TEMPO SPATIAL DATA EXTRACTION FROM NETWORK CONNECTED DEVICES

• US 20110055216A1
• Filed: 11/11/2010
• Published: 03/03/2011
• Est. Priority Date: 05/15/2008
• Status: Active Grant

• Current Assignee: Zone Technologies, Inc. (Helios & Matheson Analytics, Inc.)
• Original Assignee: trendIT, Ltd.
• Inventors: WEINROTH, Erez
• Granted Patent: US 8,700,631 B2
• Time in Patent Office: Days
• US Class Current: 707/740
• CPC Class Codes: H04W 24/08 Testing, supervising or monitoring using real traffic
• CPC Class Codes: H04W 8/18 Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data

Abstract

A computer implemented data processing system for estimating an amount of people situated in a specific location and their geo-demographic classification within time range is provided herein. The system is combined of a collector that is configured to collect data on signals and each signal is given a unique ID; an association module configured to associate each signal with a respective location, namely, place of origin; a processing unit configured to calculate total number of users subscribed to a specific network service provider situated in a specific location and time range; calculate a dynamic ratio by research and statistical data; and an estimation module configured to estimate the amount of people originated from a specific location and the overall amount of people in a location within a time range, by applying the calculated dynamic ratio, that was calculated to each time stamp separately.

Claims

1. A data processing system for estimating an amount of people in a specific location and their geo-demographic classification, the data processing system comprising:

a collector configured to collect data on signals that are broadcasted by a network service provider over time, wherein each signal is given a unique ID;

an association module configured to associate each signal with a respective location, based on calculated median number of transmissions of detected signals in a specified location in a specified period of time;

a processing unit configured to;

(a) calculate total number of users subscribed to a specific network service provider situated in a specific location and time range; and

(b) calculate a dynamic ratio by research and statistical data, between (i) the number of users of a specific network service provider situated in a specified location and time range originated in a specific location and (ii) a number of people originated in a specific location; and

an estimation module configured to estimate the amount of people originated from a specific location and the overall amount of people in a location within a time range, by applying the calculated dynamic ratio, that was calculated to each time stamp separately.

2. The data processing system according to claim 1, further comprising a combining module, and wherein the combining module combines the aggregated user related data from the aggregation module with corresponding geographical coordinates received from the location module.

3. The data processing system according to claim 2, further comprising an interpolating module and wherein the interpolating module spatially interpolates the combined aggregated user related data.

4. The data processing system according to claim 3, further comprising a calibrating module, and wherein the calibrating module calibrates the interpolated data with exogamic statistical data.

5. The data processing system according to claim 4, wherein the data processing system creates tempo-spatial related network-connected devices masses pattern representations using spatial and temporal geo-statistics techniques.

6. The data processing system according to claim 1, further comprising:

a client relationship management (CRM) database exhibiting unique user identifiers corresponding with the user profiles of the network-connected devices;

a CRM data categorizer; and

a location-based combiner, wherein the network-connected devices identifier is arranged to;

repeatedly identify, every a first time period, all network-connected devices which are both active and idle in each location area;

repeatedly create a table, every a second time period comprising a plurality of the first time period, for all location areas, each table exhibiting;

location area identifier, unique user identifier, time of inflow to the location area, time of outflow from the location area; and

differentiate table of time N−

1 over table of time N thereby detecting inflow outflow quantities of unique identifiers for each location area; and

wherein the CRM data categorizer is arranged to;

decipher the difference table by the authentication center of the network; and

analyze the deciphered tables using CRM profiles; and

wherein the location-based combiner is arranged to join over time, the deciphered tables with corresponding location area thereby creating at least one Geographic Information System (GIS) data layer.

7. The data processing system according to claim 6, wherein the location-based combiner is further arranged to estimate global phenomena to specific carrier network connected-devices ratios.

8. The data processing system according to claim 6, wherein the CRM data categorizer analyzes the deciphered tables using CRM profiles by categorizing and summing the CRM data by user profiles.

9. The data processing system according to claim 6, wherein the CRM data categorizer analyzes the deciphered tables using CRM profiles is conducted such that properties of a particular area are used to deduce further information in relation to the users located in the particular location area.

10. The data processing system according to claim 6, wherein the CRM data categorizer analyzes the deciphered tables using CRM profiles such that properties of a particular categorized user profile are used to deduce further information in relation to the particular location area in which the users are located.

