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Systems, Applications and Services for Smart Cities

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

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 33162

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Special Issue Editors

Prof. Dr. Maria Cristina Rodríguez Sánchez

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Electronic Technology Area, Universidad Rey Juan Carlos, 28933 Madrid, Spain
Interests: Internet of Things; monitoring; accessibility; security services; telemedicine applications; real-time systems; autonomous system
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. José Luis Lázaro-Galilea

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Guest Editor

Department of Electronics, Polytechnic School Office O-334, University of Alcalá, Campus Universitario, 28871 – Alcalá, Madrid, Spain
Interests: intelligent sensors; indoor positioning systems; visible light positioning; optical sensorial systems; sensor networks; electronic design
Special Issues, Collections and Topics in MDPI journals

Dr. Juan Martinez-Romo

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Guest Editor

Computer Languages and Systems Departament, UNED, 28006 Madrid, Spain
Interests: Machine learning; Context-aware inference models; telemedicine applications

Prof. Dr. Susana Borromeo

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Guest Editor

Department of Electronics, Universidad Rey Juan Carlos, 28933 Madrid, Spain
Interests: Sensor system electronics; integrated circuit design; low-noise and low-power design; telemedicine signal acquisition

Prof. Dr. Jorge Portilla

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Guest Editor

Centro de Electrónica Industrial, Universidad Politécnica de Madrid, 28006 Madrid, Spain
Interests: embedded-system design; wireless-sensor networks; Internet of Things and FPGA-based reconfigurable systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few years, interdisciplinary information and communications technologies (ICT) are increasingly being used to build smart and large-scale systems. ICT technologies, such as IoT (Internet of Things), 5G, data analytics, machine learning, deep learning, smart sensors, and artificial intelligence have further enabled the realisation of future smart cities.

This Special Issue will address standards, technologies, systems, research, implementation, deployment, applications, benchmarking, and policy. It will also cover various aspects of smart cities, such as smart transport, energy, homes, living, emergency security services, emergency protocols, quality of environment, smart health as telemedicine or bioengineering applications, artificial Intelligence, software and requirements engineering, human–computer interaction, individual methods, techniques in knowledge acquisition and representation, and the application, evaluation, and construction of systems.

Prof. Dr. Cristina Rodriguez-Sanchez
Prof. Dr. José Luis Lázaro-Galilea
Prof. Dr. Susana Borromeo
Prof. Dr. Juan Martínez Romo
Prof. Dr. Jorge Portilla
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.

Keywords

Internet of Things
real-time interventions
autonomous systems
remote monitoring
context-aware inference models
security and defence
behaviour monitoring
predictive models
personalised health

Published Papers (11 papers)

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Research

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24 pages, 3289 KiB

Open AccessArticle

GWLBC: Gray Wolf Optimization Based Load Balanced Clustering for Sustainable WSNs in Smart City Environment

by Surjit Singh, Srete Nikolovski and Prasun Chakrabarti

Sensors 2022, 22(19), 7113; https://0-doi-org.brum.beds.ac.uk/10.3390/s22197113 - 20 Sep 2022

Cited by 6 | Viewed by 2226

Abstract

In a smart city environment, with increased demand for energy efficiency, information exchange and communication through wireless sensor networks (WSNs) plays an important role. In WSNs, the sensors are usually operating in clusters, and they are allowed to restructure for effective communication over a large area and for a long time. In this scenario, load-balanced clustering is the cost-effective means of improving the system performance. Although clustering is a discrete problem, the computational intelligence techniques are more suitable for load balancing and minimizing energy consumption with different operating constraints. The literature reveals that the swarm intelligence-inspired computational approaches give excellent results among population-based meta-heuristic approaches because of their more remarkable exploration ability. Conversely, in this work, load-balanced clustering for sustainable WSNs is presented using improved gray wolf optimization (IGWO). In a smart city environment, the significant parameters of energy-efficient load-balanced clustering involve the network lifetime, dead cluster heads, dead gateways, dead sensor nodes, and energy consumption while ensuring information exchange and communication among the sensors and cluster heads. Therefore, based on the above parameters, the proposed IGWO is compared with the existing GWO and several other techniques. Moreover, the convergence characteristics of the proposed algorithm are demonstrated for an extensive network in a smart city environment, which consists of 500 sensors and 50 cluster heads deployed in an area of 500 × 500 m², and it was found to be significantly improved. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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12 pages, 2459 KiB

