| 1. |
- Abdalla, Suliman, et al.
(author)
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Architecture and Circuit Design for Color X-Ray Pixal Array Detector Read-Out Electronics
- 2007
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In: 24th Norchip Conference, 2006. - New York : IEEE conference proceedings. - 9781424407729 ; , s. 271-276
-
Conference paper (peer-reviewed)abstract
- This paper proposes an area- and power-efficient implementation of the read-out electronics for color X-ray pixel detectors for imaging. Introducing multiple levels of energy discrimination will increase the complexity of the read-out electronics in each pixel. The proposed architecture has full resolution for the intensity and reduced resolution for the energy spectrum (color), which leads to a good compromise of image quality and circuit complexity. We show that the increase in complexity, compared to single energy-range pixel, will lead to increase in circuit area of less than 20%.
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| 2. |
- Ahmad, Naeem, et al.
(author)
-
A taxonomy of visual surveillance systems
- 2013
-
Reports (other academic/artistic)abstract
- The increased security risk in society and the availability of low cost sensors and processors has expedited the research in surveillance systems. Visual surveillance systems provide real time monitoring of the environment. Designing an optimized surveillance system for a given application is a challenging task. Moreover, the choice of components for a given surveillance application out of a wide spectrum of available products is not an easy job. In this report, we formulate a taxonomy to ease the design and classification of surveillance systems by combining their main features. The taxonomy is based on three main models: behavioral model, implementation model, and actuation model. The behavioral model helps to understand the behavior of a surveillance problem. The model is a set of functions such as detection, positioning, identification, tracking, and content handling. The behavioral model can be used to pinpoint the functions which are necessary for a particular situation. The implementation model structures the decisions which are necessary to implement the surveillance functions, recognized by the behavioral model. It is a set of constructs such as sensor type, node connectivity and node fixture. The actuation model is responsible for taking precautionary measures when a surveillance system detects some abnormal situation. A number of surveillance systems are investigated and analyzed on the basis of developed taxonomy. The taxonomy is general enough to handle a vast range of surveillance systems. It has organized the core features of surveillance systems at one place. It may be considered an important tool when designing surveillance systems. The designers can use this tool to design surveillance systems with reduced effort, cost, and time.
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| 3. |
- Ahmad, Naeem, et al.
(author)
-
Cost Optimization of a Sky Surveillance Visual Sensor Network
- 2012
-
In: Proceedings of SPIE - The International Society for Optical Engineering. - Belgium : SPIE - International Society for Optical Engineering. - 9780819491299 ; , s. Art. no. 84370U-
-
Conference paper (peer-reviewed)abstract
- A Visual Sensor Network (VSN) is a network of spatially distributed cameras. The primary difference between VSN and other type of sensor network is the nature and volume of information. A VSN generally consists of cameras, communication, storage and central computer, where image data from multiple cameras is processed and fused. In this paper, we use optimization techniques to reduce the cost as derived by a model of a VSN to track large birds, such as Golden Eagle, in the sky. The core idea is to divide a given monitoring range of altitudes into a number of sub-ranges of altitudes. The sub-ranges of altitudes are monitored by individual VSNs, VSN1 monitors lower range, VSN2 monitors next higher and so on, such that a minimum cost is used to monitor a given area. The VSNs may use similar or different types of cameras but different optical components, thus, forming a heterogeneous network. We have calculated the cost required to cover a given area by considering an altitudes range as single element and also by dividing it into sub-ranges. To cover a given area with given altitudes range, with a single VSN requires 694 camera nodes in comparison to dividing this range into sub-ranges of altitudes, which requires only 96 nodes, which is 86% reduction in the cost.
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| 4. |
- Ahmad, Naeem, et al.
(author)
-
Model and placement optimization of a sky surveillance visual sensor network
- 2011
-
In: Proceedings - 2011 International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA 2011. - : IEEE Computer Society. - 9781457714559 ; , s. 357-362
-
Conference paper (peer-reviewed)abstract
- Visual Sensor Networks (VSNs) are networks which generate two dimensional data. The major difference between VSN and ordinary sensor network is the large amount of data. In VSN, a large number of camera nodes form a distributed system which can be deployed in many potential applications. In this paper we present a model of the physical parameters of a visual sensor network to track large birds, such as Golden Eagle, in the sky. The developed model is used to optimize the placement of the camera nodes in the VSN. A camera node is modeled as a function of its field of view, which is derived by the combination of the lens focal length and camera sensor. From the field of view and resolution of the sensor, a model for full coverage between two altitude limits has been developed. We show that the model can be used to minimize the number of sensor nodes for any given camera sensor, by exploring the focal lengths that both give full coverage and meet the minimum object size requirement. For the case of large bird surveillance we achieve 100% coverage for relevant altitudes using 20 camera nodes per km2 for the investigated camera sensors.
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| 5. |
- Ahmad, Naeem, et al.
(author)
-
Model, placement optimization and verification of a sky surveillance visual sensor network
- 2013
-
In: International Journal of Space-Based and Situated Computing (IJSSC). - 2044-4893 .- 2044-4907. ; 3:3, s. 125-135
-
Journal article (peer-reviewed)abstract
- A visual sensor network (VSN) is a distributed system of a large number of camera nodes, which generates two dimensional data. This paper presents a model of a VSN to track large birds, such as golden eagle, in the sky. The model optimises the placement of camera nodes in VSN. A camera node is modelled as a function of lens focal length and camera sensor. The VSN provides full coverage between two altitude limits. The model can be used to minimise the number of sensor nodes for any given camera sensor, by exploring the focal lengths that fulfils both the full coverage and minimum object size requirement. For the case of large bird surveillance, 100% coverage is achieved for relevant altitudes using 20 camera nodes per km² for the investigated camera sensors. A real VSN is designed and measurements of VSN parameters are performed. The results obtained verify the VSN model.
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| 6. |
- Ahmad, Naeem, et al.
(author)
-
Modeling and Verification of a Heterogeneous Sky Surveillance Visual Sensor Network
- 2013
-
In: International Journal of Distributed Sensor Networks. - : SAGE Publications. - 1550-1329 .- 1550-1477. ; , s. Art. id. 490489-
-
Journal article (peer-reviewed)abstract
- A visual sensor network (VSN) is a distributed system of a large number of camera nodes and has useful applications in many areas. The primary difference between a VSN and an ordinary scalar sensor network is the nature and volume of the information. In contrast to scalar sensor networks, a VSN generates two-dimensional data in the form of images. In this paper, we design a heterogeneous VSN to reduce the implementation cost required for the surveillance of a given area between two altitude limits. The VSN is designed by combining three sub-VSNs, which results in a heterogeneous VSN. Measurements are performed to verify full coverage and minimum achieved object image resolution at the lower and higher altitudes, respectively, for each sub-VSN. Verification of the sub-VSNs also verifies the full coverage of the heterogeneous VSN, between the given altitudes limits. Results show that the heterogeneous VSN is very effective to decrease the implementation cost required for the coverage of a given area. More than 70% decrease in cost is achieved by using a heterogeneous VSN to cover a given area, in comparison to homogeneous VSN. © 2013 Naeem Ahmad et al.
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| 7. |
- Ahmad, Naeem
(author)
-
Modelling and optimization of sky surveillance visual sensor network
- 2012
-
Licentiate thesis (other academic/artistic)abstract
- A Visual Sensor Network (VSN) is a distributed system of a largenumber of camera sensor nodes. The main components of a camera sensornode are image sensor, embedded processor, wireless transceiver and energysupply. The major difference between a VSN and an ordinary sensor networkis that a VSN generates two dimensional data in the form of an image, whichcan be exploited in many useful applications. Some of the potentialapplication examples of VSNs include environment monitoring, surveillance,structural monitoring, traffic monitoring, and industrial automation.However, the VSNs also raise new challenges. They generate large amount ofdata which require higher processing powers, large bandwidth requirementsand more energy resources but the main constraint is that the VSN nodes arelimited in these resources.This research focuses on the development of a VSN model to track thelarge birds such as Golden Eagle in the sky. The model explores a number ofcamera sensors along with optics such as lens of suitable focal length whichensures a minimum required resolution of a bird, flying at the highestaltitude. The combination of a camera sensor and a lens formulate amonitoring node. The camera node model is used to optimize the placementof the nodes for full coverage of a given area above a required lower altitude.The model also presents the solution to minimize the cost (number of sensornodes) to fully cover a given area between the two required extremes, higherand lower altitudes, in terms of camera sensor, lens focal length, camera nodeplacement and actual number of nodes for sky surveillance.The area covered by a VSN can be increased by increasing the highermonitoring altitude and/or decreasing the lower monitoring altitude.However, it also increases the cost of the VSN. The desirable objective is toincrease the covered area but decrease the cost. This objective is achieved byusing optimization techniques to design a heterogeneous VSN. The core ideais to divide a given monitoring range of altitudes into a number of sub-rangesof altitudes. The sub-ranges of monitoring altitudes are covered by individualsub VSNs, the VSN1 covers the lower sub-range of altitudes, the VSN2 coversthe next higher sub-range of altitudes and so on, such that a minimum cost isused to monitor a given area.To verify the concepts, developed to design the VSN model, and theoptimization techniques to decrease the VSN cost, the measurements areperformed with actual cameras and optics. The laptop machines are used withthe camera nodes as data storage and analysis platforms. The area coverage ismeasured at the desired lower altitude limits of homogeneous as well asheterogeneous VSNs and verified for 100% coverage. Similarly, the minimumresolution is measured at the desired higher altitude limits of homogeneous aswell as heterogeneous VSNs to ensure that the models are able to track thebird at these highest altitudes.
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| 8. |
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| 9. |
- Ahmad, Naeem, et al.
(author)
-
Solution space exploration of volumetric surveillance using a general taxonomy
- 2013
-
In: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819495044 ; , s. Art. no. 871317-
-
Conference paper (peer-reviewed)abstract
- Visual surveillance systems provide real time monitoring of the events or the environment. The availability of low cost sensors and processors has increased the number of possible applications of these kinds of systems. However, designing an optimized visual surveillance system for a given application is a challenging task, which often becomes a unique design task for each system. Moreover, the choice of components for a given surveillance application out of a wide spectrum of available alternatives is not an easy job. In this paper, we propose to use a general surveillance taxonomy as a base to structure the analysis and development of surveillance systems. We demonstrate the proposed taxonomy for designing a volumetric surveillance system for monitoring the movement of eagles in wind parks aiming to avoid their collision with wind mills. The analysis of the problem is performed based on taxonomy and behavioral and implementation models are identified to formulate the solution space for the problem. Moreover, we show that there is a need for generalized volumetric optimization methods for camera deployment.
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| 10. |
- Alam, Anzar, et al.
(author)
-
Online surface characterization of paper and paperboards in a wide-range of the spatial wavelength spectrum
- 2012
-
In: Applied Surface Science. - : Elsevier BV. - 0169-4332 .- 1873-5584. ; 258:20, s. 7928-7935
-
Journal article (peer-reviewed)abstract
- In the paper industry, surface topography is the essence of both paper and paperboard, and accurate topographical measurements are equally essential in order to achieve a uniform smooth surface. The traditional laboratory methods measure only a few samples from the entire tambour and there are other obvious limitations to this approach. Online measurements may be of significant value to improve the surface quality throughout the production. Roughness is one of the topography components and the majority of techniques measure paper by means of a single predictor of average roughness, R a which is inadequate in providing a comprehensive characterization of the surface. Measurements, in a wide range ofwavelengths, can characterize topography components such as roughness, waviness, cockling, etc. Online measurements were taken for various grades of 8 paper reels, containing the wireside and topsides for newspaper, and uncoated and coated sides of paperboards. Their surfacecharacterization, in the spatial wavelength spectrum, from 0.1 to 10 mm was obtained. This article presents the online characterizationresults which have efficiently distinguished the surfaces of same family materials including the edge and the middle position reels of fine coatedpaperboard. Online measurements were taken, at Iggesund Paperboard Pilot Coater in Sweden, by using a recently developed OnlineTopography (OnTop) device which is based on the principle of light triangulation. © 2012 Elsevier B.V. All rights reserved.
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| 11. |
- Alam, Anzar, et al.
(author)
-
Online surface roughness characterization of paper and paperboard using a line of light triangulation technique
- 2012
-
In: Nordic Pulp & Paper Research Journal. - 0283-2631 .- 2000-0669. ; 27:3, s. 662-670
-
Journal article (peer-reviewed)abstract
- Within both the paper and paperboard industries, real time monitoring and measurement of surface roughness of a paper moving at high velocities is an important and challenging area of research. The uniform surface, for an entire production, can be effectively achieved by monitoring and controlling the paper surface roughness, in real time during the manufacturing steps. Presently the majority of paper industries rely on traditional laboratory profilometers. The obvious limitations of lab profilometers are that these are slow, do not measure the quality of entire reels but rather deal with only a few small pieces of samples taken from the end of the reels and it is difficult to make any possible correction in the productionlines without knowing the online roughness data. To eradicate the disadvantages associated with conventional measurements, an online prototype instrument has been developed that measures the surface roughness during the manufacturing steps, and is based on a line of lighttriangulation technique. The prototype technique will be of assistance in ensuring tight process control in order to maintain both a better and auniform quality throughout the entire production. It measures the whole reel, meter by meter, in traditional units of roughness and is also capable of characterizing the topography in a wide range of wavelength spectra. The article presents the online analyses results obtained from the developed prototype. The real time measurements, in a paperboard pilot mill, have successfully characterized and distinguished 16 different grades of newspaper and paperboard reels including reels which have the same family of quality grades and materials.
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| 12. |
- Alam, Mohammad Anzar, et al.
(author)
-
Investigation of the surface topographical differences between the Cross Direction and the Machine Direction for newspaper and paperboard
- 2011
-
In: Nordic Pulp & Paper Research Journal. - 0283-2631 .- 2000-0669. ; 26:4, s. 468-475
-
Journal article (peer-reviewed)abstract
- Paper and paperboard surface quality is constantly being improved by the industry. This improvement work deals with the essential fact that the surface topography must be measured, both in relation to offline and online measurements for the manufactured products. Most measurements relating to surface topography (especially online) are performed either in the machine direction (MD) or in the cross direction (CD). It has been the opinion of SCA Ortviken AB and Iggesund Paperboard AB that the surface topography amplitudes are almost always higher in the CD than in the MD, for their products which consist of newspaper and paperboard. This article aims to investigate the rela-tionship between the CD and the MD surface topography amplitudes for a wide range of spatial wavelength for both newspaper and paperboard. The tests and investiga-tions have been conducted using an FRT Microprof profilometer within the range 20 μm up to 8 mm, and the results confirm that the surface topography amplitudes are higher in the CD for most of the shorter spatial wavelength within this range. The results also show significant differences between measurements for different paper qualities, suggesting a requirement to investigate the relationship between the CD and the MD topography for all paper and paperboard qualities of interest for a paper or paperboard mill, before a decision is made in relation to a measurement method.
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| 13. |
- Alam, Mohammad Anzar, et al.
(author)
-
Limitation of a line-of-light online paper surface measurement system
- 2014
-
In: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 14:8, s. 2715-2724
-
Journal article (peer-reviewed)abstract
- A new prototype device has been developed based on a laser triangulation principle to measure online surface topography in the paper and paperboard industries. It characterizes the surface in a wide spatial scale of topography from 0.09-10 mm. The prototype's technique projects a narrow line-of-light perpendicularly onto the moving paper-Web surface and scattered reflected light is collected at a low angle, low specular, and reduced coherent length onto the CCD sensors synchronized with the laser sources. The scattering phenomenon determines surface deviations in the z-direction. The full-width, at half-maximum of a laser line in cross section is sensitive in computation of the surface topography. The signal processing aspect of the image processing, for example, threshold and filtering algorithms are also sensitive in estimating the accurate surface features. Moreover, improper light illumination, intensity, reflection, occlusion, surface motion, and noise in the imaging sensor, and so forth, all contribute to deteriorate the measurements. Optical techniques measure the surface indirectly and, in general, an evaluation of the performance and the limitations of the technique are both essential and challenging. The paper describes the accuracy, uncertainty, and limitations of the developed technique in the raw profiles and in terms of the rms roughness. The achieved image subpixel resolution is 0.01 times a pixel. Statistically estimated uncertainty (2σ) in the laboratory environment was found 0.05 μm for a smooth sample, which provides a 95% confidence level in the rms roughness results. The depth of field of the prototype is ~2.4 mm.
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| 14. |
- Alam, Mohammad Anzar
(author)
-
Online optical method for real-time surface measurement using line-of-light triangulation
- 2013
-
Doctoral thesis (other academic/artistic)abstract
- Real time paper surface-web measurement is one of the challenging research fields. The traditional laboratory method has many limitations and is unable to measure the entire tambour during the manufacturing process. It has been necessary to develop an online technique that could measure the surface topography in real time. An optical technique was developed, based on laser triangulation, and is applied to develop a new prototype device, which characterizes high speed paper-web surfaces over a wide scale of spatial wavelengths spectrum and computes the surface roughness in real time. The used multi channel pulsed laser diode, source of illumination onto the paper-web, is of benefit due to its low coherence length and is capable to deliver a powerful burst of light beam over a 1 µs duration, which delivers energy of 100 µJ per pulse. The short exposure time avoids blurriness in the acquired images which could possible due to the high speed and vibrations on the paper-web.The laser beam is shaped into a narrow line-of-light using cylindrical lenses and is projected onto a paper-web surface, which covers a physical length of about 210 mm. The created line-of-light cross section full width at half maximum, FWHM Gaussian distribution, is 2-3 pixels on the image. The line-of-light is projected onto the paper-web perpendicular to the plane of the surface. The low angled, low specular, reduced coherence length, scattered reflected laser line is captured by the 3 CCD sensors, which are synchronized with the laser source. The low specular light ensures to avoid saturation of the imaging sensors if the surface is very smooth, and obliquely captures the z-directional fine feature of the surface.The scattered phenomenon of the reflected light is responsible for the surface irregularity measurements. The basic image processing algorithm is applied in order to remove noise and cropped the images widthwise so that only pixels above a preset threshold gray level can be processed, which enables efficient real time measurement. The image is transformed into a 1D array using the center of gravity, COG. The accuracy and precision of the COG depends on the line-of-light FWHM, which, in turn, is responsible for the accuracy, noise and the resolution of the developed technique. The image subpixel resolution achieved is 0.01 times a pixel and uuncertainty in the raw data is 0.43 µm while it is 0.05 µm in the rms roughness.The signal processing steps combining the B-Spline filter and the filter in the spatial frequency domain were employed in order to separate roughness, waviness, and form and position error in the raw profile. The prototype is designed to measure online surface roughness and to characterize surface in a spatial wavelength spectrum from 0.09 to 30 mm, which is extendable to any required spatial range in order to cover a wide scale surface feature such as micro roughness, macro roughness and waviness. It is proven that exploitation of a simple laser triangulation technique could lead to an improvement in the overall quality and efficiency in the paper and paperboard industries and it can also be of potential interest for the other surface characterization problems.
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| 15. |
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| 16. |
- Alam, Mohammad Anzar, et al.
(author)
-
Real time surface measurement technique in a wide range of wavelengths spectrum
- 2014
-
In: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 14:1, s. 285-294
-
Journal article (peer-reviewed)abstract
- Real time surface topography measurement in the paper and paperboard industries is a challenging research field. The existing online techniques measure only a small area of paper surface and estimate topographical irregularities in a narrow scale as a single predictor. Considering the limitations and complications in measuring the surface at high speed, a laser line triangulation technique is explored to measure surface topography in a wide scale. The developed technique is new for the paper and paperboard application that scans a line onto the paper-web surface up to 210 mm in length in the cross machine direction. The combination of a narrow laser linewidth imaging, a subpixel resolution, and the selection of a unique measurement location has made it possible to measure roughness and simultaneously characterize paper surface topography from 0.1 to 30 mm spatial wavelength. This spatial range covers wide scale surface properties such as roughness, cockling, and waviness. The technique clearly distinguishes and characterizes the surface of newspaper, and lightweight coated, coated, and uncoated paperboard in real time during the paper manufacturing process. The system temporal noise for the average roughness is estimated as 37 dB. The signal to noise ratio found is from 5.4 to 8.1 in the short spatial wavelength up to 1 mm, whereas it is more than 75 in the long spatial wavelength from 5 to 10 mm.
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| 17. |
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| 18. |
- Alqaysi, Hiba, et al.
(author)
-
A temporal boosted yolo-based model for birds detection around wind farms
- 2021
-
In: Journal of Imaging. - : MDPI AG. - 2313-433X. ; 7:11
-
Journal article (peer-reviewed)abstract
- Object detection for sky surveillance is a challenging problem due to having small objects in a large volume and a constantly changing background which requires high resolution frames. For example, detecting flying birds in wind farms to prevent their collision with the wind turbines. This paper proposes a YOLOv4-based ensemble model for bird detection in grayscale videos captured around wind turbines in wind farms. In order to tackle this problem, we introduce two datasets—(1) Klim and (2) Skagen—collected at two locations in Denmark. We use Klim training set to train three increasingly capable YOLOv4 based models. Model 1 uses YOLOv4 trained on the Klim dataset, Model 2 introduces tiling to improve small bird detection, and the last model uses tiling and temporal stacking and achieves the best mAP values on both Klim and Skagen datasets. We used this model to set up an ensemble detector, which further improves mAP values on both datasets. The three models achieve testing mAP values of 82%, 88%, and 90% on the Klim dataset. mAP values for Model 1 and Model 3 on the Skagen dataset are 60% and 92%. Improving object detection accuracy could mitigate birds’ mortality rate by choosing the locations for such establishment and the turbines location. It can also be used to improve the collision avoidance systems used in wind energy facilities.
