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Advances in Wireless Sensor Networks Applications for Health and Environment

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

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 34901

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Special Issue Editors

Dr. Antonio-Javier Garcia-Sanchez

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Department of Information and Communication Technologies, Universidad Politecnica de Cartagenadisabled, 30202 Cartagena, Spain
Interests: WSN; Internet of Things; LPWAN; streaming services; performance evaluation of communication networks; smart data processing and nanocommunications
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Rafael Asorey-Cacheda

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Guest Editor

Department of Information and Communication Technologies, Universidad Politécnica de Cartagena (UPCT), Campus Muralla del Mar, E-30202 Cartagena, Spain
Interests: wireless networks; internet of things; nanocommunications; streaming services
Special Issues, Collections and Topics in MDPI journals

Prof. Joan García-Haro

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Guest Editor

Department of Information Technologies and Communications, Universidad Politécnica de Cartagena (UPCT), 30202 Cartagena, Spain
Interests: Wireless Networks; Vehicular Networks; RFIDMAC protocols
Special Issues, Collections and Topics in MDPI journals

Dr. Victoria Beltran Martinez

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Guest Editor

Department of Telematics and Electronics, Universidad Politécnica de Madrid, Campus Sur, Ctra. de Valencia Km 7, 28031 Madrid, Spain
Interests: WSN; Internet of Things; communication protocols

Special Issue Information

Dear Colleagues,

Wireless sensor networks (WSNs) are considered a well-established and sound ICT technology consisting of an arbitrarily large number of low-cost, small, portable, low-consumption, and always connected devices that work collaboratively to offer a wide range of pervasive and ubiquitous smart services and applications in many areas. Under this technological umbrella, advances in WSN have become the cornerstone of recent paradigms such as the Internet of Things (IoT) or even Nanocommunications and Nanonetworks. They have already opened new opportunities in both the environment and health fields by developing innovative applications that represent a step forward to significantly improve our quality of life and preserve the environment. In this sense, sensors arranged on or inside the human body are able to monitor in a timely fashion the physiological condition of patients measuring their vital signs (e.g., temperature, heart rate, blood pressure, oxygen saturation) and sending these data to remote medical staff that interpret sensor readings and accurately assess the patient’s health. On the other hand, WSN devices together with their integrated physical sensors are a powerful tool to acquire environmental parameters and help in the air, water, and soil quality improvement. In addition, it should be highlighted that both aspects (health and environment) are not isolated since, for instance, a poor air quality in cities may expose citizens to pollution, compromising their health. Topics of interest include but are not limited to the following:

WSN and Internet of Things breakthroughs for health and the environment;
Low-power wide-area network solutions for health and environmental applications;
Body area sensor networks;
WSN and IoT in smart cities and smart territories for health and the environment;
Crowdsourcing/crowdsensing in WSN for health and the environment;
Nanocommunications and nanonetworks for health and environmental services;
Artificial intelligence and machine learning applied to WSN;
Security and privacy issues in WSN for health and the environment.

Dr. Antonio-Javier Garcia-Sanchez
Dr. Rafael Asorey-Cacheda
Prof. Dr. Joan García-Haro
Dr. Victoria Beltran Martinez
Guest Editors

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Published Papers (7 papers)

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Research

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27 pages, 6124 KiB

Open AccessArticle

Three-Factor Fast Authentication Scheme with Time Bound and User Anonymity for Multi-Server E-Health Systems in 5G-Based Wireless Sensor Networks

by Alice May-Kuen Wong, Chien-Lung Hsu, Tuan-Vinh Le, Mei-Chen Hsieh and Tzu-Wei Lin

Sensors 2020, 20(9), 2511; https://doi.org/10.3390/s20092511 - 29 Apr 2020

Cited by 44 | Viewed by 5002

Abstract

The fifth generation (5G) mobile network delivers high peak data rates with ultra-low latency and massive network capacity. Wireless sensor network (WSN) in Internet of Thing (IoT) architecture is of prominent use in 5G-enabled applications. The electronic healthcare (e-health) system has gained a lot of research attention since it allows e-health users to store and share data in a convenient way. By the support of 5G technology, healthcare data produced by sensor nodes are transited in the e-health system with high efficiency and reliability. It helps in reducing the treatment cost, providing efficient services, better analysis reports, and faster access to treatment. However, security and privacy issues become big concerns when the number of sensors and mobile devices is increasing. Moreover, existing single-server architecture requires to store a massive number of identities and passwords, which causes a significant database cost. In this paper, we propose a three-factor fast authentication scheme with time bound and user anonymity for multi-server e-health systems in 5G-based wireless sensor networks. In our work, the three-factor authentication scheme integrating biometrics, password, and smart card ensures a high-security sensor-enabled environment for communicating parties. User anonymity is preserved during communication process. Besides, time bound authentication can be applied to various healthcare scenarios to enhance security. The proposed protocol includes fast authentication, which can provide a fast communication for participating parties. Our protocol is also designed with multi-server architecture to simplify network load and significantly save database cost. Furthermore, security proof and performance analysis results show that our proposed protocol can resist various attacks and bear a rational communication cost. Full article

