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Sensors, Volume 17, Issue 4 (April 2017) – 280 articles

Cover Story (view full-size image): Potential use of real-time GNSS-RF mobile geofences to define occupational safety hazard zones around ground workers and equipment on active logging operations. A field experiment and simulation were used to evaluate the factors affecting signal alert delays for mobile geofences. Results show that corrections are needed in order to account for error in the timing of alerts associated with path intersection angle and other factors. To read the full article, click here: View this paper.
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810 KiB  
Article
Direction of Arrival Estimation for MIMO Radar via Unitary Nuclear Norm Minimization
by Xianpeng Wang, Mengxing Huang, Xiaoqin Wu and Guoan Bi
Sensors 2017, 17(4), 939; https://doi.org/10.3390/s17040939 - 24 Apr 2017
Cited by 14 | Viewed by 6000
Abstract
In this paper, we consider the direction of arrival (DOA) estimation issue of noncircular (NC) source in multiple-input multiple-output (MIMO) radar and propose a novel unitary nuclear norm minimization (UNNM) algorithm. In the proposed method, the noncircular properties of signals are used to [...] Read more.
In this paper, we consider the direction of arrival (DOA) estimation issue of noncircular (NC) source in multiple-input multiple-output (MIMO) radar and propose a novel unitary nuclear norm minimization (UNNM) algorithm. In the proposed method, the noncircular properties of signals are used to double the virtual array aperture, and the real-valued data are obtained by utilizing unitary transformation. Then a real-valued block sparse model is established based on a novel over-complete dictionary, and a UNNM algorithm is formulated for recovering the block-sparse matrix. In addition, the real-valued NC-MUSIC spectrum is used to design a weight matrix for reweighting the nuclear norm minimization to achieve the enhanced sparsity of solutions. Finally, the DOA is estimated by searching the non-zero blocks of the recovered matrix. Because of using the noncircular properties of signals to extend the virtual array aperture and an additional real structure to suppress the noise, the proposed method provides better performance compared with the conventional sparse recovery based algorithms. Furthermore, the proposed method can handle the case of underdetermined DOA estimation. Simulation results show the effectiveness and advantages of the proposed method. Full article
(This article belongs to the Special Issue Recent Advances in Array Signal Processing and Its Applications in IoT Security)
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5466 KiB  
Review
Progress in the Correlative Atomic Force Microscopy and Optical Microscopy
by Lulu Zhou, Mingjun Cai, Ti Tong and Hongda Wang
Sensors 2017, 17(4), 938; https://doi.org/10.3390/s17040938 - 24 Apr 2017
Cited by 41 | Viewed by 10607
Abstract
Atomic force microscopy (AFM) has evolved from the originally morphological imaging technique to a powerful and multifunctional technique for manipulating and detecting the interactions between molecules at nanometer resolution. However, AFM cannot provide the precise information of synchronized molecular groups and has many [...] Read more.
Atomic force microscopy (AFM) has evolved from the originally morphological imaging technique to a powerful and multifunctional technique for manipulating and detecting the interactions between molecules at nanometer resolution. However, AFM cannot provide the precise information of synchronized molecular groups and has many shortcomings in the aspects of determining the mechanism of the interactions and the elaborate structure due to the limitations of the technology, itself, such as non-specificity and low imaging speed. To overcome the technical limitations, it is necessary to combine AFM with other complementary techniques, such as fluorescence microscopy. The combination of several complementary techniques in one instrument has increasingly become a vital approach to investigate the details of the interactions among molecules and molecular dynamics. In this review, we reported the principles of AFM and optical microscopy, such as confocal microscopy and single-molecule localization microscopy, and focused on the development and use of correlative AFM and optical microscopy. Full article
(This article belongs to the Special Issue Single-Molecule Sensing)
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8812 KiB  
Article
Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing
by Chengbing He, Lianyou Jing, Rui Xi, Qinyuan Li and Qunfei Zhang
Sensors 2017, 17(4), 937; https://doi.org/10.3390/s17040937 - 24 Apr 2017
Cited by 12 | Viewed by 4961
Abstract
Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial [...] Read more.
Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial and temporal focusing. In this paper, we present a novel receiver structure to combine passive time reversal with a low-order multichannel adaptive decision feedback equalizer (TR-MC-DFE) to improve the performance of the conventional TR-DFE. First, the proposed method divides the whole received array into several subarrays. Second, we conduct passive time reversal processing in each subarray. Third, the multiple subarray outputs are equalized with a low-order multichannel DFE. We also investigated different channel estimation methods, including least squares (LS), orthogonal matching pursuit (OMP), and improved proportionate normalized least mean squares (IPNLMS). The bit error rate (BER) and output signal-to-noise ratio (SNR) performances of the receiver algorithms are evaluated using simulation and real data collected in a lake experiment. The source-receiver range is 7.4 km, and the data rate with quadrature phase shift keying (QPSK) signal is 8 kbits/s. The uncoded BER of the single input multiple output (SIMO) systems varies between 1 × 10 − 1 and 2 × 10 − 2 for the conventional TR-DFE, and between 1 × 10 − 2 and 1 × 10 − 3 for the proposed TR-MC-DFE when eight hydrophones are utilized. Compared to conventional TR-DFE, the average output SNR of the experimental data is enhanced by 3 dB. Full article
(This article belongs to the Section Sensor Networks)
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3372 KiB  
Article
Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair
by Young-Joo Lee, Robin E. Kim, Wonho Suh and Kiwon Park
Sensors 2017, 17(4), 936; https://doi.org/10.3390/s17040936 - 24 Apr 2017
Cited by 18 | Viewed by 5184
Abstract
Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target [...] Read more.
Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed. Full article
(This article belongs to the Section Physical Sensors)
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2701 KiB  
Article
Improved Line Tracing Methods for Removal of Bad Streaks Noise in CCD Line Array Image—A Case Study with GF-1 Images
by Bo Wang, Jianwei Bao, Shikui Wang, Houjun Wang and Qinghong Sheng
Sensors 2017, 17(4), 935; https://doi.org/10.3390/s17040935 - 24 Apr 2017
Cited by 5 | Viewed by 4305
Abstract
Remote sensing images could provide us with tremendous quantities of large-scale information. Noise artifacts (stripes), however, made the images inappropriate for vitalization and batch process. An effective restoration method would make images ready for further analysis. In this paper, a new method is [...] Read more.
