Special Issue "Advanced Internet of Things for Smart Infrastructure System"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (31 July 2018)

Special Issue Editors

Guest Editor
Dr. Po Yang

Computer Science, Liverpool John Moores University, Liverpool L3 2ET, UK
Website | E-Mail
Interests: Internet of Things; pervasive computing; personalised healthcare
Guest Editor
Prof. Dr. Manolis Tsiknakis

Department of Applied Informatics and Multimedia, ICS-Forth, N. Plastira 100, Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece
Website | E-Mail
Phone: +30 2810 391690
Interests: biomedical informatics and engineering, service oriented SW architectures and their application in biomedicine
Guest Editor
Prof. Dr. Wenyan Wu

School of Engineering and the Built Environment, Birmingham City University, Birmingham B152TT, UK
Website | E-Mail
Interests: smart sensor and sensor network; energy efficiency; water quality modelling and calibration
Guest Editor
Prof. Dr. Zofia Lukszo

Engineering Systems and Services, Delft University of Technology, 2600 GA Delft, The Netherlands
Website | E-Mail
Interests: Her research concentrates on a wide range of problems in the way complex sociotechnical systems are functioning today and can be (re-)shaped for a sustainable future. She is an expert on modeling and analyzing systems in the energy and industry domain. The questions she works on concern investigation of supporting technology and emerging institutions for the transition towards future sustainable energy systems
Guest Editor
Prof. Dr. Li Da Xu

Department of Information Technology, Old Dominion University, Norfolk, VA 23529, USA
Website | E-Mail
Interests: Enterprise systems, Information Technology & Decision Sciences, Internet of Things, cyber-physics system, big data analytics, industrial informatics

Special Issue Information

Dear Colleagues,

Due to the rapid proliferation of smart sensors and meters, wearable devices and smartphone, the Internet of Things enabled technology is evolving infrastructure from conventional operation and maintenance business model to more efficient, sustainable, and smart and resilience system. Currently there are IoT smart applications in energy, home, building, water and cities. Such as smart devices are already being used at home, building and infrastructure without human intervention. However, empowering the utility of IoT enabled technology in infrastructure is still significantly challenging in the area considering shortage of cost-effective and accurate smart sensors and meters, unstandardized IoT system architectures, heterogeneity of wearable devices connected, high demand for interoperability. Also, complexity will be an important factor to study and control: The behaviour of every single node in IoT will need to be considered to determine its potential impact on the whole system. These above challenges and needs grant a lot of opportunities to explore and investigate new concepts, algorithms and applications in IoT enabled smart infrastructure. The central theme of the proposed special issue is on the development and application of advanced internet of things technologies for smart infrastructure, where smart sensing technologies, IoT architectures, services, applications, and data analytics for infrastructure applications are the focus areas, and broad aspects and issues will be well discussed. The theme of the special issue (SI) is especially focused on the three major aspects of IoT for infrastructure: (1) intelligent monitoring with increased reliability and validity by using a variety of IoT assets or technologies, including sensors, devices and mobile applications. (2) Development of specifications for interoperability and data sharing across services and infrastructures, An interoperable and internet-based IoT infrastructure supporting heterogeneous devices to access, share, (3) Creation of ecosystems of "Platforms for Connected Smart Objects", integrating the future generations of smart devices (i.e. sensors) and network technologies and other evolving ICT advances.

Dr. Po Yang  
Prof. Manolis Tsiknakis
Prof. Wenyan Wu
Prof. Zofia Lukszo
Prof. Li Da Xu
Guest Editors

Manuscript Submission Information

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Keywords

  • Internet of Things

  • Smart Infrastructure

  • Data sharing

  • Smart Sensors

  • Interoperability

Published Papers (18 papers)