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| 19. |
- Alqaysi, Hiba
(author)
-
Cost Optimization of Volumetric Surveillance for Sky Monitoring : Towards Flying Object Detection and Positioning
- 2022
-
Doctoral thesis (other academic/artistic)abstract
- Unlike surface surveillance, volumetric monitoring deals with three-dimensional target space and moving objects within it. In sky monitoring, objects fly within outdoor and often remote volumes, such as wind farms and airport runways. Therefore, multiple cameras should be implemented to monitor these volumes and analyze flying activities.Due to that, challenges in designing and deploying volumetric surveillance systems for these applications arise. These include configuring the multi-camera node placement, coverage, cost, and the system's ability to detect and position flying objects.The research in this dissertation focuses on three aspects to optimize volumetric surveillance systems in sky monitoring applications. First, the node placement and coverage should be considered in accordance with the monitoring constraints. Also, the node architecture should be configured to minimize the design cost and maximize the coverage. Last, the system should detect small flying objects with good accuracy.Placing the multi-camera nodes in a hexagonal pattern while allowing overlap between adjacent nodes optimizes the placement. The inclusion of monitoring constraints like monitoring altitude and detection pixel resolution influences the node design. Furthermore, presented results show that modeling the multi-camera nodes as a cylinder rather than a hemisphere minimizes the cost of each node. The design exploration in this thesis provides a method to minimize the node cost based on defined design constraints. It also maximizes the coverage in terms of the number of square meters per dollar. Surveillance systems for sky monitoring should be able to detect and position flying objects. Therefore, two new annotated datasets were introduced that can be used for developing in-flight birds detection methods. The datasets were collected by Mid Sweden University at two locations in Denmark. A YOLOv4-based model for birds detection in 4k grayscale videos captured in wind farms is developed. The model overcomes the problem of detecting small objects in dynamic background, and it improves detection accuracy through tiling and temporal information incorporation, compared to the standard YOLOv4 and background subtraction.
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| 20. |
- Alqaysi, Hiba, et al.
(author)
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Cost Optimized Design of Multi-Camera Domefor Volumetric Surveillance
- 2021
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In: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 21:3, s. 3730-3737
-
Journal article (peer-reviewed)abstract
- A multi-camera dome consists of number ofcameras arranged in layers to monitor a hemisphere aroundits center. In volumetric surveillance,a 3D space is required tobemonitoredwhich can be achievedby implementing numberof multi-camera domes. A monitoring height is consideredas a constraint to ensure full coverage of the space belowit. Accordingly, the multi-camera dome can be redesignedinto a cylinder such that each of its multiple layers hasdifferent coverage radius. Minimum monitoring constraintsshould be met at all layers. This work is presenting a costoptimized design for the multi-camera dome that maximizesits coverage. The cost per node and number of squaremetersper dollar of multiple configurations are calculated using asearch space of cameras and considering a set of monitoring and coverage constraints. The proposed design is costoptimized per node and provides more coverage as compared to the hemispherical multi-camera dome.
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| 21. |
- Alqaysi, Hiba, et al.
(author)
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Design Exploration of Multi-Camera Dome
- 2019
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In: ICDSC 2019 Proceedings of the 13th International Conference on Distributed Smart Cameras. - New York, NY : ACM Digital Library. - 9781450371896
-
Conference paper (peer-reviewed)abstract
- Visual monitoring systems employ distributed smart cameras toeffectively cover a given area satisfying specific objectives. Thechoice of camera sensors and lenses and their deployment affectsdesign cost, accuracy of the monitoring system and the ability toposition objects within the monitored area. Design cost can bereduced by investigating deployment topology such as groupingcameras together to form a dome at a node and optimize it formonitoring constraints. The constraints may include coverage area,number of cameras that can be integrated in a node and pixelresolution at a given distance. This paper presents a method foroptimizing the design cost of multi-camera dome by analyzing tradeoffsbetween monitoring constraints. The proposed method can beused to reduce monitoring cost while fulfilling design objectives.Results show how to increase coverage area for a given cost byrelaxing requirements on design constraints. Multi-camera domescan be used in sky monitoring applications such as monitoring windparks and remote air-traffic control of airports where all-round fieldof view about a point is required to monitor.
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| 22. |
- Alqaysi, Hiba, et al.
(author)
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Evaluating Coverage Effectiveness of Multi-Camera Domes Placement for Volumetric Surveillance
- 2017
-
In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450354875 ; , s. 49-54
-
Conference paper (peer-reviewed)abstract
- Multi-camera dome is composed of a number of cameras arranged to monitor a half sphere of the sky. Designing a network of multi-camera domes can be used to monitor flying activities in open large area, such as birds' activities in wind parks. In this paper, we present a method for evaluating the coverage effectiveness of the multi-camera domes placement in such areas. We used GPS trajectories of free flying birds over an area of 9 km2 to analyze coverage effectiveness of randomly placed domes. The analysis is based on three criteria namely, detection, positioning and the maximum resolution captured. The developed method can be used to evaluate results of designing and optimizing dome placement algorithms for volumetric monitoring systems in order to achieve maximum coverage.
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| 23. |
- Alqaysi, Hiba, et al.
(author)
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Full Coverage Optimization for Multi Camera Dome Placement in Volumetric Monitoring
- 2018
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In: ACM International Conference Proceeding Series. - New York, NY, USA : ACM Digital Library. - 9781450365116
-
Conference paper (peer-reviewed)abstract
- Volumetric monitoring can be challenging due to having a 3D target space and moving objects within it. Multi camera dome is proposed to provide a hemispherical coverage of the 3D space around it. This paper introduces a method that optimizes multi camera placement for full coverage in volumetric monitoring system. Camera dome placement is modeled in a volume by adapting the hexagonal packing of circles to provide full coverage at a given height, and 100% detection of flying objects within it. The coverage effectiveness of different placement configurations was assessed using an evaluation environment. The proposed placement is applicable in designing and deploying surveillance systems for remote outdoor areas, such as sky monitoring in wind farms and airport runways in order to record and analyze flying activities.
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| 24. |
- Anwar, Qaiser, et al.
(author)
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Intelligence Partitioning as a Method for Architectural Exploration of Wireless Sensor Node
- 2016
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In: Proceedings of the International Conference on Computational Science and Computational Intelligence (CSCI), 2016.. - : IEEE Press. - 9781509055104 ; , s. 935-940
-
Conference paper (peer-reviewed)abstract
- Embedded systems with integrated sensing, processing and wireless communication are driving future connectivity concepts such as Wireless Sensor Networks (WSNs) and Internet of Things (IoTs). Because of resource limitations, there still exists a number of challenges such as low latency and energy consumption to realize these concepts to full potential. To address and understand these challenges, we have developed and employed an intelligence partitioning method which generates different implementation alternatives by distributing processing load across multiple nodes. The task-to-node mapping has exponential complexity which is hard to compute for a large scale system. Regarding this, our method provides recommendation to handle and minimize such complexity for a large system. Experiments on a use-case concludes that the proposed method is able to identify unfavourable architecture solutions in which forward and backword communication paths exists in task-to-node mapping. These solution can be avoided for further architectural exploration, thus limiting the space for architecture exploration of a sensor node.