Remote sensing images could provide us with tremendous quantities of large-scale information. Noise artifacts (stripes), however, made the images inappropriate for vitalization and batch process. An effective restoration method would make images ready for further analysis. In this paper, a new method is proposed to correct the stripes and bad abnormal pixels in charge-coupled device (CCD) linear array images. The method involved a line tracing method, limiting the location of noise to a rectangular region, and corrected abnormal pixels with the Lagrange polynomial algorithm. The proposed detection and restoration method were applied to Gaofen-1 satellite (GF-1) images, and the performance of this method was evaluated by omission ratio and false detection ratio, which reached 0.6% and 0%, respectively. This method saved 55.9% of the time, compared with traditional method. Full article
(This article belongs to the Section Physical Sensors)
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3749 KiB  
Article
Convergent Validity of a Wearable Sensor System for Measuring Sub-Task Performance during the Timed Up-and-Go Test
by James Beyea, Chris A. McGibbon, Andrew Sexton, Jeremy Noble and Colleen O’Connell
Sensors 2017, 17(4), 934; https://doi.org/10.3390/s17040934 - 23 Apr 2017
Cited by 57 | Viewed by 7025
Abstract
Background: The timed-up-and-go test (TUG) is one of the most commonly used tests of physical function in clinical practice and for research outcomes. Inertial sensors have been used to parse the TUG test into its composite phases (rising, walking, turning, etc.), but have [...] Read more.
Background: The timed-up-and-go test (TUG) is one of the most commonly used tests of physical function in clinical practice and for research outcomes. Inertial sensors have been used to parse the TUG test into its composite phases (rising, walking, turning, etc.), but have not validated this approach against an optoelectronic gold-standard, and to our knowledge no studies have published the minimal detectable change of these measurements. Methods: Eleven adults performed the TUG three times each under normal and slow walking conditions, and 3 m and 5 m walking distances, in a 12-camera motion analysis laboratory. An inertial measurement unit (IMU) with tri-axial accelerometers and gyroscopes was worn on the upper-torso. Motion analysis marker data and IMU signals were analyzed separately to identify the six main TUG phases: sit-to-stand, 1st walk, 1st turn, 2nd walk, 2nd turn, and stand-to-sit, and the absolute agreement between two systems analyzed using intra-class correlation (ICC, model 2) analysis. The minimal detectable change (MDC) within subjects was also calculated for each TUG phase. Results: The overall difference between TUG sub-tasks determined using 3D motion capture data and the IMU sensor data was <0.5 s. For all TUG distances and speeds, the absolute agreement was high for total TUG time and walk times (ICC > 0.90), but less for chair activity (ICC range 0.5–0.9) and typically poor for the turn time (ICC < 0.4). MDC values for total TUG time ranged between 2–4 s or 12–22% of the TUG time measurement. MDC of the sub-task times were higher proportionally, being 20–60% of the sub-task duration. Conclusions: We conclude that a commercial IMU can be used for quantifying the TUG phases with accuracy sufficient for clinical applications; however, the MDC when using inertial sensors is not necessarily improved over less sophisticated measurement tools. Full article
(This article belongs to the Special Issue Wearable and Ambient Sensors for Healthcare and Wellness Applications)
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2730 KiB  
Article
Using Wavelet Packet Transform for Surface Roughness Evaluation and Texture Extraction
by Xiao Wang, Tielin Shi, Guanglan Liao, Yichun Zhang, Yuan Hong and Kepeng Chen
Sensors 2017, 17(4), 933; https://doi.org/10.3390/s17040933 - 23 Apr 2017
Cited by 47 | Viewed by 6373
Abstract
Surface characterization plays a significant role in evaluating surface functional performance. In this paper, we introduce wavelet packet transform for surface roughness characterization and surface texture extraction. Surface topography is acquired by a confocal laser scanning microscope. Smooth border padding and de-noise process [...] Read more.
Surface characterization plays a significant role in evaluating surface functional performance. In this paper, we introduce wavelet packet transform for surface roughness characterization and surface texture extraction. Surface topography is acquired by a confocal laser scanning microscope. Smooth border padding and de-noise process are implemented to generate a roughness surface precisely. By analyzing the high frequency components of a simulated profile, surface textures are separated by using wavelet packet transform, and the reconstructed roughness and waviness coincide well with the original ones. Wavelet packet transform is then used as a smooth filter for texture extraction. A roughness specimen and three real engineering surfaces are also analyzed in detail. Profile and areal roughness parameters are calculated to quantify the characterization results and compared with those measured by a profile meter. Most obtained roughness parameters agree well with the measurement results, and the largest deviation occurs in the skewness. The relations between the roughness parameters and noise are analyzed by simulation for explaining the relatively large deviations. The extracted textures reflect the surface structure and indicate the manufacturing conditions well, which is helpful for further feature recognition and matching. By using wavelet packet transform, engineering surfaces are comprehensively characterized including evaluating surface roughness and extracting surface texture. Full article
(This article belongs to the Section Physical Sensors)
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1527 KiB  
Article
Implementation Issues of Adaptive Energy Detection in Heterogeneous Wireless Networks
by Iker Sobron, Iñaki Eizmendi, Wallace A. Martins, Paulo S. R. Diniz, Juan Luis Ordiales and Manuel Velez
Sensors 2017, 17(4), 932; https://doi.org/10.3390/s17040932 - 23 Apr 2017
Cited by 1 | Viewed by 4650
Abstract
Spectrum sensing (SS) enables the coexistence of non-coordinated heterogeneous wireless systems operating in the same band. Due to its computational simplicity, energy detection (ED) technique has been widespread employed in SS applications; nonetheless, the conventional ED may be unreliable under environmental impairments, justifying [...] Read more.
