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Architectures and Platforms for Smart and Sustainable Cities

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

Deadline for manuscript submissions: closed (15 December 2019) | Viewed by 70366

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Dr. Alfonso González-Briones

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Department of Computer Science and Automation Control, University of Salamanca, 37007 Salamanca, Spain
Interests: smart cities; IoT; Industry 4.0; machine learning; artificial intelligence natural language processing; computational technologies; sentiment analysis
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Juan M. Corchado

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Guest Editor

1. BISITE Research Group, University of Salamanca, 37007 Salamanca, Spain
2. Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain
3. Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan
Interests: artificial intelligence; smart cities; smart grids
Special Issues, Collections and Topics in MDPI journals

Dr. Pablo Chamoso

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Guest Editor

BISITE Research Group, University of Salamanca, Calle Espejo sn, 24.2, 37007 Salamanca, Spain
Interests: smart cities; machine learning; IoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Technology is beginning to play a key role in cities’ urban sustainability plans. This is because new technologies can provide them with robust solutions that benefit their citizens. Cities aim to incorporate smart systems in their industrial, infrastructural, educational, and social activities. A Smart City is managed with intelligent technologies which improve the quality of the services offered to citizens and make all processes more efficient. However, the concept of a Smart City is fairly recent. The ideas that it encompasses have not yet been consolidated due to the large number of fields and technologies that fit under this concept. All of this has led to confusion about the definition of a Smart City, and this is evident in the literature.

This Special Issue aims to explore the topic of Smart Cities and the different artificial intelligence techniques that can be employed in the development of architectures for these cities or for the analysis of their data. Areas of interest include but are not limited to virtual organizations for the design of social computing systems, fog/edge computing mechanisms, the development of different types of applications and Cloud platforms, use of natural language processing (NLP) and information extraction techniques, sentiment analysis and other mechanisms for the conceptualization of data, deep learning systems, the development of intelligent algorithms for different purposes (such as the development of machine learning capabilities for applications, or the detection of patterns and relationships between data within Big Data systems), social machines for the development of decision support systems—DSS (based on hybrid algorithms that combine case-based reasoning—CBR with mixtures of experts), etc.

The topics of interest for this issue include but are not limited to:

Smart city modeling and simulation;
Smart mobility and transportation;
Intelligent vehicles;
Smart traffic system operations;
Smart integrated grids;
Intelligent infrastructure;
Sensors and actuators;
Open data and big data analytics;
Smart health and emergency management;
Smart environments;
Smart education;
Smart home and smart buildings;
Smart manufacturing and logistics.

Dr. Alfonso González-Briones
Prof. Dr. Juan Manuel Corchado
Dr. Pablo Chamoso
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.

Published Papers (12 papers)

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Research

23 pages, 5682 KiB

Open AccessFeature PaperArticle

Interoperable Open Specifications Framework for the Implementation of Standardized Urban Platforms

by José L. Hernández, Rubén García, Joachim Schonowski, Daniel Atlan, Guillaume Chanson and Timo Ruohomäki

Sensors 2020, 20(8), 2402; https://doi.org/10.3390/s20082402 - 23 Apr 2020

Cited by 19 | Viewed by 4137

Abstract

The current cities’ urban challenges go through digitalization and integration of new technologies under the perspective of actual and future ecological, as well as socio-economic commitments. This process is translated into the Open Standardized Urban Data Platform, which plays a pivotal role. Within its main functionalities, data ingestion, analytics and services as vertical domains become necessary to create more environmentally friendly cities. However, there still exist some deficits. Among them, openness and interoperability are outlined. On the one hand, there is a lack of open data initiatives for increasing the smart services stock. On the other hand, interoperability depends upon vendors and integrators, reducing the possibilities of Smart City growth. In this context, under the mySMARTLife project (GA #731297) umbrella, an Open Specifications Framework has been developed in order to address four main issues: (1) data interoperability; (2) services or verticals interoperability; (3) openness; and (4) replicability. It enlightens the implementation and integration of multiple city domains (like infrastructures, mobility, energy, buildings) for smart management and big-data analytics. Its applicability is demonstrated in the three lighthouse cities of the project, Nantes (France), Hamburg (Germany) and Helsinki (Finland). Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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14 pages, 8908 KiB

