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Sensors, Volume 16, Issue 11 (November 2016)

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Open AccessArticle
Service Demand Discovery Mechanism for Mobile Social Networks
Sensors 2016, 16(11), 1982; https://doi.org/10.3390/s16111982
Received: 12 October 2016 / Revised: 16 November 2016 / Accepted: 17 November 2016 / Published: 23 November 2016
Cited by 4 | Viewed by 1385 | PDF Full-text (2031 KB) | HTML Full-text | XML Full-text
Abstract
In the last few years, the service demand for wireless data over mobile networks has continually been soaring at a rapid pace. Thereinto, in Mobile Social Networks (MSNs), users can discover adjacent users for establishing temporary local connection and thus sharing already downloaded [...] Read more.
In the last few years, the service demand for wireless data over mobile networks has continually been soaring at a rapid pace. Thereinto, in Mobile Social Networks (MSNs), users can discover adjacent users for establishing temporary local connection and thus sharing already downloaded contents with each other to offload the service demand. Due to the partitioned topology, intermittent connection and social feature in such a network, the service demand discovery is challenging. In particular, the service demand discovery is exploited to identify the best relay user through the service registration, service selection and service activation. In order to maximize the utilization of limited network resources, a hybrid service demand discovery architecture, such as a Virtual Dictionary User (VDU) is proposed in this paper. Based on the historical data of movement, users can discover their relationships with others. Subsequently, according to the users activity, VDU is selected to facilitate the service registration procedure. Further, the service information outside of a home community can be obtained through the Global Active User (GAU) to support the service selection. To provide the Quality of Service (QoS), the Service Providing User (SPU) is chosen among multiple candidates. Numerical results show that, when compared with other classical service algorithms, the proposed scheme can improve the successful service demand discovery ratio by 25% under reduced overheads. Full article
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Open AccessArticle
Radius and Orientation Measurement for Cylindrical Objects by a Light Section Sensor
Sensors 2016, 16(11), 1981; https://doi.org/10.3390/s16111981
Received: 17 October 2016 / Revised: 18 November 2016 / Accepted: 21 November 2016 / Published: 23 November 2016
Viewed by 2040 | PDF Full-text (10302 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, an efficient method based on a light section sensor is presented for measuring cylindrical objects’ radii and orientations in a robotic application. By this method, the cylindrical objects can be measured under some special conditions, such as when the cylindrical [...] Read more.
In this paper, an efficient method based on a light section sensor is presented for measuring cylindrical objects’ radii and orientations in a robotic application. By this method, the cylindrical objects can be measured under some special conditions, such as when the cylindrical objects are welded with others, or in the presence of interferences. Firstly, the measurement data are roughly identified and accurately screened to effectively recognize ellipses. Secondly, the data are smoothed and homogenized to eliminate the effect of laser line loss or jump and reduce the influence of the inhomogeneity of measurement data on the ellipse fitting to a minimum. Finally, the ellipse fitting is carried out to obtain the radii and orientations of the cylindrical objects. Measuring experiments and results demonstrate the effective of the proposed radius and orientation measurement method for cylindrical object. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
A Testbed to Evaluate the FIWARE-Based IoT Platform in the Domain of Precision Agriculture
Sensors 2016, 16(11), 1979; https://doi.org/10.3390/s16111979
Received: 28 September 2016 / Revised: 11 November 2016 / Accepted: 18 November 2016 / Published: 23 November 2016
Cited by 9 | Viewed by 3032 | PDF Full-text (1290 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor networks (WSNs) represent one of the most promising technologies for precision farming. Over the next few years, a significant increase in the use of such systems on commercial farms is expected. WSNs present a number of problems, regarding scalability, interoperability, communications, [...] Read more.
Wireless sensor networks (WSNs) represent one of the most promising technologies for precision farming. Over the next few years, a significant increase in the use of such systems on commercial farms is expected. WSNs present a number of problems, regarding scalability, interoperability, communications, connectivity with databases and data processing. Different Internet of Things middleware is appearing to overcome these challenges. This paper checks whether one of these middleware, FIWARE, is suitable for the development of agricultural applications. To the authors’ knowledge, there are no works that show how to use FIWARE in precision agriculture and study its appropriateness, its scalability and its efficiency for this kind of applications. To do this, a testbed has been designed and implemented to simulate different deployments and load conditions. The testbed is a typical FIWARE application, complete, yet simple and comprehensible enough to show the main features and components of FIWARE, as well as the complexity of using this technology. Although the testbed has been deployed in a laboratory environment, its design is based on the analysis of an Internet of Things use case scenario in the domain of precision agriculture. Full article
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Open AccessArticle
Representation Method for Spectrally Overlapping Signals in Flow Cytometry Based on Fluorescence Pulse Time-Delay Estimation
Sensors 2016, 16(11), 1978; https://doi.org/10.3390/s16111978
Received: 25 October 2016 / Revised: 15 November 2016 / Accepted: 18 November 2016 / Published: 23 November 2016
Cited by 2 | Viewed by 2534 | PDF Full-text (11341 KB) | HTML Full-text | XML Full-text
Abstract
Flow cytometry is being applied more extensively because of the outstanding advantages of multicolor fluorescence analysis. However, the intensity measurement is susceptible to the nonlinearity of the detection method. Moreover, in multicolor analysis, it is impossible to discriminate between fluorophores that spectrally overlap; [...] Read more.