Spectrum sensing (SS) enables the coexistence of non-coordinated heterogeneous wireless systems operating in the same band. Due to its computational simplicity, energy detection (ED) technique has been widespread employed in SS applications; nonetheless, the conventional ED may be unreliable under environmental impairments, justifying the use of ED-based variants. Assessing ED algorithms from theoretical and simulation viewpoints relies on several assumptions and simplifications which, eventually, lead to conclusions that do not necessarily meet the requirements imposed by real propagation environments. This work addresses those problems by dealing with practical implementation issues of adaptive least mean square (LMS)-based ED algorithms. The paper proposes a new adaptive ED algorithm that uses a variable step-size guaranteeing the LMS convergence in time-varying environments. Several implementation guidelines are provided and, additionally, an empirical assessment and validation with a software defined radio-based hardware is carried out. Experimental results show good performance in terms of probabilities of detection ( P d > 0 . 9 ) and false alarm ( P f ∼ 0 . 05 ) in a range of low signal-to-noise ratios around [ - 4 , 1 ] dB, in both single-node and cooperative modes. The proposed sensing methodology enables a seamless monitoring of the radio electromagnetic spectrum in order to provide band occupancy information for an efficient usage among several wireless communications systems. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2016)
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1153 KiB  
Article
Smartphone Location-Independent Physical Activity Recognition Based on Transportation Natural Vibration Analysis
by Taeho Hur, Jaehun Bang, Dohyeong Kim, Oresti Banos and Sungyoung Lee
Sensors 2017, 17(4), 931; https://doi.org/10.3390/s17040931 - 23 Apr 2017
Cited by 18 | Viewed by 6371
Abstract
Activity recognition through smartphones has been proposed for a variety of applications. The orientation of the smartphone has a significant effect on the recognition accuracy; thus, researchers generally propose using features invariant to orientation or displacement to achieve this goal. However, those features [...] Read more.
Activity recognition through smartphones has been proposed for a variety of applications. The orientation of the smartphone has a significant effect on the recognition accuracy; thus, researchers generally propose using features invariant to orientation or displacement to achieve this goal. However, those features reduce the capability of the recognition system to differentiate among some specific commuting activities (e.g., bus and subway) that normally involve similar postures. In this work, we recognize those activities by analyzing the vibrations of the vehicle in which the user is traveling. We extract natural vibration features of buses and subways to distinguish between them and address the confusion that can arise because the activities are both static in terms of user movement. We use the gyroscope to fix the accelerometer to the direction of gravity to achieve an orientation-free use of the sensor. We also propose a correction algorithm to increase the accuracy when used in free living conditions and a battery saving algorithm to consume less power without reducing performance. Our experimental results show that the proposed system can adequately recognize each activity, yielding better accuracy in the detection of bus and subway activities than existing methods. Full article
(This article belongs to the Special Issue Smartphone-based Pedestrian Localization and Navigation)
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1230 KiB  
Article
Simulation Study of the Localization of a Near-Surface Crack Using an Air-Coupled Ultrasonic Sensor Array
by Steven Delrue, Vladislav Aleshin, Mikael Sørensen and Lieven De Lathauwer
Sensors 2017, 17(4), 930; https://doi.org/10.3390/s17040930 - 22 Apr 2017
Cited by 8 | Viewed by 5441
Abstract
The importance of Non-Destructive Testing (NDT) to check the integrity of materials in different fields of industry has increased significantly in recent years. Actually, industry demands NDT methods that allow fast (preferably non-contact) detection and localization of early-stage defects with easy-to-interpret results, so [...] Read more.
The importance of Non-Destructive Testing (NDT) to check the integrity of materials in different fields of industry has increased significantly in recent years. Actually, industry demands NDT methods that allow fast (preferably non-contact) detection and localization of early-stage defects with easy-to-interpret results, so that even a non-expert field worker can carry out the testing. The main challenge is to combine as many of these requirements into one single technique. The concept of acoustic cameras, developed for low frequency NDT, meets most of the above-mentioned requirements. These cameras make use of an array of microphones to visualize noise sources by estimating the Direction Of Arrival (DOA) of the impinging sound waves. Until now, however, because of limitations in the frequency range and the lack of integrated nonlinear post-processing, acoustic camera systems have never been used for the localization of incipient damage. The goal of the current paper is to numerically investigate the capabilities of locating incipient damage by measuring the nonlinear airborne emission of the defect using a non-contact ultrasonic sensor array. We will consider a simple case of a sample with a single near-surface crack and prove that after efficient excitation of the defect sample, the nonlinear defect responses can be detected by a uniform linear sensor array. These responses are then used to determine the location of the defect by means of three different DOA algorithms. The results obtained in this study can be considered as a first step towards the development of a nonlinear ultrasonic camera system, comprising the ultrasonic sensor array as the hardware and nonlinear post-processing and source localization software. Full article
(This article belongs to the Special Issue Sensor Technologies for Health Monitoring of Composite Structures)
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4162 KiB  
Article
A Miniature Aerosol Sensor for Detecting Polydisperse Airborne Ultrafine Particles
by Chao Zhang, Dingqu Wang, Rong Zhu, Wenming Yang and Peng Jiang
Sensors 2017, 17(4), 929; https://doi.org/10.3390/s17040929 - 22 Apr 2017
Cited by 14 | Viewed by 6157
Abstract
Counting and sizing of polydisperse airborne nanoparticles have attracted most attentions owing to increasing widespread presence of airborne engineered nanoparticles or ultrafine particles. Here we report a miniature aerosol sensor to detect particle size distribution of polydisperse ultrafine particles based on ion diffusion [...] Read more.
