Location-based cognitive and predictive communication system

• US 9,514,473 B2
• Filed: 04/06/2015
• Issued: 12/06/2016
• Est. Priority Date: 05/07/2012
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Sen, Prabir
• Primary Examiner(s): Gelin, Jean
• Application Number:
  US14/679,880
• Publication Number:
  US 20150220952A1
• Time in Patent Office: 610 Days
• Field of Search: 455/404.2, 455/414.1, 455/418, 455/420, 455/456.1, 455/456.2, 455/456.3, 455/3.01, 455/3.05, 705/1, 705/7, 701/200, 701/201
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• 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 4/21 for social networking applications
• 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 location-based cognitive and predictive communication system includes an interface connected to sensors to receive transactional data for an individual measured by the sensors. A memory stores the transactional data. The transactional data may be associated with a current travel path for the individual and includes a time and geographic location for the individual on the travel path. A prediction module may determine a current activity for the individual based on a prediction determined from the transactional data and may determine a choice set for the individual based on the current activity and based on predictions for a group for which the individual is a member. The choice set may include choices associated with transportation for the current travel path of the individual.

Claims

1. A location-based cognitive and predictive communication system comprising:

a network interface connected to sensors to receive transactional data for an individual measured by the sensors;

a memory to store the transactional data, wherein the transactional data is associated with at least one of a current travel path for the individual; and

a processor to;

determine a cognitive state of the individual;

determine a current activity for the individual based on a prediction determined from the transactional data and the determined cognitive state of the individual; and

determine content related to the determined current activity;

transmit, via the network interface, the content to the individual via a network access device;

determine a speed gap between the individual and a second individual, wherein the speed gap is a difference between a speed the individual is moving on the current travel path and a speed the second individual is moving on the current travel path; and

in response to a determination that the speed gap is less than a predetermined threshold, transmit content generated by the second individual to the individual.

2. The system of claim 1, wherein the transactional data includes a time and geographic location for the individual on the travel path, and historical data pertaining to previous decision making, and wherein the content related to the current activity is related to a choice in a choice set for the individual, and the content is transmitted to the access device with the choice set.

3. The system of claim 1, wherein the processor is to facilitate a dynamic communication thread between the individual and the second individual.

4. The system of claim 1, wherein processor is further to:

determine choice set attributes for choices in a choice set;

calculate a utility for each choice based on the choice set attributes and variables associated with the choices, and

determine for each utility, a probability of the individual being in a state at a particular time, and a multidimensional optimizing factor.

5. The system of claim 4, wherein to determine the choice set, the processor is to:

accumulate the cognitive state for a plurality of individuals;

model each individual as a quantum particle based on time and location;

sheaf the modeled quantum particles to determine groups of the individuals; and

determine the choice set based on predictions for the group for which the individual is a member.

6. The system of claim 1, wherein the processor is to:

determine a location, speed, and direction of the individual based upon the speed gap;

determine an inventory of a number of available transportation types in a geographic location of the individual based upon the determined location, speed, and direction of the individual; and

perform queue-tradeoff-optimization to facilitate transportation demand forecasting.

7. The system of claim 1, wherein the network interface connected to sensors includes the network interface connected to at least one of an Arterial Variable Message Service (AVMS), video traffic surveillance equipment, and a vehicle detection system (VDS).

8. A method of providing prediction-based travel choice set comprising:

storing transactional data from sensors, wherein the transactional data is associated with at least one of a current travel path for an individual;

determining a cognitive state of the individual;

determining, by a processor, a current activity for the individual based on a prediction determined from the transactional data and the determined cognitive state of the individual;

determining, by the processor, content related to the determined current activity;

transmitting the content to the individual via a network interface;

determining a speed gap between the individual and a second individual, wherein the speed gap is a difference between a speed the individual is moving on the current travel path and a speed the second individual is moving on the current travel path; and

in response to a determination that the speed gap is less than a predetermined threshold, transmitting content generated by the second individual to the individual.

9. The method of claim 8, wherein the transactional data includes a time and geographic location for the individual on the travel path, and historical data pertaining to previous decision making, and wherein the content related to the current activity is related to a choice in a choice set for the individual.

10. The method of claim 9, wherein determining a cognitive state comprises:

determining choice set attributes for each choice in the choice set;

calculating a utility for each choice based on the choice set attributes and variables associated with each choice; and

determining, for each utility, a probability of the individual being in a state at a particular time, and a multidimensional optimizing factor.

11. The method of claim 9, comprising:

accumulating cognitive states for individuals;

modeling each individual as a quantum particle based on time and location;

sheafing the modeled quantum particles to determine groups of the individuals; and

determining the choice set based on predictions for the group for which the individual is a member.

12. The method of claim 8, comprising:

facilitating a dynamic communication thread between the individual and the second individual.

13. The method of claim 8, comprising:

determining a location, speed, and direction of the individual based upon the speed gap; and

determining an inventory of a number of available transportation types in a geographic location of the individual based upon the determined location, speed, and direction of the individual.

14. A location-based cognitive and predictive communication system comprising:

a network interface connected to sensors to receive transactional data for an individual measured by the sensors, wherein the transactional data is associated with a current travel path for the individual;

a memory to store the transactional data; and

a processor coupled to the memory, the processor to;

determine a cognitive state of the individual;

determine a current activity for the individual based on a prediction determined from the transactional data and the determined cognitive state of the individual;

determine content related to the determined current activity;

determine a speed gap between the individual and a second individual, wherein the speed gap is a difference between a speed the individual is moving on the current travel path and a speed the second individual is moving on the current travel path, and wherein the content includes content generated by the second individual; and

transmit, via the network interface, the content to the individual in response to a determination that the speed gap is less than a predetermined threshold.

15. The system of claim 14, wherein to determine the cognitive state for the individual, the processor is to:

determine a choice set for the individual;

determine choice set attributes for choices in the choice set;

calculate a utility for each choice in the choice set based on the choice set attributes and variables associated with the choices; and

determine, for each utility, a probability of the individual being in a state at a particular time, and a multidimensional optimizing factor.

16. The system of claim 15, wherein to determine the choice set, the processor is to:

accumulate cognitive states for individuals;

model each individual as a quantum particle based on time and location;

sheaf the modeled quantum particles to determine groups of the individuals; and

determine the choice set based on predictions for the group for which the individual is a member.

17. The system of claim 14, wherein the network interface connected to sensors includes the network interface connected to at least one of an Arterial Variable Message Service (AVMS), video traffic surveillance equipment, and a vehicle detection system (VDS).

18. The system of claim 14, further to:

determine a location, speed, and direction of the individual based upon the speed gap; and

determine an inventory of a number of available transportation types in a geographic location of the individual based upon the determined location, speed, and direction of the individual.