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| 25. |
- Aurangzeb, Khursheed, et al.
(author)
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Analysis of Binary Image Coding Methods for Outdoor Applications of Wireless Vision sensor Networks
- 2018
-
In: IEEE Access. - 2169-3536. ; 6, s. 16932-16941
-
Journal article (peer-reviewed)abstract
- The processing of images at the vision sensor nodes (VSN) requires a high computation power and their transmission requires a large communication bandwidth. The energy budget is limited in outdoor applications of wireless vision sensor networks (WVSN). This means that both the processing of images at the VSN and the communication to server must be energy efficient. The wireless communication of uncompressed data consumes huge amounts of energy. Data compression methods are efficient in reducing data in images and can be used for the reduction in transmission energy. We have evaluated seven binary image coding techniques. Our evaluation is based on the processing complexity and energy consumption of the compression methods on the embedded platforms. The focus is to come up with a binary image coding method, which has good compression efficiency and short processing time. An image coding method with such attributes will result in reduced total energy requirement of the node. We have used both statistically generated images and real captured images, in our experiments. Based on our results, we conclude that International Telegraph and Telephone Consultative Committee Group 4, gzip_pack and JPEG-LS are suitable coding methods for the outdoor applications of WVSNs.
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| 26. |
- Aurangzeb, Khursheed, et al.
(author)
-
Data Reduction Using Change Coding for Remote Applications of wireless Visual Sensor Networks
- 2018
-
In: IEEE Access. - : IEEE. - 2169-3536. ; 6, s. 37738-37747
-
Journal article (peer-reviewed)abstract
- The data reduction capability of image compression schemes is limited by the underlying compression technique. For applications with minor changes between consecutive frames, change coding can be used to further reduce the data. We explored the efficiency of change coding for data reduction in a wireless visual sensor network (WVSN). This paper presents an analysis of the compression efficiency of change coding for a variety of changes, such as different shapes, sizes, and locations of white objects in adjacent sets of frames. Compressing change frame provides a better performance compared with compressing the original frames for up to 95% changes in the number of objects in adjacent frames. Due to illumination noise, the size of the objects increases at its boundaries, which negatively affects the performance of change coding. We experimentally proved that the negative impact of illumination noise could be reduced by applying morphology on the change frame. Communication energy consumption of the VSN is dependent on the data that are transmitted to the server. Our results show that the communication energy consumption of the VSN can be reduced by 27%, 29%, and 46% by applying change coding in combination with JBIG2, Group4, and Gzip_pack, respectively. The findings presented in this paper will aid researchers in enhancing the compression potential of image coding schemes in the energy-constrained applications of WVSNs.
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| 27. |
- Bader, Sebastian, et al.
(author)
-
Remote image capturing with low-cost and low-power wireless camera nodes
- 2014
-
In: Proceedings of IEEE Sensors. - : IEEE Sensors Council. ; , s. 730-733
-
Conference paper (peer-reviewed)abstract
- Wireless visual sensor networks provide featurerich information about their surrounding and can thus be used as a universal measurement tool for a great number of applications. Existing solutions, however, have mainly been focused on high sample rate applications, such as video surveillance, object detection and tracking. In this paper, we present a wireless camera node architecture that targets low sample rate applications (e.g., manual inspections and meter reading). The major design considerations are a long system lifetime, a small size and a low production cost.We present the overall architecture with its individual design choices, and evaluate the architecture with respect to its application constraints. With a typical image acquisition cost of 1.5 J for medium quality images and a quiescent power demand of only 7 uW, the evaluation results demonstrate that long operation periods of the order of years can be achieved in low sample rate scenarios.
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| 28. |
- Cao, Cao, et al.
(author)
-
A Tool for Low-Power Synthesis of FSMs with Mixed Synchronous/Asynchronous State Memory
- 2004
-
In: 22ND NORCHIP CONFERENCE, PROCEEDINGS. - : IEEE. - 0780385101 ; , s. 199-202
-
Conference paper (peer-reviewed)abstract
- An efficient way to obtain Finite-State Machines (FSMs) with low power consumption is to,partition the machine into two or more sub-FSMs and use dynamic power management, where all sub-FSMs not active are shut down, to reduce dynamic power dissipation. In this paper we focus on FSM partitioning algorithms and RT-level power estimation functions that are the key issues in the design of a CAD tool for synthesis of low-power partitioned FSMS. We target an implementation architecture that is based on both synchronous and asynchronous state memory elements that enables larger power reductions than fully synchronous architectures do. Power reductions of up to 77% have been achieved at a cost of an increase in area of 18%.
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| 29. |
- Cao, Cao, et al.
(author)
-
Synthesis tool for low-power finite-state machines with mixed synchronous/asynchronous state memory
- 2006
-
In: IEE Proceedings - Computers and digital Techniques. - : Institution of Engineering and Technology (IET). - 1350-2387 .- 1359-7027. ; 153:4, s. 243-248
-
Journal article (peer-reviewed)abstract
- An efficient way to obtain finite-state machines (FSMs) with low-power consumption is to partition the machine into two or more sub-FSMs and then use dynamic power management where all sub-FSMs not active are shut down, with the effect of reducing dynamic power dissipation. Thus, FSM partitioning algorithms and register-transfer-level power estimation functions are the main focus of the paper as these are key issues in the design of a computer-aided design tool for synthesis of low-power partitioned FSMs. An implementation architecture is targeted, which is based on both synchronous and asynchronous state memory elements that enable larger power reductions than fully synchronous architectures do. Power reductions of up to 77 have been achieved at a cost of an 18 increase in area.
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| 30. |
- Carratu, M., et al.
(author)
-
A CNN-based approach to measure wood quality in timber bundle images
- 2021
-
In: 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). - : IEEE. - 9781728195391
-
Conference paper (peer-reviewed)abstract
- At present, the Smart Industry is becoming a field of great interest for many worldwide researchers since it allows to experiment and research new advanced techniques. One of the most common explored approaches in operations where image processing has already been a milestone is the use of Convolutional Neural Networks (CNN). Those networks have enhanced the current image processing algorithms, achieving an improvement in decision processes usually based on human experience, where an analytical model is not always available. This paper proposes a novel approach for measuring the number of rotted logs in timber bundles using a CNN trained on thousands of timber log images extracted from bundles. Today, the Swedish forest industry bases the selling price of timber bundles on the evaluation of a visual inspection. This operation is based on human experience to evaluate and measure timber bundles' features, which is necessary to categorize them. The proposed approach has shown promising results compared to the actual visual inspection made by operators showing an F1 score with the best CNN architecture of 0.89.
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| 31. |
- Carratú, Marco, et al.