Counting and sizing of polydisperse airborne nanoparticles have attracted most attentions owing to increasing widespread presence of airborne engineered nanoparticles or ultrafine particles. Here we report a miniature aerosol sensor to detect particle size distribution of polydisperse ultrafine particles based on ion diffusion charging and electrical detection. The aerosol sensor comprises a couple of planar electrodes printed on two circuit boards assembled in parallel, where charging, precipitation and measurement sections are integrated into one chip, which can detect aerosol particle size in of 30–500 nm, number concentration in range of 5 × 102 – 5 × 107 /cm3. The average relative errors of the measured aerosol number concentration and the particle size are estimated to be 12.2% and 13.5% respectively. A novel measurement scheme is proposed to actualize a real-time detection of polydisperse particles by successively modulating the measurement voltage and deducing the particle size distribution through a smart data fusion algorithm. The effectiveness of the aerosol sensor is experimentally demonstrated via measurements of polystyrene latex (PSL) aerosol and nucleic acid aerosol, as well as sodium chloride aerosol particles. Full article
(This article belongs to the Section Chemical Sensors)
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337 KiB  
Article
A Weighted Belief Entropy-Based Uncertainty Measure for Multi-Sensor Data Fusion
by Yongchuan Tang, Deyun Zhou, Shuai Xu and Zichang He
Sensors 2017, 17(4), 928; https://doi.org/10.3390/s17040928 - 22 Apr 2017
Cited by 84 | Viewed by 6802
Abstract
In real applications, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. In this paper, in the frame of Dempster–Shafer evidence theory, a weighted belief entropy based on Deng entropy is proposed to quantify [...] Read more.
In real applications, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. In this paper, in the frame of Dempster–Shafer evidence theory, a weighted belief entropy based on Deng entropy is proposed to quantify the uncertainty of uncertain information. The weight of the proposed belief entropy is based on the relative scale of a proposition with regard to the frame of discernment (FOD). Compared with some other uncertainty measures in Dempster–Shafer framework, the new measure focuses on the uncertain information represented by not only the mass function, but also the scale of the FOD, which means less information loss in information processing. After that, a new multi-sensor data fusion approach based on the weighted belief entropy is proposed. The rationality and superiority of the new multi-sensor data fusion method is verified according to an experiment on artificial data and an application on fault diagnosis of a motor rotor. Full article
(This article belongs to the Special Issue Soft Sensors and Intelligent Algorithms for Data Fusion)
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3928 KiB  
Article
The Use of IMMUs in a Water Environment: Instrument Validation and Application of 3D Multi-Body Kinematic Analysis in Medicine and Sport
by Anna Lisa Mangia, Matteo Cortesi, Silvia Fantozzi, Andrea Giovanardi, Davide Borra and Giorgio Gatta
Sensors 2017, 17(4), 927; https://doi.org/10.3390/s17040927 - 22 Apr 2017
Cited by 21 | Viewed by 6531
Abstract
The aims of the present study were the instrumental validation of inertial-magnetic measurements units (IMMUs) in water, and the description of their use in clinical and sports aquatic applications applying customized 3D multi-body models. Firstly, several tests were performed to map the magnetic [...] Read more.
The aims of the present study were the instrumental validation of inertial-magnetic measurements units (IMMUs) in water, and the description of their use in clinical and sports aquatic applications applying customized 3D multi-body models. Firstly, several tests were performed to map the magnetic field in the swimming pool and to identify the best volume for experimental test acquisition with a mean dynamic orientation error lower than 5°. Successively, the gait and the swimming analyses were explored in terms of spatiotemporal and joint kinematics variables. The extraction of only spatiotemporal parameters highlighted several critical issues and the joint kinematic information has shown to be an added value for both rehabilitative and sport training purposes. Furthermore, 3D joint kinematics applied using the IMMUs provided similar quantitative information than that of more expensive and bulky systems but with a simpler and faster setup preparation, a lower time consuming processing phase, as well as the possibility to record and analyze a higher number of strides/strokes without limitations imposed by the cameras. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technologies in Italy 2016)
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2615 KiB  
Article
Experimental Demonstration and Circuitry for a Very Compact Coil-Only Pulse Echo EMAT
by Dirk Rueter
Sensors 2017, 17(4), 926; https://doi.org/10.3390/s17040926 - 22 Apr 2017
Cited by 10 | Viewed by 7696
Abstract
This experimental study demonstrates for the first time a solid-state circuitry and design for a simple compact copper coil (without an additional bulky permanent magnet or bulky electromagnet) as a contactless electromagnetic acoustic transducer (EMAT) for pulse echo operation at MHz frequencies. A [...] Read more.
This experimental study demonstrates for the first time a solid-state circuitry and design for a simple compact copper coil (without an additional bulky permanent magnet or bulky electromagnet) as a contactless electromagnetic acoustic transducer (EMAT) for pulse echo operation at MHz frequencies. A pulsed ultrasound emission into a metallic test object is electromagnetically excited by an intense MHz burst at up to 500 A through the 0.15 mm filaments of the transducer. Immediately thereafter, a smoother and quasi “DC-like” current of 100 A is applied for about 1 ms and allows an echo detection. The ultrasonic pulse echo operation for a simple, compact, non-contacting copper coil is new. Application scenarios for compact transducer techniques include very narrow and hostile environments, in which, e.g., quickly moving metal parts must be tested with only one, non-contacting ultrasound shot. The small transducer coil can be operated remotely with a cable connection, separate from the much bulkier supply circuitry. Several options for more technical and fundamental progress are discussed. Full article
(This article belongs to the Special Issue Acoustic Sensing and Ultrasonic Drug Delivery)
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2584 KiB  
Article
Imaging of the Finger Vein and Blood Flow for Anti-Spoofing Authentication Using a Laser and a MEMS Scanner
by Jaekwon Lee, Seunghwan Moon, Juhun Lim, Min-Joo Gwak, Jae Gwan Kim, Euiheon Chung and Jong-Hyun Lee
Sensors 2017, 17(4), 925; https://doi.org/10.3390/s17040925 - 22 Apr 2017
Cited by 18 | Viewed by 8156
Abstract
A new authentication method employing a laser and a scanner is proposed to improve image contrast of the finger vein and to extract blood flow pattern for liveness detection. A micromirror reflects a laser beam and performs a uniform raster scan. Transmissive vein [...] Read more.
A new authentication method employing a laser and a scanner is proposed to improve image contrast of the finger vein and to extract blood flow pattern for liveness detection. A micromirror reflects a laser beam and performs a uniform raster scan. Transmissive vein images were obtained, and compared with those of an LED. Blood flow patterns were also obtained based on speckle images in perfusion and occlusion. Curvature ratios of the finger vein and blood flow intensities were found to be nearly constant, regardless of the vein size, which validated the high repeatability of this scheme for identity authentication with anti-spoofing. Full article
(This article belongs to the Section Biosensors)
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3015 KiB  
Article
State Estimation Using Dependent Evidence Fusion: Application to Acoustic Resonance-Based Liquid Level Measurement
by Xiaobin Xu, Zhenghui Li, Guo Li and Zhe Zhou
Sensors 2017, 17(4), 924; https://doi.org/10.3390/s17040924 - 21 Apr 2017
Cited by 5 | Viewed by 4120
Abstract
Estimating the state of a dynamic system via noisy sensor measurement is a common problem in sensor methods and applications. Most state estimation methods assume that measurement noise and state perturbations can be modeled as random variables with known statistical properties. However in [...] Read more.
Estimating the state of a dynamic system via noisy sensor measurement is a common problem in sensor methods and applications. Most state estimation methods assume that measurement noise and state perturbations can be modeled as random variables with known statistical properties. However in some practical applications, engineers can only get the range of noises, instead of the precise statistical distributions. Hence, in the framework of Dempster-Shafer (DS) evidence theory, a novel state estimatation method by fusing dependent evidence generated from state equation, observation equation and the actual observations of the system states considering bounded noises is presented. It can be iteratively implemented to provide state estimation values calculated from fusion results at every time step. Finally, the proposed method is applied to a low-frequency acoustic resonance level gauge to obtain high-accuracy measurement results. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications 2017)
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2516 KiB  
Article
A Novel Method of Localization for Moving Objects with an Alternating Magnetic Field
by Xiang Gao, Shenggang Yan and Bin Li
Sensors 2017, 17(4), 923; https://doi.org/10.3390/s17040923 - 21 Apr 2017
Cited by 21 | Viewed by 4334
Abstract
Magnetic detection technology has wide applications in the fields of geological exploration, biomedical treatment, wreck removal and localization of unexploded ordinance. A large number of methods have been developed to locate targets with static magnetic fields, however, the relation between the problem of [...] Read more.
Magnetic detection technology has wide applications in the fields of geological exploration, biomedical treatment, wreck removal and localization of unexploded ordinance. A large number of methods have been developed to locate targets with static magnetic fields, however, the relation between the problem of localization of moving objectives with alternating magnetic fields and the localization with a static magnetic field is rarely studied. A novel method of target localization based on coherent demodulation was proposed in this paper. The problem of localization of moving objects with an alternating magnetic field was transformed into the localization with a static magnetic field. The Levenberg-Marquardt (L-M) algorithm was applied to calculate the position of the target with magnetic field data measured by a single three-component magnetic sensor. Theoretical simulation and experimental results demonstrate the effectiveness of the proposed method. Full article
(This article belongs to the Section Physical Sensors)
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1389 KiB  
Article
Zero-Sum Matrix Game with Payoffs of Dempster-Shafer Belief Structures and Its Applications on Sensors
by Xinyang Deng, Wen Jiang and Jiandong Zhang
Sensors 2017, 17(4), 922; https://doi.org/10.3390/s17040922 - 21 Apr 2017
Cited by 42 | Viewed by 6424
Abstract
The zero-sum matrix game is one of the most classic game models, and it is widely used in many scientific and engineering fields. In the real world, due to the complexity of the decision-making environment, sometimes the payoffs received by players may be [...] Read more.
The zero-sum matrix game is one of the most classic game models, and it is widely used in many scientific and engineering fields. In the real world, due to the complexity of the decision-making environment, sometimes the payoffs received by players may be inexact or uncertain, which requires that the model of matrix games has the ability to represent and deal with imprecise payoffs. To meet such a requirement, this paper develops a zero-sum matrix game model with Dempster–Shafer belief structure payoffs, which effectively represents the ambiguity involved in payoffs of a game. Then, a decomposition method is proposed to calculate the value of such a game, which is also expressed with belief structures. Moreover, for the possible computation-intensive issue in the proposed decomposition method, as an alternative solution, a Monte Carlo simulation approach is presented, as well. Finally, the proposed zero-sum matrix games with payoffs of Dempster–Shafer belief structures is illustratively applied to the sensor selection and intrusion detection of sensor networks, which shows its effectiveness and application process. Full article
(This article belongs to the Special Issue Soft Sensors and Intelligent Algorithms for Data Fusion)
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2865 KiB  
Article
A New Method for Single-Epoch Ambiguity Resolution with Indoor Pseudolite Positioning
by Xin Li, Peng Zhang, Jiming Guo, Jinling Wang and Weining Qiu
Sensors 2017, 17(4), 921; https://doi.org/10.3390/s17040921 - 21 Apr 2017
Cited by 30 | Viewed by 4572
Abstract
Ambiguity resolution (AR) is crucial for high-precision indoor pseudolite positioning. Due to the existing characteristics of the pseudolite positioning system, such as the geometry structure of the stationary pseudolite which is consistently invariant, the indoor signal is easy to interrupt and the first [...] Read more.
Ambiguity resolution (AR) is crucial for high-precision indoor pseudolite positioning. Due to the existing characteristics of the pseudolite positioning system, such as the geometry structure of the stationary pseudolite which is consistently invariant, the indoor signal is easy to interrupt and the first order linear truncation error cannot be ignored, and a new AR method based on the idea of the ambiguity function method (AFM) is proposed in this paper. The proposed method is a single-epoch and nonlinear method that is especially well-suited for indoor pseudolite positioning. Considering the very low computational efficiency of conventional AFM, we adopt an improved particle swarm optimization (IPSO) algorithm to search for the best solution in the coordinate domain, and variances of a least squares adjustment is conducted to ensure the reliability of the solving ambiguity. Several experiments, including static and kinematic tests, are conducted to verify the validity of the proposed AR method. Numerical results show that the IPSO significantly improved the computational efficiency of AFM and has a more elaborate search ability compared to the conventional grid searching method. For the indoor pseudolite system, which had an initial approximate coordinate precision better than 0.2 m, the AFM exhibited good performances in both static and kinematic tests. With the corrected ambiguity gained from our proposed method, indoor pseudolite positioning can achieve centimeter-level precision using a low-cost single-frequency software receiver. Full article
(This article belongs to the Section Physical Sensors)
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1178 KiB  
Article
Dynamic Construction Scheme for Virtualization Security Service in Software-Defined Networks
by Zhaowen Lin, Dan Tao and Zhenji Wang
Sensors 2017, 17(4), 920; https://doi.org/10.3390/s17040920 - 21 Apr 2017
Cited by 13 | Viewed by 5155
Abstract
For a Software Defined Network (SDN), security is an important factor affecting its large-scale deployment. The existing security solutions for SDN mainly focus on the controller itself, which has to handle all the security protection tasks by using the programmability of the network. [...] Read more.
