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Symmetry
Special Issues
Applications of Internet of Things
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Applications of Internet of Things

A special issue of Symmetry (ISSN 2073-8994).

Deadline for manuscript submissions: closed (31 October 2017) | Viewed by 56877

Special Issue Editors

Prof. Dr. Chi-Hua Chen

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Guest Editor
College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
Interests: machine learning; internet of things; healthcare systems
Special Issues, Collections and Topics in MDPI journals
Dr. Eyhab Al-Masri

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Guest Editor
School of Business & Economics, Wilfrid Laurier University, Waterloo, Canada
Interests: internet of things; cloud computing; service oriented computing; big data analytics
Dr. Feng-Jang Hwang

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Guest Editor
School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
Interests: scheduling; linear programming; integer programming; deep learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Despo Ktoridou

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Guest Editor
Department of Management & MIS, University of Nicosia, 2417-Nicosia, Cyprus
Interests: ICT integration in the educational practice; technology and innovation management pedagogies; open and online distance learning practices
Special Issues, Collections and Topics in MDPI journals
Dr. Kuen-Rong Lo

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Guest Editor
Telecommunication Laboratories, Chunghwa Telecom Co. Ltd., Yangmei District, Taoyuan City 32661, Taiwan
Interests: internet of things; smart city; intelligent transportation system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the techniques of Internet of Things (IoT) and mobile communication have been developed to detect human and environment information (e.g., geo-information, weather information, bio-information, human behaviors, etc.) for a variety of intelligent services and applications. The three layers in IoT are sensors, networking, and application layers. For sensors and networking layers, the rise of mobile technology advancements (e.g., wireless sensor networking, Wi-Fi, Bluetooth, smart mobile device, and Long Term Evolution (LTE)) has led to a new wave of machine-to-machine (M2M), machine-to-human (M2H), human-to-human (H2H), and human-to-machine (H2M) communications. For application layer, several IoT applications, which include energy, enterprise, healthcare, public services, residency, retail, and transportation, have been designed and implemented to detect environmental changes and send instant updates to a cloud computing server farm via mobile communications and middleware for big geo-data analyses. For instance, on-board units in cars can instantly detect and share information about the geolocation of the car, speed, following distance, and gaps with other neighboring cars. While the area of IoT applications and mobile communication is a rapidly expanding field of scientific research, several open research questions are still needed to be discussed and studied. This Special Issue will solicit papers on various disciplines of IoT. Potential topics include, but are not limited to:

IoT Applications of Agriculture
IoT Applications of Energy
IoT Applications of Enterprise
IoT Applications of Finance
IoT Applications of Healthcare
IoT Applications of Industry
IoT Applications of Public Services
IoT Applications of Residency
IoT Applications of Retail
IoT Applications of Transportation
Sensing Techniques for IoT
Communication Techniques for IoT
Middleware Techniques for IoT
Data Analysis Techniques for IoT

We look forward to receiving your contributions.

Dr. Chi-Hua Chen
Dr. Feng-Jang Hwang
Dr. Eyhab Al-Masri
Dr. Despo Ktoridou
Dr. Kuen-Rong Lo
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. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Editorial

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6 pages, 206 KiB  
Editorial
Introduction to the Special Issue: Applications of Internet of Things
by Chi-Hua Chen, Eyhab Al-Masri, Feng-Jang Hwang, Despo Ktoridou and Kuen-Rong Lo
Symmetry 2018, 10(9), 374; https://0-doi-org.brum.beds.ac.uk/10.3390/sym10090374 - 01 Sep 2018
Cited by 4 | Viewed by 3004
Abstract
This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. [...] Read more.
This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) “Reliability of improved cooperative communication over wireless sensor networks”, by Chen et al.; (2) “User classification in crowdsourcing-based cooperative spectrum sensing”, by Zhai and Wang; (3) “IoT’s tiny steps towards 5G: Telco’s perspective”, by Cero et al.; and (4) “An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios”, by Parada et al. One paper on data science techniques and applications is as follows: “Internet of things: a scientometric review”, by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) “An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships”, by He et al.; and (2) “The development of key technologies in applications of vessels connected to the Internet”, by Tian et al. Two papers on smart home are as follows: (1) “A novel approach based on time cluster for activity recognition of daily living in smart homes”, by Liu et al.; and (2) “IoT-based image recognition system for smart home-delivered meal services”, by Tseng et al. Full article
(This article belongs to the Special Issue Applications of Internet of Things)