(author)
-
A novel IVS procedure for handling Big Data with Artificial Neural Networks
- 2020
-
In: 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). - : IEEE. - 9781728144603
-
Conference paper (peer-reviewed)abstract
- In recent times, thanks to the availability of a large quantity of data coming from the industrial process, several techniques based on a data-driven approach could be developed. Between all the data-driven techniques, as Principle Component Regression, Support Vector Machines, Artificial Neural Networks, Neuro-Fuzzy Systems, and many others, the data on which they rely should be analyzed to find correlations and dependencies that could improve their design. For this reason, the Input variable Selection (IVS) process has become of great interest in the recent period. The classical IVS relies on classical statistics, as Pearson coefficients, able to discover linear dependencies among data; today, due to the significant amount of data available, the challenge of also discovering non-linear dependencies appears to be a necessary skill, mainly for the design and development of a neural network. This paper proposes the use of a novel statistical tool named Maximal Information Coefficient (MIC) for developing an IVS procedure able to discover dependencies in a considerable dataset and guide the IVS designer to the selection of input variables in a data-driven application. As a case study, the procedure will be applied to a real application developed in the context of the Swedish forest industry, in order to choose the input variables of a neural network able to estimate the timber bundles volume, which represents an expensive parameter to measure in this context.
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| 32. |
- Carratu, M., et al.
(author)
-
An innovative method for log diameter measurements based on deep learning
- 2023
-
In: 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). - : IEEE. - 9781665453837
-
Conference paper (peer-reviewed)abstract
- The widespread adoption of Deep Learning techniques for Computer Vision in recent years has brought major changes to the world of industry, contributing greatly to this sector's transition to Industry 4.0, also referred to as Smart Industry. This involves an increasingly predominant role of machines and automation within industrial processes. In this context, the Swedish forest industry is an excellent context for applying these techniques. In particular, this work will deal with automating the measurement of log diameters to date carried out manually by operators in the industry. The proposed methodology will use two object detection neural networks, one deputed to detect logs in the scene and the other for the calibrated target. The latter thus allows the camera calibration to be fully automated, enabling each diameter to be measured without any further operations by the operator. The results obtained are satisfactory and open the way for the industrial application of the proposed methodology.
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| 33. |
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| 34. |
- Carratù, M., et al.
(author)
-
Vision-Based System for Measuring the Diameter of Wood Logs
- 2023
-
In: IEEE Open Journal of Instrumentation and Measurement. - : IEEE. - 2768-7236. ; 2, s. 1-12
-
Journal article (peer-reviewed)abstract
- Detecting and measuring objects with vision-based systems in uncontrolled environments is a difficult task that today, thanks to the development of increasingly advanced artificial intelligence-based techniques, can be solved with greater ease. In this context, this article proposes a novel approach for the vision-based measurement of objects in uncontrolled environments using a specific type of convolutional neural network (CNN) named you only look once (YOLO) and a direct linear transformation (DLT) process. The case study concerned designing a novel vision-based system for measuring the diameter of wood logs cut and loaded onto trucks. This problem has been occurring in the Swedish forestry industry. In fact, this operation is not carried out with computer vision algorithms because of the high variability of environmental conditions caused by the changing position of the sun, weather conditions, and the variability of truck positioning. To solve this problem, the YOLO network is proposed to locate logs while attempting to maintain a high Intersection over Union (IoU) value for the correct estimation of log size. Furthermore, in order to obtain accurate measurements, the DLT is used to convert into world coordinates the dimensions of the logs themselves. The proposed CNN-based solution is described after briefly introducing today’s methodologies adopted for wood bundle analysis. Particular attention is paid to both the training and the calibration steps. Results report that for 80% of cases, the error reported has been smaller than 4 cm, representing only 8% of the measurement, considering a mean log diameter for the application of 50 cm.
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| 35. |
- Carratù, Marco, et al.
(author)
-
Wireless Sensor Network Calibration for PM10 Measurement
- 2020
-
In: 2020 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). - : IEEE. - 9781728144337
-
Conference paper (peer-reviewed)abstract
- The proposal of an Advanced Metering Infrastructure based on short-range communication is suggested for the continuous monitoring of Particulate Matter. A prototype of Automatic Measurement System (AMS), including a low-cost off-the-shelf PM sensor, has been developed as a remote node to be adopted in the radio Local Area Network. The results of the system calibration and comparison with the data quality requirements of the PM measurement according to European regulations, as well as the simulation of a typical Smart City scenario in terms of communication performance, confirm the feasibility of the proposed distributed AMS for an effective adoption within an urban area.
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| 36. |
- Cheng, Peng
(author)
-
Applications of embedded sensors in loader crane positioning and rotor RPM measurement
- 2011
-
Doctoral thesis (other academic/artistic)abstract
- In this thesis, two novel applications involving embedded sensors arestudied, one dealing with loader crane positioning and the other involving rotorRevolutions Per Minute (RPM) measurement. The thesis presents a generalintroduction to the embedded sensor, its architecture and its use in mechanicalindustry, and provides the reader with an overview of conventional sensortechnologies within the fields of angle sensors and angular speed sensors, coveringtheir working principles, features, advantages and disadvantages and typicalapplications. The particular problems associated with the use of conventionalsensors in both loader crane positioning and rotor RPM measurement aredescribed and these problems provided the motivation for the designs of theembedded sensor systems developed in this thesis.In the case of the loader crane positioning, the origins of the project and thespecial requirements of the application are described in detail. In addition, apreliminary study is conducted in relation to the idea of a contactless joint angularsensor using MEMS inertial sensors in which four different methods, namely, theCommon-Mode-Rejection with Gyro Integration (CMRGI), Common-Mode-Rejection (CMR), Common-Mode-Rejection with Gyro Differentiation (CMRGD)and Distributed Common-Mode-Rejection (DCMR), are conceived, modeled andtested on a custom-designed prototype experimental setup. The results gatheredfrom these four methods are compared and analyzed in order to identify thedifferences in their performances. The methods, which proved to be suitable, arethen further tested using the prototype sensor setup on a loader crane and theperformance results are analyzed in order to make a decision in relation to the twomost suitable methods for the application of the loader crane positioning. Theresults suggested that the two most suitable were the CMRGD and the DCMR. Thepractical design issues relating to this sensor system are highlighted andsuggestions are made in the study. Additionally, possible future work for thisproject is also covered.In the first case for the rotor RPM measurement, the thesis presents themodeling and simulation of the stator-free RPM sensor idea using the Monte Carlomethod, which demonstrated the special features and performance of this sensor.The design aspects of the prototype sensor are described in detail and theprototype is tested on an experimental setup. The conclusions for the stator-freeRPM sensor are then made from the analysis of the experimental results and futurework in relation to this sensor is also proposed.In the second case of the rotor RPM measurement, the thesis presentsanother idea involving the laser mouse RPM sensor and the main focus of thestudy is on the performance characterization of the laser mouse sensor and theverification of the RPM sensor idea. Experiments are conducted using the test setup and results are gathered and analyzed and conclusions are drawn.Possibilities in relation to future work for this laser mouse RPM sensor are alsoprovided.The summary and the conclusion form the final chapter of the thesis andseveral important aspects of the designs relating to both the loader cranepositioning project and the rotor RPM measurement project are discussed.
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| 37. |
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| 38. |
- Ericsson, A., et al.
(author)
-
Comparison of Noise Reduction and MPEG-2 Compression Efficiency for Pre-Processing Video Filters
- 2004
-
In: IWSSIP'04 : international workshop on systems, signals and image processing : ( Poznan, 13-15 September 2004 ). - Poznan, Poland : Polish Society for Theoretical and Applied Electrical Engineering.
