Leveraging provenance to improve data fusion in sensor networks

Gulustan Dogan, Eunsoo Seo, Theodore Brown, Tarek F. Abdelzaher

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Provenance is the information about the origin of the data inputs and the data manipulations to a obtain a final result. With the huge amount of information input and potential processing available in sensor networks, provenance is crucial for understanding the creation, manipulation and quality of data and processes. Thus maintaining provenance in a sensor network has substantial advantages. In our paper, we will concentrate on showing how provenance improves the outcome of a multi-modal sensor network with fusion. To make the ideas more concrete and to show what maintaining provenance provides, we will use a sensor network composed of binary proximity sensors and cameras to monitor intrusions as an example. Provenance provides improvements in many aspects such as sensing energy consumption, network lifetime, result accuracy, node failure rate. We will illustrate the improvements in accuracy of the position of the intruder in a target localization network by simulations.

Original languageEnglish (US)
Title of host publicationMultisensor, Multisource Information Fusion
Subtitle of host publicationArchitectures, Algorithms, and Applications 2012
ISBN (Print)9780819490858
StatePublished - 2012
EventMultisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012 - Baltimore, MD, United States
Duration: Apr 25 2012Apr 26 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherMultisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012
Country/TerritoryUnited States
CityBaltimore, MD


  • Data Fusion
  • Provenance
  • Sensor Networks

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'Leveraging provenance to improve data fusion in sensor networks'. Together they form a unique fingerprint.

Cite this