Knowledge-based multi-criteria optimization to support indoor positioning

  • Alessandra MileoEmail author
  • Torsten Schaub
  • Davide Merico
  • Roberto Bisiani


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.


Knowledge representation Answer Set Programming Wireless Sensor Networks Localization Tracking 

Mathematics Subject Classifications (2010)

68T27 68T30 68T37 68N17 94A99 


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Alessandra Mileo
    • 1
    Email author
  • Torsten Schaub
    • 2
  • Davide Merico
    • 3
  • Roberto Bisiani
    • 3
  1. 1.Digital Enterprise Research InstituteNational University of Ireland, Galway (NUIG)GalwayIreland
  2. 2.Institut für InformatikUniversität PotsdamPotsdamGermany
  3. 3.NOMADIS Research Lab, Department of Informatics, Systems and CommunicationUniversity of Milan-BicoccaMilanItaly

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