Research

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592 KiB  
Article
Internet of Things: A Scientometric Review
by Juan Ruiz-Rosero, Gustavo Ramirez-Gonzalez, Jennifer M. Williams, Huaping Liu, Rahul Khanna and Greeshma Pisharody
Symmetry 2017, 9(12), 301; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9120301 - 06 Dec 2017
Cited by 49 | Viewed by 10369
Abstract
Internet of Things (IoT) is connecting billions of devices to the Internet. These IoT devices chain sensing, computation, and communication techniques, which facilitates remote data collection and analysis. wireless sensor networks (WSN) connect sensing devices together on a local network, thereby eliminating wires, [...] Read more.
Internet of Things (IoT) is connecting billions of devices to the Internet. These IoT devices chain sensing, computation, and communication techniques, which facilitates remote data collection and analysis. wireless sensor networks (WSN) connect sensing devices together on a local network, thereby eliminating wires, which generate a large number of samples, creating a big data challenge. This IoT paradigm has gained traction in recent years, yielding extensive research from an increasing variety of perspectives, including scientific reviews. These reviews cover surveys related to IoT vision, enabling technologies, applications, key features, co-word and cluster analysis, and future directions. Nevertheless, we lack an IoT scientometrics review that uses scientific databases to perform a quantitative analysis. This paper develops a scientometric review about IoT over a data set of 19,035 documents published over a period of 15 years (2002–2016) in two main scientific databases (Clarivate Web of Science and Scopus). A Python script called ScientoPy was developed to perform quantitative analysis of this data set. This provides insight into research trends by investigating a lead author’s country affiliation, most published authors, top research applications, communication protocols, software processing, hardware, operating systems, and trending topics. Furthermore, we evaluate the top trending IoT topics and the popular hardware and software platforms that are used to research these trends. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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5439 KiB  
Article
Internet of THings Area Coverage Analyzer (ITHACA) for Complex Topographical Scenarios
by Raúl Parada, Daniel Cárdenes-Tacoronte, Carlos Monzo and Joan Melià-Seguí
Symmetry 2017, 9(10), 237; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9100237 - 19 Oct 2017
Cited by 9 | Viewed by 5597
Abstract
The number of connected devices is increasing worldwide. Not only in contexts like the Smart City, but also in rural areas, to provide advanced features like smart farming or smart logistics. Thus, wireless network technologies to efficiently allocate Internet of Things (IoT) and [...] Read more.
The number of connected devices is increasing worldwide. Not only in contexts like the Smart City, but also in rural areas, to provide advanced features like smart farming or smart logistics. Thus, wireless network technologies to efficiently allocate Internet of Things (IoT) and Machine to Machine (M2M) communications are necessary. Traditional cellular networks like Global System for Mobile communications (GSM) are widely used worldwide for IoT environments. Nevertheless, Low Power Wide Area Networks (LP-WAN) are becoming widespread as infrastructure for present and future IoT and M2M applications. Based also on a subscription service, the LP-WAN technology SIGFOXTM may compete with cellular networks in the M2M and IoT communications market, for instance in those projects where deploying the whole communications infrastructure is too complex or expensive. For decision makers to decide the most suitable technology for each specific application, signal coverage is within the key features. Unfortunately, besides simulated coverage maps, decision-makers do not have real coverage maps for SIGFOXTM, as they can be found for cellular networks. Thereby, we propose Internet of THings Area Coverage Analyzer (ITHACA), a signal analyzer prototype to provide automated signal coverage maps and analytics for LP-WAN. Experiments performed in the Gran Canaria Island, Spain (with both urban and complex topographic rural environments), returned a real SIGFOXTM service availability above 97% and above 11% more coverage with respect to the company-provided simulated maps. We expect that ITHACA may help decision makers to deploy the most suitable technologies for future IoT and M2M projects. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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1898 KiB  
Article
IoT’s Tiny Steps towards 5G: Telco’s Perspective
by Enida Cero, Jasmina Baraković Husić and Sabina Baraković
Symmetry 2017, 9(10), 213; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9100213 - 02 Oct 2017
Cited by 23 | Viewed by 7674
Abstract
The numerous and diverse applications of the Internet of Things (IoT) have the potential to change all areas of daily life of individuals, businesses, and society as a whole. The vision of a pervasive IoT spans a wide range of application domains and [...] Read more.
