SYSTEM AND METHOD FOR IDENTIFYING AND ANALYZING PERSONAL CONTEXT OF A USER

• US 20140351337A1
• Filed: 01/22/2013
• Published: 11/27/2014
• Est. Priority Date: 02/02/2012
• Status: Active Grant

• Current Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Original Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Inventors: Pal, Arpan, Purushothaman, Balamuralidhar, Misra, Prateep, Kopparapu, Sunil Kumar, Sinha, Aniruddha, Bhaumik, Chirabrata, Sinha, Priyanka, Ghose, Avik
• Granted Patent: US 9,560,094 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G01S 5/02585 at least one of the measurements being a non-radio measurement
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G09B 19/06 Foreign languages with audible presentation of material to be studied G09B5/04
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04M 1/72454 according to context-related or environment-related conditions
• CPC Class Codes: H04M 1/72457 according to geographic location
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/08 User group management

Abstract

A method and system for identifying personal context of a user having a portable mobile communication device at a particular location for deriving social interaction information of the user, wherein the user within a predefined range is identified using personal context of the user at the particular location and the identified personal context of the user is assigned with the confidence value. Further the current location information of the user within the particular location is obtained by fusing assigned confidence value. Further the proximity of the user in the current location is estimated by finding the accurate straight line distance between users. Further the two users having similar current location information at the particular location are grouped together with the predefined density criteria. Finally the social interaction information of the user is derived by multimodal sensor data fusion at the fusion engine and represented using a human network graph.

Claims

1. A method for identifying personal context of at least one user having a portable mobile communication device at a location for deriving social interaction information of the user, the method comprising:

determining a location of at least one user within a predefined range by identifying a personal context of the user at the location, wherein the personal context of the user is identified using at least an external sensor and an internal sensor embedded in the mobile communication device;

assigning predefined confidence values to the identified personal context;

obtaining current location information relating to the user at the location by fusing the assigned confidence values;

grouping, based on predefined density criteria, at least two users having similar current location information at the location of the user;

estimating, using the external sensor and internal sensor, a straight line distance between the at least two grouped users; and

deriving social interaction information of the user by fusing the current location information of the user, the estimated straight line distance, and data received from a web sensor.

2. The method of claim 1, wherein the personal context of the user is at least one of an identity, proximity, an activity, and a location.

3. The method of claim 1, wherein the mobile communication device is at least one of a mobile phone, a smartphone, a laptop, a palmtop, and a personal data assistant (PDA).

4. The method of claim 1, wherein the external sensor is at least one of a building management system (BMS), a 3-D depth camera, and an ultrasound sensor.

5. The method of claim 1, wherein the internal sensor is at least one of an accelerometer, a magnetometer, a speech recognizer, a Bluetooth RSSI, and a wireless frequency (Wi-Fi) signature.

6. The method of claim 1, wherein the predefined density criteria is derived using a density based clustering method.

7. The method of claim 1, wherein the external sensor and the internal sensor are physical sensors.

8. The method of claim 1, wherein the web sensor is at least one of a social networking website profile of the user, email headers associated with the user, an RSS feed, and a social blog profile of the user.

9. The method of claim 1, wherein:

the external sensor and the internal sensor are communicatively coupled with a processing module;

the external sensor transmits sensory data to the processing module via an external sensor interface; and

the internal sensor transmits sensory data to the processing module directly.

10. The method of claim 9, wherein the sensory data transmitted by the external sensor and the internal sensor is stored in an internal memory communicatively coupled with the processing module.

11. The method of claim 1, wherein the derived social interaction information is displayed using a front end application.

12. The method of claim 1, wherein the derived social interaction information is at least one of an interaction while working in cubicle, an interaction while leading a meeting, an interaction of a presenter in a session, a passive listener in meeting, and an interaction during a group discussion.

13. The method of claim 1, wherein the fused confidence value, the fused current location information, and the personal context of the user are stored in a database that is communicatively coupled to a back end server.

14. The method of claim 1, further comprising switching between other mobile device applications of the internal sensor and personal context of the user when an interrupt is generated from regular activities of the mobile communication device.

15. A system for identifying a personal context of at least one user at a location for deriving social interaction information of the user, the system comprising:

a mobile communication device, comprising;

an internal sensor adapted for sensing a personal context of the user and sending the personal context to a processing module of the mobile communication device;

the processing module adapted to perform on-board processing of sensory data received from an external sensor and the internal sensor;

an internal memory communicatively coupled with the processing module and adapted to store the processed sensory data;

a transmission module adapted to transmit the processed sensory data to a back end server hosting a fusion engine and communicatively coupled to a database adapted to store fused confidence values, fused current location information of the user, and the personal context of the user; and

a switching module adapted for switching between other mobile device applications of the internal sensor and the personal context of the user when an interrupt is generated from regular activities of the mobile communication device; and

wherein the external sensor is adapted for sensing the personal context of the user and sending the personal context of the user to the processing module via an external sensor interface of the mobile communication device, and

wherein the back end server is adapted for fusing assigned predefined confidence values of the personal context of the user, current location information of the user, and a derived accurate straight line distance between at least two users in a group at a location of the user.

16. The system of claim 15, wherein the system further comprises:

a localization module adapted for locating at least one user within a predefined range by identifying the personal context of the user at the location, wherein the personal context of the user is identified using the external sensor and the internal sensor;

a confidence value assignment module adapted for assigning the predefined confidence values to the identified personal context of the user;

a current location identification module adapted for obtaining current location information of the user within the location by fusing the assigned confidence values using a fusion engine;

a grouping module adapted for grouping, using a predefined density criteria, at least two users having similar current location information at the location; and

a proximity estimation module adapted for estimating, using the external sensor and the internal sensor, an accurate straight line distance between the grouped at least two users;

wherein the fusion engine is adapted for deriving the social interaction information of the user by fusing the current location information of the user and estimated accurate straight line distance.

17. The system of claim 15, wherein the mobile communication device is at least one of a mobile phone, a smartphone, a laptop, a palmtop, and a personal data assistant (PDA).

18. The system of claim 15, wherein the external sensor is at least one of a building management system (BMS), a 3-D depth camera, a wearable EEG, and an ultrasound sensor.

19. The system of claim 15, wherein the internal sensor is at least one of an accelerometer, a magnetometer, a speech recognizer, and a Wi-Fi signature.

20. A non-transitory computer readable medium storing machine readable instructions executable by one or more processors for:

determining a location of at least one user within a predefined range by identifying a personal context of the user at the location, wherein the personal context of the user is identified using at least an external sensor and an internal sensor embedded in the mobile communication device;

assigning predefined confidence values to the identified personal context;

obtaining current location information relating to the user at the location by fusing the assigned confidence values;

grouping, based on predefined density criteria, at least two users having similar current location information at the location of the user;

estimating, using the external sensor and internal sensor, a straight line distance between the at least two grouped users; and

deriving social interaction information of the user by fusing the current location information of the user, the estimated straight line distance, and data received from a web sensor.