11. The data processing system according to claim 1, further comprising:

a CRM database not exhibiting unique user identifiers corresponding with the user profiles of the network-connected devices;

a CRM data categorizer; and

a location-based combiner, wherein the network-connected devices identifier is arranged to;

repeatedly identify, every a first time period, all active network-connected devices in each location area using the unique identifier;

repeatedly create a table, every a second time period comprising a plurality of the first time period, for all location areas, each table exhibiting;

location area identifier, unique user identifier, time of inflow to the location area, time of outflow from the location area;

differentiate table of time N−

1 over table of time N thereby detecting inflow outflow quantities of unique identifiers for each location area;

factorize said difference by the ratio of stationary non-active network-connected device and the total number of network-connected devices and wherein the CRM data categorizer is arranged to;

decipher the difference table by the authentication center of the network; and

analyze the deciphered tables using CRM profiles; and

wherein the location-based combiner is arranged to join over time, the deciphered tables with corresponding location area thereby creating at least one GIS data layer.

12. A method of estimating an amount of people in a specific location and their geo-demographic classification, the method comprising:

collecting data on signals that are broadcasted by a network service provider over time, wherein each signal is given a unique ID;

associating each signal with a respective location, based on calculated median number of transmissions of detected signals in a specified location in a specified period of time;

calculating total number of users subscribed to a specific network service provider situated in a specific location and time range;

calculating a dynamic ratio by research and statistical data, between (i) the number of users of a specific network service provider situated in a specified location and time range originated in a specific location and (ii) a number of people originated in a specific location; and

estimating the amount of people originated from a specific location and the overall amount of people in a location within a time range, by applying the calculated dynamic ratio, that was calculated to each time stamp separately.

13. The method according to claim 12, further comprising periodically repeating the aggregating of the collected data thereby creating tempo-spatial data stamps, each exhibiting anonymous aggregated profiles classes associated with geographical locations.

14. The method according to claim 13, further comprising estimating global phenomena in accordance with the tempo-spatial data stamps, in view of the network-connected devices ratios.

15. The method according to claim 12, further comprising creating, using geo-statistical methods, a GIS layer presenting the anonymous aggregated profiles classes associated with geographical locations.

16. The method according to claim 12, further comprising:

receiving CRM data exhibiting unique user identifiers corresponding CRM profiles of the network-connected devices;

repeatedly identifying, every first time period, all active network-connected devices in each location area;

repeatedly creating a table, every second time period comprising a plurality of the first time period, for all location areas, each table exhibiting;

location area identifier, unique user identifier, time of inflow to the location area, time of outflow from the location area;

differentiating table of time N−

1 over table of time N thereby detecting inflow outflow quantities of unique identifiers for each location area;

deciphering the difference table by the authentication center of the network; and

analyze the deciphered tables using the CRM profiles; and

joining over time, the deciphered tables with corresponding location area thereby creating at least one GIS data layer.

17. The method according to claim 12, further comprising:

receiving CRM data not exhibiting unique user identifiers corresponding CRM profiles of the network-connected devices;

repeatedly identifying, every first time period, all active network-connected devices in each location area;

repeatedly creating a table, every second time period comprising a plurality of the first time period, for all location areas, each table exhibiting;

location area identifier, unique user identifier, time of inflow to the location area, time of outflow from the location area;

differentiating table of time N−

1 over table of time N thereby detecting inflow outflow quantities of unique identifiers for each location area;

factorizing said difference by the ratio of stationary non-active network-connected device and the total number of network-connected devices;

deciphering the difference table by the authentication center of the network; and

analyze the deciphered tables using the CRM profiles; and

joining over time, the deciphered tables with corresponding location area thereby creating at least one GIS data layer.

18. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method of estimating an amount of people in a specific location and their geo-demographic classification, the method comprising:

collecting data on signals that are broadcasted by a network service provider over time, wherein each signal is given a unique ID;

associating each signal with a respective location, based on calculated median number of transmissions of detected signals in a specified location in a specified period of time;

calculating total number of users subscribed to a specific network service provider situated in a specific location and time range;

calculating a dynamic ratio by research and statistical data, between (i) the number of users of a specific network service provider situated in a specified location and time range originated in a specific location and (ii) a number of people originated in a specific location; and

estimating the amount of people originated from a specific location and the overall amount of people in a location within a time range, by applying the calculated dynamic ratio, that was calculated to each time stamp separately.

19. The computer program product according to claim 18, wherein the method further comprising periodically repeating the aggregating of the combined data thereby creating tempo-spatial data stamps, each exhibiting anonymous aggregated profiles classes associated with geographical locations.

20. The computer program product according to claim 18, wherein the method further comprising estimating global phenomena in accordance with the tempo-spatial data stamps, in view of the network-connected devices ratios.