Open AccessArticle

Implementation of ISO/IEEE 11073 PHD SpO2 and ECG Device Specializations over Bluetooth HDP following Health Care Profile for Smart Living

by Alexandra Cristobal-Huerta, Angel Torrado-Carvajal, Cristina Rodriguez-Sanchez, Juan Antonio Hernandez-Tamames, Maria Luaces and Susana Borromeo

Sensors 2022, 22(15), 5648; https://0-doi-org.brum.beds.ac.uk/10.3390/s22155648 - 28 Jul 2022

Cited by 1 | Viewed by 2025

Abstract

Current m-Health scenarios in the smart living era, as the interpretation of the smart city at each person’s level, present several challenges associated with interoperability between different clinical devices and applications. The Continua Health Alliance establishes design guidelines to standardize application communication to guarantee interoperability among medical devices. In this paper, we describe the implementation of two IEEE agents for oxygen saturation level (SpO2) measurements and electrocardiogram (ECG) data acquisition, respectively, and a smartphone IEEE manager for validation. We developed both IEEE agents over the Bluetooth Health Device Profile following the Continua guidelines and they are part of a telemonitoring system. This system was evaluated in a sample composed of 10 volunteers (mean age 29.8 ± 7.1 y/o; 5 females) under supervision of an expert cardiologist. The evaluation consisted of measuring the SpO2 and ECG signal sitting and at rest, before and after exercising for 15 min. Physiological measurements were assessed and compared against commercial devices, and our expert physician did not find any relevant differences in the ECG signal. Additionally, the system was assessed when acquiring and processing different heart rate data to prove that warnings were generated when the heart rate was under/above the thresholds for bradycardia and tachycardia, respectively. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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16 pages, 2260 KiB

Open AccessArticle

Data Loss Reconstruction Method for a Bridge Weigh-in-Motion System Using Generative Adversarial Networks

by Yizhou Zhuang, Jiacheng Qin, Bin Chen, Chuanzhi Dong, Chenbo Xue and Said M. Easa

Sensors 2022, 22(3), 858; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030858 - 23 Jan 2022

Cited by 5 | Viewed by 2648

Abstract

In the application of a bridge weigh-in-motion (WIM) system, the collected data may be temporarily or permanently lost due to sensor failure or system transmission failure. The high data loss rate weakens the distribution characteristics of the collected data and the ability of the monitoring system to conduct assessments on bridge condition. A deep learning-based model, or generative adversarial network (GAN), is proposed to reconstruct the missing data in the bridge WIM systems. The proposed GAN in this study can model the collected dataset and predict the missing data. Firstly, the data from stable measurements before the data loss are provided, and then the generator is trained to extract the retained features from the dataset and the data lost in the process are collected by using only the responses of the remaining functional sensors. The discriminator feeds back the recognition results to the generator in order to improve its reconstruction accuracy. In the model training, two loss functions, generation loss and confrontation loss, are used, and the general outline and potential distribution characteristics of the signal are well processed by the model. Finally, by applying the engineering data of the Hangzhou Jiangdong Bridge to the GAN model, this paper verifies the effectiveness of the proposed method. The results show that the final reconstructed dataset is in good agreement with the actual dataset in terms of total vehicle weight and axle weight. Furthermore, the approximate contour and potential distribution characteristics of the original dataset are reproduced. It is suggested that the proposed method can be used in real-life applications. This research can provide a promising method for the data reconstruction of bridge monitoring systems. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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18 pages, 5886 KiB

Open AccessArticle

Energy Management Strategy for an Autonomous Hybrid Power Plant Destined to Supply Controllable Loads

by Imene Yahyaoui and Natalia Vidal de la Peña

Sensors 2022, 22(1), 357; https://0-doi-org.brum.beds.ac.uk/10.3390/s22010357 - 04 Jan 2022