Flow cytometry is being applied more extensively because of the outstanding advantages of multicolor fluorescence analysis. However, the intensity measurement is susceptible to the nonlinearity of the detection method. Moreover, in multicolor analysis, it is impossible to discriminate between fluorophores that spectrally overlap; this influences the accuracy of the fluorescence pulse signal representation. Here, we focus on spectral overlap in two-color analysis, and assume that the fluorescence follows the single exponential decay model. We overcome these problems by analyzing the influence of the spectral overlap quantitatively, which enables us to propose a method of fluorescence pulse signal representation based on time-delay estimation (between fluorescence and scattered pulse signals). First, the time delays are estimated using a modified chirp Z-transform (MCZT) algorithm and a fine interpolation of the correlation peak (FICP) algorithm. Second, the influence of hardware is removed via calibration, in order to acquire the original fluorescence lifetimes. Finally, modulated signals containing phase shifts associated with these lifetimes are created artificially, using a digital signal processing method, and reference signals are introduced in order to eliminate the influence of spectral overlap. Time-delay estimation simulation and fluorescence signal representation experiments are conducted on fluorescently labeled cells. With taking the potentially overlap of autofluorescence as part of the observed fluorescence spectrum, rather than distinguishing the individual influence, the results show that the calculated lifetimes with spectral overlap can be rectified from 8.28 and 4.86 ns to 8.51 and 4.63 ns, respectively, using the comprehensive approach presented in this work. These values agree well with the lifetimes (8.48 and 4.67 ns) acquired for cells stained with single-color fluorochrome. Further, these results indicate that the influence of spectral overlap can be eliminated effectively. Moreover, modulation, mixing with reference signals, and low-pass filtering are performed with a digital signal processing method, thereby obviating the need for a high-speed analog device and complex circuit system. Finally, the flexibility of the comprehensive method presented in this work is significantly higher than that of existing methods. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle
Ultra-Low Power Optical Sensor for Xylophagous Insect Detection in Wood
Sensors 2016, 16(11), 1977; https://doi.org/10.3390/s16111977
Received: 22 September 2016 / Revised: 16 November 2016 / Accepted: 18 November 2016 / Published: 23 November 2016
Cited by 3 | Viewed by 1396 | PDF Full-text (11254 KB) | HTML Full-text | XML Full-text
Abstract
The early detection of pests is key for the maintenance of high-value masterpieces and historical buildings made of wood. In this work, we the present detailed design of an ultra-low power sensor device that permits the continuous monitoring of the presence of termites [...] Read more.
The early detection of pests is key for the maintenance of high-value masterpieces and historical buildings made of wood. In this work, we the present detailed design of an ultra-low power sensor device that permits the continuous monitoring of the presence of termites and other xylophagous insects. The operating principle of the sensor is based on the variations of reflected light induced by the presence of termites, and specific processing algorithms that deal with the behavior of the electronics and the natural ageing of components. With a typical CR2032 lithium battery, the device lasts more than nine years, and is ideal for incorporation in more complex monitoring systems where maintenance tasks should be minimized. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Improved Goldstein Interferogram Filter Based on Local Fringe Frequency Estimation
Sensors 2016, 16(11), 1976; https://doi.org/10.3390/s16111976
Received: 11 August 2016 / Revised: 12 November 2016 / Accepted: 14 November 2016 / Published: 23 November 2016
Cited by 4 | Viewed by 1715 | PDF Full-text (3264 KB) | HTML Full-text | XML Full-text
Abstract
The quality of an interferogram, which is limited by various phase noise, will greatly affect the further processes of InSAR, such as phase unwrapping. Interferometric SAR (InSAR) geophysical measurements’, such as height or displacement, phase filtering is therefore an essential step. In this [...] Read more.
The quality of an interferogram, which is limited by various phase noise, will greatly affect the further processes of InSAR, such as phase unwrapping. Interferometric SAR (InSAR) geophysical measurements’, such as height or displacement, phase filtering is therefore an essential step. In this work, an improved Goldstein interferogram filter is proposed to suppress the phase noise while preserving the fringe edges. First, the proposed adaptive filter step, performed before frequency estimation, is employed to improve the estimation accuracy. Subsequently, to preserve the fringe characteristics, the estimated fringe frequency in each fixed filtering patch is removed from the original noisy phase. Then, the residual phase is smoothed based on the modified Goldstein filter with its parameter alpha dependent on both the coherence map and the residual phase frequency. Finally, the filtered residual phase and the removed fringe frequency are combined to generate the filtered interferogram, with the loss of signal minimized while reducing the noise level. The effectiveness of the proposed method is verified by experimental results based on both simulated and real data. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Peroxynitrite Sensor Based on a Screen Printed Carbon Electrode Modified with a Poly(2,6-dihydroxynaphthalene) Film
Sensors 2016, 16(11), 1975; https://doi.org/10.3390/s16111975
Received: 24 October 2016 / Revised: 18 November 2016 / Accepted: 19 November 2016 / Published: 23 November 2016
Cited by 2 | Viewed by 1990 | PDF Full-text (5617 KB) | HTML Full-text | XML Full-text
Abstract
For the first time the electropolymerization of 2,6-dihydroxynaphthalene (2,6-DHN) on a screen printed carbon electrode (SPCE) was investigated and evaluated for peroxynitrite (PON) detection. Cyclic voltammetry was used to electrodeposit the poly(2,6-DHN) on the carbon electrode surface. The surface morphology and structure of [...] Read more.
For the first time the electropolymerization of 2,6-dihydroxynaphthalene (2,6-DHN) on a screen printed carbon electrode (SPCE) was investigated and evaluated for peroxynitrite (PON) detection. Cyclic voltammetry was used to electrodeposit the poly(2,6-DHN) on the carbon electrode surface. The surface morphology and structure of poly(2,6-DHN) film were investigated by SEM and FTIR analysis, and the electrochemical features by cyclic voltammetry. The poly(2,6-DHN)/SPCE sensor showed excellent electrocatalytic activity for PON oxidation in alkaline solutions at very low potentials (0–100 mV vs. Ag/AgCl pseudoreference). An amperometric FIA (flow injection analysis) system based on the developed sensor was optimized for PON measurements and a linear concentration range from 2 to 300 μM PON, with a LOD of 0.2 μM, was achieved. The optimized sensor inserted in the FIA system exhibited good sensitivity (4.12 nA·μM−1), selectivity, stability and intra-/inter-electrode reproducibility for PON determination. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle
Molecularly Imprinted Filtering Adsorbents for Odor Sensing
Sensors 2016, 16(11), 1974; https://doi.org/10.3390/s16111974
Received: 9 September 2016 / Revised: 8 November 2016 / Accepted: 16 November 2016 / Published: 23 November 2016
Cited by 5 | Viewed by 2003 | PDF Full-text (2723 KB) | HTML Full-text | XML Full-text
Abstract
Versatile odor sensors that can discriminate among huge numbers of environmental odorants are desired in many fields, including robotics, environmental monitoring, and food production. However, odor sensors comparable to an animal’s nose have not yet been developed. An animal’s olfactory system recognizes odor [...] Read more.
Versatile odor sensors that can discriminate among huge numbers of environmental odorants are desired in many fields, including robotics, environmental monitoring, and food production. However, odor sensors comparable to an animal’s nose have not yet been developed. An animal’s olfactory system recognizes odor clusters with specific molecular properties and uses this combinatorial information in odor discrimination. This suggests that measurement and clustering of odor molecular properties (e.g., polarity, size) using an artificial sensor is a promising approach to odor sensing. Here, adsorbents composed of composite materials with molecular recognition properties were developed for odor sensing. The selectivity of the sensor depends on the adsorbent materials, so specific polymeric materials with particular solubility parameters were chosen to adsorb odorants with various properties. The adsorption properties of the adsorbents could be modified by mixing adsorbent materials. Moreover, a novel molecularly imprinted filtering adsorbent (MIFA), composed of an adsorbent substrate covered with a molecularly imprinted polymer (MIP) layer, was developed to improve the odor molecular recognition ability. The combination of the adsorbent and MIP layer provided a higher specificity toward target molecules. The MIFA thus provides a useful technique for the design and control of adsorbents with adsorption properties specific to particular odor molecules. Full article
(This article belongs to the Special Issue Olfactory and Gustatory Sensors)
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Open AccessArticle
Design of Fresnel Lens-Type Multi-Trapping Acoustic Tweezers
Sensors 2016, 16(11), 1973; https://doi.org/10.3390/s16111973
Received: 16 September 2016 / Revised: 8 November 2016 / Accepted: 17 November 2016 / Published: 23 November 2016
Cited by 2 | Viewed by 2157 | PDF Full-text (3093 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, acoustic tweezers which use beam forming performed by a Fresnel zone plate are proposed. The performance has been demonstrated by finite element analysis, including the acoustic intensity, acoustic pressure, acoustic potential energy, gradient force, and particle distribution. The acoustic tweezers [...] Read more.
In this paper, acoustic tweezers which use beam forming performed by a Fresnel zone plate are proposed. The performance has been demonstrated by finite element analysis, including the acoustic intensity, acoustic pressure, acoustic potential energy, gradient force, and particle distribution. The acoustic tweezers use an ultrasound beam produced by a lead zirconate titanate (PZT) transducer operating at 2.4 MHz and 100 Vpeak-to-peak in a water medium. The design of the Fresnel lens (zone plate) is based on air reflection, acoustic impedance matching, and the Fresnel half-wave band (FHWB) theory. This acoustic Fresnel lens can produce gradient force and acoustic potential wells that allow the capture and manipulation of single particles or clusters of particles. Simulation results strongly indicate a good trapping ability, for particles under 150 µm in diameter, in the minimum energy location. This can be useful for cell or microorganism manipulation. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Identification-While-Scanning of a Multi-Aircraft Formation Based on Sparse Recovery for Narrowband Radar
Sensors 2016, 16(11), 1972; https://doi.org/10.3390/s16111972
Received: 18 July 2016 / Revised: 26 September 2016 / Accepted: 18 November 2016 / Published: 23 November 2016
Cited by 1 | Viewed by 1579 | PDF Full-text (2065 KB) | HTML Full-text | XML Full-text
Abstract
It is known that the identification performance of a multi-aircraft formation (MAF) of narrowband radar mainly depends on the time on target (TOT). To realize the identification task in one rotated scan with limited TOT, the paper proposes a novel identification-while-scanning (IWS) method [...] Read more.
It is known that the identification performance of a multi-aircraft formation (MAF) of narrowband radar mainly depends on the time on target (TOT). To realize the identification task in one rotated scan with limited TOT, the paper proposes a novel identification-while-scanning (IWS) method based on sparse recovery to maintain high rotating speed and super-resolution for MAF identification, simultaneously. First, a multiple chirp signal model is established for MAF in a single scan, where different aircraft may have different Doppler centers and Doppler rates. Second, based on the sparsity of MAF in the Doppler parameter space, a novel hierarchical basis pursuit (HBP) method is proposed to obtain satisfactory sparse recovery performance as well as high computational efficiency. Furthermore, the parameter estimation performance of the proposed IWS identification method is analyzed with respect to recovery condition, signal-to-noise ratio and TOT. It is shown that an MAF can be effectively identified via HBP with a TOT of only about one hundred microseconds for IWS applications. Finally, some numerical experiment results are provided to demonstrate the effectiveness of the proposed method based on both simulated and real measured data. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
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Open AccessArticle
Co-Creating the Cities of the Future
Sensors 2016, 16(11), 1971; https://doi.org/10.3390/s16111971
Received: 22 September 2016 / Revised: 3 November 2016 / Accepted: 10 November 2016 / Published: 23 November 2016
Cited by 12 | Viewed by 3095 | PDF Full-text (6661 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, the evolution of urban environments, jointly with the progress of the Information and Communication sector, have enabled the rapid adoption of new solutions that contribute to the growth in popularity of Smart Cities. Currently, the majority of the world population [...] Read more.
