miun.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Investigation of intelligence partitioning and data reduction in wireless visual sensor network
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.ORCID iD: 0000-0002-6484-9260
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University , 2013. , p. 208
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 150
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-20976Local ID: STCISBN: 978-91-87103-75-9 (print)OAI: oai:DiVA.org:miun-20976DiVA, id: diva2:684451
Supervisors
Available from: 2014-01-08 Created: 2014-01-08 Last updated: 2016-10-20Bibliographically approved
List of papers
1. Exploration of tasks partitioning between hardware software and locality for a wireless camera based vision sensor node
Open this publication in new window or tab >>Exploration of tasks partitioning between hardware software and locality for a wireless camera based vision sensor node
Show others...
2011 (English)In: Proceedings - 6th International Symposium on Parallel Computing in Electrical Engineering, PARELEC 2011, IEEE conference proceedings, 2011, p. 127-132Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we have explored different possibilities for partitioning the tasks between hardware, software and locality for the implementation of the vision sensor node, used in wireless vision sensor network. Wireless vision sensor network is an emerging field which combines image sensor, on board computation and communication links. Compared to the traditional wireless sensor networks which operate on one dimensional data, wireless vision sensor networks operate on two dimensional data which requires higher processing power and communication bandwidth. The research focus within the field of wireless vision sensor networks have been on two different assumptions involving either sending raw data to the central base station without local processing or conducting all processing locally at the sensor node and transmitting only the final results. Our research work focus on determining an optimal point of hardware/software partitioning as well as partitioning between local and central processing, based on minimum energy consumption for vision processing operation. The lifetime of the vision sensor node is predicted by evaluating the energy requirement of the embedded platform with a combination of FPGA and micro controller for the implementation of the vision sensor node. Our results show that sending compressed images after pixel based tasks will result in a longer battery life time with reasonable hardware cost for the vision sensor node. © 2011 IEEE.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011
Keywords
Hardware/Software Partioning, Image Processing, Reconfigurable Architecture, Vision Sensor Node, Wireless Vision Sensor Networks, Battery life time, Communication bandwidth, Compressed images, Embedded platforms, Energy requirements, Hardware cost, Hardware/software partitioning, Local processing, Minimum energy, Optimal points, Partioning, Processing power, Vision processing, Vision sensors, Wireless cameras, Work Focus, Computer hardware, Electrical engineering, Energy utilization, Engineering research, Field programmable gate arrays (FPGA), Parallel architectures, Sensors, Telecommunication equipment, Telecommunication systems, Wireless networks, Sensor nodes
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14195 (URN)10.1109/PARELEC.2011.21 (DOI)2-s2.0-79958725347 (Scopus ID)STC (Local ID)9780769543970 (ISBN)STC (Archive number)STC (OAI)
Conference
6th International Symposium on Parallel Computing in Electrical Engineering, PARELEC 2011; Luton; 4 April 2011 through 5 April 2011; Category number E4397; Code 85105
Available from: 2011-07-19 Created: 2011-07-19 Last updated: 2016-10-19Bibliographically approved
2. Implementation of wireless Vision Sensor Node for Characterization of Particles in Fluids
Open this publication in new window or tab >>Implementation of wireless Vision Sensor Node for Characterization of Particles in Fluids
Show others...
2012 (English)In: IEEE transactions on circuits and systems for video technology (Print), ISSN 1051-8215, E-ISSN 1558-2205, Vol. 22, no 11, p. 1634-1643Article in journal (Refereed) Published
Abstract [en]

Wireless Vision Sensor Networks (WVSNs) have a number of wireless Vision Sensor Nodes (VSNs), often spread over a large geographical area. Each node has an image capturing unit, a battery or alternative energy source, a memory unit, a light source, a wireless link and a processing unit. The challenges associated with WVSNs include low energy consumption, low bandwidth, limited memory and processing capabilities. In order to meet these challenges, our research is focused on the exploration of energy efficient reconfigurable architectures for VSN. In this work, the design/research challenges associated with the implementation of VSN on different computational platforms such as micro-controller, FPGA and server, are explored. In relation to this, the effect on the energy consumption and the design complexity at the node, when the functionality is moved from one platform to another are analyzed. Based on the implementation of the VSN on embedded platforms, the lifetime of the VSN is predicted using the measured energy values of the platforms for different implementation strategies. The implementation results show that an architecture, where the compressed images after pixel based operation are transmitted, realize a WVSN system with low energy consumption. Moreover, the complex post processing tasks are moved to a server, with reduced constraints. 