-
Conference paper (peer-reviewed)abstract
- Video information that is input in digital video recorders or distributed over the Internet comes in various different qualities. One possibility to improve the video quality and also to improve the efficiency of the video encoder is to use different types of spatial or temporal video filters. This paper presents a comparison of the noise reduction efficiency for three different video filters. Additionally, the improvement of MPEG-2 encoding efficiency is compared. The results provide an efficiency function that can be used to select an appropriate filter type for a special situation.
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| 39. |
- Fedorov, Igor, et al.
(author)
-
A two-layer 3D reconstruction method and calibration for multi-camera-based volumetric positioning and characterization
- 2021
-
In: IEEE Transactions on Instrumentation and Measurement. - 0018-9456 .- 1557-9662. ; 70
-
Journal article (peer-reviewed)abstract
- A three-dimensional (3D) reconstruction method and multi-camera calibration using multiple artificial reference markers have been used for precise volumetric surveillance of fast-flying objects. The method uses a two-layer 3D reconstruction that integrates two multi-camera stereo-nodes. The fields of view of stereo nodes are directed at an acute angles to each other to provide greater coverage with the given constraints and to determine the flight characteristics of objects in 3D. The object’s flight reconstruction includes a “rough” estimation of its positions relative to selected artificial reference points in both stereo nodes separately and subsequent “refinement” of calculated positions. In this paper, we describe the proposed method and calibration technique, using a multi-camera system to measure object characteristics in 3D. The proposed method applies to volumetric surveillance in situations where it is necessary to count, track, and analyze the activities of flying objects, especially birds, using high spatial resolution.
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| 40. |
- Fedorov, Igor, et al.
(author)
-
Placement Strategy of Multi-Camera Volumetric Surveillance System for Activities Monitoring
- 2017
-
In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450354875 ; , s. 113-118
-
Conference paper (peer-reviewed)abstract
- The design of multi-camera surveillance system comes with many advantages, for example it facilitates as understanding how flying objects act in a given volume. One possible application is for the observation interaction of birds and calculate their trajectories around wind turbines to create promising systems for preventing bird collisions with turbine blades. However, there are also challenges, such as finding the optimal node placement and camera calibration. To address these challenges we investigated a trade-off between calibration accuracy and node requirements, including resolution, modulation transfer function, field of view and angle baseline. We developed a strategy for camera placement to achieve improved coverage for golden eagle monitoring and tracking. This strategy based on the modified resolution criterion taking into account the contrast function of the camera and the estimation of the base angle between the cameras.
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| 41. |
- Fedorov, Igor, 1980-, et al.
(author)
-
Towards calibration of outdoor multi-camera visual monitoring system
- 2018
-
In: ACM International Conference Proceeding Series. - New York, NY, US : ACM Digital Library. - 9781450365116
-
Conference paper (peer-reviewed)abstract
- This paper proposes a method for calibrating of multi-camera systems where no natural reference points exist in the surrounding environment. Monitoring the air space at wind farms is our test case. The goal is to monitor the trajectories of flying birds to prevent them from colliding with rotor blades. Our camera calibration method is based on the observation of a portable artificial reference marker made out of a pulsed light source and a navigation satellite sensor module. The reference marker can determine and communicate its position in the world coordinate system at centimeter precision using navigartion sensors. Our results showed that simultaneous detection of the same marker in several cameras having overlapping field of views allowed us to determine the markers position in 3D world coordinate space with an accuracy of 3-4 cm. These experiments were made in the volume around a wind turbine at distances from cameras to marker within a range of 70 to 90 m.
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| 42. |
- Forsström, Stefan, 1984-, et al.
(author)
-
Specialanpassade kurser för yrkesverksamma ingenjörer : Erfarenheter och upplevelser
- 2023
-
In: Bidrag från den 9:e utvecklingskonferensen för Sveriges ingenjörsutbildningar. - : Mälardalens universitet. - 9789174856200 ; , s. 348-353
-
Conference paper (other academic/artistic)abstract
- I dagens samhälle blir det allt viktigare att fortbilda sig under hela sitt yrkesverksamma liv. För att möta efterfrågan på det livslånga lärandet har Mittuniversitetet utvecklat och genomfört ett antal kurser som riktar sig mot yrkesverksamma ingenjörer. Detta arbete presenterar våra erfarenheter av att ge dessa kurser, med en tyngdpunkt på studenternas upplevelser. Syftet med detta är att bygga upp en vetenskaplig bas för vad vi gör som är bra, men även vad som kan förbättras och förändras. Målsättningen är att göra dessa specialanpassade kurser riktade mot yrkesverksamma ingenjörer så givande och flexibla som möjligt. Våra initiala resultat visar bland annat att studenternas negativa upplevelser ofta var kopplade till antagningsförfarandet och det praktiska genomförandet av kurserna. Man hade svårigheter med att hitta hur man skulle registrera sig på kursen och att tidsramen för registrering kunde vara ett problem. Läroplattformen uppfattades som svår att överblicka och det förekom även viss otydlighet gällande var undervisningen skulle äga rum. Den positiva responsen i utvärderingarna gällde främst det faktiska kursinnehållet, då man ansåg att uppgifter och kursmaterial var givande. Vidare uppskattades kursupplägget, att man kunde kombinera studierna med arbete. Framledes kommer vi att fortsätta med dessa utvärderingar i takt med att kurserna ges, och därefter anpassa vårt mottagande och kommunikationen med studenterna. Även kursupplägget ses över kontinuerligt via den återkoppling vi mottar.
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| 43. |
- Gallo, Vincenzo, et al.
(author)
-
Metrological Characterization of a Clip Fastener assembly fault detection system based on Deep Learning
- 2023
-
In: 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). - : IEEE. - 9781665453837
-
Conference paper (peer-reviewed)abstract
- In a time when Artificial Intelligence (AI) technologies are nearly ubiquitous, railway construction and maintenance systems have not fully grasped the capabilities of such technologies. Traditional railway inspection methods rely on inspection from experienced workers, making such tasks costly from both, the monetary and the time perspective. From an overview of the state-of-the-art research in this area regarding AI-based systems, we observed that their main focus was solely on detection accuracy of different railway components. However, if we consider the critical importance of railway fastening in the overall safety of the railway, there is a need for a thorough analysis of these AI-based methodologies, to define their uncertainty also from a metrological perspective. In this article we address this issue, proposing an image-based system that detects the rotational displacement of the fastened railway clips. Furthermore, we provide an uncertainty analysis of the measurement system, where the resulting uncertainty is of 0.42°, within the 3° error margin defined by the clip manufacturer.
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| 44. |
- Hussain, Mazhar, 1980-, et al.
(author)
-
A Deep Learning Approach for Classification and Measurement of Hazardous Gases Using Multi-Sensor Data Fusion
- 2023
-
In: 2023 IEEE Sensors Applications Symposium (SAS). - : IEEE conference proceedings.
-
Conference paper (peer-reviewed)abstract
- Significant risks to public health and the environment are posed by the release of hazardous gases from industries such as pulp and paper. In this study, the aim was to develop a multi-sensor system with a minimal number of sensors to detect and identify hazardous gases. Training and test data for two gases, hydrogen sulfide and methyl mercaptan, which are known to contribute significantly to odors, were generated in a controlled laboratory environment. The performance of two deep learning models, a 1d-CNN and a stacked LSTM, for data fusion with different sensor configurations was evaluated. The performance of these models was compared with a baseline machine learning model. It was observed that the baseline model was outperformed by the deep learning models and achieved good accuracy with a four-sensor configuration. The potential of a cost-effective multi-sensor system and deep learning models in detecting and identifying hazardous gases is demonstrated by this study, which can be used to collect data from multiple locations and help guide the development of in-situ measurement systems for real-time detection and identification of hazardous gases at industrial sites. The proposed system has important implications for reducing pollution and protecting public health.