In recent years, the evolution of urban environments, jointly with the progress of the Information and Communication sector, have enabled the rapid adoption of new solutions that contribute to the growth in popularity of Smart Cities. Currently, the majority of the world population lives in cities encouraging different stakeholders within these innovative ecosystems to seek new solutions guaranteeing the sustainability and efficiency of such complex environments. In this work, it is discussed how the experimentation with IoT technologies and other data sources form the cities can be utilized to co-create in the OrganiCity project, where key actors like citizens, researchers and other stakeholders shape smart city services and applications in a collaborative fashion. Furthermore, a novel architecture is proposed that enables this organic growth of the future cities, facilitating the experimentation that tailors the adoption of new technologies and services for a better quality of life, as well as agile and dynamic mechanisms for managing cities. In this work, the different components and enablers of the OrganiCity platform are presented and discussed in detail and include, among others, a portal to manage the experiment life cycle, an Urban Data Observatory to explore data assets, and an annotations component to indicate quality of data, with a particular focus on the city-scale opportunistic data collection service operating as an alternative to traditional communications. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
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Open AccessArticle
A Laminar Flow-Based Microfluidic Tesla Pump via Lithography Enabled 3D Printing
Sensors 2016, 16(11), 1970; https://doi.org/10.3390/s16111970
Received: 20 September 2016 / Revised: 12 November 2016 / Accepted: 18 November 2016 / Published: 23 November 2016
Cited by 5 | Viewed by 3377 | PDF Full-text (2389 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Tesla turbine and its applications in power generation and fluid flow were demonstrated by Nicholas Tesla in 1913. However, its real-world implementations were limited by the difficulty to maintain laminar flow between rotor disks, transient efficiencies during rotor acceleration, and the lack of [...] Read more.
Tesla turbine and its applications in power generation and fluid flow were demonstrated by Nicholas Tesla in 1913. However, its real-world implementations were limited by the difficulty to maintain laminar flow between rotor disks, transient efficiencies during rotor acceleration, and the lack of other applications that fully utilize the continuous flow outputs. All of the aforementioned limits of Tesla turbines can be addressed by scaling to the microfluidic flow regime. Demonstrated here is a microscale Tesla pump designed and fabricated using a Digital Light Processing (DLP) based 3D printer with 43 µm lateral and 30 µm thickness resolutions. The miniaturized pump is characterized by low Reynolds number of 1000 and a flow rate of up to 12.6 mL/min at 1200 rpm, unloaded. It is capable of driving a mixer network to generate microfluidic gradient. The continuous, laminar flow from Tesla turbines is well-suited to the needs of flow-sensitive microfluidics, where the integrated pump will enable numerous compact lab-on-a-chip applications. Full article
(This article belongs to the Special Issue Microfluidics-Based Microsystem Integration Research)
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Open AccessArticle
Three-Dimensional Object Recognition and Registration for Robotic Grasping Systems Using a Modified Viewpoint Feature Histogram
Sensors 2016, 16(11), 1969; https://doi.org/10.3390/s16111969
Received: 3 June 2016 / Revised: 12 November 2016 / Accepted: 14 November 2016 / Published: 23 November 2016
Cited by 8 | Viewed by 2607 | PDF Full-text (7101 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a novel 3D feature descriptor for object recognition and to identify poses when there are six-degrees-of-freedom for mobile manipulation and grasping applications. Firstly, a Microsoft Kinect sensor is used to capture 3D point cloud data. A viewpoint feature histogram (VFH) [...] Read more.
This paper presents a novel 3D feature descriptor for object recognition and to identify poses when there are six-degrees-of-freedom for mobile manipulation and grasping applications. Firstly, a Microsoft Kinect sensor is used to capture 3D point cloud data. A viewpoint feature histogram (VFH) descriptor for the 3D point cloud data then encodes the geometry and viewpoint, so an object can be simultaneously recognized and registered in a stable pose and the information is stored in a database. The VFH is robust to a large degree of surface noise and missing depth information so it is reliable for stereo data. However, the pose estimation for an object fails when the object is placed symmetrically to the viewpoint. To overcome this problem, this study proposes a modified viewpoint feature histogram (MVFH) descriptor that consists of two parts: a surface shape component that comprises an extended fast point feature histogram and an extended viewpoint direction component. The MVFH descriptor characterizes an object’s pose and enhances the system’s ability to identify objects with mirrored poses. Finally, the refined pose is further estimated using an iterative closest point when the object has been recognized and the pose roughly estimated by the MVFH descriptor and it has been registered on a database. The estimation results demonstrate that the MVFH feature descriptor allows more accurate pose estimation. The experiments also show that the proposed method can be applied in vision-guided robotic grasping systems. Full article
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Open AccessReview
State of the Art, Trends and Future of Bluetooth Low Energy, Near Field Communication and Visible Light Communication in the Development of Smart Cities
Sensors 2016, 16(11), 1968; https://doi.org/10.3390/s16111968
Received: 6 August 2016 / Revised: 10 November 2016 / Accepted: 14 November 2016 / Published: 23 November 2016
Cited by 13 | Viewed by 2917 | PDF Full-text (1438 KB) | HTML Full-text | XML Full-text
Abstract
The current social impact of new technologies has produced major changes in all areas of society, creating the concept of a smart city supported by an electronic infrastructure, telecommunications and information technology. This paper presents a review of Bluetooth Low Energy (BLE), Near [...] Read more.
The current social impact of new technologies has produced major changes in all areas of society, creating the concept of a smart city supported by an electronic infrastructure, telecommunications and information technology. This paper presents a review of Bluetooth Low Energy (BLE), Near Field Communication (NFC) and Visible Light Communication (VLC) and their use and influence within different areas of the development of the smart city. The document also presents a review of Big Data Solutions for the management of information and the extraction of knowledge in an environment where things are connected by an “Internet of Things” (IoT) network. Lastly, we present how these technologies can be combined together to benefit the development of the smart city. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
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Open AccessArticle
Effects of Sampling Conditions and Environmental Factors on Fecal Volatile Organic Compound Analysis by an Electronic Nose Device
Sensors 2016, 16(11), 1967; https://doi.org/10.3390/s16111967
Received: 6 August 2016 / Revised: 27 October 2016 / Accepted: 17 November 2016 / Published: 23 November 2016
Cited by 14 | Viewed by 1991 | PDF Full-text (1185 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Prior to implementation of volatile organic compound (VOC) analysis in clinical practice, substantial challenges, including methodological, biological and analytical difficulties are faced. The aim of this study was to evaluate the influence of several sampling conditions and environmental factors on fecal VOC profiles, [...] Read more.
