Pre-processing of mobile communication device geolocations according to travel mode in traffic analysis

• US 10,555,130 B1
• Filed: 04/09/2019
• Issued: 02/04/2020
• Est. Priority Date: 04/09/2019
• Status: Active Grant

• Current Assignee: T-Mobile Innovations LLC (Deutsche Telekom AG)
• Original Assignee: Sprint Communications Company LP (Deutsche Telekom AG)
• Inventors: Burcham, Robert H., Habiger, Matthew, Pickett, Adam C.
• Primary Examiner(s): Vu, Michael T
• Application Number:
  US16/379,784
• Time in Patent Office: 301 Days
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

A geolocating method to determine a traffic flow at a point-of-interest (POI). The method comprises clustering geolocation data associated with a plurality of mobile communication devices by an analysis application executing on a computer system based on different clustering algorithms associated with different travel modes identified by the geolocation data, for each of the plurality of mobile communication devices, determining travel routes traversed by the mobile communication device by the analysis application based on the clustering of the geolocation data and based on a map of travel routes, where each of the travel routes is one of a highway travel route, a light rail travel route, or a footpath travel route, and, for each of a plurality of POIs, determining by the analysis application a number of different mobile communication devices that intersect with the POI based on the travel routes traversed by the mobile communication devices.

Claims

1. A geolocating method of sorting geolocation data associated with a plurality of mobile communication devices into different travel modes, clustering the geolocation data according to different clustering algorithms based on the different travel modes of the geolocation data, determining travel routes traversed by the plurality of mobile communication devices based on the clustering of the geolocation data, and analyzing the intersections of points-of-interest (POIs) and the travel routes to determine a traffic flow at the POI, comprising:

storing a map of travel routes in a first data store, where each of the travel routes is one of a highway travel route, a light rail travel route, or a footpath travel route;

storing geolocation data associated with a plurality of mobile communication devices in a second data store, where each item of geolocation data identifies a location of a mobile communication device, identifies the mobile communication device, identifies a cell site to which the mobile communication device attached to, and identifies a timestamp comprising a date and a time;

designating some of the geolocation data stored in the second data store by an analysis application executing on a computer system as associated with a light rail travel mode based on the identity of the cell site contained in the geolocation data;

designating some of the geolocation data stored in the second data store by the analysis application as associated with a footpath travel mode based on the location contained in the geolocation data;

inferring a speed of travel associated with some of the geolocation data by the analysis application;

designating some of the geolocation data stored in the second data store by the analysis application as associated with a highway travel mode based on the inferred speed of travel associated with the geolocation data;

designating some of the geolocation data stored in the second data store by the analysis application as associated with the footpath travel mode based on the inferred speed of travel associated with the geolocation data;

clustering the geolocation data associated with the light rail travel mode by the analysis application based on a light rail travel mode clustering algorithm;

clustering the geolocation data associated with the footpath travel mode by the analysis application based on a footpath travel mode clustering algorithm;

clustering the geolocation data associated with the highway travel mode by the analysis application based on a highway travel mode clustering algorithm;

for each of the plurality of mobile communication devices, determining travel routes traversed by the mobile communication device based on the clustering of the geolocation data by the analysis application and based on the map of travel routes; and

for each of a plurality of POIs, determining by the analysis application a number of different mobile communication devices that intersect with the POI based on the travel routes traversed by the mobile communication devices, whereby traffic flows at the geolocation of the POIs are determined.

2. The geolocating method of claim 1, wherein the POI is one of a billboard, a building, or a presentation screen.

3. The geolocating method of claim 1, wherein the mobile communication devices are selected from the group consisting of mobile phones, smart phones, headset computers, wearable computers, laptop computers, notebook computers, and tablet computers.

4. The geolocating method of claim 1, wherein the map of travel routes comprises at least one highway travel route digital map, at least one light rail travel route digital map, and at least one footpath travel route digital map.

