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Implementation of Wireless Vision Sensor Node With a Lightweight Bi-Level Video Coding
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Avdelningen för elektronikkonstruktion.ORCID-id: 0000-0003-1923-3843
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Avdelningen för elektronikkonstruktion.
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Avdelningen för elektronikkonstruktion.ORCID-id: 0000-0002-6484-9260
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Avdelningen för elektronikkonstruktion.
Vise andre og tillknytning
2013 (engelsk)Inngår i: IEEE Journal on Emerging and Selected Topics in Circuits and Systems, ISSN 2156-3357, Vol. 3, nr 2, s. 198-209, artikkel-id 6508941Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
IEEE Press, 2013. Vol. 3, nr 2, s. 198-209, artikkel-id 6508941
Emneord [en]
Architecture, smart camera, video coding, wireless vision sensor networks (WVSNs), wireless vision sensor node (VSN)
HSV kategori
Identifikatorer
URN: urn:nbn:se:miun:diva-19193DOI: 10.1109/JETCAS.2013.2256816ISI: 000337789200009Scopus ID: 2-s2.0-84879076204Lokal ID: STCOAI: oai:DiVA.org:miun-19193DiVA, id: diva2:627733
Tilgjengelig fra: 2013-06-12 Laget: 2013-06-12 Sist oppdatert: 2016-10-20bibliografisk kontrollert
Inngår i avhandling
1. Energy Efficient and Programmable Architecture for Wireless Vision Sensor Node
Åpne denne publikasjonen i ny fane eller vindu >>Energy Efficient and Programmable Architecture for Wireless Vision Sensor Node
2013 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Sundsvall: Mid Sweden University, 2013. s. 115
Serie
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 167
Emneord
Wireless Vision Sensor Node, Smart camera, Wireless Vision Sensor Networks, Architecture, Video coding.
HSV kategori
Identifikatorer
urn:nbn:se:miun:diva-20179 (URN)STC (Lokal ID)978-91-87557-12-5 (ISBN)STC (Arkivnummer)STC (OAI)
Disputas
2013-10-22, M108, holmgatan 10,SE 85170, sundsvall, 10:03 (engelsk)
Opponent
Veileder
Forskningsfinansiär
Knowledge Foundation
Tilgjengelig fra: 2013-11-11 Laget: 2013-11-11 Sist oppdatert: 2016-10-20bibliografisk kontrollert
2. Investigation of intelligence partitioning and data reduction in wireless visual sensor network
Åpne denne publikasjonen i ny fane eller vindu >>Investigation of intelligence partitioning and data reduction in wireless visual sensor network
2013 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
sted, utgiver, år, opplag, sider
Sundsvall: Mid Sweden University, 2013. s. 208
Serie
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 150
HSV kategori
Identifikatorer
urn:nbn:se:miun:diva-20976 (URN)STC (Lokal ID)978-91-87103-75-9 (ISBN)STC (Arkivnummer)STC (OAI)
Veileder
Tilgjengelig fra: 2014-01-08 Laget: 2014-01-08 Sist oppdatert: 2016-10-20bibliografisk kontrollert
3. Modelling, optimization and design of visual sensor networks for sky surveillance
Åpne denne publikasjonen i ny fane eller vindu >>Modelling, optimization and design of visual sensor networks for sky surveillance
2013 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
sted, utgiver, år, opplag, sider
Sundsvall: Mid Sweden University, 2013. s. 210
Serie
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 166
HSV kategori
Identifikatorer
urn:nbn:se:miun:diva-21022 (URN)978-91-87557-11-8 (ISBN)
Veileder
Tilgjengelig fra: 2014-01-13 Laget: 2014-01-13 Sist oppdatert: 2014-04-24bibliografisk kontrollert

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