Prior to implementation of volatile organic compound (VOC) analysis in clinical practice, substantial challenges, including methodological, biological and analytical difficulties are faced. The aim of this study was to evaluate the influence of several sampling conditions and environmental factors on fecal VOC profiles, analyzed by an electronic nose (eNose). Effects of fecal sample mass, water content, duration of storage at room temperature, fecal sample temperature, number of freeze–thaw cycles and effect of sampling method (rectal swabs vs. fecal samples) on VOC profiles were assessed by analysis of totally 725 fecal samples by means of an eNose (Cyranose320®). Furthermore, fecal VOC profiles of totally 1285 fecal samples from 71 infants born at three different hospitals were compared to assess the influence of center of origin on VOC outcome. We observed that all analyzed variables significantly influenced fecal VOC composition. It was feasible to capture a VOC profile using rectal swabs, although this differed significantly from fecal VOC profiles of similar subjects. In addition, 1285 fecal VOC-profiles could significantly be discriminated based on center of birth. In conclusion, standardization of methodology is necessary before fecal VOC analysis can live up to its potential as diagnostic tool in clinical practice. Full article
(This article belongs to the Special Issue Gas Sensors for Health Care and Medical Applications)
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Open AccessArticle
A Real-Time Kinect Signature-Based Patient Home Monitoring System
Sensors 2016, 16(11), 1965; https://doi.org/10.3390/s16111965
Received: 9 August 2016 / Revised: 10 November 2016 / Accepted: 12 November 2016 / Published: 23 November 2016
Cited by 15 | Viewed by 2532 | PDF Full-text (5341 KB) | HTML Full-text | XML Full-text
Abstract
Assessment of body kinematics during performance of daily life activities at home plays a significant role in medical condition monitoring of elderly people and patients with neurological disorders. The affordable and non-wearable Microsoft Kinect (“Kinect”) system has been recently used to estimate human [...] Read more.
Assessment of body kinematics during performance of daily life activities at home plays a significant role in medical condition monitoring of elderly people and patients with neurological disorders. The affordable and non-wearable Microsoft Kinect (“Kinect”) system has been recently used to estimate human subject kinematic features. However, the Kinect suffers from a limited range and angular coverage, distortion in skeleton joints’ estimations, and erroneous multiplexing of different subjects’ estimations to one. This study addresses these limitations by incorporating a set of features that create a unique “Kinect Signature”. The Kinect Signature enables identification of different subjects in the scene, automatically assign the kinematics feature estimations only to the subject of interest, and provide information about the quality of the Kinect-based estimations. The methods were verified by a set of experiments, which utilize real-time scenarios commonly used to assess motor functions in elderly subjects and in subjects with neurological disorders. The experiment results indicate that the skeleton based Kinect Signature features can be used to identify different subjects in high accuracy. We demonstrate how these capabilities can be used to assign the Kinect estimations to the Subject of Interest, and exclude low quality tracking features. The results of this work can help in establishing reliable kinematic features, which can assist in future to obtain objective scores for medical analysis of patient condition at home while not restricted to perform daily life activities. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle
Multi-Target Tracking Using an Improved Gaussian Mixture CPHD Filter
Sensors 2016, 16(11), 1964; https://doi.org/10.3390/s16111964
Received: 21 August 2016 / Revised: 29 October 2016 / Accepted: 17 November 2016 / Published: 23 November 2016
Cited by 6 | Viewed by 1282 | PDF Full-text (1595 KB) | HTML Full-text | XML Full-text
Abstract
The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the full multi-target Bayesian filter for tracking multiple targets. However, although the joint propagation of the posterior intensity and cardinality distribution in its recursion allows more reliable estimates of the target [...] Read more.
The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the full multi-target Bayesian filter for tracking multiple targets. However, although the joint propagation of the posterior intensity and cardinality distribution in its recursion allows more reliable estimates of the target number than the PHD filter, the CPHD filter suffers from the spooky effect where there exists arbitrary PHD mass shifting in the presence of missed detections. To address this issue in the Gaussian mixture (GM) implementation of the CPHD filter, this paper presents an improved GM-CPHD filter, which incorporates a weight redistribution scheme into the filtering process to modify the updated weights of the Gaussian components when missed detections occur. In addition, an efficient gating strategy that can adaptively adjust the gate sizes according to the number of missed detections of each Gaussian component is also presented to further improve the computational efficiency of the proposed filter. Simulation results demonstrate that the proposed method offers favorable performance in terms of both estimation accuracy and robustness to clutter and detection uncertainty over the existing methods. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design
Sensors 2016, 16(11), 1963; https://doi.org/10.3390/s16111963
Received: 24 August 2016 / Revised: 11 November 2016 / Accepted: 15 November 2016 / Published: 23 November 2016
Cited by 3 | Viewed by 1513 | PDF Full-text (2632 KB) | HTML Full-text | XML Full-text
Abstract
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms [...] Read more.
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Automated Urban Travel Interpretation: A Bottom-up Approach for Trajectory Segmentation
Sensors 2016, 16(11), 1962; https://doi.org/10.3390/s16111962
Received: 1 October 2016 / Revised: 16 November 2016 / Accepted: 17 November 2016 / Published: 23 November 2016
Cited by 7 | Viewed by 2203 | PDF Full-text (1455 KB) | HTML Full-text | XML Full-text
Abstract
Understanding travel behavior is critical for an effective urban planning as well as for enabling various context-aware service provisions to support mobility as a service (MaaS). Both applications rely on the sensor traces generated by travellers’ smartphones. These traces can be used to [...] Read more.