The numerous and diverse applications of the Internet of Things (IoT) have the potential to change all areas of daily life of individuals, businesses, and society as a whole. The vision of a pervasive IoT spans a wide range of application domains and addresses the enabling technologies needed to meet the performance requirements of various IoT applications. In order to accomplish this vision, this paper aims to provide an analysis of literature in order to propose a new classification of IoT applications, specify and prioritize performance requirements of such IoT application classes, and give an insight into state-of-the-art technologies used to meet these requirements, all from telco’s perspective. A deep and comprehensive understanding of the scope and classification of IoT applications is an essential precondition for determining their performance requirements with the overall goal of defining the enabling technologies towards fifth generation (5G) networks, while avoiding over-specification and high costs. Given the fact that this paper presents an overview of current research for the given topic, it also targets the research community and other stakeholders interested in this contemporary and attractive field for the purpose of recognizing research gaps and recommending new research directions. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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4737 KiB  
Article
A Novel Approach Based on Time Cluster for Activity Recognition of Daily Living in Smart Homes
by Yaqing Liu, Dantong Ouyang, Yong Liu and Rong Chen
Symmetry 2017, 9(10), 212; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9100212 - 01 Oct 2017
Cited by 17 | Viewed by 4311
Abstract
With the trend of the increasing ageing population, more elderly people often encounter some problems in their daily lives. To enable these people to have more carefree lives, smart homes are designed to assist elderly people by recognizing their daily activities. Although different [...] Read more.
With the trend of the increasing ageing population, more elderly people often encounter some problems in their daily lives. To enable these people to have more carefree lives, smart homes are designed to assist elderly people by recognizing their daily activities. Although different models and algorithms that use temporal and spatial features for activity recognition have been proposed, the rigid representations of these features damage the accuracy of activity recognition. In this paper, a two-stage approach is proposed to recognize the activities of a single resident. Firstly, in terms of temporal features, the approximate duration, start and end time are extracted from the activity records. Secondly, a set of activity records is clustered according to the records’ temporal features. Then, the classifiers are used to recognize the daily activities in each cluster according to the spatial features. Finally, two experiments are done to validate the recognition of daily activities in order to compare the proposed approach with a one-dimensional model. The results demonstrate that the proposed approach favorably outperforms the one-dimensional model. Two public datasets are used to evaluate the proposed approach. The experiment results show that the proposed approach achieves average accuracies of 80% and 89%, respectively. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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6977 KiB  
Article
Reliability Improved Cooperative Communication over Wireless Sensor Networks
by Zhuangbin Chen, Ming Ma, Xiao Liu, Anfeng Liu and Ming Zhao
Symmetry 2017, 9(10), 209; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9100209 - 01 Oct 2017
Cited by 23 | Viewed by 4465
Abstract
With the development of smart devices and connection technologies, Wireless Sensor Networks (WSNs) are becoming increasingly intelligent. New or special functions can be obtained by receiving new versions of program codes to upgrade their software systems, forming the so-called smart Internet of Things [...] Read more.
With the development of smart devices and connection technologies, Wireless Sensor Networks (WSNs) are becoming increasingly intelligent. New or special functions can be obtained by receiving new versions of program codes to upgrade their software systems, forming the so-called smart Internet of Things (IoT). Due to the lossy property of wireless channels, data collection in WSNs still suffers from a long delay, high energy consumption, and many retransmissions. Thanks to wireless software-defined networks (WSDNs), software in sensors can now be updated to help them transmit data cooperatively, thereby achieving more reliable communication. In this paper, a Reliability Improved Cooperative Communication (RICC) data collection scheme is proposed to improve the reliability of random-network-coding-based cooperative communications in multi-hop relay WSNs without reducing the network lifetime. In WSNs, sensors in different positions can have different numbers of packets to handle, resulting in the unbalanced energy consumption of the network. In particular, nodes in non-hotspot areas have up to 90% of their original energy remaining when the network dies. To efficiently use the residual energy, in RICC, high data transmission power is adopted in non-hotspot areas to achieve a higher reliability at the cost of large energy consumption, and relatively low transmission power is adopted in hotspot areas to maintain the long network lifetime. Therefore, high reliability and a long network lifetime can be obtained simultaneously. The simulation results show that compared with other scheme, RICC can reduce the end-to-end Message Fail delivering Ratio (MFR) by 59.4%–62.8% under the same lifetime with a more balanced energy utilization. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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5577 KiB  
Article
An Internet of Things Approach for Extracting Featured Data Using AIS Database: An Application Based on the Viewpoint of Connected Ships
by Wei He, Zhixiong Li, Reza Malekian, Xinglong Liu and Zhihe Duan
Symmetry 2017, 9(9), 186; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9090186 - 07 Sep 2017
Cited by 10 | Viewed by 4916
Abstract
Automatic Identification System (AIS), as a major data source of navigational data, is widely used in the application of connected ships for the purpose of implementing maritime situation awareness and evaluating maritime transportation. Efficiently extracting featured data from AIS database is always a [...] Read more.