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Research

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Open AccessArticle Tongue–Computer Interface Prototype Design Based on T-Type Magnet Localization for Smart Environment Control
Appl. Sci. 2018, 8(12), 2498; https://doi.org/10.3390/app8122498
Received: 8 November 2018 / Revised: 26 November 2018 / Accepted: 29 November 2018 / Published: 5 December 2018
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Abstract
The interactions between paralyzed individuals with severe physical disabilities and smart infrastructure need to be facilitated, and the tongue–computer interface (TCI) provides an efficient and feasible solution. By attaching a permanent magnet (PM) on the apex of the tongue, the real-time tongue motion [...] Read more.
The interactions between paralyzed individuals with severe physical disabilities and smart infrastructure need to be facilitated, and the tongue–computer interface (TCI) provides an efficient and feasible solution. By attaching a permanent magnet (PM) on the apex of the tongue, the real-time tongue motion tracking can be switching to solve a nonlinear inverse magnetic problem. This paper presents a proof-of-concept prototype TCI system utilizing a combined T-type PM marker for potential environment control. The introduction of the combined T-type PM promotes the anisotropy of the magnetic field distribution. A comprehensive calibration method for the sensing system is proposed to figure out the bias in the magnetic moment of the PM marker and the sensing axis rotation of the sensors. To address the influence of initialization in solving the overdetermined inverse magnetic problem, an adaptive Levenberg–Marquardt algorithm is designed utilizing real-time measurements. Bench-top experiments were carried out based on a high-precision three-dimensional (3D) translation platform, and the feasibility of the proposed TCI system in magnetic localization accuracy and efficiency is fully assessed. The mean localization error is 1.65 mm with a mean processing time of 65.7 ms, and a mean improvement of 54.7% can be achieved compared with a traditional LM algorithm. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle A Novel Gesture Recognition System for Intelligent Interaction with a Nursing-Care Assistant Robot
Appl. Sci. 2018, 8(12), 2349; https://doi.org/10.3390/app8122349
Received: 20 September 2018 / Revised: 17 November 2018 / Accepted: 19 November 2018 / Published: 22 November 2018
Cited by 1 | PDF Full-text (5287 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The expansion of nursing-care assistant robots in smart infrastructure has provided more applications for homecare services, which has raised new demands for smart and natural interaction between humans and robots. This article proposed an innovative hand motion trajectory (HMT) gesture recognition system based [...] Read more.
The expansion of nursing-care assistant robots in smart infrastructure has provided more applications for homecare services, which has raised new demands for smart and natural interaction between humans and robots. This article proposed an innovative hand motion trajectory (HMT) gesture recognition system based on background velocity features. Here, a new wearable wrist-worn camera prototype for gesture’s video collection was designed, and a new method for the segmentation of continuous gestures was shown. Meanwhile, a nursing-care assistant robot prototype was designed for assisting the elderly, which is capable of carrying the elderly with omnidirectional motion and grabbing the specified object at home. In order to evaluate the performance of the gesture recognition system, 10 special gestures were defined as the move commands for interaction with the robot, and 1000 HMT gesture samples were obtained from five subjects for leave-one-subject-out (LOSO) cross-validation classification with an average recognition accuracy of up to 97.34%. Moreover, the performance and practicability of the proposed system were further demonstrated by controlling the omnidirectional movement of the nursing-care assistant robot using the predefined gesture commands. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Design and Implementation of a Smart IoT Based Building and Town Disaster Management System in Smart City Infrastructure
Appl. Sci. 2018, 8(11), 2239; https://doi.org/10.3390/app8112239
Received: 30 September 2018 / Revised: 27 October 2018 / Accepted: 8 November 2018 / Published: 13 November 2018
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Abstract
Recently, fire accidents in buildings have become bigger around the world, and it has become necessary to build an efficient building disaster management system suitable for fires in a Smart City. As building fires increase the number of casualties and property damage, it [...] Read more.
