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Implementation of wireless Vision Sensor Node for Characterization of Particles in Fluids
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.ORCID iD: 0000-0002-3429-273X
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
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2012 (English)In: IEEE transactions on circuits and systems for video technology (Print), ISSN 1051-8215, E-ISSN 1558-2205, Vol. 22, no 11, 1634-1643 p.Article 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. 

Place, publisher, year, edition, pages
2012. Vol. 22, no 11, 1634-1643 p.
Keyword [en]
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: urn:nbn:se:miun:diva-14389DOI: 10.1109/TCSVT.2012.2202189ISI: 000313971700010Scopus ID: 2-s2.0-84875631744Local ID: STCOAI: oai:DiVA.org:miun-14389DiVA: diva2:436582
Available from: 2011-08-24 Created: 2011-08-24 Last updated: 2016-10-20Bibliographically approved
In thesis
1. Investigation of Architectures for Wireless Visual Sensor Nodes
Open this publication in new window or tab >>Investigation of Architectures for Wireless Visual Sensor Nodes
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Wireless visual sensor network is an emerging field which has proveduseful in many applications, including industrial control and monitoring,surveillance, environmental monitoring, personal care and the virtual world.Traditional imaging systems used a wired link, centralized network, highprocessing capabilities, unlimited storage and power source. In manyapplications, the wired solution results in high installation and maintenancecosts. However, a wireless solution is the preferred choice as it offers lessmaintenance, infrastructure costs and greater scalability.The technological developments in image sensors, wirelesscommunication and processing platforms have paved the way for smartcamera networks usually referred to as Wireless Visual Sensor Networks(WVSNs). WVSNs consist of a number of Visual Sensor Nodes (VSNs)deployed over a large geographical area. The smart cameras can performcomplex vision tasks using limited resources such as batteries or alternativeenergy sources, embedded platforms, a wireless link and a small memory.Current research in WVSNs is focused on reducing the energyconsumption of the node so as to maximise the life of the VSN. To meet thischallenge, different software and hardware solutions are presented in theliterature for the implementation of VSNs.The focus in this thesis is on the exploration of energy efficientreconfigurable architectures for VSNs by partitioning vision tasks on software,hardware platforms and locality. For any application, some of the vision taskscan be performed on the sensor node after which data is sent over the wirelesslink to the server where the remaining vision tasks are performed. Similarly,at the VSN, vision tasks can be partitioned on software and the hardwareplatforms.In the thesis, all possible strategies are explored, by partitioning visiontasks on the sensor node and on the server. The energy consumption of thesensor node is evaluated for different strategies on software platform. It isobserved that performing some of the vision tasks on the sensor node andsending compressed images to the server where the remaining vision tasks areperformed, will have lower energy consumption.In order to achieve better performance and low power consumption,Field Programmable Gate Arrays (FPGAs) are introduced for theimplementation of the sensor node. The strategies with reasonable designtimes and costs are implemented on hardware-software platform. Based onthe implementation of the VSN on the FPGA together with micro-controller,the lifetime of the VSN is predicted using the measured energy values of theplatforms for different processing strategies. The implementation resultsprove our analysis that a VSN with such characteristics will result in a longerlife time.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2011. 80 p.
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 66
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14388 (URN)STC (Local ID)978-91-86694-45-6 (ISBN)STC (Archive number)STC (OAI)
Presentation
2011-06-10, O102, Sundsvall, 10:27 (English)
Supervisors
Available from: 2011-08-24 Created: 2011-08-24 Last updated: 2016-10-19Bibliographically approved
2. 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. 115 p.
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 167
Keyword
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
3. Investigation of intelligence partitioning and data reduction in wireless visual sensor network
Open this publication in new window or tab >>Investigation of intelligence partitioning and data reduction in wireless visual sensor network
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2013. 208 p.
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 150
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-20976 (URN)STC (Local ID)978-91-87103-75-9 (ISBN)STC (Archive number)STC (OAI)
Supervisors
Available from: 2014-01-08 Created: 2014-01-08 Last updated: 2016-10-20Bibliographically approved

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