Annals of Mathematics and Artificial Intelligence

, Volume 62, Issue 3, pp 345–370

Knowledge-based multi-criteria optimization to support indoor positioning

Authors

    • Digital Enterprise Research InstituteNational University of Ireland, Galway (NUIG)
  • Torsten Schaub
    • Institut für InformatikUniversität Potsdam
  • Davide Merico
    • NOMADIS Research Lab, Department of Informatics, Systems and CommunicationUniversity of Milan-Bicocca
  • Roberto Bisiani
    • NOMADIS Research Lab, Department of Informatics, Systems and CommunicationUniversity of Milan-Bicocca
Article

DOI: 10.1007/s10472-011-9241-2

Cite this article as:
Mileo, A., Schaub, T., Merico, D. et al. Ann Math Artif Intell (2011) 62: 345. doi:10.1007/s10472-011-9241-2

Abstract

Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision has to be compensated by advanced techniques for localization and tracking. Although there are well established quantitative methods in robotics and neighboring fields for addressing these problems, they lack advanced knowledge representation and reasoning capacities. Such capabilities are not only useful in dealing with heterogeneous and incomplete information but moreover they allow for a better inclusion of semantic information and more general homecare and patient-related knowledge. We address this problem and investigate how state-of-the-art localization and tracking methods can be combined with Answer Set Programming, as a popular knowledge representation and reasoning formalism. We report upon a case-study and provide a first experimental evaluation of knowledge-based position estimation both in a simulated as well as in a real setting.

Keywords

Knowledge representation Answer Set Programming Wireless Sensor Networks Localization Tracking

Mathematics Subject Classifications (2010)

68T27 68T30 68T37 68N17 94A99

Copyright information

© Springer Science+Business Media B.V. 2011