Recently, fire accidents in buildings have become bigger around the world, and it has become necessary to build an efficient building disaster management system suitable for fires in a Smart City. As building fires increase the number of casualties and property damage, it is necessary to take appropriate action accordingly. There has been an increasing effort to develop such disaster management systems worldwide by applying information communication technology (ICT), and many studies have been conducted in practice. In this paper, an augmented reality (AR)-based Smart Building and Town Disaster Management System is suggested in order to acquire visibility and to grasp occupants in case of fire disasters in buildings. This system provides visualization information and optimal guide for quick initial response by utilizing smart element AR-based disaster management service through linkage of physical virtual domain in the building. Additionally, we show a scenario flow chart of the fire extinguishment process according to the time from the ignition stage to the extinguishment stage in the building. Finally, we introduce the related sensors, the actuators, and a small test-bed for AR-based disaster management service. This test-bed was designed for interlocking and interoperability test of the system between the sensors and the actuators. It is expected that the proposed system can provide a quick and safe rescue guideline to the occupants and rescuers in the building where fire is generated and in regions of poor visibility. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Enabling Technologies for Operator 4.0: A Survey
Appl. Sci. 2018, 8(9), 1650; https://doi.org/10.3390/app8091650
Received: 31 July 2018 / Revised: 25 August 2018 / Accepted: 7 September 2018 / Published: 13 September 2018
Cited by 2 | PDF Full-text (743 KB) | HTML Full-text | XML Full-text
Abstract
The fast development of smart sensors and wearable devices has provided the opportunity to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems (H-CPS) integrate the operators into flexible and multi-purpose manufacturing processes. The primary enabling factor of the resultant Operator 4.0 paradigm is [...] Read more.
The fast development of smart sensors and wearable devices has provided the opportunity to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems (H-CPS) integrate the operators into flexible and multi-purpose manufacturing processes. The primary enabling factor of the resultant Operator 4.0 paradigm is the integration of advanced sensor and actuator technologies and communications solutions. This work provides an extensive overview of these technologies and highlights that the design of future workplaces should be based on the concept of intelligent space. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Cooperative Crossing Cache Placement in Cache-Enabled Device to Device-Aided Cellular Networks
Appl. Sci. 2018, 8(9), 1578; https://doi.org/10.3390/app8091578
Received: 19 July 2018 / Revised: 15 August 2018 / Accepted: 22 August 2018 / Published: 7 September 2018
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Abstract
In cache-enabled device-to-device (D2D) -aided cellular networks, the technique of caching contents in the cooperative crossing between base stations (BSs) and devices can significantly reduce core traffic and enhance network capacity. In this paper, we propose a scheme that establishes device availability, which [...] Read more.
In cache-enabled device-to-device (D2D) -aided cellular networks, the technique of caching contents in the cooperative crossing between base stations (BSs) and devices can significantly reduce core traffic and enhance network capacity. In this paper, we propose a scheme that establishes device availability, which indicates whether a cache-enabled device can handle the transmission of the desired content within the required sending time, called the delay, while achieving optimal probabilistic caching. We also investigate the impact of transmission device availability on the effectiveness of a scenario of cooperative crossing cache placement, where content delivery traffic can be offloaded from the local cache, a D2D transmitter’s cache via a D2D link, or else directly from a BS via a cellular link, in order to maximize the offloading probability. Further, we derive the cooperation content offloading strategy while considering successful content transmission by D2D transmitters or BSs to guarantee the delay, even though reducing the delay is not the focus of this study. Finally, the proposed problem is formulated. Owing to the non-convexity of the optimization problem, it can be rewritten as a minimization of the difference between the convex functions; thus, it can be solved by difference of convex (DC) programming using a low-complexity algorithm. Simulation results show that the proposed cache placement scheme improves the offloading probability by 13.5% and 23% compared to Most Popular Content (MPC) scheme, in which both BSs and devices cache the most popular content and Coop. BS/D2D caching scheme, in which each BS tier and user tier applies cooperative content caching separately. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Novel Internet of Things Platform for In-Building Power Quality Submetering
Appl. Sci. 2018, 8(8), 1320; https://doi.org/10.3390/app8081320
Received: 21 June 2018 / Revised: 18 July 2018 / Accepted: 27 July 2018 / Published: 7 August 2018
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Abstract