Understanding travel behavior is critical for an effective urban planning as well as for enabling various context-aware service provisions to support mobility as a service (MaaS). Both applications rely on the sensor traces generated by travellers’ smartphones. These traces can be used to interpret travel modes, both for generating automated travel diaries as well as for real-time travel mode detection. Current approaches segment a trajectory by certain criteria, e.g., drop in speed. However, these criteria are heuristic, and, thus, existing approaches are subjective and involve significant vagueness and uncertainty in activity transitions in space and time. Also, segmentation approaches are not suited for real time interpretation of open-ended segments, and cannot cope with the frequent gaps in the location traces. In order to address all these challenges a novel, state based bottom-up approach is proposed. This approach assumes a fixed atomic segment of a homogeneous state, instead of an event-based segment, and a progressive iteration until a new state is found. The research investigates how an atomic state-based approach can be developed in such a way that can work in real time, near-real time and offline mode and in different environmental conditions with their varying quality of sensor traces. The results show the proposed bottom-up model outperforms the existing event-based segmentation models in terms of adaptivity, flexibility, accuracy and richness in information delivery pertinent to automated travel behavior interpretation. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
An Improved Mobility-Based Control Protocol for Tolerating Clone Failures in Wireless Sensor Networks
Sensors 2016, 16(11), 1955; https://doi.org/10.3390/s16111955
Received: 16 August 2016 / Revised: 4 November 2016 / Accepted: 14 November 2016 / Published: 23 November 2016
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Abstract
Nowadays, with the ubiquitous presence of the Internet of Things industry, the application of emerging sensor networks has become a focus of public attention. Unattended sensor nodes can be comprised and cloned to destroy the network topology. This paper proposes a novel distributed [...] Read more.
Nowadays, with the ubiquitous presence of the Internet of Things industry, the application of emerging sensor networks has become a focus of public attention. Unattended sensor nodes can be comprised and cloned to destroy the network topology. This paper proposes a novel distributed protocol and management technique for the detection of mobile replicas to tolerate node failures. In our scheme, sensors’ location claims are forwarded to obtain samples only when the corresponding witnesses meet. Meanwhile, sequential tests of statistical hypotheses are applied to further detect the cloned node by witnesses. The combination of randomized detection based on encountering and sequential tests drastically reduces the routing overhead and false positive/negative rate for detection. Theoretical analysis and simulation results show the detection efficiency and reasonable overhead of the proposed method. Full article
(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)
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Open AccessArticle
Optical Aptamer Probes of Fluorescent Imaging to Rapid Monitoring of Circulating Tumor Cell
Sensors 2016, 16(11), 1909; https://doi.org/10.3390/s16111909
Received: 5 August 2016 / Revised: 2 November 2016 / Accepted: 2 November 2016 / Published: 23 November 2016
Cited by 7 | Viewed by 2202 | PDF Full-text (2729 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Fluorescence detecting of exogenous EpCAM (epithelial cell adhesion molecule) or muc1 (mucin1) expression correlated to cancer metastasis using nanoparticles provides pivotal information on CTC (circulating tumor cell) occurrence in a noninvasive tool. In this study, we study a new skill to detect extracellular [...] Read more.
Fluorescence detecting of exogenous EpCAM (epithelial cell adhesion molecule) or muc1 (mucin1) expression correlated to cancer metastasis using nanoparticles provides pivotal information on CTC (circulating tumor cell) occurrence in a noninvasive tool. In this study, we study a new skill to detect extracellular EpCAM/muc1 using quantum dot-based aptamer beacon (QD-EpCAM/muc1 ALB (aptamer linker beacon). The QD-EpCAM/muc1 ALB was designed using QDs (quantum dots) and probe. The EpCAM/muc1-targeting aptamer contains a Ep-CAM/muc1 binding sequence and BHQ1 (black hole quencher 1) or BHQ2 (black hole quencher2). In the absence of target EpCAM/muc1, the QD-EpCAM/muc1 ALB forms a partial duplex loop-like aptamer beacon and remained in quenched state because the BHQ1/2 quenches the fluorescence signal-on of the QD-EpCAM/muc1 ALB. The binding of EpCAM/muc1 of CTC to the EpCAM/muc1 binding aptamer sequence of the EpCAM/muc1-targeting oligonucleotide triggered the dissociation of the BHQ1/2 quencher and subsequent signal-on of a green/red fluorescence signal. Furthermore, acute inflammation was stimulated by trigger such as caerulein in vivo, which resulted in increased fluorescent signal of the cy5.5-EpCAM/muc1 ALB during cancer metastasis due to exogenous expression of EpCAM/muc1 in Panc02-implanted mouse model. Full article
(This article belongs to the Special Issue Nanobiosensing for Sensors)
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Open AccessArticle
Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors
Sensors 2016, 16(11), 1961; https://doi.org/10.3390/s16111961
Received: 8 September 2016 / Revised: 3 November 2016 / Accepted: 17 November 2016 / Published: 22 November 2016
Cited by 10 | Viewed by 4204 | PDF Full-text (2815 KB) | HTML Full-text | XML Full-text
Abstract
A quanta image sensor (QIS) is a class of single-photon imaging devices that measure light intensity using oversampled binary observations. Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal [...] Read more.
A quanta image sensor (QIS) is a class of single-photon imaging devices that measure light intensity using oversampled binary observations. Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal of image reconstruction is to recover the underlying image from these bits. In this paper, we present a non-iterative image reconstruction algorithm for QIS. Unlike existing reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising algorithm. By skipping the usual optimization procedure, we achieve orders of magnitude improvement in speed and even better image reconstruction quality. We validate the new algorithm on synthetic datasets, as well as real videos collected by one-bit single-photon avalanche diode (SPAD) cameras. Full article
(This article belongs to the Special Issue Photon-Counting Image Sensors) Printed Edition available
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Open AccessArticle
IEEE 802.11ah: A Technology to Face the IoT Challenge
Sensors 2016, 16(11), 1960; https://doi.org/10.3390/s16111960
Received: 8 October 2016 / Revised: 11 November 2016 / Accepted: 19 November 2016 / Published: 22 November 2016
Cited by 20 | Viewed by 3412 | PDF Full-text (1095 KB) | HTML Full-text | XML Full-text
Abstract
Since the conception of the Internet of things (IoT), a large number of promising applications and technologies have been developed, which will change different aspects in our daily life. This paper explores the key characteristics of the forthcoming IEEE 802.11ah specification. This future [...] Read more.
