Method and system for classifying mobile terminals

• US 6,853,848 B2
• Filed: 06/20/2002
• Issued: 02/08/2005
• Est. Priority Date: 06/20/2002
• Status: Active Grant

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Sahinoglu, Zafer
• Primary Examiner(s): Nguyen, Lee
• Assistant Examiner(s): PHU, SANH D
• Application Number:
  US10/175,530
• Publication Number:
  US 20040203861A1
• Time in Patent Office: 964 Days
• Field of Search: 455/456.1, 455/456.3, 455/456.5, 455/457, 455/414.2, 342/450, 342/451, 340/992, 340/993, 340/994
• US Class Current: 455/456.1
• CPC Class Codes: H04W 8/02 Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]; Transfer of mobility data, e.g. between HLR, VLR or external networks
• CPC Class Codes: H04W 8/10 between location register and external networks
• 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 method classifies a mobile terminal by a-periodically obtaining locations of the mobile terminal. Location update intervals are determined from update times associated with the locations. Frequency characteristics are generated from the location update intervals, and a probability distribution function is generated from the location update interval. Then, the mobile terminal is classified according to the frequency characteristics and the probability distribution function.

Claims

1. A method for classifying a mobile terminal, comprising:

a-periodically obtaining locations of the mobile terminal;

determining location update intervals from update times associated with the locations;

generating frequency characteristics from the location update intervals;

generating a probability distribution function from the location update intervals; and

classifying the mobile terminal according to the frequency characteristics and the probability distribution function.

2. The method of claim 1 further comprising:

converting serial location update intervals to parallel location update intervals;

sampling and holding the parallel location update intervals as samples;

upsampling the sample; and

transforming the samples into the frequency characteristics.

3. The method of claim 1 wherein the transform is a fast Fourier transform.

4. The method of claim 1 further comprising:

adapting and delivering location aware services according to the classification of the mobile terminal.

5. The method of claim 1 wherein the locations are obtained via a network.

6. The method of claim 1 wherein the mobile terminal is classified as pedestrian, urban driver, or highway driver.

7. The method of claim 1 wherein a frequency of obtaining the locations depends on a speed at which the mobile terminal is moving.