For a Software Defined Network (SDN), security is an important factor affecting its large-scale deployment. The existing security solutions for SDN mainly focus on the controller itself, which has to handle all the security protection tasks by using the programmability of the network. This will undoubtedly involve a heavy burden for the controller. More devastatingly, once the controller itself is attacked, the entire network will be paralyzed. Motivated by this, this paper proposes a novel security protection architecture for SDN. We design a security service orchestration center in the control plane of SDN, and this center physically decouples from the SDN controller and constructs SDN security services. We adopt virtualization technology to construct a security meta-function library, and propose a dynamic security service composition construction algorithm based on web service composition technology. The rule-combining method is used to combine security meta-functions to construct security services which meet the requirements of users. Moreover, the RETE algorithm is introduced to improve the efficiency of the rule-combining method. We evaluate our solutions in a realistic scenario based on OpenStack. Substantial experimental results demonstrate the effectiveness of our solutions that contribute to achieve the effective security protection with a small burden of the SDN controller. Full article
(This article belongs to the Special Issue New Advances in Identification, Information & Knowledge in the Internet of Things)
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4160 KiB  
Article
Image-Guided Laparoscopic Surgical Tool (IGLaST) Based on the Optical Frequency Domain Imaging (OFDI) to Prevent Bleeding
by Byung Jun Park, Seung Rag Lee, Hyun Jin Bang, Byung Yeon Kim, Jeong Hun Park, Dong Guk Kim, Sung Soo Park and Young Jae Won
Sensors 2017, 17(4), 919; https://doi.org/10.3390/s17040919 - 21 Apr 2017
Cited by 6 | Viewed by 6026
Abstract
We present an image-guided laparoscopic surgical tool (IGLaST) to prevent bleeding. By applying optical frequency domain imaging (OFDI) to a specially designed laparoscopic surgical tool, the inside of fatty tissue can be observed before a resection, and the presence and size of blood [...] Read more.
We present an image-guided laparoscopic surgical tool (IGLaST) to prevent bleeding. By applying optical frequency domain imaging (OFDI) to a specially designed laparoscopic surgical tool, the inside of fatty tissue can be observed before a resection, and the presence and size of blood vessels can be recognized. The optical sensing module on the IGLaST head has a diameter of less than 390 µm and is moved back and forth by a linear servo actuator in the IGLaST body. We proved the feasibility of IGLaST by in vivo imaging inside the fatty tissue of a porcine model. A blood vessel with a diameter of about 2.2 mm was clearly observed. Our proposed scheme can contribute to safe surgery without bleeding by monitoring vessels inside the tissue and can be further expanded to detect invisible nerves of the laparoscopic thyroid during prostate gland surgery. Full article
(This article belongs to the Special Issue Optical Methods in Sensing and Imaging for Medical and Biological Applications)
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1598 KiB  
Article
Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment
by Branko Ristic, Daniel Angley, Bill Moran and Jennifer L. Palmer
Sensors 2017, 17(4), 918; https://doi.org/10.3390/s17040918 - 21 Apr 2017
Cited by 33 | Viewed by 4892
Abstract
Finding the source of an accidental or deliberate release of a toxic substance into the atmosphere is of great importance for national security. The paper presents a search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms. [...] Read more.
Finding the source of an accidental or deliberate release of a toxic substance into the atmosphere is of great importance for national security. The paper presents a search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms. Bayesian estimation of the source parameter vector is carried out using the Rao–Blackwell dimension-reduction method, while the robots are controlled autonomously to move in a scalable formation. Estimation and control are carried out in a centralised replicated fusion architecture assuming all-to-all communication. The paper presents a comprehensive numerical analysis of the proposed algorithm, including the search-time and displacement statistics. Full article
(This article belongs to the Special Issue Sensor Intelligence Assisted by Data Analytics and Cognitive Computing)
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9406 KiB  
Article
Accurate Ambient Noise Assessment Using Smartphones
by Willian Zamora, Carlos T. Calafate, Juan-Carlos Cano and Pietro Manzoni
Sensors 2017, 17(4), 917; https://doi.org/10.3390/s17040917 - 21 Apr 2017
Cited by 43 | Viewed by 7266
Abstract
Nowadays, smartphones have become ubiquitous and one of the main communication resources for human beings. Their widespread adoption was due to the huge technological progress and to the development of multiple useful applications. Their characteristics have also experienced a substantial improvement as they [...] Read more.
Nowadays, smartphones have become ubiquitous and one of the main communication resources for human beings. Their widespread adoption was due to the huge technological progress and to the development of multiple useful applications. Their characteristics have also experienced a substantial improvement as they now integrate multiple sensors able to convert the smartphone into a flexible and multi-purpose sensing unit. The combined use of multiple smartphones endowed with several types of sensors gives the possibility to monitor a certain area with fine spatial and temporal granularity, a procedure typically known as crowdsensing. In this paper, we propose using smartphones as environmental noise-sensing units. For this purpose, we focus our study on the sound capture and processing procedure, analyzing the impact of different noise calculation algorithms, as well as in determining their accuracy when compared to a professional noise measurement unit. We analyze different candidate algorithms using different types of smartphones, and we study the most adequate time period and sampling strategy to optimize the data-gathering process. In addition, we perform an experimental study comparing our approach with the results obtained using a professional device. Experimental results show that, if the smartphone application is well tuned, it is possible to measure noise levels with a accuracy degree comparable to professional devices for the entire dynamic range typically supported by microphones embedded in smartphones, i.e., 35–95 dB. Full article
(This article belongs to the Special Issue New Advances in Identification, Information & Knowledge in the Internet of Things)
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5590 KiB  
Article
Suitability of Strain Gage Sensors for Integration into Smart Sport Equipment: A Golf Club Example
by Anton Umek, Yuan Zhang, Sašo Tomažič and Anton Kos
Sensors 2017, 17(4), 916; https://doi.org/10.3390/s17040916 - 21 Apr 2017
Cited by 27 | Viewed by 9147
Abstract
Wearable devices and smart sport equipment are being increasingly used in amateur and professional sports. Smart sport equipment employs various sensors for detecting its state and actions. The correct choice of the most appropriate sensor(s) is of paramount importance for efficient and successful [...] Read more.