Since the conception of the Internet of things (IoT), a large number of promising applications and technologies have been developed, which will change different aspects in our daily life. This paper explores the key characteristics of the forthcoming IEEE 802.11ah specification. This future IEEE 802.11 standard aims to amend the IEEE 802.11 legacy specification to support IoT requirements. We present a thorough evaluation of the foregoing amendment in comparison to the most notable IEEE 802.11 standards. In addition, we expose the capabilities of future IEEE 802.11ah in supporting different IoT applications. Also, we provide a brief overview of the technology contenders that are competing to cover the IoT communications framework. Numerical results are presented showing how the future IEEE 802.11ah specification offers the features required by IoT communications, thus putting forward IEEE 802.11ah as a technology to cater the needs of the Internet of Things paradigm. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
Evaluation of Hyaluronic Acid Dilutions at Different Concentrations Using a Quartz Crystal Resonator (QCR) for the Potential Diagnosis of Arthritic Diseases
Sensors 2016, 16(11), 1959; https://doi.org/10.3390/s16111959
Received: 10 August 2016 / Revised: 30 September 2016 / Accepted: 20 October 2016 / Published: 22 November 2016
Cited by 2 | Viewed by 1788 | PDF Full-text (3495 KB) | HTML Full-text | XML Full-text
Abstract
The main objective of this article is to demonstrate through experimental means the capacity of the quartz crystal resonator (QCR) to characterize biological samples of aqueous dilutions of hyaluronic acid according to their viscosity and how this capacity may be useful in the [...] Read more.
The main objective of this article is to demonstrate through experimental means the capacity of the quartz crystal resonator (QCR) to characterize biological samples of aqueous dilutions of hyaluronic acid according to their viscosity and how this capacity may be useful in the potential diagnosis of arthritic diseases. The synovial fluid is viscous due to the presence of hyaluronic acid, synthesized by synovial lining cells (type B), and secreted into the synovial fluid thus making the fluid viscous. In consequence, aqueous dilutions of hyaluronic acid may be used as samples to emulate the synovial fluid. Due to the viscoelastic and pseudo-plastic behavior of hyaluronic acid, it is necessary to use the Rouse model in order to obtain viscosity values comparable with viscometer measures. A Fungilab viscometer (rheometer) was used to obtain reference measures of the viscosity in each sample in order to compare them with the QCR prototype measures. Full article
(This article belongs to the Special Issue Point-of-Care Biosensors)
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Open AccessArticle
Queuing Time Prediction Using WiFi Positioning Data in an Indoor Scenario
Sensors 2016, 16(11), 1958; https://doi.org/10.3390/s16111958
Received: 19 July 2016 / Revised: 27 October 2016 / Accepted: 16 November 2016 / Published: 22 November 2016
Cited by 2 | Viewed by 1726 | PDF Full-text (3562 KB) | HTML Full-text | XML Full-text
Abstract
Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This [...] Read more.
Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This paper proposes a novel method to estimate and predict queuing time in indoor environments based on WiFi positioning data. First, we use a series of parameters to identify the trajectories that can be used as representatives of queuing time. Next, we divide the day into equal time slices and estimate individuals’ average queuing time during specific time slices. Finally, we build a nonstandard autoregressive (NAR) model trained using the previous day’s WiFi estimation results and actual queuing time to predict the queuing time in the upcoming time slice. A case study comparing two other time series analysis models shows that the NAR model has better precision. Random topological errors caused by the drift phenomenon of WiFi positioning technology (locations determined by a WiFi positioning system may drift accidently) and systematic topological errors caused by the positioning system are the main factors that affect the estimation precision. Therefore, we optimize the deployment strategy during the positioning system deployment phase and propose a drift ratio parameter pertaining to the trajectory screening phase to alleviate the impact of topological errors and improve estimates. The WiFi positioning data from an eight-day case study conducted at the T3-C entrance of Beijing Capital International Airport show that the mean absolute estimation error is 147 s, which is approximately 26.92% of the actual queuing time. For predictions using the NAR model, the proportion is approximately 27.49%. The theoretical predictions and the empirical case study indicate that the NAR model is an effective method to estimate and predict queuing time in indoor public areas. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Bamboo Classification Using WorldView-2 Imagery of Giant Panda Habitat in a Large Shaded Area in Wolong, Sichuan Province, China
Sensors 2016, 16(11), 1957; https://doi.org/10.3390/s16111957
Received: 3 October 2016 / Revised: 14 November 2016 / Accepted: 16 November 2016 / Published: 22 November 2016
Cited by 4 | Viewed by 2158 | PDF Full-text (10902 KB) | HTML Full-text | XML Full-text
Abstract
This study explores the ability of WorldView-2 (WV-2) imagery for bamboo mapping in a mountainous region in Sichuan Province, China. A large area of this place is covered by shadows in the image, and only a few sampled points derived were useful. In [...] Read more.
This study explores the ability of WorldView-2 (WV-2) imagery for bamboo mapping in a mountainous region in Sichuan Province, China. A large area of this place is covered by shadows in the image, and only a few sampled points derived were useful. In order to identify bamboos based on sparse training data, the sample size was expanded according to the reflectance of multispectral bands selected using the principal component analysis (PCA). Then, class separability based on the training data was calculated using a feature space optimization method to select the features for classification. Four regular object-based classification methods were applied based on both sets of training data. The results show that the k-nearest neighbor (k-NN) method produced the greatest accuracy. A geostatistically-weighted k-NN classifier, accounting for the spatial correlation between classes, was then applied to further increase the accuracy. It achieved 82.65% and 93.10% of the producer’s and user’s accuracies respectively for the bamboo class. The canopy densities were estimated to explain the result. This study demonstrates that the WV-2 image can be used to identify small patches of understory bamboos given limited known samples, and the resulting bamboo distribution facilitates the assessments of the habitats of giant pandas. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Probabilistic Model Updating for Sizing of Hole-Edge Crack Using Fiber Bragg Grating Sensors and the High-Order Extended Finite Element Method
Sensors 2016, 16(11), 1956; https://doi.org/10.3390/s16111956
Received: 8 October 2016 / Revised: 16 November 2016 / Accepted: 17 November 2016 / Published: 21 November 2016
Cited by 11 | Viewed by 2028 | PDF Full-text (5694 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a novel framework for probabilistic crack size quantification using fiber Bragg grating (FBG) sensors. The key idea is to use a high-order extended finite element method (XFEM) together with a transfer (T)-matrix method to analyze the reflection intensity spectra of [...] Read more.
