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Special Issue "Internet of Things and Ubiquitous Sensing"

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

Deadline for manuscript submissions: closed (31 December 2018).

Special Issue Editor

Prof. Dr. James (Jong Hyuk) Park
E-Mail Website
Guest Editor

Special Issue Information

Dear Colleagues,

Rapid advances in the manufacturing of wireless sensor nodes have expanded the range of Wireless Sensor Networks (WSNs) applications in Internet-of-Things (IoT) networks, such as monitoring and gathering information from public infrastructure, natural disaster relief, healthcare, smart homes, and industries. Ubiquitous Sensing (US) including WSN and various applications, offers significant advantages over traditional networks, and it brought a revolution in the perception of information by self-organizing, distributed, low cost and power. Many factors that may affect the design of US include, but not are limited to cost, power, topology, scalability, reliability, energy consumption, and operating environment. Meanwhile, computational intelligence (CI) is a source of artificial intelligence, and includes techniques such as deep learning, evolutionary algorithms, and fuzzy logic. To address challenges such as localization, optimal deployment, security, energy aware routing and task scheduling, and data aggregation and fusion, CI paradigms have been successfully used in recent years. In complex and dynamic US environments, CI provides adaptive mechanisms that exhibit intelligent behaviors. It offers flexibility, autonomous behavior, and robustness against topology changes, communication failures, and scenario changes.

This special issue expects innovative work to explore new frontiers and challenges in the field of IoT&US research, including optimal usage and management of energy resources, node deployment, applications and services in US for scalable IoT networks.

The particular topics of interest include, but are not limited to:

  • IoT architectures and framework
  • Software defined network architecture integration with IoT
  • Cloud and edge computing for IoT
  • Embedded software and cyber physical system for IoT
  • Device-to-Device communications for IoT
  • Smart grid and smart factory in IoT
  • Fault-tolerance in US
  • Topology control and routing protocols for US
  • Low-power, energy efficiency, and energy-harvesting in US
  • Hybrid intelligent systems and applications for IoT&US
  • Computational intelligence for IoT&US
  • Deep learning algorithms for IoT&US
  • Big data analytics and data-mining for IoT&US
  • Security and privacy-preserving protocols for IoT&US
  • Human-centric services and applications for IoT&US
  • Integration of wireless sensor networks with smart city

Prof. Dr. Jong Hyuk Park
Guest Editor

Manuscript Submission Information

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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.

Keywords

  • Internet-of-Things and SDN
  • Ubiquitous sensing and WSN
  • Computational intelligence and deep learning
  • Sensing big data analytics
  • IoT security and privacy
  • Cloud and edge computing

Published Papers (20 papers)

