Method for Detecting Airplane Flight Events, Mobile Communication Device, and Computational Unit Therefor

• US 20110047112A1
• Filed: 08/12/2010
• Published: 02/24/2011
• Est. Priority Date: 08/13/2009
• Status: Abandoned Application

• Current Assignee: Deutsche Telekom AG, Technische Universitã¤T Berlin (Tu)
• Original Assignee: Deutsche Telekom AG, Technische Universitã¤T Berlin (Tu)
• Inventors: PEYLO, Christoph, KETABDAR, Hamed
• Application Number:
  US12/855,256
• Publication Number:
  US 20110047112A1
• Time in Patent Office: Days
• US Class Current: 706/20
• CPC Class Codes: G01S 5/0018 Transmission from mobile station to base station
• CPC Class Codes: G06N 3/02 Neural networks

Abstract

A method for detecting airplane flight events using at least one acceleration sensor associated with a mobile communication device includes obtaining at least one acceleration signal from the at least one acceleration sensor; pre-processing the obtained at least one acceleration signal to remove redundant information present in the at least one acceleration signal; performing a feature extraction on the pre-processed at least one acceleration signal; and classifying airplane flight events based on an acceleration pattern represented by the extracted acceleration features.

Claims

1. A method for detecting airplane flight events using at least one acceleration sensor associated with a mobile communication device, the method comprising the steps of:

obtaining at least one acceleration signal from said at least one acceleration sensor;

pre-processing said obtained at least one acceleration signal to remove redundant information present in said at least one acceleration signal;

performing a feature extraction on said pre-processed at least one acceleration signal; and

classifying airplane flight events based on an acceleration pattern represented by the extracted acceleration features.

2. The method of claim 1, wherein the step of classifying airplane flight events comprises comparing said acceleration pattern with statistical reference models for different events.

3. The method of claim 2, wherein said statistical model is an artificial neural network or a Gaussian mixture model.

4. The method of claim 1, wherein the step of classifying airplane flight events comprises comparing said acceleration pattern with a hidden Markov model, wherein each state of the model models an event class.

5. The method of claim 1, wherein features extracted from said pre-processed at least one acceleration signal are include at least one of an acceleration magnitude over different axes, a rate of change in acceleration over different axis, an absolute magnitude of the acceleration, and a pairwise difference between acceleration magnitudes over different axis.

6. The method of claim 1, further comprising the step of changing an operating state of the mobile communication device depending on the classification result.

7. The method of claim 6, wherein the mobile communication device is turned on or off to adapt the mobile communication device to the detected airplane flight event.

8. The method of claim 1, further comprising the step of comparing the detected airplane flight event with one or more regular airplane flight events.

9. The method of claim 8, wherein taking off or landing is detected if the result of the comparing step is a match below a predetermined threshold between the detected airplane flight event and the one or more regular airplane flight events.

10. The method of claim 2, wherein the statistical reference models are trained for typical airplane flight events except for taking off and landing.

16. The method of claim 1 wherein the flight event include at least one of a takeoff and landing.

11. A mobile communication device comprising:

a processor; and

at least one acceleration sensor configured to provide at least one acceleration signal to the processor;

the processor being configured to pre-process said at least one acceleration signal to remove redundant information present in said at least one acceleration signal, the processor being further configured to perform a feature extraction on said pre-processed at least one acceleration signal, and the processor being configured to classify airplane flight events based on an acceleration pattern represented by the extracted acceleration features.

14. An air cargo carrier comprising the mobile communication device of claim 11.

12. A computational unit connectable with a mobile communication device, the computational unit for detecting airplane flight events, the computational unit comprising:

a processor;

at least one acceleration sensor configured to provide at least one acceleration signal to the processor;

the processor being configured to pre-process said at least one acceleration signal to remove redundant information present in said at least one acceleration signal, the processor being further configured to perform a feature extraction on said pre-processed at least one acceleration signal; and

the processor being configured to classify airplane flight events based on an acceleration pattern represented by the extracted acceleration features; and

a controller configured to receive information from the processor and to initiate transmission of a control command to the mobile communication device once connected with the computational unit, based on the detected airplane flight event.

13. The computational unit of claim 12 wherein the computation unit is connected to a mobile communication device.

15. An air cargo carrier comprising the computational unit of claim 12.