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| 45. |
- Hussain, Mazhar, 1980-, et al.
(author)
-
A Study on the Correlation between Change in the Geometrical Dimension of a Free-Falling Molten Glass Gob and Its Viscosity
- 2022
-
In: Sensors. - : MDPI. - 1424-8220. ; 22:2, s. 661-661
-
Journal article (other academic/artistic)abstract
- To produce flawless glass containers, continuous monitoring of the glass gob is required. It is essential to ensure production of molten glass gobs with the right shape, temperature, viscosity and weight. At present, manual monitoring is common practice in the glass container industry, which heavily depends on previous experience, operator knowledge and trial and error. This results in inconsistent measurements and consequently loss of production. In this article, a multi-camera based setup is used as a non-invasive real-time monitoring system. We have shown that under certain conditions, such as keeping the glass composition constant, it is possible to do in-line measurement of viscosity using sensor fusion to correlate the rate of geometrical change in the gob and its temperature. The correlation models presented in this article show that there is a strong correlation, i.e., 0.65, between our measurements and the projected viscosity.
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| 46. |
- Hussain, Mazhar, 1980-, et al.
(author)
-
Multi-Camera Based Setup for Geometrical Measurement of Free-Falling Molten Glass Gob
- 2021
-
In: Sensors. - : MDPI AG. - 1424-8220. ; 21:4
-
Journal article (peer-reviewed)abstract
- High temperatures complicate the direct measurements needed for continuous characterization of the properties of molten materials such as glass. However, the assumption that geometrical changes when the molten material is in free-fall can be correlated with material characteristics such as viscosity opens the door to a highly accurate contactless method characterizing small dynamic changes. This paper proposes multi-camera setup to achieve accuracy close to the segmentation error associated with the resolution of the images. The experimental setup presented shows that the geometrical parameters can be characterized dynamically through the whole free-fall process at a frame rate of 600 frames per second. The results achieved show the proposed multi-camera setup is suitable for estimating the length of free-falling molten objects.
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| 47. |
- Hussain, Mazhar, 1980-, et al.
(author)
-
Selection of optimal parameters to predict fuel consumption of city buses using data fusion
- 2022
-
In: 2022 IEEE Sensors Applications Symposium (SAS). - : IEEE. - 9781665409810
-
Conference paper (peer-reviewed)abstract
- The study aims to explore the fuel consumption of city buses with data fusion using a dataset with multiple parameters such as travelled distance, weekday, hour of the day, drivers, buses, and routes, that influence the trip fuel consumption. In this study, manipulated parameters such as modified driver, bus and route identification numbers are used together with original parameters to identify the optimal combination of parameters that can be used to enhance the accuracy of the prediction model. Two regression methods, i.e. cubic SVM and artificial neural networks (ANN), are used to demonstrate the performance of the proposed approach. Results shows that a combination of original parameters and processed parameters increases the performance.
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| 48. |
- Imran, Muhammad, et al.
(author)
-
Analysis and Characterization of Embedded Vision Systems for Taxonomy Formulation
- 2013
-
In: Proceedings of SPIE - The International Society for Optical Engineering. - USA : SPIE - International Society for Optical Engineering. - 9780819494290 ; , s. Art. no. 86560J-
-
Conference paper (peer-reviewed)abstract
- The current trend in embedded vision systems is to propose bespoke solutions for specific problems as each application has different requirement and constraints. There is no widely used model or benchmark which aims to facilitate generic solutions in embedded vision systems. Providing such model is a challenging task due to the wide number of use cases, environmental factors, and available technologies. However, common characteristics can be identified to propose an abstract model. Indeed, the majority of vision applications focus on the detection, analysis and recognition of objects. These tasks can be reduced to vision functions which can be used to characterize the vision systems. In this paper, we present the results of a thorough analysis of a large number of different types of vision systems. This analysis led us to the development of a system’s taxonomy, in which a number of vision functions as well as their combination characterize embedded vision systems. To illustrate the use of this taxonomy, we have tested it against a real vision system that detects magnetic particles in a flowing liquid to predict and avoid critical machinery failure. The proposed taxonomy is evaluated by using a quantitative parameter which shows that it covers 95 percent of the investigated vision systems and its flow is ordered for 60 percent systems. This taxonomy will serve as a tool for classification and comparison of systems and will enable the researchers to propose generic and efficient solutions for same class of systems.
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| 49. |
- Imran, Muhammad, et al.
(author)
-
Architecture Exploration Based on Tasks Partitioning Between Hardware, Software and Locality for a Wireless Vision Sensor Node
- 2012
-
In: International Journal of Distributed Systems and Technologies. - IGI Global, USA. : IGI Global. - 1947-3532 .- 1947-3540. ; 3:2, s. 58-71
-
Journal article (peer-reviewed)abstract
- Wireless Vision Sensor Networks (WVSNs) is an emerging field which consists of a number of Visual Sensor Nodes (VSNs). Compared to traditional sensor networks, WVSNs operates on two dimensional data, which requires high bandwidth and high energy consumption. In order to minimize the energy consumption, the focus is on finding energy efficient and programmable architectures for the VSN by partitioning the vision tasks among hardware (FPGA), software (Micro-controller) and locality (sensor node or server). The energy consumption, cost and design time of different processing strategies is analyzed for the implementation of VSN. Moreover, the processing energy and communication energy consumption of VSN is investigated in order to maximize the lifetime. Results show that by introducing a reconfigurable platform such as FPGA with small static power consumption and by transmitting the compressed images after pixel based tasks from the VSN results in longer battery lifetime for the VSN.
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| 50. |
- Imran, Muhammad, et al.
(author)
-
Architecture of Wireless Visual Sensor Node with Region of Interest Coding
- 2012
-
In: Proceedings - 2012 IEEE 3rd International Conference on Networked Embedded Systems for Every Application, NESEA 2012. - : IEEE conference proceedings. - 9781467347235 ; , s. Art. no. 6474029-
-
Conference paper (peer-reviewed)abstract
- The challenges involved in designing a wirelessVision Sensor Node include the reduction in processing andcommunication energy consumption, in order to maximize itslifetime. This work presents an architecture for a wireless VisionSensor Node, which consumes low processing andcommunication energy. The processing energy consumption isreduced by processing lightweight vision tasks on the VSN andby partitioning the vision tasks between the wireless VisionSensor Node and the server. The communication energyconsumption is reduced with Region Of Interest coding togetherwith a suitable bi-level compression scheme. A number ofdifferent processing strategies are investigated to realize awireless Vision Sensor Node with a low energy consumption. Theinvestigation shows that the wireless Vision Sensor Node, usingRegion Of Interest coding and CCITT group4 compressiontechnique, consumes 43 percent lower processing andcommunication energy as compared to the wireless Vision SensorNode implemented without Region Of Interest coding. Theproposed wireless Vision Sensor Node can achieve a lifetime of5.4 years, with a sample period of 5 minutes by using 4 AAbatteries.
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