Wearable devices and smart sport equipment are being increasingly used in amateur and professional sports. Smart sport equipment employs various sensors for detecting its state and actions. The correct choice of the most appropriate sensor(s) is of paramount importance for efficient and successful operation of sport equipment. When integrated into the sport equipment, ideal sensors are unobstructive, and do not change the functionality of the equipment. The article focuses on experiments for identification and selection of sensors that are suitable for the integration into a golf club with the final goal of their use in real time biofeedback applications. We tested two orthogonally affixed strain gage (SG) sensors, a 3-axis accelerometer, and a 3-axis gyroscope. The strain gage sensors are calibrated and validated in the laboratory environment by a highly accurate Qualisys Track Manager (QTM) optical tracking system. Field test results show that different types of golf swing and improper movement in early phases of golf swing can be detected with strain gage sensors attached to the shaft of the golf club. Thus they are suitable for biofeedback applications to help golfers to learn repetitive golf swings. It is suggested that the use of strain gage sensors can improve the golf swing technical error detection accuracy and that strain gage sensors alone are enough for basic golf swing analysis. Our final goal is to be able to acquire and analyze as many parameters of a smart golf club in real time during the entire duration of the swing. This would give us the ability to design mobile and cloud biofeedback applications with terminal or concurrent feedback that will enable us to speed-up motor skill learning in golf. Full article
(This article belongs to the Special Issue New Advances in Identification, Information & Knowledge in the Internet of Things)
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8256 KiB  
Article
Celestial Object Imaging Model and Parameter Optimization for an Optical Navigation Sensor Based on the Well Capacity Adjusting Scheme
by Hao Wang, Jie Jiang and Guangjun Zhang
Sensors 2017, 17(4), 915; https://doi.org/10.3390/s17040915 - 21 Apr 2017
Cited by 6 | Viewed by 4781
Abstract
The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally [...] Read more.
The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally large. Multi-sensor integration or complex image processing algorithms are commonly utilized to solve the said problem. This study analyzes and demonstrates the feasibility of simultaneously imaging the target celestial body and stars well-exposed within a single exposure through a single field of view (FOV) optical navigation sensor using the well capacity adjusting (WCA) scheme. First, the irradiance characteristics of the celestial body are analyzed. Then, the celestial body edge model and star spot imaging model are established when the WCA scheme is applied. Furthermore, the effect of exposure parameters on the accuracy of star centroiding and edge extraction is analyzed using the proposed model. Optimal exposure parameters are also derived by conducting Monte Carlo simulation to obtain the best performance of the navigation sensor. Finally, laboratorial and night sky experiments are performed to validate the correctness of the proposed model and optimal exposure parameters. Full article
(This article belongs to the Section Physical Sensors)
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1778 KiB  
Article
Influence of Wind Speed on RGB-D Images in Tree Plantations
by Dionisio Andújar, José Dorado, José María Bengochea-Guevara, Jesús Conesa-Muñoz, César Fernández-Quintanilla and Ángela Ribeiro
Sensors 2017, 17(4), 914; https://doi.org/10.3390/s17040914 - 21 Apr 2017
Cited by 18 | Viewed by 5650
Abstract
Weather conditions can affect sensors’ readings when sampling outdoors. Although sensors are usually set up covering a wide range of conditions, their operational range must be established. In recent years, depth cameras have been shown as a promising tool for plant phenotyping and [...] Read more.
Weather conditions can affect sensors’ readings when sampling outdoors. Although sensors are usually set up covering a wide range of conditions, their operational range must be established. In recent years, depth cameras have been shown as a promising tool for plant phenotyping and other related uses. However, the use of these devices is still challenged by prevailing field conditions. Although the influence of lighting conditions on the performance of these cameras has already been established, the effect of wind is still unknown. This study establishes the associated errors when modeling some tree characteristics at different wind speeds. A system using a Kinect v2 sensor and a custom software was tested from null wind speed up to 10 m·s−1. Two tree species with contrasting architecture, poplars and plums, were used as model plants. The results showed different responses depending on tree species and wind speed. Estimations of Leaf Area (LA) and tree volume were generally more consistent at high wind speeds in plum trees. Poplars were particularly affected by wind speeds higher than 5 m·s−1. On the contrary, height measurements were more consistent for poplars than for plum trees. These results show that the use of depth cameras for tree characterization must take into consideration wind conditions in the field. In general, 5 m·s−1 (18 km·h−1) could be established as a conservative limit for good estimations. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
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3462 KiB  
Article
Synthesis, Characterization and Enhanced Sensing Properties of a NiO/ZnO p–n Junctions Sensor for the SF6 Decomposition Byproducts SO2, SO2F2, and SOF2
by Hongcheng Liu, Qu Zhou, Qingyan Zhang, Changxiang Hong, Lingna Xu, Lingfeng Jin and Weigen Chen
Sensors 2017, 17(4), 913; https://doi.org/10.3390/s17040913 - 21 Apr 2017
Cited by 85 | Viewed by 7400
Abstract
The detection of partial discharge and analysis of the composition and content of sulfur hexafluoride SF6 gas components are important to evaluate the operating state and insulation level of gas-insulated switchgear (GIS) equipment. This paper reported a novel sensing material made of [...] Read more.
