Method for improving discovery of preferred mobile computing locations

• US 9,002,377 B2
• Filed: 08/13/2013
• Issued: 04/07/2015
• Est. Priority Date: 05/09/2011
• Status: Active Grant

• Current Assignee: Google Technology Holdings LLC (Alphabet Inc.)
• Original Assignee: Google Technology Holdings LLC (Alphabet Inc.)
• Inventors: Ayalur, Venkateswaran S., Taranowski, William F., Yan, Haijin
• Primary Examiner(s): Georgewill, Opiribo
• Application Number:
  US13/965,663
• Publication Number:
  US 20130331122A1
• Time in Patent Office: 602 Days
• Field of Search: 455/456.1, 342/357.2
• US Class Current: 455/456.1
• CPC Class Codes: H04W 48/16 Discovering, processing access restriction or access information
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

A method for improving discovery of preferred mobile computing locations includes monitoring sensor data corresponding to a mobile computing device (MCD) and monitoring non-GPS network data implemented by the mobile computing device. Additionally, the method determines whether sensor data and non-GPS network data indicate that the mobile computing device is stationary within a cell site as well as scanning any network that the mobile computing device is electronically linked to. In short, the method discovers an improved preferred mobile computing location based on the sensor data and non-GPS network data that provide reliable information that the mobile computing device is stationary within the cell site. The sensor data and non-GPS network data are converged when several corresponding scans produce overlapping results.

Claims

1. A method for improving discovery of preferred mobile computing locations without relying on GPS data, comprising:

scanning during at least two time periods a network that the mobile computing device is linked to, including receiving cell identification data;

monitoring sensor data corresponding to a mobile computing device (MCD);

monitoring non-GPS network data implemented by the mobile computing device;

determining whether sensor data and non-GPS network data indicate that the mobile computing device is stationary within a cell site; and

discovering an improved preferred mobile computing location based on the sensor data and non-GPS network data providing reliable information that the mobile computing device is stationary within the cell site, wherein mobile computing locations are converged when a plurality of scans associated with sensor data and non-GPS network data produce overlapping results.

2. The method according to claim 1, wherein the sensor data is selected from the group consisting of electrical charging port data, pedometer data, accelerometer data, and remaining battery life data.

3. The method according to claim 1, wherein the non-GPS network data is selected from the group consisting of connection to Bluetooth device, connection to a near field communication device, connection to a Wi-Fi device;

and connection to a cellular device.

4. The method according to claim 1, wherein the sensor data indicates that the MCD is charging.

5. The method according to claim 1, wherein the elapsed time periods for receiving cell identification data are reduced when the MCD is charging.

6. The method according to claim 1, wherein data corresponding to at least one cell ID is stored during at least one elapsed time period.

7. The method according to claim 1, wherein a plurality of cell IDs are received during the elapsed time periods.

8. The method according to claim 7, further comprising the step of comparing the plurality of cell IDs to Wi-Fi access points.

9. The method according to claim 8, further comprising the step of converging at least one cell ID and at least one Wi-Fi access point where an overlap of similar set of cell ID and Wi-Fi access point are found.

10. A mobile computing device for discovery of mobile computing locations without relying on GPS data, the mobile computing device comprising:

one or more physical sensors associated with the mobile computing device for collecting sensor data including one or more detected values; and

one or more processor devices including processor devices adapted for scanning during at least two time periods a network that the mobile computing device is linked to, including receiving cell identification data;

monitoring sensor data corresponding to the mobile computing device;

monitoring non-GPS network data implemented by the mobile computing device;

determining whether sensor data and non-GPS network data indicate that the mobile computing device is stationary within a cell site; and

discovering a mobile computing location based on the sensor data and non-GPS network data providing reliable information that the mobile computing device is stationary within the cell site, wherein mobile computing locations are converged when a plurality of scans associated with sensor data and non-GPS network data produce overlapping results.

11. The mobile computing device according to claim 10, wherein the one or more physical sensors include one or more of infrared sensors, integrated Bluetooth systems, retina-scanning devices, and fingerprint devices.

12. The mobile computing device according to claim 10, wherein the sensor data collected by the one or more physical sensors include sensor data selected from the group consisting of electrical charging port data, pedometer data, accelerometer data and remaining battery life data.

13. The mobile computing device according to claim 10, wherein the non-GPS network data monitored by the mobile computing device is selected from the group consisting of connection to Bluetooth device, connection to a near field communication device, connection to a Wi-Fi device;

and connection to a cellular device.

14. The mobile computing device according to claim 10, wherein the sensor data collected by the one or more physical sensors include sensor data that indicates the mobile computing device is charging.