(This article belongs to the Special Issue Advances in Wireless Sensor Networks Applications for Health and Environment)

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14 pages, 1442 KiB

Open AccessArticle

An Optimal Multi-Channel Trilateration Localization Algorithm by Radio-Multipath Multi-Objective Evolution in RSS-Ranging-Based Wireless Sensor Networks

by Xuming Fang and Lijun Chen

Sensors 2020, 20(6), 1798; https://doi.org/10.3390/s20061798 - 24 Mar 2020

Cited by 20 | Viewed by 4043

Abstract

The Global Positioning System (GPS) is unable to provide precise localization services indoors, which has led to wireless sensor network (WSN) localization technology becoming a hot research issue in the field of indoor location. At present, the ranging technology of wireless sensor networks based on received signal strength has been extensively used in indoor positioning. However, wireless signals have serious multipath effects in indoor environments. In order to reduce the adverse influence of multipath effects on distance estimation between nodes, a multi-channel ranging localization algorithm based on signal diversity is herein proposed. In real indoor environments, the parameters used for multi-channel localization algorithms are generally unknown or time-varying. In order to increase the positioning accuracy of the multi-channel location algorithm in a multipath environment, we propose an optimal multi-channel trilateration positioning algorithm (OMCT) by establishing a novel multi-objective evolutionary model. The presented algorithm utilizes a three-edge constraint to prevent the traditional multi-channel localization algorithm falling into local optima. The results of a large number of practical experiments and numerical simulations show that no matter how the channel number and multipath number change, the positioning error of our presented algorithm is always smaller compared with that of the state-of-the-art algorithm. Full article

(This article belongs to the Special Issue Advances in Wireless Sensor Networks Applications for Health and Environment)

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19 pages, 1500 KiB

Open AccessArticle

A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor

by Jesús Pérez-Valero, Antonio-Javier Garcia-Sanchez, Manuel Ruiz Marín and Joan Garcia-Haro

Sensors 2020, 20(3), 896; https://doi.org/10.3390/s20030896 - 7 Feb 2020

Cited by 3 | Viewed by 3481

Abstract

Cardiovascular diseases are the leading cause of death around the world. As a result, low-cost biomedical sensors have been gaining importance in business and research over the last few decades. Their main benefits include their small size, light weight, portability and low power consumption. Despite these advantages, they are not generally used for clinical monitoring mainly because of their low accuracy in data acquisition. In this emerging technological context, this paper contributes by discussing a methodology to help practitioners build a prototype framework based on a low-cost commercial sensor. The resulting application consists of four modules; namely, a digitalization module whose input is an electrocardiograph signal in portable document format (PDF) or joint photographic expert group format (JPEG), a module to further process and filter the digitalized signal, a selectable data calibration module and, finally, a module implementing a classification algorithm to distinguish between individuals with normal sinus rhythms and those with atrial fibrillation. This last module employs our recently published symbolic recurrence quantification analysis (SRQA) algorithm on a time series of RR intervals. Moreover, we show that the algorithm applies to any biomedical low-cost sensor, achieving good results without requiring any calibration of the raw data acquired. In addition, it has been validated with a well-accepted public electrocardiograph (ECG) data base, obtaining 87.65%, 91.84%, and 91.31% in terms of sensitivity, specificity and accuracy, respectively. Full article

(This article belongs to the Special Issue Advances in Wireless Sensor Networks Applications for Health and Environment)

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27 pages, 3642 KiB

Open AccessArticle

Consumption Analysis of Smartphone based Fall Detection Systems with Multiple External Wireless Sensors

by Francisco Javier González-Cañete and Eduardo Casilari

Sensors 2020, 20(3), 622; https://doi.org/10.3390/s20030622 - 22 Jan 2020

Cited by 11 | Viewed by 4936

Abstract

Fall Detection Systems (FDSs) based on wearable technologies have gained much research attention in recent years. Due to the networking and computing capabilities of smartphones, these widespread personal devices have been proposed to deploy cost-effective wearable systems intended for automatic fall detection. In spite of the fact that smartphones are natively provided with inertial sensors (accelerometers and gyroscopes), the effectiveness of a smartphone-based FDS can be improved if it also exploits the measurements collected by small low-power wireless sensors, which can be firmly attached to the user’s body without causing discomfort. For these architectures with multiple sensing points, the smartphone transported by the user can act as the core of the FDS architecture by processing and analyzing the data measured by the external sensors and transmitting the corresponding alarm whenever a fall is detected. In this context, the wireless communications with the sensors and with the remote monitoring point may impact on the general performance of the smartphone and, in particular, on the battery lifetime. In contrast with most works in the literature (which disregard the real feasibility of implementing an FDS on a smartphone), this paper explores the actual potential of current commercial smartphones to put into operation an FDS that incorporates several external sensors. This study analyzes diverse operational aspects that may influence the consumption (as the use of a GPS sensor, the coexistence with other apps, the retransmission of the measurements to an external server, etc.) and identifies practical scenarios in which the deployment of a smartphone-based FDS is viable. Full article

(This article belongs to the Special Issue Advances in Wireless Sensor Networks Applications for Health and Environment)

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Review

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32 pages, 1264 KiB

Open AccessReview

A Survey on Trust Management for WBAN: Investigations and Future Directions

by Samiha Ayed, Lamia Chaari and Amina Fares

Sensors 2020, 20(21), 6041; https://doi.org/10.3390/s20216041 - 23 Oct 2020

Cited by 21 | Viewed by 3950

Abstract

The rapid uptake of the Wireless Body Area Networks (WBAN) and their services poses unprecedented security requirements. WBAN are evolving to support these requirements. Fulfilling these tasks is challenging as their mobile context is increasingly complex, heterogeneous, and evolving. One potential solution to meet the WBAN security requirements is trust management that helps to reach a more secure and adaptable WBAN environment. Accordingly, this article aims to serve as a brief survey of trust management approaches within intra-WBAN and inter-WBAN. For that, we first summarize trust management concepts, discuss WBAN challenges and classify the attacks on WBAN trust management models. Subsequently, we detail and compare the existing trust based approaches in a WBAN context. We pinpoint their limitations and provide a new classification of these different approaches. We also propose a set of best practices that may help the reader to build a robust and an efficient trust management framework. We complete this survey by highlighting the open future directions and perspectives for research. Full article

(This article belongs to the Special Issue Advances in Wireless Sensor Networks Applications for Health and Environment)

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22 pages, 3743 KiB

Open AccessReview

Performance Analysis of IoT-Based Health and Environment WSN Deployment

by Maryam Shakeri, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi and S. M. Riazul Islam

Sensors 2020, 20(20), 5923; https://doi.org/10.3390/s20205923 - 20 Oct 2020

Cited by 25 | Viewed by 4293

Abstract

With the development of Internet of Things (IoT) applications, applying the potential and benefits of IoT technology in the health and environment services is increasing to improve the service quality using sensors and devices. This paper aims to apply GIS-based optimization algorithms for optimizing IoT-based network deployment through the use of wireless sensor networks (WSNs) and smart connected sensors for environmental and health applications. First, the WSN deployment research studies in health and environment applications are reviewed including fire monitoring, precise agriculture, telemonitoring, smart home, and hospital. Second, the WSN deployment process is modeled to optimize two conflict objectives, coverage and lifetime, by applying Minimum Spanning Tree (MST) routing protocol with minimum total network lengths. Third, the performance of the Bees Algorithm (BA) and Particle Swarm Optimization (PSO) algorithms are compared for the evaluation of GIS-based WSN deployment in health and environment applications. The algorithms were compared using convergence rate, constancy repeatability, and modeling complexity criteria. The results showed that the PSO algorithm converged to higher values of objective functions gradually while BA found better fitness values and was faster in the first iterations. The levels of stability and repeatability were high with 0.0150 of standard deviation for PSO and 0.0375 for BA. The PSO also had lower complexity than BA. Therefore, the PSO algorithm obtained better performance for IoT-based sensor network deployment. Full article

(This article belongs to the Special Issue Advances in Wireless Sensor Networks Applications for Health and Environment)

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26 pages, 1131 KiB

Open AccessReview

A Survey of Marker-Less Tracking and Registration Techniques for Health & Environmental Applications to Augmented Reality and Ubiquitous Geospatial Information Systems

by Abolghasem Sadeghi-Niaraki and Soo-Mi Choi

Sensors 2020, 20(10), 2997; https://doi.org/10.3390/s20102997 - 25 May 2020

Cited by 35 | Viewed by 8098

Abstract

Most existing augmented reality (AR) applications are suitable for cases in which only a small number of real world entities are involved, such as superimposing a character on a single surface. In this case, we only need to calculate pose of the camera relative to that surface. However, when an AR health or environmental application involves a one-to-one relationship between an entity in the real-world and the corresponding object in the computer model (geo-referenced object), we need to estimate the pose of the camera in reference to a common coordinate system for better geo-referenced object registration in the real-world. New innovations in developing cheap sensors, computer vision techniques, machine learning, and computing power have helped to develop applications with more precise matching between a real world and a virtual content. AR Tracking techniques can be divided into two subcategories: marker-based and marker-less approaches. This paper provides a comprehensive overview of marker-less registration and tracking techniques and reviews their most important categories in the context of ubiquitous Geospatial Information Systems (GIS) and AR focusing to health and environmental applications. Basic ideas, advantages, and disadvantages, as well as challenges, are discussed for each subcategory of tracking and registration techniques. We need precise enough virtual models of the environment for both calibrations of tracking and visualization. Ubiquitous GISs can play an important role in developing AR in terms of providing seamless and precise spatial data for outdoor (e.g., environmental applications) and indoor (e.g., health applications) environments. Full article

(This article belongs to the Special Issue Advances in Wireless Sensor Networks Applications for Health and Environment)

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