The detection of partial discharge and analysis of the composition and content of sulfur hexafluoride SF6 gas components are important to evaluate the operating state and insulation level of gas-insulated switchgear (GIS) equipment. This paper reported a novel sensing material made of pure ZnO and NiO-decorated ZnO nanoflowers which were synthesized by a facile and environment friendly hydrothermal process for the detection of SF6 decomposition byproducts. X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) were used to characterize the structural and morphological properties of the prepared gas-sensitive materials. Planar-type chemical gas sensors were fabricated and their gas sensing performances toward the SF6 decomposition byproducts SO2, SO2F2, and SOF2 were systemically investigated. Interestingly, the sensing behaviors of the fabricated ZnO nanoflowers-based sensor to SO2, SO2F2, and SOF2 gases can be obviously enhanced in terms of lower optimal operating temperature, higher gas response and shorter response-recovery time by introducing NiO. Finally, a possible gas sensing mechanism for the formation of the p–n junctions between NiO and ZnO is proposed to explain the enhanced gas response. All results demonstrate a promising approach to fabricate high-performance gas sensors to detect SF6 decomposition byproducts. Full article
(This article belongs to the Section Physical Sensors)
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7690 KiB  
Article
A Multi-Platform Optical Sensor for In Vivo and In Vitro Algae Classification
by Chee-Loon Ng, Qing-Qing Chen, Jia-Jing Chua and Harold F. Hemond
Sensors 2017, 17(4), 912; https://doi.org/10.3390/s17040912 - 20 Apr 2017
Cited by 7 | Viewed by 7235
Abstract
Differentiation among major algal groups is important for the ecological and biogeochemical characterization of water bodies, and for practical management of water resources. It helps to discern the taxonomic groups that are beneficial to aquatic life from the organisms causing harmful algal blooms. [...] Read more.
Differentiation among major algal groups is important for the ecological and biogeochemical characterization of water bodies, and for practical management of water resources. It helps to discern the taxonomic groups that are beneficial to aquatic life from the organisms causing harmful algal blooms. An LED-induced fluorescence (LEDIF) instrument capable of fluorescence, absorbance, and scattering measurements; is used for in vivo and in vitro identification and quantification of four algal groups found in freshwater and marine environments. Aqueous solutions of individual and mixed dissolved biological pigments relevant to different algal groups were measured to demonstrate the LEDIF’s capabilities in measuring extracted pigments. Different genera of algae were cultivated and the cell counts of the samples were quantified with a hemacytometer and/or cellometer. Dry weight of different algae cells was also measured to determine the cell counts-to-dry weight correlations. Finally, in vivo measurements of different genus of algae at different cell concentrations and mixed algal group in the presence of humic acid were performed with the LEDIF. A field sample from a local reservoir was measured with the LEDIF and the results were verified using hemacytometer, cellometer, and microscope. The results demonstrated the LEDIF’s capabilities in classifying and quantifying different groups of live algae. Full article
(This article belongs to the Special Issue Specialty Optical Fibers for Chemical and Biochemical Sensing: From Evanescent Waves to Plasmonic Interaction)
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8377 KiB  
Article
Rapid Texture Optimization of Three-Dimensional Urban Model Based on Oblique Images
by Weilong Zhang, Ming Li, Bingxuan Guo, Deren Li and Ge Guo
Sensors 2017, 17(4), 911; https://doi.org/10.3390/s17040911 - 20 Apr 2017
Cited by 12 | Viewed by 4978
Abstract
Seamless texture mapping is one of the key technologies for photorealistic 3D texture reconstruction. In this paper, a method of rapid texture optimization of 3D urban reconstruction based on oblique images is proposed aiming at the existence of texture fragments, seams, and inconsistency [...] Read more.
Seamless texture mapping is one of the key technologies for photorealistic 3D texture reconstruction. In this paper, a method of rapid texture optimization of 3D urban reconstruction based on oblique images is proposed aiming at the existence of texture fragments, seams, and inconsistency of color in urban 3D texture mapping based on low-altitude oblique images. First, we explore implementing radiation correction on the experimental images with a radiation procession algorithm. Then, an efficient occlusion detection algorithm based on OpenGL is proposed according to the mapping relation between the terrain triangular mesh surface and the images to implement the occlusion detection of the visible texture on the triangular facets as well as create a list of visible images. Finally, a texture clustering algorithm is put forward based on Markov Random Field utilizing the inherent attributes of the images and solve the energy function minimization by Graph-Cuts. The experimental results display that the method is capable of decreasing the existence of texture fragments, seams, and inconsistency of color in the 3D texture model reconstruction. Full article
(This article belongs to the Special Issue Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment)
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4835 KiB  
Article
Investigating Surface and Near-Surface Bushfire Fuel Attributes: A Comparison between Visual Assessments and Image-Based Point Clouds
by Christine Spits, Luke Wallace and Karin Reinke
Sensors 2017, 17(4), 910; https://doi.org/10.3390/s17040910 - 20 Apr 2017
Cited by 15 | Viewed by 5692
Abstract
Visual assessment, following guides such as the Overall Fuel Hazard Assessment Guide (OFHAG), is a common approach for assessing the structure and hazard of varying bushfire fuel layers. Visual assessments can be vulnerable to imprecision due to subjectivity between assessors, while emerging techniques [...] Read more.
Visual assessment, following guides such as the Overall Fuel Hazard Assessment Guide (OFHAG), is a common approach for assessing the structure and hazard of varying bushfire fuel layers. Visual assessments can be vulnerable to imprecision due to subjectivity between assessors, while emerging techniques such as image-based point clouds can offer land managers potentially more repeatable descriptions of fuel structure. This study compared the variability of estimates of surface and near-surface fuel attributes generated by eight assessment teams using the OFHAG and Fuels3D, a smartphone method utilising image-based point clouds, within three assessment plots in an Australian lowland forest. Surface fuel hazard scores derived from underpinning attributes were also assessed. Overall, this study found considerable variability between teams on most visually assessed variables, resulting in inconsistent hazard scores. Variability was observed within point cloud estimates but was, however, on average two to eight times less than that seen in visual estimates, indicating greater consistency and repeatability of this method. It is proposed that while variability within the Fuels3D method may be overcome through improved methods and equipment, inconsistencies in the OFHAG are likely due to the inherent subjectivity between assessors, which may be more difficult to overcome. This study demonstrates the capability of the Fuels3D method to efficiently and consistently collect data on fuel hazard and structure, and, as such, this method shows potential for use in fire management practices where accurate and reliable data is essential. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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