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Distributed data fusion in peer-to-peer environment

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Distributed data fusion in peer-to-peer environment. Sergiy Nazarko, InBCT 3.2, Agora center, University of Jyväskylä. Data fusion. Branch of applied mathematics Combines different pieces of information to receive: new compatible information more accurate data. - PowerPoint PPT Presentation
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Distributed data Distributed data fusion in peer-to-peer fusion in peer-to-peer environment environment Sergiy Nazarko, InBCT 3.2, Agora center, University of Jyväskylä
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Page 1: Distributed data fusion in peer-to-peer environment

Distributed data fusion in Distributed data fusion in peer-to-peer environmentpeer-to-peer environment

Sergiy Nazarko, InBCT 3.2, Agora center, University of Jyväskylä

Page 2: Distributed data fusion in peer-to-peer environment

Data fusionData fusion

Branch of applied mathematicsCombines different pieces of information to

receive:– new compatible information– more accurate data

Page 3: Distributed data fusion in peer-to-peer environment

Sundial – simple example of Sundial – simple example of data fusiondata fusion

Page 4: Distributed data fusion in peer-to-peer environment

Data fusion applicationsData fusion applications

Military– target tracking– target identification– data association– situation assessment

Non-military– machine vision– medical decision

support systems– environmental

monitoring

Page 5: Distributed data fusion in peer-to-peer environment

Multisensor data fusionMultisensor data fusion

Improved estimatesProblems:

– corrupt data– different data– different level of precision– conflicting data

Page 6: Distributed data fusion in peer-to-peer environment

Area of interestArea of interestData fusion algorithms which can be

used for target tracking and identification– Transferable Belief Model– Kalman Filtering

Page 7: Distributed data fusion in peer-to-peer environment

““Eye Of Ra”Eye Of Ra”

User InterfaceTBM Kalman Filter

Page 8: Distributed data fusion in peer-to-peer environment

Decentralized data fusion Decentralized data fusion systemssystems

Collection of processing nodesNone of the nodes has knowledge about the

overall network topologyEach node performs a specific computing

taskNo central node exists that controls the

network

Page 9: Distributed data fusion in peer-to-peer environment

Features of DDFSsFeatures of DDFSs

Reliability– no central node– loss of nodes or links does not prevent rest of

the system from functioningFlexibility

– nodes can be added or deleted by making only local changes

– only establishment of links to one or more nodes is needed

Page 10: Distributed data fusion in peer-to-peer environment

Work doneWork done

Master’s thesises: – S. Nazarko, Evaluation of Data Fusion Methods Using

Kalman Filter and TBM– V. Smirnova, Multiagent System for Distributed Data

Fusion in Peer-to-Peer Environment

Gained experience in applying data fusion methods

“Eye Of Ra”

Page 11: Distributed data fusion in peer-to-peer environment

Work in processWork in processIntegration of evaluated algorithm into Chedar

– To get a little bit clearer picture on this step only Kalman filter will be implemented as part of Chedar

Page 12: Distributed data fusion in peer-to-peer environment

Interaction between nodesInteraction between nodes

Page 13: Distributed data fusion in peer-to-peer environment

Network componentsNetwork components

-little Square – sensor node with transmission capabilities

- bold square –control node with sensor’s node capabilities

GUI – user interface which displays tracking trajectory.

Page 14: Distributed data fusion in peer-to-peer environment

Future workFuture work

Further learning of data fusion methodsFusion of TBM and Kalman filterImplementing totally distributed data fusion

system based on peer-to-peer platformEvaluation and research

Page 15: Distributed data fusion in peer-to-peer environment

Thank you!Thank you!


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