Keywords
Reconfigurable architecture, Image processing, Wireless vision sensor networks, Wireless vision sensor node.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14389 (URN)10.1109/TCSVT.2012.2202189 (DOI)000313971700010 ()2-s2.0-84875631744 (Scopus ID)STC (Local ID)STC (Archive number)STC (OAI)
Available from: 2011-08-24 Created: 2011-08-24 Last updated: 2017-12-08Bibliographically approved
3. The effect of packets relaying on the implementation issues of the visual sensor node
Open this publication in new window or tab >>The effect of packets relaying on the implementation issues of the visual sensor node
2013 (English)In: Electronics and Electrical Engineering, ISSN 1392-1215, Vol. 19, no 10, p. 155-161Article in journal (Refereed) Published
Abstract [en]

Wireless Visual Sensor Networks (WVSNs) are used for the monitoring of large and inaccessible areas. WVSNs are feasible today due to the advancement in many fields of electronics such as CMOS cameras, low power computing platforms, distributed computing and radio transceivers. The energy budget in a WVSN is limited because of the wireless nature of the applications and the small physical size of the Visual Sensor Node (VSN). The WVSN covers a large area where every node cannot transmit its results directly to the server. Receiving and forwarding other node's packets consumes a large portion of the energy budget of the VSNs. This paper explores the effect of packets relaying in a multihop WVSN on the implementation issues of the VSN. It also explores the effect of node density in the multihop WVSN on the energy consumption, which in turn, has an impact on the lifetime of the VSN. Results show that the network topology does not affect the software implementation of the VSN because of the relatively high execution time of the image processing tasks on the microcontroller. For hardware implementation, network topology and node density does affect the architecture of the VSN due to the fact that communication energy consumption is dominant (because of the low execution time on FPGAs).

Keywords
Embedded computing, Image communication, Low power electronics, Wireless sensor networks
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-20972 (URN)10.5755/j01.eee.19.10.5912 (DOI)000330689000034 ()2-s2.0-84890758469 (Scopus ID)STC (Local ID)STC (Archive number)STC (OAI)
Note

Alternative title for journal: Elektronika ir Elektrotechnika

Available from: 2014-01-08 Created: 2014-01-08 Last updated: 2016-10-20Bibliographically approved
4. Performance analysis of bi-level image compression methods for machine vision embedded applications
Open this publication in new window or tab >>Performance analysis of bi-level image compression methods for machine vision embedded applications
(English)Manuscript (preprint) (Other academic)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-20973 (URN)
Available from: 2014-01-08 Created: 2014-01-08 Last updated: 2016-12-09Bibliographically approved
5. Analysis of change coding for data reduction in wireless visual sensor network
Open this publication in new window or tab >>Analysis of change coding for data reduction in wireless visual sensor network
(English)Manuscript (preprint) (Other academic)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-20974 (URN)
Available from: 2014-01-08 Created: 2014-01-08 Last updated: 2016-12-09Bibliographically approved
6. Detecting and Coding Region of Interests in Bi-Level Images for Data Reduction in Wireless Visual Sensor Network
Open this publication in new window or tab >>Detecting and Coding Region of Interests in Bi-Level Images for Data Reduction in Wireless Visual Sensor Network
2012 (English)In: Wireless and Mobile Computing, Networking and Communications (WiMob), 2012 IEEE 8th International Conference on, IEEE conference proceedings, 2012, p. 705-712Conference paper, Published paper (Refereed)
Abstract [en]

Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. The VSNs acquire images of the area of interest in the field, perform some local processing on these images and transmit the results using an embedded wireless transceiver. The energy consumption on transmitting the results wirelessly is correlated with the information amount that is being transmitted.  The images acquired by the VSNs contain huge amount of data due to many kinds of redundancies in the images. Suitable bi-level image compression standards can efficiently reduce the information amount in images and will thus be effective in reducing the communication energy consumption in the WVSN. But compression capability of the bi-level image compression standards is limited to the underline compression algorithm. Further data reduction can be achieved by detecting Region of Interest (ROI) in the bi-level images and then coding these ROIs using bi-level image compression method. We explored the compression performance of the lossless ROI detection and coding method for various kinds of changes such as different shapes, locations and number of objects in the continuous set of frames. The CCITT Group 4, JBIG2 and Gzip are used for coding the detected ROIs. We concluded that CCITT Group 4 is a better choice for coding the ROIs in the Bi-level images because of its comparatively good compression performance and less computational complexity. This paper is intended to be a resource for the researchers interested in reducing the amount of data in the bi-level images for energy constrained WVSNs.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2012
Keywords
ROI coding, Image Coding, Wireless Visual Sensor Network, Energy Consumption.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:miun:diva-18030 (URN)10.1109/WiMOB.2012.6379153 (DOI)2-s2.0-84872055183 (Scopus ID)STC (Local ID)978-1-4673-1429-9 (ISBN)STC (Archive number)STC (OAI)
Conference
The 1st International Workshop on Wireless Multimedia Sensor Networks (WMSN 2012) in conjunction with The 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2012)
Available from: 2012-12-20 Created: 2012-12-20 Last updated: 2016-10-20Bibliographically approved
7. Efficient Data Reduction Techniques for Remote Applications of a Wireless Visual Sensor Network
Open this publication in new window or tab >>Efficient Data Reduction Techniques for Remote Applications of a Wireless Visual Sensor Network
2013 (English)In: International Journal of Advanced Robotic Systems, ISSN 1729-8806, E-ISSN 1729-8814, Vol. 10, p. Art. no. 240-Article in journal (Refereed) Published
Abstract [en]

A Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. After acquiring an image of the area of interest, the VSN performs local processing on it and transmits the result using an embedded wireless transceiver. Wireless data transmission consumes a great deal of energy, where energy consumption is mainly dependent on the amount of information being transmitted. The image captured by the VSN contains a huge amount of data. For certain applications, segmentation can be performed on the captured images. The amount of information in the segmented images can be reduced by applying efficient bi-level image compression methods. In this way, the communication energy consumption of each of the VSNs can be reduced. However, the data reduction capability of bi-level image compression standards is fixed and is limited by the used compression algorithm. For applications attributing few changes in adjacent frames, change coding can be applied for further data reduction. Detecting and compressing only the Regions of Interest (ROIs) in the change frame is another possibility for further data reduction. In a communication system, where both the sender and the receiver know the employed compression standard, there is a possibility for further data reduction by not including the header information in the compressed bit stream of the sender. This paper summarizes different information reduction techniques such as image coding, change coding and ROI coding. The main contribution is the investigation of the combined effect of all these coding methods and their application to a few representative real life applications. This paper is intended to be a resource for researchers interested in techniques for information reduction in energy constrained embedded applications.

Keywords
Image Coding; Change Coding; ROI Coding; Energy Consumption; Visual Sensor Node; Image Header; Wireless Visual Sensor Network
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Embedded Systems
Identifiers
urn:nbn:se:miun:diva-18596 (URN)10.5772/55996 (DOI)000318670000003 ()2-s2.0-84879235380 (Scopus ID)STC (Local ID)STC (Archive number)STC (OAI)
Available from: 2013-03-15 Created: 2013-03-15 Last updated: 2017-12-06Bibliographically approved
8. Implementation of Wireless Vision Sensor Node With a Lightweight Bi-Level Video Coding
Open this publication in new window or tab >>Implementation of Wireless Vision Sensor Node With a Lightweight Bi-Level Video Coding
Show others...
2013 (English)In: IEEE Journal on Emerging and Selected Topics in Circuits and Systems, ISSN 2156-3357, Vol. 3, no 2, p. 198-209, article id 6508941Article in journal (Refereed) Published
Abstract [en]

Wireless vision sensor networks (WVSNs) consist ofa number of wireless vision sensor nodes (VSNs) which have limitedresources i.e., energy, memory, processing, and wireless bandwidth.The processing and communication energy requirements ofindividual VSN have been a challenge because of limited energyavailability. To meet this challenge, we have proposed and implementeda programmable and energy efficient VSN architecturewhich has lower energy requirements and has a reduced designcomplexity. In the proposed system, vision tasks are partitionedbetween the hardware implemented VSN and a server. The initialdata dominated tasks are implemented on the VSN while thecontrol dominated complex tasks are processed on a server. Thisstrategy will reduce both the processing energy consumption andthe design complexity. The communication energy consumption isreduced by implementing a lightweight bi-level video coding on theVSN. The energy consumption is measured on real hardware fordifferent applications and proposed VSN is compared against publishedsystems. The results show that, depending on the application,the energy consumption can be reduced by a factor of approximately1.5 up to 376 as compared to VSN without the bi-level videocoding. The proposed VSN offers energy efficient, generic architecturewith smaller design complexity on hardware reconfigurableplatform and offers easy adaptation for a number of applicationsas compared to published systems.

Place, publisher, year, edition, pages
IEEE Press, 2013
Keywords
Architecture, smart camera, video coding, wireless vision sensor networks (WVSNs), wireless vision sensor node (VSN)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:miun:diva-19193 (URN)10.1109/JETCAS.2013.2256816 (DOI)000337789200009 ()2-s2.0-84879076204 (Scopus ID)STC (Local ID)STC (Archive number)STC (OAI)
Available from: 2013-06-12 Created: 2013-06-12 Last updated: 2016-10-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Khursheed, Khursheed

Search in DiVA

By author/editor
Khursheed, Khursheed
By organisation
Department of Electronics Design
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 1183 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf