Patent ID: 8989774
Filing Date: 2015-03-24
Classification: G01S,H04W

Abstract:
1. A method executed by a computer system implementing a semantic indoor positioning system, the semantic indoor positioning system to locate a mobile device inside a building by using a plurality of reference areas as satellites, where the building includes the plurality of reference areas, where a scan of a plurality of wireless radio signals is obtained by the mobile device of a user at an unknown location in the building, where the plurality of wireless radio signals is generated by a plurality of wireless access points (WAPs), where the scan includes a plurality of detected WAPs with a corresponding received signal strength indication (RSSI) for each detected WAP in the plurality of detected WAPs, the method to improve accuracy of the semantic indoor positioning system by generating a vector of distance scores for the unknown location based on the scan for comparison with a plurality of vectors of survey distance scores corresponding to the plurality of reference areas, the method comprising the steps of: arranging the plurality of detected WAPs into an ordered list of WAPs according to the corresponding RSSI for each detected WAP in the plurality of detected WAPs; extracting a set of WAP tuples from the ordered list of WAPs, wherein each WAP tuple in the set of WAP tuples includes a preset number of adjacent WAPs from the ordered list; retrieving a set of probabilities for each reference area in the plurality of reference areas based on the set of WAP tuples, wherein each probability in the set of probabilities for a corresponding reference area is calculated from a plurality of survey scans obtained at the corresponding reference area; calculating a plurality of distance scores for the plurality of reference areas, wherein each distance score in the plurality of distance scores is calculated by applying a Bayesian model to the retrieved set of probabilities for the corresponding reference area; generating the vector of distance scores for the unknown location using each reference area in the plurality of reference areas as a direction and each distance score in the plurality of distance scores as a magnitude; and comparing the vector of distance scores for the unknown location with each of the plurality of vectors of survey distance scores to find the reference area that has a highest probability of including the unknown location.