As the number of facilities adopting a Building Management System under the Industry 4.0 paradigm increases, it is critical to ensure the good health of their operations. Business continuity and uninterrupted operations are key requirements for any building, for which Power Quality and [...] Read more.
As the number of facilities adopting a Building Management System under the Industry 4.0 paradigm increases, it is critical to ensure the good health of their operations. Business continuity and uninterrupted operations are key requirements for any building, for which Power Quality and Supply Reliability sophisticated monitoring can play an extremely important role. Submetering, as opposed to bulk-metering, implies measuring power consumption for individual units or appliances in a building complex. An Internet of Things mesh network, which brings ubiquitous power quality submetering inside the entire facility, would be extremely beneficial for the management of the building thus ensuring seamless business operations. This work describes a novel low-cost Internet of Things sensor for measuring and analyzing power quality at the input of any individual Alternating Current (AC) appliance, providing an early detection and analysis system which controls those critical variables inside the facility and leads to anticipate faults with early-stage alerts based on on-time data streams treatment. Moreover, the recorded power quality parameters that are processed in the Cloud system can help to reduce energy consumption, as power quality disturbances can be automatically analyzed and even compared to standard values. The proposed Internet of Things sensor will help users to detect most power quality steady-state and events disturbances, while monitoring the energy consumption. This Internet of Things Power Quality sensor is built around a flexible microcontroller, which manages an energy metering Integrated Circuit (IC) through Serial Peripheral Interface (SPI), increasing its original capabilities by including new sophisticated software functionality. Additionally, it wirelessly communicates with a cloud-based Internet of Things Platform to allow the storage and supervision of the different power quality events for the entire facility. An example of the access to the data is also included. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle A Background Subtraction Algorithm in Complex Environments Based on Category Entropy Analysis
Appl. Sci. 2018, 8(6), 885; https://doi.org/10.3390/app8060885
Received: 26 April 2018 / Revised: 18 May 2018 / Accepted: 25 May 2018 / Published: 28 May 2018
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Abstract
Background subtraction is a mainstream algorithm for moving object detection in video surveillance systems. It segments moving objects by using the difference between the background and input images. The key to background subtraction is to establish a reliable initial background. In this study, [...] Read more.
Background subtraction is a mainstream algorithm for moving object detection in video surveillance systems. It segments moving objects by using the difference between the background and input images. The key to background subtraction is to establish a reliable initial background. In this study, we propose a background subtraction algorithm based on category entropy analysis that dynamically creates color categories for each pixel in the images. The algorithm uses the concept of a joint category to build background categories that can adapt to the color disturbance of the background. Furthermore, in order to overcome dynamic background environments, this paper proposes the concept of color category entropy to estimate the number of necessary background categories and establish sufficient and representative background categories to adapt to dynamic background environments. In addition, recent mainstream methods for background subtraction were implemented and analyzed in comparison with our algorithm. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Application of Workflow Technology for Big Data Analysis Service
Appl. Sci. 2018, 8(4), 591; https://doi.org/10.3390/app8040591
Received: 28 January 2018 / Revised: 14 March 2018 / Accepted: 3 April 2018 / Published: 9 April 2018
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Abstract
This study presents a lightweight representational state transfer-based cloud workflow system to construct a big data intelligent software-as-a-service (SaaS) platform. The system supports the dynamic construction and operation of an intelligent data analysis application, and realizes rapid development and flexible deployment of the [...] Read more.
