Inferring Position Knowledge from Location Predicates [chapter]

Jörg Roth
Location- and Context-Awareness  
Many context-and location-aware applications request high accuracy and availability of positioning systems. In reality however, knowledge about the current position may be incomplete or inaccurate as a result of, e.g., limited coverage. Often, position data is thus merged from a set of systems, each contributing a piece of position knowledge. Traditional sensor fusion approaches such as Kalman or Particle filters have certain demands concerning the statistical distribution and relation between
more » ... d relation between position and sensor output. Negated position statements ("I'm not at home"), cell-based information or external spatial data are difficult to incorporate into existing mechanisms. In this paper, we introduce a new approach to deal with different types of position data which typically appear in context-or location-aware application scenarios.
doi:10.1007/978-3-540-75160-1_15 dblp:conf/loca/Roth07 fatcat:utt66vwrnnc63fchdx5ebcltru