5. The geolocating method of claim 1, wherein designating some of the geolocation data as associated with the light rail travel mode comprises accessing a list of cell sites located in a subway system and comparing the identity of cell sites contained in the geolocation data to the identity of cell sites contained in the list of cell sites located in the subway system.

6. The geolocating method of claim 1, wherein the footpath travel mode clustering algorithm uses a footpath clustering radius parameter, the light rail travel mode clustering algorithm uses a light rail clustering radius parameter, and the highway travel mode clustering algorithm uses a highway clustering radius parameter.

7. The geolocating method of claim 1, wherein the first data store comprises a plurality of maps of geofenced areas, where each geofenced area is a contiguous extent of space that is associated with one of the footpath travel mode, the highway travel mode, or the light rail travel mode, and wherein designating some of the geolocation data as associated with the footpath travel mode based on the location contained in the geolocation data comprises determining that the location contained in the geolocation data falls within a geofenced area associated with the footpath travel mode.

8. The geolocating method of claim 1, wherein the geolocation data further identifies a tile in which the location of the geolocation data lies, wherein the POIs are each associated with a tile in which the POI lies, and where for each POI the analysis application compares geolocations associated with the same tile as the POI of travel routes traversed by the mobile communication devices in determining a number of intersections with the POI.

9. A geolocating system that clusters geolocation data associated with a plurality of mobile communication devices according to different clustering algorithms based on different travel modes associated with the geolocation data, determines travel routes traversed by the plurality of mobile communication devices based on the clustering of the geolocation data, and analyzes the intersections of points-of-interest (POIs) and the travel routes to determine a traffic flow at the POI, comprising:

at least one processor;

a non-transitory memory;

a first data store comprising a map of travel routes, where each travel route is one of a highway travel route, a light rail travel route, or a footpath travel route;

a second data store comprising geolocation data associated with a plurality of mobile communication devices, where each item of geolocation data identifies a location of a mobile communication device, identifies the mobile communication device, identifies a cell site to which the mobile communication device is attached to, and identifies a timestamp comprising a date and a time; and

an analysis application stored in the non-transitory memory that, when executed by the at least one processor;

designates some of the geolocation data stored in the second data store as associated with a light rail travel mode based on the identity of the cell site contained in the geolocation data,

designates some of the geolocation data stored in the second data store as associated with a footpath travel mode based on the location contained in the geolocation data,

infers a speed of travel associated with some of the geolocation data,

designates some of the geolocation data stored in the second data store as associated with a highway travel mode based on the inferred speed of travel associated with the geolocation data,

designates some of the geolocation data stored in the second data store as associated with the footpath travel mode based on the inferred speed of travel associated with the geolocation data,

clusters the geolocation data associated with the highway travel mode based on a highway travel mode clustering algorithm,

clusters the geolocation data associated with the light rail travel mode based on a light rail travel mode clustering algorithm,

clusters the geolocation data associated with the footpath travel mode based on a footpath travel mode clustering algorithm,

for each of the plurality of mobile communication devices, determines travel routes traversed by the mobile communication device based on the clustering of the geolocation data and based on the map of travel routes, and

for each of a plurality of POIs, determines a number of different mobile communication devices that intersect with the POI based on the travel routes traversed by the mobile communication devices, whereby traffic flows at the geolocation of the POIs are determined.

10. The geolocating system of claim 9, wherein the map comprises a first digital map comprising highway routes, a second digital map comprising light rail routes, and a third digital map comprising footpath routes.

11. The geolocating system of claim 10, wherein the first digital map, the second digital map, and the third digital map represent routes as a plurality of route segments, and each route is represented as an edge terminated at each end by a vertex.

12. The geolocating system of claim 9, wherein the geolocations are represented in part as geohashes or as latitude-longitude coordinates.

13. The geolocating system of claim 9, wherein the POIs each comprises a location and a perimeter.