This study presents a lightweight representational state transfer-based cloud workflow system to construct a big data intelligent software-as-a-service (SaaS) platform. The system supports the dynamic construction and operation of an intelligent data analysis application, and realizes rapid development and flexible deployment of the business analysis process that can improve the interaction and response time of the process. The proposed system integrates offline-batch and online-streaming analysis models that allow users to conduct batch and streaming computing simultaneously. Users can rend cloud capabilities and customize a set of big data analysis applications in the form of workflow processes. This study elucidates the architecture and application modeling, customization, dynamic construction, and scheduling of a cloud workflow system. A chain workflow foundation mechanism is proposed to combine several analysis components into a chain component that can promote efficiency. Four practical application cases are provided to verify the analysis capability of the system. Experimental results show that the proposed system can support multiple users in accessing the system concurrently and effectively uses data analysis algorithms. The proposed SaaS workflow system has been used in network operators and has achieved good results. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Finger Angle-Based Hand Gesture Recognition for Smart Infrastructure Using Wearable Wrist-Worn Camera
Appl. Sci. 2018, 8(3), 369; https://doi.org/10.3390/app8030369
Received: 8 February 2018 / Revised: 26 February 2018 / Accepted: 28 February 2018 / Published: 3 March 2018
Cited by 1 | PDF Full-text (3423 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The arising of domestic robots in smart infrastructure has raised demands for intuitive and natural interaction between humans and robots. To address this problem, a wearable wrist-worn camera (WwwCam) is proposed in this paper. With the capability of recognizing human hand gestures in [...] Read more.
The arising of domestic robots in smart infrastructure has raised demands for intuitive and natural interaction between humans and robots. To address this problem, a wearable wrist-worn camera (WwwCam) is proposed in this paper. With the capability of recognizing human hand gestures in real-time, it enables services such as controlling mopping robots, mobile manipulators, or appliances in smart-home scenarios. The recognition is based on finger segmentation and template matching. Distance transformation algorithm is adopted and adapted to robustly segment fingers from the hand. Based on fingers’ angles relative to the wrist, a finger angle prediction algorithm and a template matching metric are proposed. All possible gesture types of the captured image are first predicted, and then evaluated and compared to the template image to achieve the classification. Unlike other template matching methods relying highly on large training set, this scheme possesses high flexibility since it requires only one image as the template, and can classify gestures formed by different combinations of fingers. In the experiment, it successfully recognized ten finger gestures from number zero to nine defined by American Sign Language with an accuracy up to 99.38%. Its performance was further demonstrated by manipulating a robot arm using the implemented algorithms and WwwCam to transport and pile up wooden building blocks. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle An Experimental Study of a Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of a Long-Span Bridge
Appl. Sci. 2018, 8(3), 361; https://doi.org/10.3390/app8030361
Received: 11 January 2018 / Revised: 13 February 2018 / Accepted: 27 February 2018 / Published: 2 March 2018
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Abstract
There has recently been an increase in interest in structural health monitoring (SHM) using wireless sensor networks. For SHM, in particular, it is important to accurately and efficiently measure the dynamic acceleration response using wireless sensor networks in real-time. For the purpose, a [...] Read more.
There has recently been an increase in interest in structural health monitoring (SHM) using wireless sensor networks. For SHM, in particular, it is important to accurately and efficiently measure the dynamic acceleration response using wireless sensor networks in real-time. For the purpose, a CAFB (cochlea-inspired artificial filter bank) has been developed in a previous study, which is a dynamic data compression technology. Since the developed CAFB can select and compress only the interested range of frequency signals from an entire response of a structure, it efficiently provides a real-time dynamic response based on wireless networking. CAFB of the previous study is optimized to selectively acquire low-frequency signals of sub-10 Hz, which is required for SHM of long and large-scale structures. According to the CAFB’s optimization using an El-Centro seismic waveform, six band-pass filters, 1.0 Hz interval, and 0.6 Hz bandwidth have been adapted. This article is to evaluate dynamic acceleration response performance of civil structures using the CAFB developed in the previous study. To achieve the purpose, the optimally-designed CAFB was embedded in an intelligent data acquisition (IDAQ) system. To evaluate the performance of the IDAQ system with the embedded CAFB, the real-time dynamic response was investigated for a model cable-stayed bridge, measured by a wire-measuring system and the CAFB-based IDAQ system simultaneously. The results show excellent agreement between the compressed dynamic response acquired by the CAFB-based IDAQ system and that acquired by the wire measuring system. In addition, the measurement from the CAFB-based IDAQ system revealed the modal information of the model bridge. The developed CAFB can determine and reconstruct the entire dynamic response from compression with modal information only; its efficient operation illustrates its potential to be utilized in real-time structural health monitoring. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Robust Sampling Frequency Offset Estimation for OFDM over Frequency Selective Fading Channels
