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A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks

Tom Van Haute (UGent) , Jen Rossey (UGent) , Pieter Becue (UGent) , Eli De Poorter (UGent) , Ingrid Moerman (UGent) and Piet Demeester (UGent)
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Abstract
Indoor localization and navigation using wireless sensor networks is still a big challenge if expensive sensor nodes are not involved. Previous research has shown that in a sparse distributed sensor network the error distance is way too high. Even room accuracy can not be guaranteed. In this paper, an easy-to-use generic positioning framework is proposed, which allows users to plug in a single or multiple positioning algorithms. We illustrate the usability of the framework by discussing a new hybrid positioning solution. The combination of a weighted (range-based) and proximity (range-free) algorithm is made. Roth solutions separately have an average error distance of 13.5m and 2.5m respectively. The latter result is quite accurate due to the fact that our testbeds are not sparse distributed. Our hybrid algorithm has an average error distance of 2.66m only using a selected set of nodes, simulating a sparse distributed sensor network. All our experiments have been executed in the iMinds testbed: namely at "de Zuiderpoort". These algorithms are also deployed in two real-life environments: "De Vooruit" and "De Vijvers".
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Citation

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MLA
Van Haute, Tom, et al. “A Hybrid Indoor Localization Solution Using a Generic Architectural Framework for Sparse Distributed Wireless Sensor Networks.” 2014 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), IEEE, 2014, pp. 1009–15.
APA
Van Haute, T., Rossey, J., Becue, P., De Poorter, E., Moerman, I., & Demeester, P. (2014). A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks. 2014 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 1009–1015. IEEE.
Chicago author-date
Van Haute, Tom, Jen Rossey, Pieter Becue, Eli De Poorter, Ingrid Moerman, and Piet Demeester. 2014. “A Hybrid Indoor Localization Solution Using a Generic Architectural Framework for Sparse Distributed Wireless Sensor Networks.” In 2014 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 1009–15. IEEE.
Chicago author-date (all authors)
Van Haute, Tom, Jen Rossey, Pieter Becue, Eli De Poorter, Ingrid Moerman, and Piet Demeester. 2014. “A Hybrid Indoor Localization Solution Using a Generic Architectural Framework for Sparse Distributed Wireless Sensor Networks.” In 2014 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 1009–1015. IEEE.
Vancouver
1.
Van Haute T, Rossey J, Becue P, De Poorter E, Moerman I, Demeester P. A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks. In: 2014 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS). IEEE; 2014. p. 1009–15.
IEEE
[1]
T. Van Haute, J. Rossey, P. Becue, E. De Poorter, I. Moerman, and P. Demeester, “A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks,” in 2014 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), Warsaw, Poland, 2014, pp. 1009–1015.
@inproceedings{5967760,
  abstract     = {{Indoor localization and navigation using wireless sensor networks is still a big challenge if expensive sensor nodes are not involved. Previous research has shown that in a sparse distributed sensor network the error distance is way too high. Even room accuracy can not be guaranteed.
 
In this paper, an easy-to-use generic positioning framework is proposed, which allows users to plug in a single or multiple positioning algorithms. We illustrate the usability of the framework by discussing a new hybrid positioning solution. The combination of a weighted (range-based) and proximity (range-free) algorithm is made. Roth solutions separately have an average error distance of 13.5m and 2.5m respectively. The latter result is quite accurate due to the fact that our testbeds are not sparse distributed. Our hybrid algorithm has an average error distance of 2.66m only using a selected set of nodes, simulating a sparse distributed sensor network. All our experiments have been executed in the iMinds testbed: namely at "de Zuiderpoort". These algorithms are also deployed in two real-life environments: "De Vooruit" and "De Vijvers".}},
  author       = {{Van Haute, Tom and Rossey, Jen and Becue, Pieter and De Poorter, Eli and Moerman, Ingrid and Demeester, Piet}},
  booktitle    = {{2014 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS)}},
  isbn         = {{9788360810583}},
  keywords     = {{IBCN}},
  language     = {{eng}},
  location     = {{Warsaw, Poland}},
  pages        = {{1009--1015}},
  publisher    = {{IEEE}},
  title        = {{A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks}},
  year         = {{2014}},
}

Web of Science
Times cited: