Automatic position determination of fixed infrastructure sensor network nodes based on topology sensing and maps

Werner Kurschl, Wolfgang Gottesheim, Stefan Mitsch, Rene Prokop, Johannes Schönböck

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

The tracking of objects and humans has recently received a lot of attention as a tool to improve business processes, occupational and public safety. In industrial environments wireless sensor networks can facilitate deployment of tracking applications as they can establish a standalone communication infrastructure (a so called mesh network). Many such positioning and location tracking systems deploy a fixed infrastructure (so-called beacons) with known positions to determine the position of mobile nodes in the network. For large-scale deployments the installation effort of such systems may be a major cost-factor, as the exact position of each beacon needs to be manually determined and associated with map material. We therefore propose a position determination tool that automatically finds the positions of beacons based on the sensor network's topology, digital map material of the environment, and a small set of anchor nodes.

Original languageEnglish
Title of host publicationProceedings of the 2008 International Conference on Wireless Networks, ICWN 2008
Pages17-22
Number of pages6
Publication statusPublished - 2008
Event2008 International Conference on Wireless Networks, ICWN 2008 - Las Vegas, NV, United States
Duration: 14 Jul 200817 Jul 2008

Publication series

NameProceedings of the 2008 International Conference on Wireless Networks, ICWN 2008

Conference

Conference2008 International Conference on Wireless Networks, ICWN 2008
CountryUnited States
CityLas Vegas, NV
Period14.07.200817.07.2008

Keywords

  • Deployment
  • Topology
  • Wireless sensor networks

Fingerprint Dive into the research topics of 'Automatic position determination of fixed infrastructure sensor network nodes based on topology sensing and maps'. Together they form a unique fingerprint.

Cite this