EMBEDDED MOBILE ANALYTICS IN A MOBILE DEVICE

• US 20100041391A1
• Filed: 02/26/2009
• Published: 02/18/2010
• Est. Priority Date: 08/12/2008
• Status: Abandoned Application

• Current Assignee: Taproot Systems Incorporated
• Original Assignee: Taproot Systems Incorporated
• Inventors: Collins, Keith, Rockafellow, Blane E., Smoak, Frank Andrew, Spivey, Anthony Wayne
• Application Number:
  US12/393,576
• Publication Number:
  US 20100041391A1
• Time in Patent Office: Days
• US Class Current: 455/425
• CPC Class Codes: H04W 12/02 Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
• CPC Class Codes: H04W 12/10 Integrity

Abstract

A method or process enables the collection of data from mobile devices and mobile networks using filtering, compression, encryption, memory management, and power management technologies to collect mobile device metrics at the mobile device (client side), and then transmit these metrics from the mobile device to a server for processing by analytics software. The analytics processing may also occur directly on the mobile device. Policies are determined and configured at the processing server to drive and control the mobile device metrics captured, which may include but are not limited to, data usage (e.g. time of day, amount of data sent/received), voice usage (e.g. time of day, calls in/out of network, dropped calls, call duration), the location of the mobile device, cell patterns (e.g. problem cells, roaming), touch interactions, behavioral analysis (programs used, services uses), battery performance, CPU usage, memory usage, network usage (e.g. 2G, 3G, 3.5G, 4G, Wi-Fi, WiMAX), and the like.

Claims

1. A method for enabling collection and transmittal of mobile device metrics, the mobile device metrics including one or more of, battery level, dropped calls, signal strength, numbers dialed, calls received, features used, text messages sent, and voice calls made, mobile device location, said method comprising the steps of:

generating mobile device metrics data in a probe in the mobile device;

filtering the mobile device metrics to eliminate spurious or duplicate metrics data;

encrypting the mobile device metrics data to prevent unauthorized users from reading the mobile device metrics data;

compressing the mobile device metrics data to reduce bandwidth needed to transmit the mobile device metrics data;

transmitting the mobile device data metrics from the mobile device to a server;

processing the mobile device metrics data in the server, using analytics software to analyze mobile device metrics data.

2. The method of claim 1, further comprising the steps of:

encrypting the mobile device metrics data, after said step of filtering the mobile device metrics, to prevent unauthorized users from reading the mobile device metrics data.

3. The method of claim 1, further comprising the steps of:

compressing the mobile device metrics data, after said step of filtering the mobile device metrics, to reduce bandwidth needed to transmit the mobile device metrics data.

4. The method of claim 1, wherein the step of processing the mobile device metrics data comprises the step of analyzing frequency of dropped calls and low signal strength and mobile device location to map low signal strength areas.

5. The method of claim 1, wherein said step of filtering comprises the step of filtering out dropped calls from the mobile device metrics data, where the dropped calls occur during low battery power conditions.

6. The method of claim 1, wherein the step of processing the mobile device metrics data comprises the step of analyzing mobile device usage to determine frequency of usage of mobile device features.

7. The method of claim 1, wherein the step of processing the mobile device metrics data comprises the step of analyzing location of mobile devices during mobile one or more of device voice calls and text messages to determine areas of frequent usage of mobile devices.

8. The method of claim 1, wherein the step of processing the mobile device metrics data comprises the step of analyzing mobile device battery levels to determine average battery level usage for mobile devices.

9. The method of claim 1, wherein the step of processing the mobile device metrics data comprises the step of analyzing features used on the mobile device.

10. The method of claim 1, wherein the step of generating mobile device metrics data in a probe in the mobile device;

comprises the steps of downloading to the mobile device, a software module for probing the mobile device, and operating the software module to probe the mobile device.

11. The method of claim 1, wherein the step of generating mobile device metrics data in a probe in the mobile device;

comprises the steps of installing in the mobile device, a hardware probe for probing the mobile device, and operating the hardware probe to probe the mobile device.

12. The method of claim 1, wherein the mobile device metrics comprise one or more of:

data usage, including one or more of time of day, amount of data sent and received;

voice usage, including time of day, calls in/out of network, dropped calls, and call duration;

location of the mobile device;

cell patterns, including problem cells and roaming;

touch interactions;

behavioral analysis, including programs used and services uses;

battery performance;

CPU usage;

memory usage; and

network usage, including 2G, 3G, 3.5G, 4G, Wi-Fi, and WiMAX.

13. The method of claim 1, further comprising the step of provisioning policies determining what type of probing is to be performed, when it is to be performed, and when the data is to be reported from the mobile device to the analytics server.

14. The method of claim 11 wherein the provisioning policies determine circumstances under which the probing is one or more of halted, suspended, and resumed.