Cited by 7 | Viewed by 1978

Abstract

This paper proposes an energy management strategy (EMS) for a hybrid stand-alone plant destined to supply controllable loads. The plant is composed of photovoltaic panels (PV), a wind turbine, a diesel generator, and a battery bank. The set of the power sources supplies controllable electrical loads. The proposed EMS aims to ensure the power supply of the loads by providing the required electrical power. Moreover, the EMS ensures the maximum use of the power generated by the renewable sources and therefore minimizes the use of the genset, and it ensures that the batteries bank operates into the prefixed values of state of charge to ensure their safe operation. The EMS provides the switching control of the switches that link the plant components and decides on the loads’ operation. The simulation of the system using measured climatic data of Mostoles (Madrid, Spain) shows that the proposed EMS fulfills the designed objectives. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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15 pages, 2361 KiB

Open AccessArticle

Multi-Agent System for Intelligent Urban Traffic Management Using Wireless Sensor Networks Data

by Maria Viorela Muntean

Sensors 2022, 22(1), 208; https://0-doi-org.brum.beds.ac.uk/10.3390/s22010208 - 29 Dec 2021

Cited by 8 | Viewed by 3453

Abstract

Intelligent traffic management is an important issue for smart cities. City councils try to implement the newest techniques and performant technologies in order to avoid traffic congestion, to optimize the use of traffic lights, to efficiently use car parking, etc. To find the best solution to this problem, Birmingham City Council decided to allow open-source predictive traffic forecasting by making the real-time datasets available. This paper proposes a multi-agent system (MAS) approach for intelligent urban traffic management in Birmingham using forecasting and classification techniques. The designed agents have the following tasks: forecast the occupancy rates for traffic flow, road junctions and car parking; classify the faults; control and monitor the entire process. The experimental results show that k-nearest neighbor forecasts with high accuracy rates for the traffic data and decision trees build the most accurate model for classifying the faults for their detection and repair in the shortest possible time. The whole learning process is coordinated by a monitoring agent in order to automate Birmingham city’s traffic management. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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23 pages, 12547 KiB

Open AccessArticle

A Holistic and Interoperable Approach towards the Implementation of Services for the Digital Transformation of Smart Cities: The Case of Vitoria-Gasteiz (Spain)

by Félix Larrinaga, Alain Pérez, Iñigo Aldalur, José L. Hernández, José Luis Izkara and Patxi Sáez de Viteri

Sensors 2021, 21(23), 8061; https://0-doi-org.brum.beds.ac.uk/10.3390/s21238061 - 02 Dec 2021

Cited by 11 | Viewed by 2986

Abstract

Cities in the 21st century play a major role in the sustainability and climate impact reduction challenges set by the European agenda. As the population of cities grows and their environmental impact becomes more evident, the European strategy aims to reduce greenhouse gas emissions—the main cause of climate change. Measures to reduce the impact of climate change include reducing energy consumption, improving mobility, harnessing resources and renewable energies, integrating nature-based solutions and efficiently managing infrastructure. The monitoring and control of all this activity is essential for its proper functioning. In this context, Information and Communication Technology (ICT) plays a key role in the digitisation, monitoring, and managing of these different verticals. Urban data platforms support cities on extracting Key Performance Indicators (KPI) in their efforts to make better decisions. Cities must be transformed by applying efficient urban planning measures and taking into account not only technological aspects, but also by applying a holistic vision in building solutions where citizens are at the centre. In addition, standardisation of platforms where applications are integrated as one is necessary. This requires interoperability between different verticals. This article presents the information platform developed for the city of Vitoria-Gasteiz in Spain. The platform is based on the UNE 178104 standard to provide a holistic architecture that integrates information from the different urban planning measures implemented in the city. The platform was constructed in the context of the SmartEnCity project following the urban transformation strategy established by the city. The article presents the value-added solutions implemented in the platform. These solutions have been developed by applying co-creation techniques in which stakeholders have been involved throughout the process. The platform proposes a step forward towards standardization, harmonises the integration of data from multiple vertical, provides interoperability between services, and simplifies scalability and replicability due to its microservice architecture. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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15 pages, 1623 KiB

Open AccessArticle

Spatial Autoregressive Model for Estimation of Visitors’ Dynamic Agglomeration Patterns Near Event Location

by Takumi Ban, Tomotaka Usui and Toshiyuki Yamamoto

Sensors 2021, 21(13), 4577; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134577 - 04 Jul 2021

Cited by 4 | Viewed by 2205

Abstract

The rapid development of ubiquitous mobile computing has enabled the collection of new types of massive traffic data to understand collective movement patterns in social spaces. Contributing to the understanding of crowd formation and dispersal in populated areas, we developed a model of visitors’ dynamic agglomeration patterns at a particular event using dynamic population data. This information, a type of big data, comprised aggregate Global Positioning System (GPS) location data automatically collected from mobile phones without users’ intervention over a grid with a spatial resolution of 250 m. Herein, spatial autoregressive models with two-step adjacency matrices are proposed to represent visitors’ movement between grids around the event site. We confirmed that the proposed models had a higher goodness-of-fit than those without spatial or temporal autocorrelations. The results also show a significant reduction in accuracy when applied to prediction with estimated values of the endogenous variables of prior time periods. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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17 pages, 3583 KiB

Open AccessArticle

A Pilot Study to Validate a Wearable Inertial Sensor for Gait Assessment in Older Adults with Falls

by Guillermo García-Villamil, Marta Neira-Álvarez, Elisabet Huertas-Hoyas, Antonio Ramón-Jiménez and Cristina Rodríguez-Sánchez

Sensors 2021, 21(13), 4334; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134334 - 24 Jun 2021

Cited by 11 | Viewed by 3659

Abstract

The high prevalence of falls and the enormous impact they have on the elderly population is a cause for concern. We aimed to develop a walking-monitor gait pattern (G-STRIDE) for older adults based on a 6-axis inertial measurement (IMU) with the application of pedestrian dead reckoning algorithms and tested its structural and clinical validity. A cross-sectional case–control study was conducted with 21 participants (11 fallers and 10 non-fallers). We measured gait using an IMU attached to the foot while participants walked around different grounds (indoor flooring, outdoor floor, asphalt, etc.). The G-STRIDE consisted of a portable inertial device that monitored the gait pattern and a mobile app for telematic clinical analysis. G-STRIDE made it possible to measure gait parameters under normal living conditions when walking without assessing the patient in the outpatient clinic. Moreover, we verified concurrent validity with convectional outcome measures using intraclass correlation coefficients (ICCs) and analyzed the differences between participants. G-STRIDE showed high estimation accuracy for the walking speed of the elderly and good concurrent validity compared to conventional measures (ICC = 0.69; p < 0.000). In conclusion, the developed inertial-based G-STRIDE can accurately classify older people with risk to fall with a significance as high as using traditional but more subjective clinical methods (gait speed, Timed Up and Go Test). Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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24 pages, 46517 KiB

Open AccessArticle

HelpResponder—System for the Security of First Responder Interventions

by M. Cristina Rodriguez-Sanchez, Luis Fernández-Jiménez, Antonio R. Jiménez, Joaquin Vaquero, Susana Borromeo and Jose L. Lázaro-Galilea

Sensors 2021, 21(8), 2614; https://0-doi-org.brum.beds.ac.uk/10.3390/s21082614 - 08 Apr 2021

Cited by 5 | Viewed by 3295

Abstract

Firefighter’s interventions under dense smoke and flames are hazardous and ideally need an efficient in-advance geo-located actuation plan. The existing communication and sensing technologies should be customized, optimized, and integrated to better know the conditions (flame locations, air condition) before and during the rescue team’s interventions. In this paper, we propose a firefighter intervention architecture, which consists of several sensing devices (flame detectors, carbon dioxide air content) a navigation platform (an autonomous ground wheeled robot), and a communication/localization network (BLE IoT network) that can be used before and during an intervention in rescue or fire extinguishing missions even for indoor or confined spaces. The paper’s key novelty presents our integrated solution, giving some key implementation details and an intensive experimentation campaign in two real firefighter scenarios with real controlled fires. Results carried out in these real indoor scenarios are presented to demonstrate the feasibility of the system. A fire detection system is proposed to improve fire focus in real time and moving in confined spaces with no visibility and physical references. The results obtained in the experimentation show the proposal’s effectiveness in locating the fire focus’s position and orientation reducing time and risk exposure. This kind of location-aware fire integrated systems would significantly impact the speed and security of first responder interventions. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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24 pages, 9930 KiB