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Research

Article
A Deployable LPWAN Platform for Low-Cost and Energy-Constrained IoT Applications
Sensors 2019, 19(3), 585; https://doi.org/10.3390/s19030585 - 30 Jan 2019
Cited by 9 | Viewed by 2010
Abstract
Many commercial platforms for fast prototyping have gained support for lpwan technologies. However, these solutions do not meet the low-cost and low-power requirements for a large-scale distribution of battery-powered sensor nodes. This paper presents the design, realization and validation of an open-source lpwan [...] Read more.
Many commercial platforms for fast prototyping have gained support for lpwan technologies. However, these solutions do not meet the low-cost and low-power requirements for a large-scale distribution of battery-powered sensor nodes. This paper presents the design, realization and validation of an open-source lpwan versatile platform. Energy and cost are considered key constraints for this hardware design. A power-efficient LoRa radio interface is implemented by hosting MAC functionality on the application microcontroller, eliminating the need for a modem. In the system architecture, power and cost savings are obtained by omitting and controlling lossy power circuitry. The resulting platform allows entry-level prototyping, while featuring an ultra-low sleep power of 25.2 μ W . This makes lpwan sensor applications accessible in domains that would otherwise require custom hardware development. The proposed design is validated by an illustrative but functional example of sensor nodes deployed in the field. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
IB-MAC: Transmission Latency-Aware MAC for Electro-Magnetic Intra-Body Communications
Sensors 2019, 19(2), 341; https://doi.org/10.3390/s19020341 - 16 Jan 2019
Cited by 5 | Viewed by 1519
Abstract
Intra-body Communication (IBC) is a communication method using the human body as a communication medium, in which body-attached devices exchange electro-magnetic (EM) wave signals with each other. The fact that our human body consists of water and electrolytes allows such communication methods to [...] Read more.
Intra-body Communication (IBC) is a communication method using the human body as a communication medium, in which body-attached devices exchange electro-magnetic (EM) wave signals with each other. The fact that our human body consists of water and electrolytes allows such communication methods to be possible. Such a communication technology can be used to design novel body area networks that are secure and resilient towards external radio interference. While being an attractive technology for enabling new applications for human body-centered ubiquitous applications, network protocols for IBC systems is yet under-explored. The IEEE 802.15.6 standards present physical and medium access control (MAC) layer protocols for IBC, but, due to many simplifications, we find that its MAC protocol is limited in providing an environment to enable high data rate applications. This work, based on empirical EM wave propagation measurements made for the human body communication channel, presents IB-MAC, a centralized Time-division multiple access (TDMA) protocol that takes in consideration the transmission latency the body channel induces. Our results, in which we use an event-based simulator to compare the performance of IB-MAC with two different IEEE 802.15.6 standard-compliant MAC protocols and a state-of-the art TDMA-based MAC protocol for IBC, suggest that IB-MAC is suitable for supporting high data rate applications with comparable radio duty cycle and latency performance. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Minimum Cost Deployment of Bistatic Radar Sensor for Perimeter Barrier Coverage
Sensors 2019, 19(2), 225; https://doi.org/10.3390/s19020225 - 09 Jan 2019
Cited by 3 | Viewed by 1565
Abstract
Perimeter barriers can provide intrusion detection for a closed area. It is efficient for practical applications, such as coastal shoreline monitoring and international boundary surveillance. Perimeter barrier coverage construction in some regions of interest with irregular boundaries can be represented by its minimum [...] Read more.
Perimeter barriers can provide intrusion detection for a closed area. It is efficient for practical applications, such as coastal shoreline monitoring and international boundary surveillance. Perimeter barrier coverage construction in some regions of interest with irregular boundaries can be represented by its minimum circumcircle and every point on the perimeter can be covered. This paper studies circle barrier coverage in Bistatic Radar Sensor Network (BRSN) which encircles a region of interest. To improve the coverage quality, it is required to construct a circle barrier with a predefined width. Firstly, we consider a BR deployment problem to constructing a single BR circular barrier with minimum threshold of detectability. We study the optimized BR placement patterns on the single circular ring. Then the unit costs of the BR sensor are taken into account to derive the minimum cost placement sequence. Secondly, we further consider a circular BR barrier with a predefined width, which is wider than the breadth of Cassini oval sensing area with minimum threshold of detectability. We propose two segment strategies to efficiently divide a circular barrier to several adjacent sub-ring with some appropriate width: Circular equipartition strategy and an adaptive segmentation strategy. Finally, we propose approximate optimization placement algorithms for minimum cost placement of BR sensor for circular barrier coverage with required width and detection threshold. We validate the effectiveness of the proposed algorithms through theory analysis and extensive simulation experiments. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things