This paper presents a novel framework for probabilistic crack size quantification using fiber Bragg grating (FBG) sensors. The key idea is to use a high-order extended finite element method (XFEM) together with a transfer (T)-matrix method to analyze the reflection intensity spectra of FBG sensors, for various crack sizes. Compared with the standard FEM, the XFEM offers two superior capabilities: (i) a more accurate representation of fields in the vicinity of the crack tip singularity and (ii) alleviation of the need for costly re-meshing as the crack size changes. Apart from the classical four-term asymptotic enrichment functions in XFEM, we also propose to incorporate higher-order functions, aiming to further improve the accuracy of strain fields upon which the reflection intensity spectra are based. The wavelength of the reflection intensity spectra is extracted as a damage sensitive quantity, and a baseline model with five parameters is established to quantify its correlation with the crack size. In order to test the feasibility of the predictive model, we design FBG sensor-based experiments to detect fatigue crack growth in structures. Furthermore, a Bayesian method is proposed to update the parameters of the baseline model using only a few available experimental data points (wavelength versus crack size) measured by one of the FBG sensors and an optical microscope, respectively. Given the remaining data points of wavelengths, even measured by FBG sensors at different positions, the updated model is shown to give crack size predictions that match well with the experimental observations. Full article
(This article belongs to the Special Issue Optical Fiber Sensors 2016)
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Open AccessArticle
Expanding the Detection of Traversable Area with RealSense for the Visually Impaired
Sensors 2016, 16(11), 1954; https://doi.org/10.3390/s16111954
Received: 13 September 2016 / Revised: 4 November 2016 / Accepted: 8 November 2016 / Published: 21 November 2016
Cited by 25 | Viewed by 2633 | PDF Full-text (18233 KB) | HTML Full-text | XML Full-text
Abstract
The introduction of RGB-Depth (RGB-D) sensors into the visually impaired people (VIP)-assisting area has stirred great interest of many researchers. However, the detection range of RGB-D sensors is limited by narrow depth field angle and sparse depth map in the distance, which hampers [...] Read more.
The introduction of RGB-Depth (RGB-D) sensors into the visually impaired people (VIP)-assisting area has stirred great interest of many researchers. However, the detection range of RGB-D sensors is limited by narrow depth field angle and sparse depth map in the distance, which hampers broader and longer traversability awareness. This paper proposes an effective approach to expand the detection of traversable area based on a RGB-D sensor, the Intel RealSense R200, which is compatible with both indoor and outdoor environments. The depth image of RealSense is enhanced with IR image large-scale matching and RGB image-guided filtering. Traversable area is obtained with RANdom SAmple Consensus (RANSAC) segmentation and surface normal vector estimation, preliminarily. A seeded growing region algorithm, combining the depth image and RGB image, enlarges the preliminary traversable area greatly. This is critical not only for avoiding close obstacles, but also for allowing superior path planning on navigation. The proposed approach has been tested on a score of indoor and outdoor scenarios. Moreover, the approach has been integrated into an assistance system, which consists of a wearable prototype and an audio interface. Furthermore, the presented approach has been proved to be useful and reliable by a field test with eight visually impaired volunteers. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies) Printed Edition available
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Open AccessArticle
Smart Toys Designed for Detecting Developmental Delays
Sensors 2016, 16(11), 1953; https://doi.org/10.3390/s16111953
Received: 7 September 2016 / Revised: 2 November 2016 / Accepted: 16 November 2016 / Published: 20 November 2016
Cited by 4 | Viewed by 2585 | PDF Full-text (7492 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage [...] Read more.
In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle
Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis
Sensors 2016, 16(11), 1952; https://doi.org/10.3390/s16111952
Received: 31 August 2016 / Revised: 9 November 2016 / Accepted: 10 November 2016 / Published: 20 November 2016
Cited by 7 | Viewed by 2602 | PDF Full-text (22651 KB) | HTML Full-text | XML Full-text
Abstract
In recent decades, terrain modelling and reconstruction techniques have increased research interest in precise short and long distance autonomous navigation, localisation and mapping within field robotics. One of the most challenging applications is in relation to autonomous planetary exploration using mobile robots. Rovers [...] Read more.
In recent decades, terrain modelling and reconstruction techniques have increased research interest in precise short and long distance autonomous navigation, localisation and mapping within field robotics. One of the most challenging applications is in relation to autonomous planetary exploration using mobile robots. Rovers deployed to explore extraterrestrial surfaces are required to perceive and model the environment with little or no intervention from the ground station. Up to date, stereopsis represents the state-of-the art method and can achieve short-distance planetary surface modelling. However, future space missions will require scene reconstruction at greater distance, fidelity and feature complexity, potentially using other sensors like Light Detection And Ranging (LIDAR). LIDAR has been extensively exploited for target detection, identification, and depth estimation in terrestrial robotics, but is still under development to become a viable technology for space robotics. This paper will first review current methods for scene reconstruction and terrain modelling using cameras in planetary robotics and LIDARs in terrestrial robotics; then we will propose camera-LIDAR fusion as a feasible technique to overcome the limitations of either of these individual sensors for planetary exploration. A comprehensive analysis will be presented to demonstrate the advantages of camera-LIDAR fusion in terms of range, fidelity, accuracy and computation. Full article
(This article belongs to the Special Issue Vision-Based Sensors in Field Robotics)
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