Open AccessFeature PaperArticle

ME³CA: A Cognitive Assistant for Physical Exercises that Monitors Emotions and the Environment

by Jaime A. Rincon, Angelo Costa, Paulo Novais, Vicente Julian and Carlos Carrascosa

Sensors 2020, 20(3), 852; https://doi.org/10.3390/s20030852 - 05 Feb 2020

Cited by 3 | Viewed by 2560

Abstract

Recent studies show that the elderly population has increased considerably in European society in recent years. This fact has led the European Union and many countries to propose new policies for caring services directed to this group. The current trend is to promote the care of the elderly in their own homes, thus avoiding inverting resources on residences. With this in mind, there are now new solutions in this direction, which try to make use of the continuous advances in computer science. This paper tries to advance in this area by proposing the use of a personal assistant to help older people at home while carrying out their daily activities. The proposed personal assistant is called ME³CA, and can be described as a cognitive assistant that offers users a personalised exercise plan for their rehabilitation. The system consists of a sensorisation platform along with decision-making algorithms paired with emotion detection models. ME³CA detects the users’ emotions, which are used in the decision-making process allowing for more precise suggestions and an accurate (and unbiased) knowledge about the users’ opinion towards each exercise. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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36 pages, 5671 KiB

Open AccessArticle

UAV Landing Using Computer Vision Techniques for Human Detection

by David Safadinho, João Ramos, Roberto Ribeiro, Vítor Filipe, João Barroso and António Pereira

Sensors 2020, 20(3), 613; https://doi.org/10.3390/s20030613 - 22 Jan 2020

Cited by 23 | Viewed by 6715

Abstract

The capability of drones to perform autonomous missions has led retail companies to use them for deliveries, saving time and human resources. In these services, the delivery depends on the Global Positioning System (GPS) to define an approximate landing point. However, the landscape can interfere with the satellite signal (e.g., tall buildings), reducing the accuracy of this approach. Changes in the environment can also invalidate the security of a previously defined landing site (e.g., irregular terrain, swimming pool). Therefore, the main goal of this work is to improve the process of goods delivery using drones, focusing on the detection of the potential receiver. We developed a solution that has been improved along its iterative assessment composed of five test scenarios. The built prototype complements the GPS through Computer Vision (CV) algorithms, based on Convolutional Neural Networks (CNN), running in a Raspberry Pi 3 with a Pi NoIR Camera (i.e., No InfraRed—without infrared filter). The experiments were performed with the models Single Shot Detector (SSD) MobileNet-V2, and SSDLite-MobileNet-V2. The best results were obtained in the afternoon, with the SSDLite architecture, for distances and heights between 2.5–10 m, with recalls from 59%–76%. The results confirm that a low computing power and cost-effective system can perform aerial human detection, estimating the landing position without an additional visual marker. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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20 pages, 7141 KiB

Open AccessArticle

Consumption Optimization in an Office Building Considering Flexible Loads and User Comfort

by Mahsa Khorram, Pedro Faria, Omid Abrishambaf and Zita Vale

Sensors 2020, 20(3), 593; https://doi.org/10.3390/s20030593 - 21 Jan 2020

Cited by 7 | Viewed by 2446

Abstract

This paper presents a multiperiod optimization algorithm that is implemented in a Supervisory Control and Data Acquisition system. The algorithm controls lights and air conditioners as flexible loads to reduce the consumption and controls a dishwasher as a deferrable load to implement the load shifting. Several parameters are considered to implement the algorithm for several successive periods in a real building operation. In the proposed methodology, optimization is done regarding user comfort, which is modeled in the objective function related to the indoor temperature in each room, and in the constraints in order to prevent excessive power reduction, according to users’ preferences. Additionally, the operation cycle of a dishwasher is included, and the algorithm selects the best starting point based on the appliance weights and power availability in each period. With the proposed methodology, the building energy manager can specify the moments when the optimization is run with consideration of the operational constraints. Accordingly, the main contribution of the paper is to provide and integrate a methodology to minimize the difference between the actual and the desired temperature in each room, as a measure of comfort, respecting constraints that can be easily bounded by building users and manager. The case study considers the real consumption data of an office building which contains 20 lights, 10 ACs, and one dishwasher. Three scenarios have been designed to focus on different functionalities. The outcomes of the paper include proof of the performance of the optimization algorithm and how such a system can effectively minimize electricity consumption by implementing demand response programs and using them in smart grid contexts. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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18 pages, 8540 KiB

Open AccessEditor’s ChoiceArticle

Design and Implementation of a Smart Traffic Signal Control System for Smart City Applications

by Wei-Hsun Lee and Chi-Yi Chiu

Sensors 2020, 20(2), 508; https://doi.org/10.3390/s20020508 - 16 Jan 2020

Cited by 96 | Viewed by 26720

Abstract

Infrastructure supporting vehicular network (V2X) capability is the key factor to the success of smart city because it enables many smart transportation services. In order to reduce the traffic congestion and improve the public transport efficiency, many intelligent transportation systems (ITS) need to be developed. In this paper, a smart traffic signal control (STSC) system is designed and implemented, it supports several smart city transportation applications including emergency vehicle signal preemption (EVSP), public transport signal priority (TSP), adaptive traffic signal control (ATSC), eco-driving supporting, and message broadcasting. The roadside unit (RSU) controller is the core of the proposed STSC system, where the system architecture, middleware, control algorithms, and peripheral modules are detailed discussed in this paper. It is compatible with existed traffic signal controller so that it can be fast and cost−effectively deployed. A new traffic signal scheme is specially designed for the EVSP scenario, it can inform all the drivers near the intersection regarding which direction the emergency vehicle (EV) is approaching, smoothing the traffic flow, and enhancing the safety. EVSP scenario and the related control algorithms are implemented in this work; integration test and field test are performed to demonstrate the STSC system. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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33 pages, 2157 KiB

Open AccessArticle

Component-Based Interactive Framework for Intelligent Transportation Cyber-Physical Systems

by Sangsoo Jeong, Youngmi Baek and Sang H. Son

Sensors 2020, 20(1), 264; https://doi.org/10.3390/s20010264 - 02 Jan 2020

Cited by 4 | Viewed by 3326

Abstract

While emerging technology for self-driving automation in vehicles progresses rapidly, the transition to an era of roads full of fully connected and automated vehicles (CAVs) may take longer than expected. Until then, it is inevitable that CAVs should coexist and interact with drivers of non-autonomous vehicles (NAVs) in urban roads. During this period of transition, it is critical to provide road safety with the mixed vehicular traffic and uncertainty caused by human drivers. To investigate the issues caused by the coexistence and interaction with humans, we propose to build a component-based and interactive intelligent transportation cyber-physical systems (ITCPS) framework. Our design of the interactive ITCPS framework aims to provide a standardized structure for users by defining core components. The framework is specified by behavior models and interfaces for the desired ITCPS components and is implemented as a form of human and hardware-in-the-loop system. We developed an intersection crossing assistance service and an automatic emergency braking service as an example of practical applications using the framework. To evaluate the framework, we tested its performance to show how effectively it operates while supporting real-time processing. The results indicate that it satisfies the timing requirements of vehicle-to-vehicle (V2V) communication and the limited processing time required for performing the functions of behavior models, even though the traffic volume reaches the road capacity. A case study using statistical analysis is conducted to assess the practical value of the developed experimental environment. The results of the case study validate the reliability among the specified variables for the experiments involving human drivers. It has shown that V2V communication support has positive effects on road safety, including intersection safety, braking events, and perception-reaction time (PRT) of the drivers. Furthermore, V2V communication support and PRT are identified as the important indicators affecting road safety at an un-signalized intersection. The proposed interactive framework is expected to contribute in constructing a comprehensive environment for the urban ITCPS and providing experimental support for the analysis of human behavior in the coexistence environment. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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18 pages, 2243 KiB

Open AccessArticle

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities

by Jose-Luis Poza-Lujan, Juan-Luis Posadas-Yagüe, José-Enrique Simó-Ten and Francisco Blanes

Sensors 2020, 20(1), 112; https://doi.org/10.3390/s20010112 - 23 Dec 2019

Cited by 10 | Viewed by 3474

Abstract

Object recognition, which can be used in processes such as reconstruction of the environment map or the intelligent navigation of vehicles, is a necessary task in smart city environments. In this paper, we propose an architecture that integrates heterogeneously distributed information to recognize objects in intelligent environments. The architecture is based on the IoT/Industry 4.0 model to interconnect the devices, which are called smart resources. Smart resources can process local sensor data and offer information to other devices as a service. These other devices can be located in the same operating range (the edge), in the same intranet (the fog), or on the Internet (the cloud). Smart resources must have an intelligent layer in order to be able to process the information. A system with two smart resources equipped with different image sensors is implemented to validate the architecture. Our experiments show that the integration of information increases the certainty in the recognition of objects by 2–4%. Consequently, in intelligent environments, it seems appropriate to provide the devices with not only intelligence, but also capabilities to collaborate closely with other devices. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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35 pages, 15438 KiB

Open AccessArticle

MuTraff: A Smart-City Multi-Map Traffic Routing Framework

by Alvaro Paricio and Miguel Angel Lopez-Carmona

Sensors 2019, 19(24), 5342; https://doi.org/10.3390/s19245342 - 04 Dec 2019

Cited by 4 | Viewed by 3857 | Retraction

Abstract

Urban traffic routing is deemed to be a significant challenge in intelligent transportation systems. Existing implementations suffer from several intrinsic issues such as scalability in centralized systems, unnecessary complexity of mechanisms and communication in distributed systems, and lack of privacy. These imply force intensive computational tasks in the traffic control center, continuous communication in real-time with involved stakeholders which require drivers to reveal their location, origin, and destination of their trips. In this paper we present an innovative urban traffic routing framework and reference architecture (multimap traffic control architecture, MuTraff), which is based on the strategical generation and distribution of a set of traffic network maps (traffic weighted multimaps, TWM) to vehicle categories or fleets. Each map in a TWM map set has the same topology but a different distribution of link weights, which are computed by considering policies and constraints that may apply to different vehicle groups. MuTraff delivers a traffic management system (TMS), where a traffic control center generates and distributes maps, while routing computation is performed at the vehicles. We show how this balance between generation, distribution, and routing computation improves scalability, eases communication complexities, and solves former privacy issues. Our study presents case studies in a real city environment for (a) global congestion management using random maps; (b) congestion control on road incidents; and c) emergency fleets routing. We show that MuTraff is a promising foundation framework that is easy to deploy, and is compatible with other existing TMS frameworks. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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22 pages, 1854 KiB

Open AccessArticle

QUADRIVEN: A Framework for Qualitative Taxi Demand Prediction Based on Time-Variant Online Social Network Data Analysis

by Fernando Terroso-Saenz, Andres Muñoz and José M. Cecilia

Sensors 2019, 19(22), 4882; https://doi.org/10.3390/s19224882 - 08 Nov 2019

Cited by 9 | Viewed by 2672

Abstract

Road traffic pollution is one of the key factors affecting urban air quality. There is a consensus in the community that the efficient use of public transport is the most effective solution. In that sense, much effort has been made in the data mining discipline to come up with solutions able to anticipate taxi demands in a city. This helps to optimize the trips made by such an important urban means of transport. However, most of the existing solutions in the literature define the taxi demand prediction as a regression problem based on historical taxi records. This causes serious limitations with respect to the required data to operate and the interpretability of the prediction outcome. In this paper, we introduce QUADRIVEN (QUalitative tAxi Demand pRediction based on tIme-Variant onlinE social Network data analysis), a novel approach to deal with the taxi demand prediction problem based on human-generated data widely available on online social networks. The result of the prediction is defined on the basis of categorical labels that allow obtaining a semantically-enriched output. Finally, this proposal was tested with different models in a large urban area, showing quite promising results with an F1 score above 0.8. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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22 pages, 584 KiB