Sensors 2018, 18(11), 3951; https://doi.org/10.3390/s18113951 - 15 Nov 2018
Cited by 13 | Viewed by 1670
Abstract
With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things [...] Read more.
With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things (IoT). However, due to the characteristics of massive connections, access collisions in the MAC layer lead to high power consumption for both sensor devices and UAVs, and low efficiency for the data collection. In this paper, a dynamic speed control algorithm for UAVs (DSC-UAV) is proposed to maximize the data collection efficiency, while alleviating the access congestion for the UAV-based base stations. With a cellular network considered for support of the communication between sensor devices and drones, the connection establishment process was analyzed and modeled in detail. In addition, the data collection efficiency is also defined and derived. Based on the analytical models, optimal speed under different sensor device densities is obtained and verified. UAVs can dynamically adjust the speed according to the sensor device density under their coverages to keep high data collection efficiency. Finally, simulation results are also conducted to verify the accuracy of the proposed analytical models and show that the DSC-UAV outperforms others with the highest data collection efficiency, while maintaining a high successful access probability, low average access delay, low block probability, and low collision probability. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
An Adaptive Parallel Processing Strategy for Complex Event Processing Systems over Data Streams in Wireless Sensor Networks
Sensors 2018, 18(11), 3732; https://doi.org/10.3390/s18113732 - 02 Nov 2018
Cited by 4 | Viewed by 1394
Abstract
Efficient matching of incoming events of data streams to persistent queries is fundamental to event stream processing systems in wireless sensor networks. These applications require dealing with high volume and continuous data streams with fast processing time on distributed complex event processing (CEP) [...] Read more.
Efficient matching of incoming events of data streams to persistent queries is fundamental to event stream processing systems in wireless sensor networks. These applications require dealing with high volume and continuous data streams with fast processing time on distributed complex event processing (CEP) systems. Therefore, a well-managed parallel processing technique is needed for improving the performance of the system. However, the specific properties of pattern operators in the CEP systems increase the difficulties of the parallel processing problem. To address these issues, a parallelization model and an adaptive parallel processing strategy are proposed for the complex event processing by introducing a histogram and utilizing the probability and queue theory. The proposed strategy can estimate the optimal event splitting policy, which can suit the most recent workload conditions such that the selected policy has the least expected waiting time for further processing of the arriving events. The proposed strategy can keep the CEP system running fast under the variation of the time window sizes of operators and the input rates of streams. Finally, the utility of our work is demonstrated through the experiments on the StreamBase system. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Development of Sensor Registry System-Based Predictive Information Service Using a Grid
Sensors 2018, 18(11), 3620; https://doi.org/10.3390/s18113620 - 25 Oct 2018
Cited by 3 | Viewed by 1172
Abstract
A sensor registry system (SRS) registers sensor metadata and provides them for a seamless semantic process. Recently, network coverage information-based SRS (NC-SRS) was developed to provide sensor information filtering by combining path prediction and network coverage checks. However, the NC-SRS has problems caused [...] Read more.
A sensor registry system (SRS) registers sensor metadata and provides them for a seamless semantic process. Recently, network coverage information-based SRS (NC-SRS) was developed to provide sensor information filtering by combining path prediction and network coverage checks. However, the NC-SRS has problems caused by issues such as termination of OpenSignal service and pre-building road segments. Therefore, this paper proposes a sensor registry system-based predictive information service (SRS-PIS) using a grid. SRS-PIS predicts a path based on the grid, checks the network coverage, and filters the sensor. This paper presents a grid-based real-time path prediction algorithm and an algorithm for grouping network service-disabled areas. To obtain network coverage information, we constructed and implemented a grid-based coverage map through experiment to measure the signal strength. As an evaluation, we compared features among SRS-based systems and SRS-PIS, and compared advantages and disadvantages between segment-based and grid-based methods. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
A Method of HBase Multi-Conditional Query for Ubiquitous Sensing Applications
Sensors 2018, 18(9), 3064; https://doi.org/10.3390/s18093064 - 12 Sep 2018
Cited by 1 | Viewed by 1379
Abstract
Big data gathered from real systems, such as public infrastructure, healthcare, smart homes, industries, and so on, by sensor networks contain enormous value, and need to be mined deeply, which depends on a data storing and retrieving service. HBase is playing an increasingly [...] Read more.
