GENERATING WIRELESS NETWORK ACCESS POINT MODELS USING CLUSTERING TECHNIQUES

    公开(公告)号:US20200154392A1

    公开(公告)日:2020-05-14

    申请号:US16068568

    申请日:2017-06-21

    Applicant: Google LLC

    Abstract: The technology relates to generating a wireless network access point model for determining locations within an area. In one example, a plurality of scan vectors, each scan vector representing a set of signal strengths for a set of wireless network access point identifiers and being associated with a location within the area at which a mobile device moving through the area measured the set of signal strengths are received. A set of clusters is generated by iterating through a split phase until the number of clusters in the set of clusters equals a maximum number of clusters or there are no bad scan vectors identified. A bad scan vector may include a vector having a vector difference from a center of a cluster to which that vector is assigned is less than a minimum similarity value. The set of cluster is then used to generate the model of the area.

    Generating wireless network access point models using clustering techniques

    公开(公告)号:US10820296B2

    公开(公告)日:2020-10-27

    申请号:US16068568

    申请日:2017-06-21

    Applicant: Google LLC

    Abstract: The technology relates to generating a wireless network access point model for determining locations within an area. In one example, a plurality of scan vectors, each scan vector representing a set of signal strengths for a set of wireless network access point identifiers and being associated with a location within the area at which a mobile device moving through the area measured the set of signal strengths are received. A set of clusters is generated by iterating through a split phase until the number of clusters in the set of clusters equals a maximum number of clusters or there are no bad scan vectors identified. A bad scan vector may include a vector having a vector difference from a center of a cluster to which that vector is assigned is less than a minimum similarity value. The set of cluster is then used to generate the model of the area.

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