Open AccessArticle

A Proof of Concept of a Mobile Health Application to Support Professionals in a Portuguese Nursing Home

by Márcia Esteves, Marisa Esteves, António Abelha and José Machado

Sensors 2019, 19(18), 3951; https://doi.org/10.3390/s19183951 - 12 Sep 2019

Cited by 6 | Viewed by 3586

Abstract

Over the past few years, the rapidly aging population has been posing several challenges to healthcare systems worldwide. Consequently, in Portugal, nursing homes have been getting a higher demand, and health professionals working in these facilities are overloaded with work. Moreover, the lack of health information and communication technology (HICT) and the use of unsophisticated methods, such as paper, in nursing homes to clinically manage residents lead to more errors and are time-consuming. Thus, this article proposes a proof of concept of a mobile health (mHealth) application developed for the health professionals working in a Portuguese nursing home to support them at the point-of-care, namely to manage and have access to information and to help them schedule, perform, and digitally record their tasks. Additionally, clinical and performance business intelligence (BI) indicators to assist the decision-making process are also defined. Thereby, this solution aims to introduce technological improvements into the facility to improve healthcare delivery and, by taking advantage of the benefits provided by these improvements, lessen some of the workload experienced by health professionals, reduce time-waste and errors, and, ultimately, enhance elders’ quality of life and improve the quality of the services provided. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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14 pages, 2957 KiB

Open AccessArticle

Optimal Path Planning for Selective Waste Collection in Smart Cities

by María-Victoria Bueno-Delgado, José-Luis Romero-Gázquez, Pilar Jiménez and Pablo Pavón-Mariño

Sensors 2019, 19(9), 1973; https://doi.org/10.3390/s19091973 - 27 Apr 2019

Cited by 35 | Viewed by 4619

Abstract

Waste collection is one of the targets of smart cities. It is a daily task in urban areas and it entails the planning of waste truck routes, taking into account environmental, economic and social factors. In this work, an optimal path planning algorithm has been developed together with a practical software platform for smart and sustainable cities that enables computing the optimal waste collection routes, minimizing the impact, both environmental (CO₂ emissions and acoustic damage) and socioeconomic (number of trucks to be used and fuel consumption). The algorithm is executed in Net2Plan, an open-source planning tool, typically used for modeling and planning communication networks. Net2Plan facilitates the introduction of the city layout input information to the algorithm, automatically importing it from geographical information system (GIS) databases using the so-called Net2Plan-GIS library, which can also include positions of smart bins. The algorithm, Net2Plan tool and its extension are open-source, available in a public repository. A practical case in the city of Cartagena (Spain) is presented, where the optimal path planning for plastic waste collection is addressed. This work contributes to the urban mobility plans of smart cities and could be extended to other smart cities scenarios with requests of optimal path planning. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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23 pages, 2141 KiB

Open AccessArticle

Positioning Information Privacy in Intelligent Transportation Systems: An Overview and Future Perspective

by Aleksandr Ometov, Sergey Bezzateev, Vadim Davydov, Anna Shchesniak, Pavel Masek, Elena Simona Lohan and Yevgeni Koucheryavy

Sensors 2019, 19(7), 1603; https://doi.org/10.3390/s19071603 - 03 Apr 2019

Cited by 10 | Viewed by 4767

Abstract

Today, the Intelligent Transportation Systems (ITS) are already in deep integration phase all over the world. One of the most significant enablers for ITS are vehicle positioning and tracking techniques. Worldwide integration of ITS employing Dedicated Short Range Communications (DSRC) and European standard for vehicular communication, known as ETSI ITS-G5, brings a variety of options to improve the positioning in areas where GPS connectivity is lacking precision. Utilization of the ready infrastructure, next-generation cellular 5G networks, and surrounding electronic devices together with conventional positioning techniques could become the solution to improve the overall ITS operation in vehicle-to-everything (V2X) communication scenario. Nonetheless, effective and secure communication protocols between the vehicle and roadside units should be both analyzed and improved in terms of potential attacks on the transmitted positioning-related data. In particular, said information might be misused or stolen at the infrastructure side conventionally assumed to be trusted. In this paper, we first survey different methods of vehicle positioning, which is followed by an overview of potential attacks on ITS systems. Next, we propose potential improvements allowing mutual authentication between the vehicle and infrastructure aiming at improving positioning data privacy. Finally, we propose a vision on the development and standardization aspects of such systems. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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