Big data gathered from real systems, such as public infrastructure, healthcare, smart homes, industries, and so on, by sensor networks contain enormous value, and need to be mined deeply, which depends on a data storing and retrieving service. HBase is playing an increasingly important part in the big data environment since it provides a flexible pattern for storing extremely large amounts of unstructured data. Despite the fast-speed reading by RowKey, HBase does not natively support multi-conditional query, which is a common demand and operation in relational databases, especially for data analysis of ubiquitous sensing applications. In this paper, we introduce a method to construct a linear index by employing a Hilbert space-filling curve. As a RowKey generating schema, the proposed method maps multiple index-columns into a one-dimensional encoded sequence, and then constructs a new RowKey. We also provide a R-tree-based optimization to reduce the computational cost of encoding query conditions. Without using a secondary index mode, experimental results indicate that the proposed method has better performance in multi-conditional queries. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Joint Source and Channel Rate Allocation over Noisy Channels in a Vehicle Tracking Multimedia Internet of Things System
Sensors 2018, 18(9), 2858; https://doi.org/10.3390/s18092858 - 30 Aug 2018
Cited by 2 | Viewed by 1394
Abstract
As an emerging type of Internet of Things (IoT), multimedia IoT (MIoT) has been widely used in the domains of healthcare, smart buildings/homes, transportation and surveillance. In the mobile surveillance system for vehicle tracking, multiple mobile camera nodes capture and upload videos to [...] Read more.
As an emerging type of Internet of Things (IoT), multimedia IoT (MIoT) has been widely used in the domains of healthcare, smart buildings/homes, transportation and surveillance. In the mobile surveillance system for vehicle tracking, multiple mobile camera nodes capture and upload videos to a cloud server to track the target. Due to the random distribution and mobility of camera nodes, wireless networks are chosen for video transmission. However, the tracking precision can be decreased because of degradation of video quality caused by limited wireless transmission resources and transmission errors. In this paper, we propose a joint source and channel rate allocation scheme to optimize the performance of vehicle tracking in cloud servers. The proposed scheme considers the video content features that impact tracking precision for optimal rate allocation. To improve the reliability of data transmission and the real-time video communication, forward error correction is adopted in the application layer. Extensive experiments are conducted on videos from the Object Tracking Benchmark using the H.264/AVC standard and a kernelized correlation filter tracking scheme. The results show that the proposed scheme can allocate rates efficiently and provide high quality tracking service under the total transmission rate constraints. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
A Plug-and-Play Human-Centered Virtual TEDS Architecture for the Web of Things
Sensors 2018, 18(7), 2052; https://doi.org/10.3390/s18072052 - 27 Jun 2018
Cited by 20 | Viewed by 2398
Abstract
This article presents a Virtual Transducer Electronic Data Sheet (VTEDS)-based framework for the development of intelligent sensor nodes with plug-and-play capabilities in order to contribute to the evolution of the Internet of Things (IoT) toward the Web of Things (WoT). It makes use [...] Read more.
This article presents a Virtual Transducer Electronic Data Sheet (VTEDS)-based framework for the development of intelligent sensor nodes with plug-and-play capabilities in order to contribute to the evolution of the Internet of Things (IoT) toward the Web of Things (WoT). It makes use of new lightweight protocols that allow sensors to self-describe, auto-calibrate, and auto-register. Such protocols enable the development of novel IoT solutions while guaranteeing low latency, low power consumption, and the required Quality of Service (QoS). Thanks to the developed human-centered tools, it is possible to configure and modify dynamically IoT device firmware, managing the active transducers and their communication protocols in an easy and intuitive way, without requiring any prior programming knowledge. In order to evaluate the performance of the system, it was tested when using Bluetooth Low Energy (BLE) and Ethernet-based smart sensors in different scenarios. Specifically, user experience was quantified empirically (i.e., how fast the system shows collected data to a user was measured). The obtained results show that the proposed VTED architecture is very fast, with some smart sensors (located in Europe) able to self-register and self-configure in a remote cloud (in South America) in less than 3 s and to display data to remote users in less than 2 s. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
The SDN Approach for the Aggregation/Disaggregation of Sensor Data
Sensors 2018, 18(7), 2025; https://doi.org/10.3390/s18072025 - 25 Jun 2018
Cited by 20 | Viewed by 1796
Abstract
In many Internet of Things (IoT) applications, large numbers of small sensor data are delivered in the network, which may cause heavy traffics. To reduce the number of messages delivered from the sensor devices to the IoT server, a promising approach is to [...] Read more.
In many Internet of Things (IoT) applications, large numbers of small sensor data are delivered in the network, which may cause heavy traffics. To reduce the number of messages delivered from the sensor devices to the IoT server, a promising approach is to aggregate several small IoT messages into a large packet before they are delivered through the network. When the packets arrive at the destination, they are disaggregated into the original IoT messages. In the existing solutions, packet aggregation/disaggregation is performed by software at the server, which results in long delays and low throughputs. To resolve the above issue, this paper utilizes the programmable Software Defined Networking (SDN) switch to program quick packet aggregation and disaggregation. Specifically, we consider the Programming Protocol-Independent Packet Processor (P4) technology. We design and develop novel P4 programs for aggregation and disaggregation in commercial P4 switches. Our study indicates that packet aggregation can be achieved in a P4 switch with its line rate (without extra packet processing cost). On the other hand, to disaggregate a packet that combines N IoT messages, the processing time is about the same as processing N individual IoT messages. Our implementation conducts IoT message aggregation at the highest bit rate (100 Gbps) that has not been found in the literature. We further propose to provide a small buffer in the P4 switch to significantly reduce the processing power for disaggregating a packet. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
A Correlation Driven Approach with Edge Services for Predictive Industrial Maintenance
Sensors 2018, 18(6), 1844; https://doi.org/10.3390/s18061844 - 05 Jun 2018
Cited by 6 | Viewed by 1413
Abstract
Predictive industrial maintenance promotes proactive scheduling of maintenance to minimize unexpected device anomalies/faults. Almost all current predictive industrial maintenance techniques construct a model based on prior knowledge or data at build-time. However, anomalies/faults will propagate among sensors and devices along correlations hidden among [...] Read more.
Predictive industrial maintenance promotes proactive scheduling of maintenance to minimize unexpected device anomalies/faults. Almost all current predictive industrial maintenance techniques construct a model based on prior knowledge or data at build-time. However, anomalies/faults will propagate among sensors and devices along correlations hidden among sensors. These correlations can facilitate maintenance. This paper makes an attempt on predicting the anomaly/fault propagation to perform predictive industrial maintenance by considering the correlations among faults. The main challenge is that an anomaly/fault may propagate in multiple ways owing to various correlations. This is called as the uncertainty of anomaly/fault propagation. This present paper proposes a correlation-based event routing approach for predictive industrial maintenance by improving our previous works. Our previous works mapped physical sensors into a soft-ware-defined abstraction, called proactive data service. In the service model, anomalies/faults are encapsulated into events. We also proposed a service hyperlink model to encapsulate the correlations among anomalies/faults. This paper maps the anomalies/faults propagation into event routing and proposes a heuristic algorithm based on service hyperlinks to route events among services. The experiment results show that, our approach can reach 100% precision and 88.89% recall at most. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Caching Joint Shortcut Routing to Improve Quality of Service for Information-Centric Networking
Sensors 2018, 18(6), 1750; https://doi.org/10.3390/s18061750 - 29 May 2018
Cited by 19 | Viewed by 1941
Abstract
Hundreds of thousands of ubiquitous sensing (US) devices have provided an enormous number of data for Information-Centric Networking (ICN), which is an emerging network architecture that has the potential to solve a great variety of issues faced by the traditional network. A Caching [...] Read more.
Hundreds of thousands of ubiquitous sensing (US) devices have provided an enormous number of data for Information-Centric Networking (ICN), which is an emerging network architecture that has the potential to solve a great variety of issues faced by the traditional network. A Caching Joint Shortcut Routing (CJSR) scheme is proposed in this paper to improve the Quality of service (QoS) for ICN. The CJSR scheme mainly has two innovations which are different from other in-network caching schemes: (1) Two routing shortcuts are set up to reduce the length of routing paths. Because of some inconvenient transmission processes, the routing paths of previous schemes are prolonged, and users can only request data from Data Centers (DCs) until the data have been uploaded from Data Producers (DPs) to DCs. Hence, the first kind of shortcut is built from DPs to users directly. This shortcut could release the burden of whole network and reduce delay. Moreover, in the second shortcut routing method, a Content Router (CR) which could yield shorter length of uploading routing path from DPs to DCs is chosen, and then data packets are uploaded through this chosen CR. In this method, the uploading path shares some segments with the pre-caching path, thus the overall length of routing paths is reduced. (2) The second innovation of the CJSR scheme is that a cooperative pre-caching mechanism is proposed so that QoS could have a further increase. Besides being used in downloading routing, the pre-caching mechanism can also be used when data packets are uploaded towards DCs. Combining uploading and downloading pre-caching, the cooperative pre-caching mechanism exhibits high performance in different situations. Furthermore, to address the scarcity of storage size, an algorithm that could make use of storage from idle CRs is proposed. After comparing the proposed scheme with five existing schemes via simulations, experiments results reveal that the CJSR scheme could reduce the total number of processed interest packets by 54.8%, enhance the cache hits of each CR and reduce the number of total hop counts by 51.6% and cut down the length of routing path for users to obtain their interested data by 28.6–85.7% compared with the traditional NDN scheme. Moreover, the length of uploading routing path could be decreased by 8.3–33.3%. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Cooperative Computing System for Heavy-Computation and Low-Latency Processing in Wireless Sensor Networks
