发明名称 COMPUTER IMPLEMENTED SYSTEM AND METHOD FOR WI-FI BASED INDOOR LOCALIZATION
摘要 The present disclosure envisages a computer implemented system and method for Wi-Fi based indoor localization. The system includes a repository for storing attributes of the floor plan of an indoor area with respect to the zones on the floor plan. A communicating module receives a threshold number of data points from user devices located in the area. These data points include a plurality of Received Signal Strength Indicators (RSSI) captured from the access points positioned in the area. A k-means clustering is then performed on the data points for grouping the data points into ‘k’ number of clusters and a decision tree is built by following a condition based approach. Distance values are then calculated pertaining to the RSSIs stored at the decision tree, and zone circles are plotted. Zone of user presence is then determined by correlating the plotted zone circles upon the floor plan using maximum overlap property.
申请公布号 US2015257014(A1) 申请公布日期 2015.09.10
申请号 US201414560741 申请日期 2014.12.04
申请人 TATA CONSULTANCY SERVICES LIMITED 发明人 Ahmed Nasimuddin;Bhaumik Chirabrata;Ghose Avik;Pal Arpan;Agrawal Amit;Chakravarty Tapas
分类号 H04W16/20;H04W4/04;H04W24/10 主分类号 H04W16/20
代理机构 代理人
主权项 1. A computer implemented method for indoor localization, said method comprising the following: storing, in a repository, the floor plan of an indoor area including zone details, zone boundaries, building materials and location of different access points with respect to the zones on the floor plan; collecting a threshold number of data points from at least one user device located in said area, wherein each of the data points includes a plurality of Received Signal Strength Indicators (RSSI) captured from the access points positioned in said area; performing a k-means clustering technique on the data points for grouping the data points into ‘k’ number of clusters; building at least one decision tree using the RSSIs contained by the cluster of data points, wherein the decision tree is built by following a condition based approach, and wherein the conditions are related to the values of the RSSIs related to each of the access points; calculating distance values pertaining to the RSSIs stored at the decision tree and plotting zone circles, wherein the zone circles are plotted using the distance values as radii of the zone circles, the access points as centers of the respective zone circles; and determining the zone of user presence by correlating the plotted zone circles upon the floor plan using maximum overlap property.
地址 Mumbai IN