| 1. |
- Alhashimi, Anas, 1978-, et al.
(författare)
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Calibrating distance sensors for terrestrial applications without groundtruth information
- 2017
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Ingår i: IEEE Sensors Journal. - : IEEE. - 1530-437X .- 1558-1748. ; 17:12, s. 3698-3709
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Tidskriftsartikel (refereegranskat)abstract
- This paper describes a new calibration procedure for distance sensors that does not require independent sources of groundtruth information, i.e., that is not based on comparing the measurements from the uncalibrated sensor against measurements from a precise device assumed as the groundtruth. Alternatively, the procedure assumes that the uncalibrated distance sensor moves in space on a straight line in an environment with fixed targets, so that the intrinsic parameters of the statistical model of the sensor readings are calibrated without requiring tests in controlled environments, but rather in environments where the sensor follows linear movement and objects do not move. The proposed calibration procedure exploits an approximated expectation maximization scheme on top of two ingredients: an heteroscedastic statistical model describing the measurement process, and a simplified dynamical model describing the linear sensor movement. The procedure is designed to be capable of not just estimating the parameters of one generic distance sensor, but rather integrating the most common sensors in robotic applications, such as Lidars, odometers, and sonar rangers and learn the intrinsic parameters of all these sensors simultaneously. Tests in a controlled environment led to a reduction of the mean squared error of the measurements returned by a commercial triangulation Lidar by a factor between 3 and 6, comparable to the efficiency of other state-of-the art groundtruth-based calibration procedures. Adding odometric and ultrasonic information further improved the performance index of the overall distance estimation strategy by a factor of up to 1.2. Tests also show high robustness against violating the linear movements assumption.
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| 2. |
- Choudhary, Anurag, et al.
(författare)
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Infrared Thermography-Based Fault Diagnosis of Induction Motor Bearings Using Machine Learning
- 2021
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Ingår i: IEEE Sensors Journal. - : IEEE. - 1530-437X .- 1558-1748. ; 21:2, s. 1727-1734
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Tidskriftsartikel (refereegranskat)abstract
- Bearing is one of the most crucial parts in induction motor (IM) as a result there is a constant call for effective diagnosis of bearing faults for reliable operation. Infrared thermography (IRT) is appreciably used as a non-destructive and non-contact method to detect the bearing defects in a rotary machine. However, its performance is limited by insignificant information and string noise present in the infrared thermal image. To address this issue, an emergent two dimensional discrete wavelet transform (2D-DWT) based IRT method has been proposed in this article for diagnosing the different bearing faults in IM, namely, inner and outer race defects, and lack of lubrication. The dimensionality of the extracted features was reduced using principal component analysis (PCA) and thereafter the selected features were ranked in the order of most relevant features using the Mahalanobis distance (MD) method to achieve the optimal feature set. Finally these selected features have been passed to the complex decision tree (CDT), linear discriminant analysis (LDA) and support vector machine (SVM) for fault classification and performance evaluation. The classification results reveal that the SVM outperformed CDT and LDA. The proposed strategy can be used for self-adaptive recognition of bearing faults in IM which helps to avoid the unplanned and unwanted system shutdowns due to the bearing failure. © 2001-2012 IEEE.
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| 3. |
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| 4. |
- Hostettler, Roland, et al.
(författare)
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Joint Vehicle Trajectory and Model Parameter Estimation using Road Side Sensors
- 2015
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 15:9, s. 5075-5086
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Tidskriftsartikel (refereegranskat)abstract
- This article shows how a particle smoother based system identification method can be applied for estimating the trajectory of road vehicles. As sensors, a combination of an accelerometer measuring the road surface vibrations and a magnetometer measuring magnetic disturbances mounted on the side of the road are considered. First, sensor models describing the measurements of the two sensors are introduced. It is shown that these depend on unknown, static parameters that have to be considered in the estimation. Second, the sensor models are combined with a two-dimensional constant velocity motion model. Third, the system identification algorithm is introduced which iteratively runs a Rao-Blackwellized particle smoother to estimate the vehicle trajectory followed by an expectation-maximization step to estimate the parameters. Finally, the method is applied to both simulation and measurement data. It is found that the method works well in general and some issues when real data is considered are identified as future work.