Sensors 2018, 18(6), 1686; https://doi.org/10.3390/s18061686 - 24 May 2018
Cited by 2 | Viewed by 1415
Abstract
Over the past decades, hardware and software technologies for wireless sensor networks (WSNs) have significantly progressed, and WSNs are widely used in various areas including Internet of Things (IoT). In general, existing WSNs are mainly used for applications that require delay-tolerance and low-computation [...] Read more.
Over the past decades, hardware and software technologies for wireless sensor networks (WSNs) have significantly progressed, and WSNs are widely used in various areas including Internet of Things (IoT). In general, existing WSNs are mainly used for applications that require delay-tolerance and low-computation due to the poor resources of traditional sensor nodes in WSNs. However, compared to the traditional sensor nodes, today’s devices for WSNs have more powerful resource. Thus, sensor nodes these days not only conduct sensing and transmitting data to servers but also are able to process many operations, so more diverse applications can be applied to WSNs. Especially, many applications using audio data have been proposed because audio is one of the most widely used data types, and many mobile devices already have a built-in microphone. However, many of the applications have a requirement that heavy-operations should be done by a tight deadline, so it is difficult for a single node in WSNs to run relatively heavy applications by itself. In this paper, to overcome this limitation of WSNs, we propose a new emerging system, HeaLow, a cooperative computing system for heavy-computation and low-latency processing in WSNs. We designed HeaLow and carried out the practical implementation on real devices. We confirmed the effectiveness of HeaLow through various experiments using the real devices and simulations. Using HeaLow, nodes in WSNs are able to perform heavy-computation processes while satisfying a completion time requirement. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Appdaptivity: An Internet of Things Device-Decoupled System for Portable Applications in Changing Contexts
Sensors 2018, 18(5), 1345; https://doi.org/10.3390/s18051345 - 26 Apr 2018
Cited by 3 | Viewed by 2052
Abstract
Currently, applications in the Internet of Things (IoT) are tightly coupled to the underlying physical devices. As a consequence, upon adding a device, device replacement or user’s relocation to a different physical space, application developers have to re-perform installation and configuration processes to [...] Read more.
Currently, applications in the Internet of Things (IoT) are tightly coupled to the underlying physical devices. As a consequence, upon adding a device, device replacement or user’s relocation to a different physical space, application developers have to re-perform installation and configuration processes to reconfigure applications, which bears costs in time and knowledge of low-level details. In the emerging IoT field, this issue is even more challenging due to its current unpredictable growth in term of applications and connected devices. In addition, IoT applications can be personalised to each end user and can be present in different environments. As a result, IoT scenarios are very changeable, presenting a challenge for IoT applications. In this paper we present Appdaptivity, a system that enables the development of portable device-decoupled applications that can be adapted to changing contexts. Through Appdaptivity, application developers can intuitively create portable and personalised applications, disengaging from the underlying physical infrastructure. Results confirms a good scalability of the system in terms of connected users and components involved. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
An Energy-Efficient Algorithm for Wearable Electrocardiogram Signal Processing in Ubiquitous Healthcare Applications
Sensors 2018, 18(3), 923; https://doi.org/10.3390/s18030923 - 20 Mar 2018
Cited by 45 | Viewed by 3478
Abstract
Rapid progress and emerging trends in miniaturized medical devices have enabled the un-obtrusive monitoring of physiological signals and daily activities of everyone’s life in a prominent and pervasive manner. Due to the power-constrained nature of conventional wearable sensor devices during ubiquitous sensing (US), [...] Read more.
Rapid progress and emerging trends in miniaturized medical devices have enabled the un-obtrusive monitoring of physiological signals and daily activities of everyone’s life in a prominent and pervasive manner. Due to the power-constrained nature of conventional wearable sensor devices during ubiquitous sensing (US), energy-efficiency has become one of the highly demanding and debatable issues in healthcare. This paper develops a single chip-based wearable wireless electrocardiogram (ECG) monitoring system by adopting analog front end (AFE) chip model ADS1292R from Texas Instruments. The developed chip collects real-time ECG data with two adopted channels for continuous monitoring of human heart activity. Then, these two channels and the AFE are built into a right leg drive right leg drive (RLD) driver circuit with lead-off detection and medical graded test signal. Human ECG data was collected at 60 beats per minute (BPM) to 120 BPM with 60 Hz noise and considered throughout the experimental set-up. Moreover, notch filter (cutoff frequency 60 Hz), high-pass filter (cutoff frequency 0.67 Hz), and low-pass filter (cutoff frequency 100 Hz) with cut-off frequencies of 60 Hz, 0.67 Hz, and 100 Hz, respectively, were designed with bilinear transformation for rectifying the power-line noise and artifacts while extracting real-time ECG signals. Finally, a transmission power control-based energy-efficient (ETPC) algorithm is proposed, implemented on the hardware and then compared with the several conventional TPC methods. Experimental results reveal that our developed chip collects real-time ECG data efficiently, and the proposed ETPC algorithm achieves higher energy savings of 35.5% with a slightly larger packet loss ratio (PLR) as compared to conventional TPC (e.g., constant TPC, Gao’s, and Xiao’s methods). Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Smart Winery: A Real-Time Monitoring System for Structural Health and Ullage in Fino Style Wine Casks
Sensors 2018, 18(3), 803; https://doi.org/10.3390/s18030803 - 07 Mar 2018
Cited by 13 | Viewed by 3037
Abstract
The rapid development in low-cost sensor and wireless communication technology has made it possible for a large number of devices to coexist and exchange information autonomously. It has been predicted that a substantial number of devices will be able to exchange and provide [...] Read more.
The rapid development in low-cost sensor and wireless communication technology has made it possible for a large number of devices to coexist and exchange information autonomously. It has been predicted that a substantial number of devices will be able to exchange and provide information about an environment with the goal of improving our lives, under the well-known paradigm of the Internet of Things (IoT). One of the main applications of these kinds of devices is the monitoring of scenarios. In order to improve the current wine elaboration process, this paper presents a real-time monitoring system to supervise the status of wine casks. We have focused on a special kind of white wine, called Fino, principally produced in Andalusia (Southern Spain). The process by which this kind of wind is monitored is completely different from that of red wine, as the casks are not completely full and, due to the fact that they are not renewed very often, are more prone to breakage. A smart cork prototype monitors the structural health, the ullage, and the level of light inside the cask and the room temperature. The advantage of this smart cork is that it allows winemakers to monitor, in real time, the status of each wine cask so that, if an issue is detected (e.g., a crack appears in the cask), they can act immediately to resolve it. Moreover, abnormal parameters or incorrect environmental conditions can be detected in time before the wine loses its desired qualities. The system has been tested in “Bodegas San Acacio,” a winery based in Montemayor, a town in the north of Andalusia. Results show that the use of such a system can provide a solution that tracks the evolution and assesses the suitability of the delicate wine elaboration process in real time, which is especially important for the kind of wine considered in this paper. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Electrical Design and Evaluation of Asynchronous Serial Bus Communication Network of 48 Sensor Platform LSIs with Single-Ended I/O for Integrated MEMS-LSI Sensors
Sensors 2018, 18(1), 231; https://doi.org/10.3390/s18010231 - 15 Jan 2018
Cited by 4 | Viewed by 2858
Abstract
For installing many sensors in a limited space with a limited computing resource, the digitization of the sensor output at the site of sensation has advantages such as a small amount of wiring, low signal interference and high scalability. For this purpose, we [...] Read more.
For installing many sensors in a limited space with a limited computing resource, the digitization of the sensor output at the site of sensation has advantages such as a small amount of wiring, low signal interference and high scalability. For this purpose, we have developed a dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) (referred to as “sensor platform LSI”) for bus-networked Micro-Electro-Mechanical-Systems (MEMS)-LSI integrated sensors. In this LSI, collision avoidance, adaptation and event-driven functions are simply implemented to relieve data collision and congestion in asynchronous serial bus communication. In this study, we developed a network system with 48 sensor platform LSIs based on Printed Circuit Board (PCB) in a backbone bus topology with the bus length being 2.4 m. We evaluated the serial communication performance when 48 LSIs operated simultaneously with the adaptation function. The number of data packets received from each LSI was almost identical, and the average sampling frequency of 384 capacitance channels (eight for each LSI) was 73.66 Hz. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Genetic Algorithm-Based Motion Estimation Method using Orientations and EMGs for Robot Controls
Sensors 2018, 18(1), 183; https://doi.org/10.3390/s18010183 - 11 Jan 2018
Cited by 11 | Viewed by 2048
Abstract
Demand for interactive wearable devices is rapidly increasing with the development of smart devices. To accurately utilize wearable devices for remote robot controls, limited data should be analyzed and utilized efficiently. For example, the motions by a wearable device, called Myo device, can [...] Read more.
