1st International ICST Conference on Mobile Wireless Middleware, Operating Systems and Applications

Research Article

Efficient Indoor Proximity and Separation Detection for Location Fingerprinting

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  • @INPROCEEDINGS{10.4108/ICST.MOBILWARE2008.2804,
        author={Mikkel Baun  Kj\c{c}rgaard and Georg Treu and Peter Ruppel and Axel K\'{y}pper},
        title={Efficient Indoor Proximity and Separation Detection for Location Fingerprinting},
        proceedings={1st International ICST Conference on Mobile Wireless Middleware, Operating Systems and Applications},
        publisher={ICST},
        proceedings_a={MOBILWARE},
        year={2010},
        month={5},
        keywords={LBS Proximity/Separation Detection Fingerprinting},
        doi={10.4108/ICST.MOBILWARE2008.2804}
    }
    
  • Mikkel Baun Kjærgaard
    Georg Treu
    Peter Ruppel
    Axel Küpper
    Year: 2010
    Efficient Indoor Proximity and Separation Detection for Location Fingerprinting
    MOBILWARE
    ICST
    DOI: 10.4108/ICST.MOBILWARE2008.2804
Mikkel Baun Kjærgaard1,*, Georg Treu2,*, Peter Ruppel2,*, Axel Küpper2,*
  • 1: Department of Computer Science, University of Aarhus, Denmark.
  • 2: Mobile and Distributed Systems Group, Institute for Informatics, University of Munich, Germany.
*Contact email: mikkelbk@daimi.au.dk, georg.treu@ifi.lmu.de, peter.ruppel@ifi.lmu.de, axel.kuepper@ifi.lmu.de

Abstract

Detecting proximity and separation among mobile targets is a basic mechanism for many location-based services (LBSs) and requires continuous positioning and tracking. However, realizing both mechanisms for indoor usage is still a major challenge. Positioning methods like GPS cannot be applied there, and for distance calculations the particular building topology has to be taken into account. To address these challenges, this paper presents a novel approach for indoor proximity and separation detection, which uses location fingerprinting for indoor positioning of targets and walking distances for modeling the respective building topology. The approach applies efficient strategies to reduce the number of messages transmitted between the mobile targets and a central location server, thus saving the targets’ battery power, bandwidth, and other resources. The strategies are evaluated in terms of efficiency and application-level accuracy based on numerous emulations on experimental data.