Systems and methods for transportation mode determination using motion

1. A method comprising:

obtaining motion data from one or more sensors of a mobile device during a trip;

acquiring speed data from a sensor of the one or more sensors of the mobile device during the trip;

correlating, by a processor, the motion data to the speed data to separate the motion data into one or more groupings based on the speed data;

performing, by the processor, a spectral analysis on magnitudes of the motion data for each of the one or more groupings to obtain a set of frequency components;

calculating, by the processor, an energy for each frequency component of the set of frequency components obtained from the spectral analysis;

comparing, by the processor, the energy of each frequency component of the set of frequency components to one or more baseline values for each frequency component to generate a set of differences; and

determining, by the processor, a transportation mode used for the trip based on one or more differences from the set of differences.

2. The method of claim 1 , wherein the transportation mode is a car.

3. The method of claim 2 , further comprising:

operating the one or more sensors at a first sampling frequency before determining the transportation mode; and

operating the one or more sensors at a second sampling frequency after determining the transportation mode, wherein the second sampling frequency is higher than the first sampling frequency.

4. The method of claim 1 , wherein the transportation mode is one of a bus, train, or subway.

5. The method of claim 4 , further comprising:

operating the one or more sensors at a first sampling frequency before determining the transportation mode; and

operating the one or more sensors at a second sampling frequency after determining the transportation mode, wherein the second sampling frequency is lower than the first sampling frequency.

6. The method of claim 4 , further comprising:

operating the one or more sensors at a first sampling frequency before determining the transportation mode; and

disabling the one or more sensors after determining the transportation mode.

7. The method of claim 1 , wherein the one or more sensors of the mobile device include a magnetometer and the motion data includes magnetometer data.

8. The method of claim 1 , wherein the one or more sensors of the mobile device include an accelerometer and the motion data includes accelerometer data.

9. The method of claim 1 , wherein each baseline value of the one or more baseline values is associated with a transportation mode type of a plurality of transportation mode types and a frequency component of the set of frequency components.

10. The method of claim 1 , wherein each difference of the set of differences is associated with a transportation mode type of a plurality of transportation mode types, and the method further comprises:

determining that differences of the set of differences associated with a first transportation mode type are smaller than differences of the set of differences associated with other transportation mode types; and

determining that the first transportation mode type was the transportation mode used for the trip in response.

11. A system, comprising:

one or more sensors of a mobile device; and

a processor configured to perform operations including:

obtaining motion data from the one or more sensors of the mobile device during a trip;

acquiring speed data from a sensor of the one or more sensors of the mobile device during the trip;

correlating the motion data to the speed data to separate the motion data into one or more groupings based on the speed data;

performing a spectral analysis on magnitudes of the motion data for each of the one or more groupings to obtain a set of frequency components;

calculating an energy for each frequency component of the set of frequency components obtained from the spectral analysis;

comparing the energy of each frequency component of the set of frequency components to one or more baseline values for each frequency component to generate a set of differences; and

determining a transportation mode used for the trip based on one or more differences from the set of differences.

12. The system of claim 11 , wherein the processor is separate from the mobile device.

13. The system of claim 11 , wherein the one or more sensors of the mobile device include: a magnetometer and the motion data includes magnetometer data;

an accelerometer and the motion data includes accelerometer data; or both.

14. The system of claim 11 , wherein the processor is further configured to perform operations including:

operating the one or more sensors at a first sampling frequency before determining the transportation mode; and

operating the one or more sensors at a second sampling frequency in response to determining the transportation mode.

15. The system of claim 14 , wherein:

the second sampling frequency is lower than the first sampling frequency responsive to determining that the transportation mode is one of a bus, a train, or a subway; and

the second sampling frequency is higher than the first sampling frequency responsive to determining that the transportation mode is a car.

16. A non-transitory computer readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

obtaining motion data from one or more sensors of a mobile device during a trip;

acquiring speed data from a sensor of the one or more sensors of the mobile device during the trip;

correlating the motion data to the speed data to separate the motion data into one or more groupings based on the speed data;

performing a spectral analysis on magnitudes of the motion data for each of the one or more groupings to obtain a set of frequency components;

calculating an energy for each frequency component of the set of frequency components obtained from the spectral analysis;

comparing the energy of each frequency component of the set of frequency components to one or more baseline values for each frequency component to generate a set of differences; and

determining a transportation mode used for the trip based on one or more differences from the set of differences.

17. The non-transitory computer readable medium as defined in claim 16 , wherein the one or more sensors of the mobile device include: a magnetometer and the motion data includes magnetometer data; an accelerometer and the motion data includes accelerometer data; or both.

18. The non-transitory computer readable medium as defined in claim 16 , wherein each difference of the set of differences is associated with a transportation mode type of a plurality of transportation mode types, and the operations further comprise:

determining that differences of the set of differences associated with a first transportation mode type are smaller than differences of the set of differences associated with other transportation mode types; and

determining that the first transportation mode type was the transportation mode used for the trip in response.

19. The non-transitory computer readable medium as defined in claim 16 , wherein the operations further comprise:

operating the one or more sensors at a first sampling frequency before determining the transportation mode; and

operating the one or more sensors at a second sampling frequency in response to determining the transportation mode.

20. The non-transitory computer readable medium as defined in claim 19 , wherein:

the second sampling frequency is lower than the first sampling frequency responsive to determining that the transportation mode is one of a bus, a train, or a subway; and

the second sampling frequency is higher than the first sampling frequency responsive to determining that the transportation mode is a car.