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Exploration of Local and Central Processing for a Wireless Camera Based Sensor Node
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier. (Video processing group, STC)ORCID-id: 0000-0002-6484-9260
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier. (STC)ORCID-id: 0000-0003-1923-3843
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier. (STC)
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier. (STC)ORCID-id: 0000-0002-3429-273X
2010 (engelsk)Inngår i: International Conference on Signals and Electronic Systems, ICSES'10 - Conference Proceeding 2010, Article number 5595231, IEEE conference proceedings, 2010, s. 147-150Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

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 both higher processing power and communication bandwidth. The research focus within the field of wireless vision sensor network has been based on two different assumptions involving either sending data to the central base station without local processing or conducting all processing locally at the sensor node and transmitting only the final results. In this paper we focus on determining an optimal point for intelligence partitioning between the sensor node and the central base station and by exploring compression methods. The lifetime of the visual sensor node is predicted by evaluating the energy consumption for different levels of intelligence partitioning at the sensor node. Our results show that sending compressed images after segmentation will result in a longer life for the sensor node.

sted, utgiver, år, opplag, sider
IEEE conference proceedings, 2010. s. 147-150
HSV kategori
Identifikatorer
URN: urn:nbn:se:miun:diva-12602ISI: 000299392000035Scopus ID: 2-s2.0-78649273063ISBN: 978-839047434-2 ISBN: 978-1-4244-5307-8 (tryckt)OAI: oai:DiVA.org:miun-12602DiVA, id: diva2:377018
Konferanse
International Conference on Signals and Electronic Systems, ICSES'10; Gliwice; 7 September 2010 through 10 September 2010; Category number CFP1057D-ART; Code 82386
Tilgjengelig fra: 2010-12-13 Laget: 2010-12-13 Sist oppdatert: 2013-11-11bibliografisk kontrollert
Inngår i avhandling
1. Investigation of Architectures for Wireless Visual Sensor Nodes
Åpne denne publikasjonen i ny fane eller vindu >>Investigation of Architectures for Wireless Visual Sensor Nodes
2011 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Sundsvall: Mid Sweden University, 2011. s. 80
Serie
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 66
HSV kategori
Identifikatorer
urn:nbn:se:miun:diva-14388 (URN)STC (Lokal ID)978-91-86694-45-6 (ISBN)STC (Arkivnummer)STC (OAI)
Presentation
2011-06-10, O102, Sundsvall, 10:27 (engelsk)
Veileder
Tilgjengelig fra: 2011-08-24 Laget: 2011-08-24 Sist oppdatert: 2016-10-19bibliografisk kontrollert
2. Investigation of intelligence partitioning in wireless visual sensor networks
Åpne denne publikasjonen i ny fane eller vindu >>Investigation of intelligence partitioning in wireless visual sensor networks
2011 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

The wireless visual sensor network is an emerging field which is formed by deploying many visual sensor nodes in the field and in which each individual visual sensor node contains an image sensor, on board processor, memory and wireless transceiver. In comparison to the traditional wireless sensor networks, which operate on one dimensional data, the wireless visual sensor networks operate on two dimensional data which requires higher processing power and communication bandwidth. Research focus within the field of wireless visual sensor networks has been on two different extremes, involving either sending raw data to the central base station without local processing or conducting all processing locally at the visual sensor node and transmitting only the final results.This research work focuses on determining an optimal point of hardware/software partitioning at the visual sensor node as well as partitioning tasks between local and central processing, based on the minimum energy consumption for the vision processing tasks. Different possibilities in relation to partitioning the vision processing tasks between hardware, software and locality for the implementation of the visual sensor node, used in wireless visual sensor networks have been explored. The effect of packets relaying and node density on the energy consumption and implementation of the individual wireless visual sensor node, when used in a multi-hop wireless visual sensor networks have also been explored.The lifetime of the visual sensor node is predicted by evaluating the energy requirement of the embedded platform with a combination of the Field Programmable Gate Arrays (FPGA) and the micro-controller for the implementation of the visual sensor node and, in addition, taking into account the amount of energy required for receiving/forwarding the packets of other nodes in the multi-hop network.Advancements in FPGAs have been the motivation behind their choice as the vision processing platform for implementing visual sensor node. This choice is based on the reduced time-to-market, low Non-Recurring Engineering (NRE) cost and programmability as compared to ASICs. The other part of the architecture of the visual sensor node is the SENTIO32 platform, which is used for vision processing in the software implementation of the visual sensor node and for communicating the results to the central base station in the hardware implementation (using the RF transceiver embedded in SENTIO32).

sted, utgiver, år, opplag, sider
Sundsvall: Mid Sweden University, 2011. s. 108
Serie
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 65
HSV kategori
Identifikatorer
urn:nbn:se:miun:diva-14445 (URN)STC (Lokal ID)978-91-86694-44-9 (ISBN)STC (Arkivnummer)STC (OAI)
Veileder
Tilgjengelig fra: 2011-09-06 Laget: 2011-09-05 Sist oppdatert: 2016-10-19bibliografisk kontrollert

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