Appl. Sci. 2018, 8(2), 197; https://doi.org/10.3390/app8020197
Received: 28 November 2017 / Revised: 19 January 2018 / Accepted: 22 January 2018 / Published: 29 January 2018
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Abstract
Digital radio mondiale (DRM) is a terrestrial radio broadcasting standard to replace existing analogue AM and FM broadcasting, which is based on an orthogonal frequency division multiplexing (OFDM) technique. This paper focuses on the issue of estimating a sampling frequency offset (SFO) in [...] Read more.
Digital radio mondiale (DRM) is a terrestrial radio broadcasting standard to replace existing analogue AM and FM broadcasting, which is based on an orthogonal frequency division multiplexing (OFDM) technique. This paper focuses on the issue of estimating a sampling frequency offset (SFO) in OFDM-based broadcasting systems under frequency selective fading channels. In order to design a robust SFO estimation scheme and to benchmark its performance, the performance of the various conventional SFO estimation schemes is discussed and some improvements on the conventional estimation algorithms are highlighted. The simulation results show that such a design enhances the robustness of the proposed scheme against frequency selective fading. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Placing Visual Sensors Using Heuristic Algorithms for Bridge Surveillance
Appl. Sci. 2018, 8(1), 70; https://doi.org/10.3390/app8010070
Received: 1 November 2017 / Revised: 20 December 2017 / Accepted: 3 January 2018 / Published: 6 January 2018
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Abstract
This study addresses the camera placement problem for bridge surveillance and proposes solutions that minimize the cost while satisfying the minimum coverage level. We discuss the field of view of cameras in the three-dimensional space. We also consider occlusions, the characteristics of surveillance [...] Read more.
This study addresses the camera placement problem for bridge surveillance and proposes solutions that minimize the cost while satisfying the minimum coverage level. We discuss the field of view of cameras in the three-dimensional space. We also consider occlusions, the characteristics of surveillance targets, and different pan-tilt-zoom cameras in the visibility test. To solve the camera placement problem while minimizing the total cost, we propose a genetic algorithm (GA) and a uniqueness score with a local search algorithm (ULA). Problem sets for a large-scale dimension scenario are generated based on the data of actual bridges in the Republic of Korea. For three simulation sets and a case study of Samoonjin Bridge, the proposed ULA yields better results than GA. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Linear Approximation Signal Detection Scheme in MIMO-OFDM Systems
Appl. Sci. 2018, 8(1), 49; https://doi.org/10.3390/app8010049
Received: 29 September 2017 / Revised: 25 November 2017 / Accepted: 13 December 2017 / Published: 1 January 2018
Cited by 1 | PDF Full-text (1331 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a linearly approximate signal detection scheme is proposed in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. The huge MIMO-OFDM system, which uses many transmit antennas and high order modulation, requires a detection scheme at the receiver with very [...] Read more.
In this paper, a linearly approximate signal detection scheme is proposed in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. The huge MIMO-OFDM system, which uses many transmit antennas and high order modulation, requires a detection scheme at the receiver with very low complexity for practical implementation. In the proposed detection scheme, one N × N MIMO-OFDM system is divided into N / 2 2 × 2 MIMO-OFDM systems for linear increase of complexity. After the partial zero-forcing (ZF), decision feedback equalizer (DFE) and QR decomposition-M algorithm (QRD-M) are applied to each 2 × 2 MIMO-OFDM system. Despite nonlinear detection schemes, the overall complexity of the proposed algorithm increases almost linearly because the DFE and the QRD-M are applied to 2 × 2 MIMO-OFDM systems. Also, the value of M in the QRD-M is fixed according to position of the center point in constellation for efficient signal detection. In simulation results, the proposed detection scheme has higher error performance and lower complexity than the conventional ZF. Also, the proposed detection scheme has very lower complexity than the conventional DFE, with slight loss of error performance. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Low-Complexity QRD-M with Path Eliminations in MIMO-OFDM Systems
Appl. Sci. 2017, 7(12), 1206; https://doi.org/10.3390/app7121206
Received: 18 September 2017 / Revised: 21 November 2017 / Accepted: 21 November 2017 / Published: 23 November 2017
Cited by 2 | PDF Full-text (2093 KB) | HTML Full-text | XML Full-text
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The QR decomposition-M algorithm (QRD-M) is a popular signal detector which has similar error performance with maximum likelihood (ML) in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. The QRD-M uses M candidates at each layer, unlike the [...] Read more.
The QR decomposition-M algorithm (QRD-M) is a popular signal detector which has similar error performance with maximum likelihood (ML) in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. The QRD-M uses M candidates at each layer, unlike the ML. However, the complexity of the QRD-M is high in huge MIMO-OFDM systems due to unnecessary survival paths at each layer. In this paper, a low-complexity QRD-M with variable number of survival paths at each layer is proposed. In the conventional QRD-M, path eliminations at the previous layer reduce the number of calculations for accumulated squared Euclidean distance (ASED) in subsequent layers. The proposed QRD-M eliminates unnecessary survival paths by comparing the ASED and the calculated threshold at each layer. The simulation results show that the proposed QRD-M maintains the error performance for the conventional QRD-M and has a very low complexity. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Moving-Target Position Estimation Using GPU-Based Particle Filter for IoT Sensing Applications
Appl. Sci. 2017, 7(11), 1152; https://doi.org/10.3390/app7111152
Received: 18 September 2017 / Accepted: 7 November 2017 / Published: 9 November 2017
Cited by 3 | PDF Full-text (3913 KB) | HTML Full-text | XML Full-text
Abstract
A particle filter (PF) has been introduced for effective position estimation of moving targets for non-Gaussian and nonlinear systems. The time difference of arrival (TDOA) method using acoustic sensor array has normally been used to for estimation by concealing the location of a [...] Read more.
A particle filter (PF) has been introduced for effective position estimation of moving targets for non-Gaussian and nonlinear systems. The time difference of arrival (TDOA) method using acoustic sensor array has normally been used to for estimation by concealing the location of a moving target, especially underwater. In this paper, we propose a GPU -based acceleration of target position estimation using a PF and propose an efficient system and software architecture. The proposed graphic processing unit (GPU)-based algorithm has more advantages in applying PF signal processing to a target system, which consists of large-scale Internet of Things (IoT)-driven sensors because of the parallelization which is scalable. For the TDOA measurement from the acoustic sensor array, we use the generalized cross correlation phase transform (GCC-PHAT) method to obtain the correlation coefficient of the signal using Fast Fourier Transform (FFT), and we try to accelerate the calculations of GCC-PHAT based TDOA measurements using FFT with GPU compute unified device architecture (CUDA). The proposed approach utilizes a parallelization method in the target position estimation algorithm using GPU-based PF processing. In addition, it could efficiently estimate sudden movement change of the target using GPU-based parallel computing which also can be used for multiple target tracking. It also provides scalability in extending the detection algorithm according to the increase of the number of sensors. Therefore, the proposed architecture can be applied in IoT sensing applications with a large number of sensors. The target estimation algorithm was verified using MATLAB and implemented using GPU CUDA. We implemented the proposed signal processing acceleration system using target GPU to analyze in terms of execution time. The execution time of the algorithm is reduced by 55% from to the CPU standalone operation in target embedded board, NVIDIA Jetson TX1. Also, to apply large-scaled IoT sensing applications, we use NVIDIA Tesla K40c as target GPU. The execution time of the proposed multi-state-space model-based algorithm is similar to the one-state-space model algorithm because of GPU-based parallel computing. Experimental results show that the proposed architecture is a feasible solution in terms of high-performance and area-efficient architecture. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessArticle Localization in Low Power Wide Area Networks Using Wi-Fi Fingerprints
Appl. Sci. 2017, 7(9), 936; https://doi.org/10.3390/app7090936
Received: 13 July 2017 / Revised: 2 September 2017 / Accepted: 7 September 2017 / Published: 12 September 2017
Cited by 4 | PDF Full-text (835 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Supply chain management requires regular updates of the location of assets, which can be enabled by low power wide area networks, such as Sigfox. While it is useful to localize a device simply by its communication signals, this is very difficult to do [...] Read more.