Demand for interactive wearable devices is rapidly increasing with the development of smart devices. To accurately utilize wearable devices for remote robot controls, limited data should be analyzed and utilized efficiently. For example, the motions by a wearable device, called Myo device, can be estimated by measuring its orientation, and calculating a Bayesian probability based on these orientation data. Given that Myo device can measure various types of data, the accuracy of its motion estimation can be increased by utilizing these additional types of data. This paper proposes a motion estimation method based on weighted Bayesian probability and concurrently measured data, orientations and electromyograms (EMG). The most probable motion among estimated is treated as a final estimated motion. Thus, recognition accuracy can be improved when compared to the traditional methods that employ only a single type of data. In our experiments, seven subjects perform five predefined motions. When orientation is measured by the traditional methods, the sum of the motion estimation errors is 37.3%; likewise, when only EMG data are used, the error in motion estimation by the proposed method was also 37.3%. The proposed combined method has an error of 25%. Therefore, the proposed method reduces motion estimation errors by 12%. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Enhancing Time Synchronization Support in Wireless Sensor Networks
Sensors 2017, 17(12), 2956; https://doi.org/10.3390/s17122956 - 20 Dec 2017
Cited by 21 | Viewed by 2302
Abstract
With the emerging Internet of Things (IoT) technology becoming reality, a number of applications are being proposed. Several of these applications are highly dependent on wireless sensor networks (WSN) to acquire data from the surrounding environment. In order to be really useful for [...] Read more.
With the emerging Internet of Things (IoT) technology becoming reality, a number of applications are being proposed. Several of these applications are highly dependent on wireless sensor networks (WSN) to acquire data from the surrounding environment. In order to be really useful for most of applications, the acquired data must be coherent in terms of the time in which they are acquired, which implies that the entire sensor network presents a certain level of time synchronization. Moreover, to efficiently exchange and forward data, many communication protocols used in WSN rely also on time synchronization among the sensor nodes. Observing the importance in complying with this need for time synchronization, this work focuses on the second synchronization problem, proposing, implementing and testing a time synchronization service for low-power WSN using low frequency real-time clocks in each node. To implement this service, three algorithms based on different strategies are proposed: one based on an auto-correction approach, the second based on a prediction mechanism, while the third uses an analytical correction mechanism. Their goal is the same, i.e., to make the clocks of the sensor nodes converge as quickly as possible and then to keep them most similar as possible. This goal comes along with the requirement to keep low energy consumption. Differently from other works in the literature, the proposal here is independent of any specific protocol, i.e., it may be adapted to be used in different protocols. Moreover, it explores the minimum number of synchronization messages by means of a smart clock update strategy, allowing the trade-off between the desired level of synchronization and the associated energy consumption. Experimental results, which includes data acquired from simulations and testbed deployments, provide evidence of the success in meeting this goal, as well as providing means to compare these three approaches considering the best synchronization results and their costs in terms of energy consumption. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Article
Command Disaggregation Attack and Mitigation in Industrial Internet of Things
Sensors 2017, 17(10), 2408; https://doi.org/10.3390/s17102408 - 21 Oct 2017
Cited by 9 | Viewed by 2739
Abstract
A cyber-physical attack in the industrial Internet of Things can cause severe damage to physical system. In this paper, we focus on the command disaggregation attack, wherein attackers modify disaggregated commands by intruding command aggregators like programmable logic controllers, and then maliciously manipulate [...] Read more.
A cyber-physical attack in the industrial Internet of Things can cause severe damage to physical system. In this paper, we focus on the command disaggregation attack, wherein attackers modify disaggregated commands by intruding command aggregators like programmable logic controllers, and then maliciously manipulate the physical process. It is necessary to investigate these attacks, analyze their impact on the physical process, and seek effective detection mechanisms. We depict two different types of command disaggregation attack modes: (1) the command sequence is disordered and (2) disaggregated sub-commands are allocated to wrong actuators. We describe three attack models to implement these modes with going undetected by existing detection methods. A novel and effective framework is provided to detect command disaggregation attacks. The framework utilizes the correlations among two-tier command sequences, including commands from the output of central controller and sub-commands from the input of actuators, to detect attacks before disruptions occur. We have designed components of the framework and explain how to mine and use these correlations to detect attacks. We present two case studies to validate different levels of impact from various attack models and the effectiveness of the detection framework. Finally, we discuss how to enhance the detection framework. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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