Enhanced data collection, processing, and analysis facilities

• US 9,854,450 B2
• Filed: 11/19/2015
• Issued: 12/26/2017
• Est. Priority Date: 05/01/2015
• Status: Active Grant

• Current Assignee: Sybase 365 LLC (SAP SE)
• Original Assignee: Sybase 365 LLC (SAP SE)
• Inventors: Abdullah, Khalid Ata Atiyah, Buzzalino, Arturo, Garcia, Steven Charles, Vohra, Vaibhav, Vuori, Kimmo Olavi
• Primary Examiner(s): Agosta, Steve D
• Application Number:
  US14/946,350
• Publication Number:
  US 20160323767A1
• Time in Patent Office: 768 Days
• Field of Search: 455405-408, 455418-420, 455423-425, 455446-449, 3703102, 370328, 370338
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 16/18 Network planning tools
• CPC Class Codes: H04W 24/08 Testing, supervising or monitoring using real traffic
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/14 Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]
• CPC Class Codes: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]

Abstract

A method and corresponding apparatus configured to collect raw data from a plurality of wireless devices. The raw data includes activity recorded when the wireless devices are at a selected topographic region. The raw data is combined to produce aggregated data representative of the activities of the individual wireless devices. Either the aggregated data or the raw data are selected for analysis depending on whether the raw data meets a threshold activity or subscriber density level. The selected data are analyzed to identify activity patterns of users of the wireless devices.

Claims

1. A method for implementation by one or more data processors forming one or more computing devices, the method comprising:

collecting, by at least one data processor, raw data from a plurality of wireless devices, wherein the raw data includes activity recorded when the wireless devices are at a selected topographic region, and wherein the raw data is combined to produce aggregated data representative of the activities of the individual wireless devices;

forming, by at least one data processor, a geometric representation of the selected topographic region;

adjusting, by at least one data processor, a size of the geometric representation based on a degree of confidence in coordinates of the selected topographic region;

selecting, by at least one data processor, either the aggregated data or the raw data for analysis depending on whether the raw data meets a threshold activity or subscriber density level; and

analyzing, by at least one data processor, the selected data to identify activity patterns of users of the wireless devices, wherein the analyzing;

takes the degree of confidence into consideration when the aggregated data is selected,

does not take the degree of confidence into consideration when the raw data is selected, and

includes determining, by at least one data processor, a home location of an individual wireless device by analyzing times and locations of calls made by the individual wireless device over a period of time, wherein the home location is determined by (i) analyzing, by at least one data processor, call volumes and identifying cell towers that are associated with the calls and that had the highest call volume during the period of time and (ii) by identifying, by at least one data processor, intersections of the cell towers.

2. The method of claim 1, wherein the aggregated data are selected when the raw data meets the threshold activity or subscriber density level.

3. The method of claim 1, wherein the raw data are selected when the raw data fails to meet the threshold activity or subscriber density level.

4. The method of claim 1, further comprising:

selecting, by at least one data processor, a location of a cell tower or intersection having a highest percentage of call volume coverage as the home location.

5. The method of claim 1, wherein the home location is determined by identifying, by at least one data processor, cell towers that are associated with the calls and that have the shortest distance from each other.

6. A non-transitory computer programmable product comprising a computer-readable storage medium having computer-readable program instructions, which when executed result in operations comprising:

collect raw data from a plurality of wireless devices, wherein the raw data includes activity recorded when the wireless devices are at a selected topographic region, and wherein the raw data is combined to produce aggregated data representative of the activities of the individual wireless devices;

form a geometric representation of the selected topographic region;

adjust a size of the geometric representation based on a degree of confidence in coordinates of the selected topographic region;

select either the aggregated data or the raw data for analysis depending on whether the raw data meets a threshold activity or subscriber density level; and

analyze the selected data to identify activity patterns of users of the wireless devices, wherein the analyzing;

takes the degree of confidence into consideration when the aggregated data is selected,

does not take the degree of confidence into consideration when the raw data is selected, and

includes determining, by at least one data processor, a home location of an individual wireless device by analyzing times and locations of calls made by the individual wireless device over a period of time, wherein the home location is determined by (i) analyzing, by at least one data processor, call volumes and identifying cell towers that are associated with the calls and that had the highest call volume during the period of time and (ii) by identifying, by at least one data processor, intersections of the cell towers.

7. The non-transitory computer programmable product of claim 6, wherein the aggregated data are selected when the raw data meets the threshold activity or subscriber density level.

8. The non-transitory computer programmable product of claim 6, wherein the raw data are selected when the raw data fails to meet the threshold activity or subscriber density level.

9. The non-transitory computer programmable product of claim 6, wherein the computer device is configured to:

select a location of a cell tower or intersection having a highest percentage of call volume coverage as the home location.

10. The non-transitory computer programmable product of claim 6, wherein the home location is determined by identifying cell towers that are associated with the calls and that have the shortest distance from each other.

11. A system comprising:

at least one data processor;

memory storing instructions, which when executed by the at least one data processor result in operations comprising;

collecting, by at least one data processor, raw data from a plurality of wireless devices, wherein the raw data includes activity recorded when the wireless devices are at a selected topographic region, and wherein the raw data is combined to produce aggregated data representative of the activities of the individual wireless devices;

forming, by at least one data processor, a geometric representation of the selected topographic region;

adjusting, by at least one data processor, a size of the geometric representation based on a degree of confidence in coordinates of the selected topographic region;

selecting, by at least one data processor, either the aggregated data or the raw data for analysis depending on whether the raw data meets a threshold activity or subscriber density level;

analyzing, by at least one data processor, the selected data to identify activity patterns of users of the wireless devices, wherein the analyzing;

takes the degree of confidence into consideration when the aggregated data is selected,

does not take the degree of confidence into consideration when the raw data is selected, and

includes determining, by at least one data processor, a home location of an individual wireless device by analyzing times and locations of calls made by the individual wireless device over a period of time, wherein the home location is determined by (i) analyzing, by at least one data processor, call volumes and identifying cell towers that are associated with the calls and that had the highest call volume during the period of time and (ii) by identifying, by at least one data processor, intersections of the cell towers,

selecting, by at least one data processor, a location of a cell tower or intersection having a highest percentage of call volume coverage as the home location.

12. The system of claim 11, wherein the aggregated data are selected when the raw data meets the threshold activity or subscriber density level.

13. The system of claim 11, wherein the raw data are selected when the raw data fails to meet the threshold activity or subscriber density level.

14. The system of claim 11, wherein the home location is determined by identifying, by at least one data processor, cell towers that are associated with the calls and that have the shortest distance from each other.