Open AccessEditor’s ChoiceArticle

LOCATE-US: Indoor Positioning for Mobile Devices Using Encoded Ultrasonic Signals, Inertial Sensors and Graph-Matching

by David Gualda, María Carmen Pérez-Rubio, Jesús Ureña, Sergio Pérez-Bachiller, José Manuel Villadangos, Álvaro Hernández, Juan Jesús García and Ana Jiménez

Sensors 2021, 21(6), 1950; https://0-doi-org.brum.beds.ac.uk/10.3390/s21061950 - 10 Mar 2021

Cited by 20 | Viewed by 3539

Abstract

Indoor positioning remains a challenge and, despite much research and development carried out in the last decade, there is still no standard as with the Global Navigation Satellite Systems (GNSS) outdoors. This paper presents an indoor positioning system called LOCATE-US with adjustable granularity for use with commercial mobile devices, such as smartphones or tablets. LOCATE-US is privacy-oriented and allows every device to compute its own position by fusing ultrasonic, inertial sensor measurements and map information. Ultrasonic Local Positioning Systems (U-LPS) based on encoded signals are placed in critical zones that require an accuracy below a few decimeters to correct the accumulated drift errors of the inertial measurements. These systems are well suited to work at room level as walls confine acoustic waves inside. To avoid audible artifacts, the U-LPS emission is set at 41.67 kHz, and an ultrasonic acquisition module with reduced dimensions is attached to the mobile device through the USB port to capture signals. Processing in the mobile device involves an improved Time Differences of Arrival (TDOA) estimation that is fused with the measurements from an external inertial sensor to obtain real-time location and trajectory display at a 10 Hz rate. Graph-matching has also been included, considering available prior knowledge about the navigation scenario. This kind of device is an adequate platform for Location-Based Services (LBS), enabling applications such as augmented reality, guiding applications, or people monitoring and assistance. The system architecture can easily incorporate new sensors in the future, such as UWB, RFiD or others. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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Review

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25 pages, 1867 KiB

Open AccessReview

Autonomous Intersection Management: Optimal Trajectories and Efficient Scheduling

by Abdeljalil Abbas-Turki, Yazan Mualla, Nicolas Gaud, Davide Calvaresi, Wendan Du, Alexandre Lombard, Mahjoub Dridi and Abder Koukam

Sensors 2023, 23(3), 1509; https://0-doi-org.brum.beds.ac.uk/10.3390/s23031509 - 29 Jan 2023

Cited by 3 | Viewed by 2988

Abstract

Intersections are at the core of congestion in urban areas. After the end of the Second World War, the problem of intersection management has benefited from a growing body of advances to address the optimization of the traffic lights’ phase splits, timing, and offset. These contributions have significantly improved traffic safety and efficiency in urban areas. However, with the growth of transportation demand and motorization, traffic lights show their limits. At the end of the 1990s, the perspective of autonomous and connected driving systems motivated researchers to introduce a paradigm shift for controlling intersections. This new paradigm is well known today as autonomous intersection management (AIM). It harnesses the self-organization ability of future vehicles to provide more accurate control approaches that use the smallest available time window to reach unprecedented traffic performances. This is achieved by optimizing two main points of the interaction of connected and autonomous vehicles at intersections: the motion control of vehicles and the schedule of their accesses. Considering the great potential of AIM and the complexity of the problem, the proposed approaches are very different, starting from various assumptions. With the increasing popularity of AIM, this paper provides readers with a comprehensive vision of noticeable advances toward enhancing traffic efficiency. It shows that it is possible to tailor vehicles’ speed and schedule according to the traffic demand by using distributed particle swarm optimization. Moreover, it brings the most relevant contributions in the light of traffic engineering, where flow–speed diagrams are used to measure the impact of the proposed optimizations. Finally, this paper presents the current challenging issues to be addressed. Full article

(This article belongs to the Special Issue Systems, Applications and Services for Smart Cities)

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