METHOD AND SYSTEM FOR AUTOMATING ORGANIZATIONAL TASKS USING A WIRELESS NODE NETWORK

• US 20090193080A1
• Filed: 01/24/2008
• Published: 07/30/2009
• Est. Priority Date: 01/24/2008
• Status: Abandoned Application

• Current Assignee: Intuit, Inc.
• Original Assignee: Intuit, Inc.
• Inventors: Toscano, Robert L.
• Application Number:
  US12/019,166
• Publication Number:
  US 20090193080A1
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• 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 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/20 Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel

Abstract

Some embodiments of the present invention provide a wireless node network that includes a set of portable devices associated with members of an organization and a set of client nodes. During operation, the client nodes detect the portable devices in the vicinity of the client nodes and send records of detected portable devices to the server. The records are then stored by the server and are subsequently used to automate organizational tasks for the organization.

Claims

1. A method for using a portable device, comprising:

registering the portable device with a wireless node network, wherein the portable device is associated with a member of an organization;

broadcasting tracking information from the portable device to a client node in the wireless node network; and

using the tracking information to automate an organizational task for the organization.

2. The method of claim 1, further comprising:

using the tracking information to generate a predictive model of interaction within the organization.

3. The method of claim 2, wherein a learning technique is used to generate the predictive model.

4. The method of claim 2, wherein the tracking information includes at least one of a device identifier (ID), a username, a client node ID, a timestamp, and a signal strength at the node.

5. The method of claim 1, wherein the organizational task is associated with at least one of a location of the member, a meeting of the member, a proximity of the member to another member of the organization, an attendance record of the member, and an amount of time spent with another member of the organization.

6. The method of claim 1, wherein the portable device is at least one of a mobile phone, a personal digital assistant (PDA), a portable computer, a portable media player, a global positioning system (GPS) transceiver, a Bluetooth device, an infrared wireless device, and a badge of the user.

7. A method for using a client node of a wireless node network, comprising:

connecting the client node to a server of the wireless node network;

obtaining a list of registered portable devices from the server;

scanning to detect a portable device from the list of registered portable devices; and

if the portable device is detected;

generating a record of the portable device; and

sending the record to the server,

wherein the record is associated with a member of an organization, and

wherein the record is used to automate an organizational task for the organization.

8. The method of claim 7, further comprising:

using the record to generate a predictive model of interaction within the organization.

9. The method of claim 8, wherein a learning technique is used to generate the predictive model.

10. The method of claim 7, wherein the record includes at least one of a device identifier (ID), a usemame, a client node ID, a timestamp, and a signal strength at the node.

11. The method of claim 7, wherein the organizational task is associated with at least one of a location of the member, a meeting of the member, a proximity of the member to another member of the organization, an attendance record of the member, and an amount of time spent with another member of the organization.

12. The method of claim 7, wherein the client node is at least one of a computer, a wireless access point, a Bluetooth device, and an infrared wireless device.

13. A wireless node network, comprising:

a server comprising a tracking repository;

a set of portable devices, wherein each of the portable devices is associated with one of a set of members of an organization; and

a set of client nodes configured to;

detect the portable devices in the vicinity of the client nodes; and

send records of detected portable devices to the server,

wherein the records are stored in the tracking repository, and

wherein the records are used to automate organizational tasks for the organization.

14. The wireless node network of claim 13, wherein the records are used to create a predictive model of interaction within the organization.

15. The wireless node network of claim 14, wherein a learning technique is used to generate the predictive model.

16. The wireless node network of claim 13, wherein the information is at least one of a device identifier (ID), a username, a client node ID, a timestamp, and a signal strength at the node.

17. The wireless node network of claim 13, wherein each of the organizational tasks involve at least one of a location of the members, a meeting of the members, a proximity of the members to one another, an attendance record of the members, and an amount of interaction between members of the organization.

18. The wireless node network of claim 13, wherein each of the portable devices is at least one of a mobile phone, a personal digital assistant (PDA), a portable computer, a portable media player, a global positioning system (GPS) transceiver, a Bluetooth device, an infrared wireless device, and a badge.

19. The wireless node network of claim 13, wherein each of the client nodes is at least one of a computer, a wireless access point, a Bluetooth device, and an infrared wireless device.

20. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for using a client node of a wireless node network, the method comprising:

connecting the client node to a server of the wireless node network;

obtaining a list of registered portable devices from the server;

scanning to detect a portable device from the list of registered portable devices; and

if the portable device is detected;

generating a record of the portable device; and

sending the record to the server,

wherein the record is associated with a member of an organization, and

wherein the record is used to automate an organizational task for the organization.

21. The computer-readable storage medium of claim 20, the method further comprising:

using the record to generate a predictive model of interaction within the organization.

22. The computer-readable storage medium of claim 21, wherein a learning technique is used to generate the predictive model.

23. The computer-readable storage medium of claim 20, wherein the record includes at least one of a device identifier (ID), a username, a client node ID, a timestamp, and a signal strength at the node.

24. The computer-readable storage medium of claim 20, wherein the organizational task is associated with at least one of a location of the member, a meeting of the member, a proximity of the member to another member of the organization, an attendance record of the member, and an amount of time spent with another member of the organization.

25. The computer-readable storage medium of claim 20, wherein the client node is at least one of a computer, a wireless access point, a Bluetooth device, and an infrared wireless device.