Automatic Identification System (AIS), as a major data source of navigational data, is widely used in the application of connected ships for the purpose of implementing maritime situation awareness and evaluating maritime transportation. Efficiently extracting featured data from AIS database is always a challenge and time-consuming work for maritime administrators and researchers. In this paper, a novel approach was proposed to extract massive featured data from the AIS database. An Evidential Reasoning rule based methodology was proposed to simulate the procedure of extracting routes from AIS database artificially. First, the frequency distributions of ship dynamic attributes, such as the mean and variance of Speed over Ground, Course over Ground, are obtained, respectively, according to the verified AIS data samples. Subsequently, the correlations between the attributes and belief degrees of the categories are established based on likelihood modeling. In this case, the attributes were characterized into several pieces of evidence, and the evidence can be combined with the Evidential Reasoning rule. In addition, the weight coefficients were trained in a nonlinear optimization model to extract the AIS data more accurately. A real life case study was conducted at an intersection waterway, Yangtze River, Wuhan, China. The results show that the proposed methodology is able to extract data very precisely. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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14213 KiB  
Article
IoT-Based Image Recognition System for Smart Home-Delivered Meal Services
by Hsiao-Ting Tseng, Hsin-Ginn Hwang, Wei-Yen Hsu, Pei-Chin Chou and I-Chiu Chang
Symmetry 2017, 9(7), 125; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9070125 - 21 Jul 2017
Cited by 10 | Viewed by 4426
Abstract
Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT) applications in the “10-year long-term care program 2.0”. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. [...] Read more.
Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT) applications in the “10-year long-term care program 2.0”. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. Home-delivered meal services for the elderly are important for home-based long-term care services. To ensure that the right meals are delivered to the right recipient at the right time, the runners need to take a picture of the meal recipient when the meal is delivered. This study uses the IoT-based image recognition system to design an integrated service to improve the management of image recognition. The core technology of this IoT-based image recognition system is statistical histogram-based k-means clustering for image segmentation. However, this method is time-consuming. Therefore, we proposed using the statistical histogram to obtain a probability density function of pixels of a figure and segmenting these with weighting for the same intensity. This aims to increase the computational performance and achieve the same results as k-means clustering. We combined histogram and k-means clustering in order to overcome the high computational cost for k-means clustering. The results indicate that the proposed method is significantly faster than k-means clustering by more than 10 times. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
677 KiB  
Article
User Classification in Crowdsourcing-Based Cooperative Spectrum Sensing
by Linbo Zhai and Hua Wang
Symmetry 2017, 9(7), 110; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9070110 - 06 Jul 2017
Cited by 4 | Viewed by 3265
Abstract
This paper studies cooperative spectrum sensing based on crowdsourcing in cognitive radio networks. Since intelligent mobile users such as smartphones and tablets can sense the wireless spectrum, channel sensing tasks can be assigned to these mobile users. This is referred to as the [...] Read more.
This paper studies cooperative spectrum sensing based on crowdsourcing in cognitive radio networks. Since intelligent mobile users such as smartphones and tablets can sense the wireless spectrum, channel sensing tasks can be assigned to these mobile users. This is referred to as the crowdsourcing method. However, there may be some malicious mobile users that send false sensing reports deliberately, for their own purposes. False sensing reports will influence decisions about channel state. Therefore, it is necessary to classify mobile users in order to distinguish malicious users. According to the sensing reports, mobile users should not just be divided into two classes (honest and malicious). There are two reasons for this: on the one hand, honest users in different positions may have different sensing outcomes, as shadowing, multi-path fading, and other issues may influence the sensing results; on the other hand, there may be more than one type of malicious users, acting differently in the network. Therefore, it is necessary to classify mobile users into more than two classes. Due to the lack of prior information of the number of user classes, this paper casts the problem of mobile user classification as a dynamic clustering problem that is NP-hard. The paper uses the interdistance-to-intradistance ratio of clusters as the fitness function, and aims to maximize the fitness function. To cast this optimization problem, this paper proposes a distributed algorithm for user classification in order to obtain bounded close-to-optimal solutions, and analyzes the approximation ratio of the proposed algorithm. Simulations show the distributed algorithm achieves higher performance than other algorithms. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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Review