Supply chain management requires regular updates of the location of assets, which can be enabled by low power wide area networks, such as Sigfox. While it is useful to localize a device simply by its communication signals, this is very difficult to do with Sigfox because of wide area and ultra narrowband nature. On the other hand, installing a satellite localization element on the device greatly increases its power consumption. We investigated using information about nearby Wi-Fi access points as a way to localize the asset over the Sigfox network, so without connecting to those Wi-Fi networks. This paper reports the location error that can be achieved by this type of outdoor localization. By using a combination of two databases, we could localize the device on all 36 test locations with a median location error of 39 m . This shows that the localization accuracy of this method is promising enough to warrant further study, most specifically the minimal power consumption. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessReview Towards an ICT-Based Platform for Type 1 Diabetes Mellitus Management
Appl. Sci. 2018, 8(4), 511; https://doi.org/10.3390/app8040511
Received: 30 December 2017 / Revised: 20 February 2018 / Accepted: 24 March 2018 / Published: 27 March 2018
Cited by 3 | PDF Full-text (9422 KB) | HTML Full-text | XML Full-text
Abstract
Type 1 Diabetes Mellitus (DM1) is a metabolic disease that is characterized by chronic hyperglycemia due to a lack of pancreatic insulin production. This forces patients to perform several blood glucose measurements per day—by means of capillary glucometers—in order to infer a trend [...] Read more.
Type 1 Diabetes Mellitus (DM1) is a metabolic disease that is characterized by chronic hyperglycemia due to a lack of pancreatic insulin production. This forces patients to perform several blood glucose measurements per day—by means of capillary glucometers—in order to infer a trend and try to predict future values. In this way, a decision about the insulin dosage that has to be exogenously injected to maintain glycemia within the desirable levels is made. Unfortunately, this method usually suffers from relatively high imprecision. However, recent advances in information and communication technologies (ICT), along with novel biosensors that could provide a real-time comprehensive condition of the patient, offer a new perspective in DM1 management. In this sense, new disruptive technologies like Big Data, the Internet of Things (IoT), and Cloud Computing, as well as Machine Learning (ML) can play an important role in managing DM1. In this work, firstly, an analysis of previously published ICT-based methods for the management of diabetes continuous monitoring is carried out. In this way, an assessment of the possible lack of such proposals is presented, along with the challenges to be overcome in forthcoming smart DM1 management systems. Finally, an overview of a holistic ICT-based platform for DM1 management that try to solve the limitations of previous works, while at the same time, taking advantage of the abovementioned disruptive technologies is hereby proposed. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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Open AccessReview New Advances and Challenges of Fall Detection Systems: A Survey
Appl. Sci. 2018, 8(3), 418; https://doi.org/10.3390/app8030418
Received: 31 January 2018 / Revised: 22 February 2018 / Accepted: 6 March 2018 / Published: 12 March 2018
Cited by 1 | PDF Full-text (973 KB) | HTML Full-text | XML Full-text
Abstract
Falling, as one of the main harm threats to the elderly, has drawn researchers’ attentions and has always been one of the most valuable research topics in the daily health-care for the elderly in last two decades. Before 2014, several researchers reviewed the [...] Read more.
Falling, as one of the main harm threats to the elderly, has drawn researchers’ attentions and has always been one of the most valuable research topics in the daily health-care for the elderly in last two decades. Before 2014, several researchers reviewed the development of fall detection, presented issues and challenges, and navigated the direction for the study in the future. With smart sensors and Internet of Things (IoT) developing rapidly, this field has made great progress. However, there is a lack of a review and discussion on novel sensors, technologies and algorithms introduced and employed from 2014, as well as the emerging challenges and new issues. To bridge this gap, we present an overview of fall detection research and discuss the core research questions on this topic. A total of 6830 related documents were collected and analyzed based on the key words. Among these documents, the twenty most influential and highly cited articles are selected and discussed profoundly from three perspectives: sensors, algorithms and performance. The findings would assist researchers in understanding current developments and barriers in the systems of fall detection. Although researchers achieve fruitful work and progress, this research domain still confronts challenges on theories and practice. In the near future, the new solutions based on advanced IoT will sustainably urge the development to prevent falling injuries. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
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