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| 5. |
- Jonsson, Patrik, 1968-, et al.
(författare)
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Road surface status classification using spectral analysis of NIR camera images
- 2015
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 15:3, s. 1641-1656
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Tidskriftsartikel (refereegranskat)abstract
- There is a need for an automated road status classification system considering the vast number of weather-related accidents that occur every winter. Previous research has shown that it is possible to detect hazardous road conditions, including, for example, icy pavements, using single point infrared illumination and infrared detectors. In this paper, we extend this research into camera surveillance of a road section allowing for classification of area segments of weather-related road surface conditions such as wet, snow covered, or icy. Infrared images have been obtained using an infrared camera equipped with a set of optical wavelength filters. The images have primarily been used to develop multivariate data models and also for the classification of road conditions in each pixel. This system is a vast improvement on existing single spot road status classification systems. The resulting imaging system can reliably distinguish between dry, wet, icy, or snow covered sections on road surfaces.
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| 6. |
- Ponzoni, Andrea, et al.
(författare)
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Metal oxide nanowire and thin-film-based gas sensors for chemical warfare simulants detection
- 2008
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 8:6, s. 735-742
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Tidskriftsartikel (refereegranskat)abstract
- This work concerns with metal oxide (MOX) gas sensors based on nanowires and thin films. We focus on chemical warfare agents (CWAs) detection to compare these materials from the functional point-of-view. We work with different chemicals including simulants for Sarin nerve agents, vescicant gases, cyanide agents, and analytes such as ethanol, acetone, ammonia, and carbon monoxide that can be produced by everyday activities causing false alarms. Explorative data analysis has been used to demonstrate the different sensing performances of nanowires and thin films. Within the chosen application, our analysis reveal that the introduction of nanowires inside the array composed by thin films can improve its sensing capability. Cyanide simulants have been detected at concentrations close to 1 ppm, lower than the Immediately Dangerous for Life and Health (IDLH) value of the respective warfare agent. Higher sensitivity has been obtained to simulants for Sarin and vescicant gases, which have been detected at concentrations close or even lower than 100 ppb. Results demonstrate the suitability of the proposed array to selectively detect CWA simulants with respect to some compounds produced by everyday activities. © 2008 IEEE.
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| 7. |
- Sakai, Kazuya, et al.
(författare)
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A Framework for the Optimal k-Coverage Deployment Patterns of Wireless Sensors
- 2015
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 15:12, s. 7273-7283
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Tidskriftsartikel (refereegranskat)abstract
- The strategy for node deployment to achieve multiple connectivity and coverage plays an important role in various wireless senor network applications. To alleviate the operational cost, the number of nodes to be deployed needs to be reduced. While the optimal k-connectivity deployment patterns (k <= 6) and the multiple k-coverage problem (k <= 3) have been extensively studied for 2-D networks, a general method to identify the optimal deployment pattern for any given sensor coverage requirement has yet to be found. Considering the ease of sensor deployment and operation, the deployment patterns should be identical and symmetric in the deployment region. This implies that the Voronoi diagram of the optimal deployment is a regular tessellation. Based on the fact that there exist only three regular tessellations, we propose a framework, namely, range elimination scheme (RES), to compute the optimal k-coverage deployment pattern for any given k value to accommodate various wireless sensor application requirements. We apply RES to show the optimal k-coverage deployment patterns for 4 <= k <= 9. Our analytical and simulation results show that our proposed framework successfully identifies the optimal deployment patterns and significantly reduces the number of sensors to be deployed
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| 8. |
- Sarkar, Chayan, et al.
