafoz, Gustavo Navarro, Jorge Torres, Álvaro Santiago, Jorge Nájera, Miguel Santos-Herran and Marcos Blanco
Smart Cities 2020, 3(3), 642-656; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030033 - 09 Jul 2020
Cited by 11 | Viewed by 5047
Abstract
The paper analyses the alternatives for the power supply of a Hyperloop type railway transport. The particular case of the technology of the Spanish company ZELEROS was studied. Based on previous technical specifications related to both the first prototype and a commercial system, [...] Read more.
The paper analyses the alternatives for the power supply of a Hyperloop type railway transport. The particular case of the technology of the Spanish company ZELEROS was studied. Based on previous technical specifications related to both the first prototype and a commercial system, different options were analyzed. We selected the use of a linear motor driven by a single power electronic converter, a distribution scheme comprising different sections along the acceleration area of the track, and an energy storage system based on supercapacitors for the energy supply. The power/energy ratio and the cycle capability are the reasons to become a feasible and competitive solution. A preliminary design methodology for the energy storage requirements is presented in the paper. Once the type of linear motor was selected, the power supply scheme was presented, based on a motor-side power electronic converter and a DC/DC converter which connects to the energy storage devices. An additional low power grid-tie converter for the recharge of the energy storage system was also used. Different track sections were defined, connected to the power electronic converter through corresponding switches, being supplied sequentially when the capsule presence is detected along the track. The particular characteristics of this application, with relatively short traction track area, as well as the high energy recuperation ratio due to the low losses, make more suitable the use of energy storage systems as the source of power supply than the direct connection to the grid. Full article
(This article belongs to the Special Issue Mobility and IoT for the Smart Cities)
Show Figures

Graphical abstract

38 pages, 1492 KiB  
Article
The Nexus between Market Needs and Value Attributes of Smart City Solutions towards Energy Transition. An Empirical Evidence of Two European Union (EU) Smart Cities, Evora and Alkmaar
by Paraskevi Giourka, Vasilis Apostolopoulos, Komninos Angelakoglou, Konstantinos Kourtzanidis, Nikos Nikolopoulos, Vasileios Sougkakis, Federica Fuligni, Stefano Barberis, Karin Verbeek, José Miguel Costa and João Formiga
Smart Cities 2020, 3(3), 604-641; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030032 - 06 Jul 2020
Cited by 10 | Viewed by 5086
Abstract
This study presents an experiential process and a market-oriented approach for realizing cities’ energy transition through smart solutions. The aim of this study is twofold: (a) present a process for defining a repository of innovative solutions that can be applied at building, district, [...] Read more.
This study presents an experiential process and a market-oriented approach for realizing cities’ energy transition through smart solutions. The aim of this study is twofold: (a) present a process for defining a repository of innovative solutions that can be applied at building, district, or city level, for two European Union cities, Evora and Alkmaar, and support the deployment of positive energy districts enabling a sustainable energy transition, and (b) understand in a systematic way the attributes of value offered by energy-related smart city solutions, in order to facilitate the development of sustainable value propositions that can successfully address city needs. The repository is assessed against four elements of value, which include social impact, life-changing, emotional, and functional attributes, according to the value pyramid of Maslow. Results show that the value attributes of quality, motivation, integration, cost reduction, information, and organization are highly relevant to the proposed smart solutions. The results presented in this study are useful for city planners, decision-makers, public bodies, citizens, and businesses interested in designing their energy transition strategy and defining novel technologies that promote urban energy sustainability. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Figure 1

19 pages, 1554 KiB  
Article
Shortening the Last Mile in Urban Areas: Optimizing a Smart Logistics Concept for E-Grocery Operations
by Max Leyerer, Marc-Oliver Sonneberg, Maximilian Heumann and Michael H. Breitner
Smart Cities 2020, 3(3), 585-603; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030031 - 02 Jul 2020
Cited by 19 | Viewed by 6808
Abstract
Urbanization, the corresponding road traffic, and increasing e-grocery markets require efficient and at the same time eco-friendly transport solutions. In contrast to traditional food procurement at local grocery stores, e-grocery, i.e., online ordered goods, are transported directly to end customers. We develop and [...] Read more.
Urbanization, the corresponding road traffic, and increasing e-grocery markets require efficient and at the same time eco-friendly transport solutions. In contrast to traditional food procurement at local grocery stores, e-grocery, i.e., online ordered goods, are transported directly to end customers. We develop and discuss an optimization approach to assist the planning of e-grocery deliveries in smart cities introducing a new last mile concept for the urban food supply chain. To supply city dwellers with their ordered products, a network of refrigerated grocery lockers is optimized to temporarily store the corresponding goods within urban areas. Customers either collect their orders by themselves or the products are delivered with electric cargo bicycles (ECBs). We propose a multi-echelon optimization model that minimizes the overall costs while consecutively determining optimal grocery locker locations, van routes from a depot to opened lockers, and ECB routes from lockers to customers. With our approach, we present an advanced concept for grocery deliveries in urban areas to shorten last mile distances, enhancing sustainable transportation by avoiding road traffic and emissions. Therefore, the concept is described as a smart transport system. Full article
(This article belongs to the Special Issue Smart Cities and Data-driven Innovative Solutions)
Show Figures

Figure 1

29 pages, 1425 KiB  
Review
Worldwide Coverage Mobile Systems for Supra-Smart Cities Communications: Featured Antennas and Design
by César Benavente-Peces and Iván Herrero-Sebastián
Smart Cities 2020, 3(3), 556-584; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities3030030 - 01 Jul 2020
Cited by 5 | Viewed by 3901
Abstract
Current terrestrial mobile communications networks can’t provide worldwide coverage. Satellite communications are expensive, and terminals are large and heavy. Worldwide mobile coverage requires the use of satellites providing an appropriate QoS, including polar regions. The analysis of the potential satellite constellations demonstrates that [...] Read more.
Current terrestrial mobile communications networks can’t provide worldwide coverage. Satellite communications are expensive, and terminals are large and heavy. Worldwide mobile coverage requires the use of satellites providing an appropriate QoS, including polar regions. The analysis of the potential satellite constellations demonstrates that LEO one is the best solution. A new generation of low cost, small size, lightweight and global mobile coverage LEO satellites is emerging. The main limitation of the terminals is the antenna size factor, and innovative antennas must be developed to meet this goal. This paper investigates the technologies and techniques for designing and developing antennas aimed at LEO satellite communications in Smart Cities and beyond, which are especially beneficial for mobile communications in areas without 4G/5G coverage. The paper focuses on the terrestrial segment and future mobile devices, remarking the design constraints. In this scenario, the paper reviews the most relevant technologies and techniques used to design suitable antennas. The investigation analyses the state-of-the-art and most recent advances in the design of antennas operating in the Ku-band. The main contribution of the authors is a novel antenna design approach based on SIW technology. The antenna features are compared with other approaches, highlighting the benefits, advantages and drawbacks. As a conclusion, the proposed antenna demonstrates to be a good solution to meet the design constraints for such an application: light, low cost, small size factor. Full article
(This article belongs to the Special Issue Feature Papers for Smart Cities)
Show Figures

Graphical abstract

Previous Issue
Next Issue
Back to TopTop