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
Architecture of Wireless Visual Sensor Node with Region of Interest Coding
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.ORCID iD: 0000-0003-1923-3843
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.ORCID iD: 0000-0002-6484-9260
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
Show others and affiliations
2012 (English)In: Proceedings - 2012 IEEE 3rd International Conference on Networked Embedded Systems for Every Application, NESEA 2012, IEEE conference proceedings, 2012, p. Art. no. 6474029-Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2012. p. Art. no. 6474029-
Keywords [en]
architecture, wireless vision sensor node, Region of interest coding, Smart camera, wireless visual sensor networks, wireless multimedia sensor networks.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-18021DOI: 10.1109/NESEA.2012.6474029ISI: 000319471300019Scopus ID: 2-s2.0-84875603760Local ID: STCISBN: 978-146734723-5 (print)OAI: oai:DiVA.org:miun-18021DiVA, id: diva2:579346
Conference
2012 IEEE 3rd International Conference on Networked Embedded Systems for Every Application, NESEA 2012; Liverpool; United Kingdom; 13 December 2012 through 14 December 2012; Category numberCFP12NEE-ART; Code 96291
Available from: 2012-12-19 Created: 2012-12-19 Last updated: 2016-10-20Bibliographically approved
In thesis
1. Energy Efficient and Programmable Architecture for Wireless Vision Sensor Node
Open this publication in new window or tab >>Energy Efficient and Programmable Architecture for Wireless Vision Sensor Node
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Wireless Vision Sensor Networks (WVSNs) is an emerging field which has attracted a number of potential applications because of smaller per node cost, ease of deployment, scalability and low power stand alone solutions. WVSNs consist of a number of wireless Vision Sensor Nodes (VSNs). VSN has limited resources such as embedded processing platform, power supply, wireless radio and memory.  In the presence of these limited resources, a VSN is expected to perform complex vision tasks for a long duration of time without battery replacement/recharging. Currently, reduction of processing and communication energy consumptions have been major challenges for battery operated VSNs. Another challenge is to propose generic solutions for a VSN so as to make these solutions suitable for a number of applications.

To meet these challenges, this thesis focuses on energy efficient and programmable VSN architecture for machine vision systems which can classify objects based on binary data. In order to facilitate generic solutions, a taxonomy has been developed together with a complexity model which can be used for systems’ classification and comparison without the need for actual implementation. The proposed VSN architecture is based on tasks partitioning between a VSN and a server as well as tasks partitioning locally on the node between software and hardware platforms. In relation to tasks partitioning, the effect on processing, communication energy consumptions, design complexity and lifetime has been investigated.

The investigation shows that the strategy, in which front end tasks up to segmentation, accompanied by a bi-level coding, are implemented on Field Programmable Platform (FPGA) with small sleep power, offers a generalized low complexity and energy efficient VSN architecture. The implementation of data intensive front end tasks on hardware reconfigurable platform reduces processing energy. However, there is a scope for reducing communication energy, related to output data. This thesis also explores data reduction techniques including image coding, region of interest coding and change coding which reduces output data significantly.

For proof of concept, VSN architecture together with tasks partitioning, bi-level video coding, duty cycling and low complexity background subtraction technique has been implemented on real hardware and functionality has been verified for four applications including particle detection system, remote meter reading, bird detection and people counting. The results based on measured energy values shows that, depending on the application, the energy consumption can be reduced by a factor of approximately 1.5 up to 376 as compared to currently published VSNs. The lifetime based on measured energy values showed that for a sample period of 5 minutes, VSN can achieve 3.2 years lifetime with a battery of 37.44 kJ energy. In addition to this, proposed VSN offers generic architecture with smaller design complexity on hardware reconfigurable platform and offers easy adaptation for a number of applications as compared to published systems.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2013. p. 115
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 167
Keywords
Wireless Vision Sensor Node, Smart camera, Wireless Vision Sensor Networks, Architecture, Video coding.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-20179 (URN)STC (Local ID)978-91-87557-12-5 (ISBN)STC (Archive number)STC (OAI)
Public defence
2013-10-22, M108, holmgatan 10,SE 85170, sundsvall, 10:03 (English)
Opponent
Supervisors
Funder
Knowledge Foundation
Available from: 2013-11-11 Created: 2013-11-11 Last updated: 2016-10-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopusConference page

Authority records BETA

Imran, MuhammadKhursheed, KhursheedAhmad, NaeemO'Nils, MattiasLawal, NajeemWaheed, Malik A.

Search in DiVA

By author/editor
Imran, MuhammadKhursheed, KhursheedAhmad, NaeemO'Nils, MattiasLawal, NajeemWaheed, Malik A.
By organisation
Department of Information Technology and Media
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 858 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