(författare)
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VSF: An Energy-Efficient Sensing Framework Using Virtual Sensors
- 2016
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 16:12, s. 5046-5059
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we describe virtual sensing framework (VSF), which reduces sensing and data transmission activities of nodes in a sensor network without compromising on either the sensing interval or data quality. VSF creates virtual sensors (VSs) at the sink to exploit the temporal and spatial correlations amongst sensed data. Using an adaptive model at every sensing iteration, the VSs can predict multiple consecutive sensed data for all the nodes with the help of sensed data from a few active nodes. We show that even when the sensed data represent different physical parameters (e.g., temperature and humidity), our proposed technique still works making it independent of physical parameter sensed. Applying our technique can substantially reduce data communication among the nodes leading to reduced energy consumption per node yet maintaining high accuracy of the sensed data. In particular, using VSF on the temperature data from IntelLab and GreenOrb data set, we have reduced the total data traffic within the network up to 98% and 79%, respectively. Corresponding average root mean squared error of the predicted data per node is as low as 0.36 degrees C and 0.71 degrees C, respectively. This paper is expected to support deployment of many sensors as part of Internet of Things in large scales.
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| 9. |
- Verdel, Nina, et al.
(författare)
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Reliability and validity of running step rate derived from a novel wearable Smart Patch
- 2024
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Ingår i: IEEE Sensors Journal. - : IEEE. - 1530-437X .- 1558-1748. ; 24:9, s. 14343-14351
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Tidskriftsartikel (refereegranskat)abstract
- A novel, wearable, stretchable Smart Patch can monitor various aspects of physical activity, including the dynamics of running. However, like any new device developed for such applications, it must first be tested for validity and reliability. Here, we compare the step rate while running on a treadmill measured by this smart patch with the corresponding values obtained with the ”gold standard” OptoGait, as well as with other devices commonly used to assess running dynamics, i.e., the MEMS accelerometer and commercially available and widely used Garmin Running Dynamic Pod. The 14 healthy, physically active volunteers completed two identical sessions with a 5-minute rest between. Each session involved two one-minute runs at 11 km/h and 14 km/h separated by a one-min rest. The major finding was that the Smart Patch demonstrated fair to good test-retest reliability. The best test-retest reliability for the Running Pod was observed in connection with running at 11 km/h and both velocities combined (good and excellent, respectively) and for the OptoGait when running at 14 km/h (good). The best concurrent validity was achieved with the Smart Patch, as reflected in the highest Pearson correlation coefficient for this device when running at 11 or 14 km/h, as well as for both velocities combined. In conclusion, this study demonstrates that the novel wearable Smart Patch shows promising reliability and excellent concurrent validity in measuring step rate during treadmill running, making it a viable tool for both research and practical applications in sports and exercise science.
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| 10. |
- Wan, Jiafu, et al.
(författare)
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Software-Defined Industrial Internet of Things in the Context of Industry 4.0
- 2016
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 16:20, s. 7373-7380
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, there have been great advances in industrial Internet of Things (IIoT) and its related domains, such as industrial wireless networks (IWNs), big data, and cloud computing. These emerging technologies will bring great opportunities for promoting industrial upgrades and even allow the introduction of the fourth industrial revolution, namely, Industry 4.0. In the context of Industry 4.0, all kinds of intelligent equipment (e.g., industrial robots) supported by wired or wireless networks are widely adopted, and both real-time and delayed signals coexist. Therefore, based on the advancement of software-defined networks technology, we propose a new concept for industrial environments by introducing software-defined IIoT in order to make the network more flexible. In this paper, we analyze the IIoT architecture, including physical layer, IWNs, industrial cloud, and smart terminals, and describe the information interaction among different devices. Then, we propose a software-defined IIoT architecture to manage physical devices and provide an interface for information exchange. Subsequently, we discuss the prominent problems and possible solutions for software-defined IIoT. Finally, we select an intelligent manufacturing environment as an assessment test bed, and implement the basic experimental analysis. This paper will open a new research direction of IIoT and accelerate the implementation of Industry 4.0.
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