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3966 KiB  
Review
The Development of Key Technologies in Applications of Vessels Connected to the Internet
by Zhe Tian, Fushun Liu, Zhixiong Li, Reza Malekian and Yingchun Xie
Symmetry 2017, 9(10), 211; https://0-doi-org.brum.beds.ac.uk/10.3390/sym9100211 - 01 Oct 2017
Cited by 28 | Viewed by 7731
Abstract
With the development of science and technology, traffic perception, communication, information processing, artificial intelligence and the shipping information system have become important in supporting the realization of intelligent shipping transportation. Against this background, the Internet of Vessels (IoV) is proposed to integrate all [...] Read more.
With the development of science and technology, traffic perception, communication, information processing, artificial intelligence and the shipping information system have become important in supporting the realization of intelligent shipping transportation. Against this background, the Internet of Vessels (IoV) is proposed to integrate all these advanced technologies into a platform to meet the requirements of international and regional transportations. The purpose of this paper is to analyze how to benefit from the Internet of Vessels to improve the efficiency and safety of shipping, and promote the development of world transportation. In this paper, the IoV is introduced and its main architectures are outlined. Furthermore, the characteristics of the Internet of Vessels are described. Several important applications that illustrate the interaction of the Internet of Vessels’ components are proposed. Due to the development of the Internet of Vessels still being in its primary stage, challenges and prospects are identified and addressed. Finally, the main conclusions are drawn and future research priorities are provided for reference and as professional suggestions for future researchers in this field. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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