Systems and methods for sensor calibration
US-2015285835-A1 · Oct 8, 2015 · US
US10223845B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-10223845-B1 |
| Application number | US-201615142636-A |
| Country | US |
| Kind code | B1 |
| Filing date | Apr 29, 2016 |
| Priority date | May 15, 2014 |
| Publication date | Mar 5, 2019 |
| Grant date | Mar 5, 2019 |
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A method based on separating ambient gravitational acceleration from a moving three-axis accelerometer data for determining a driving pattern is presented. A server may receive telematics data originating from a client computing device and combine the telematics data. The server may estimate a gravitational constant to the combined telematics data and generate a function for pitch and a roll angle from the combined telematics data. The server may further determine a driving pattern using at least the pitch and the roll angle.
Opening claim text (preview).
What is claimed is: 1. A method for determining a driving pattern comprising: converting a plurality of telematics data, corresponding to a trip of a moving vehicle and originating from a client computing device, from a time domain to a spectral domain, wherein the client computing device includes an accelerometer; selecting data points from the converted telematics data, wherein the selected data points are indicative of the vehicle moving; generating a total spectral power of the data points selected from the converted telematics data; determining that the total spectral power meets a threshold value; identifying a primary movement window including the selected data points if the total spectral power of the selected data points does not meet the threshold value, the primary movement window is indicative of the accelerometer being static with respect to the moving vehicle and a total spectral power that meets the threshold value is indicative of the accelerometer moving with respect to the moving vehicle; estimating a gravitational constant from the telematics data in the primary movement window; generating a pitch angle and a roll angle from the telematics data in the primary movement window; and determining the driving pattern using at least the pitch angle and the roll angle. 2. The method of claim 1 further comprising: applying a rotation matrix to the telematics data, wherein the rotation matrix accounts for the pitch angle and roll angle. 3. The method of claim 1 , wherein generating the pitch angle and roll angle further comprises: measuring an acceleration in the direction of gravity from the telematics data; maximizing the measured acceleration in the direction of gravity; and generating a function for each of the pitch and the roll angles. 4. The method of claim 1 , wherein determining the driving pattern further comprises: determining that the pitch angle and roll angle are indicative of at least one of: an acceleration event, a braking event, a left turn event and a right turn event. 5. The method of claim 1 further comprising: measuring the effect of gravity from the telematics data; minimizing a squared error in the measured gravity in the primary movement window; establishing a function of the gravitational constant based at least on the measured gravity; generating a function for each of a second pitch angle and a second roll angle using the gravitational constant; determining a difference between the pitch angle and the second pitch angle; determining a difference between the roll angle and the second roll angle; and determining whether each difference is within a defined threshold limit. 6. The method of claim 5 , wherein minimizing a squared error in the measured gravity includes a least squares solution. 7. The method of claim 1 , wherein generating the pitch angle and the roll angle further comprises incorporating a rotation matrix definition. 8. A computer device for determining a driving pattern, the computer device comprising: one or more processors; and one or more memories coupled to the one or more processors; wherein the one or more memories include non-transitory computer executable instructions stored therein that, when executed by the one or more processors, cause the one or more processors to: convert a plurality of telematics data corresponding to a trip of a moving vehicle and originating from a client computing device from a time domain to a spectral domain, wherein the client computing device includes an accelerometer; select data points from the converted telematics data, wherein the selected data points are indicative of the vehicle moving; generate a total spectral power of the data points selected from the converted telematics data; determine that the total spectral power meets a threshold value; identify a primary movement window including the selected data points if the total spectral power of the selected data points does not meet the threshold value, wherein the primary movement window is indicative of the accelerometer being static with respect to the moving vehicle and a total spectral power that meets the threshold value is indicative of the accelerometer moving with respect to the moving vehicle; estimate a gravitational constant from the telematics data in the primary movement window; generate a pitch angle and a roll angle from the telematics data in the primary movement window; and determine the driving pattern using at least the pitch angle and the roll angle. 9. The computer device of claim 8 , wherein the non-transitory computer executable instructions further cause the one or more processors to: apply a rotation matrix to the telematics data, wherein the rotation matrix accounts for the pitch angle and roll angle. 10. The computer device of claim 8 , wherein the non-transitory computer executable instructions further cause the one or more processors to: measure an acceleration in the direction of gravity from the telematics data; maximize the measured acceleration in the direction of gravity; and generate a function for each of the pitch and the roll angles. 11. The computer device of claim 8 , wherein the non-transitory computer executable instructions further cause the one or more processors to: determine that the pitch angle and roll angle are indicative of at least one of an acceleration of an acceleration event, a braking event, a left turn event and a right turn event. 12. The computer device of claim 8 , wherein the non-transitory computer executable instructions further cause the one or more processors to: measure the effect of gravity from the telematics data; minimize a squared error in the measured gravity from the telematics data in the primary movement window; establish a function of the gravitational constant based at least on the measured gravity; generate a function for each of a second pitch angle and a second roll angle using the gravitational constant; determine a difference between the pitch angle and the second pitch angle; determine a difference between the roll angle and the second roll angle; and determine whether each difference is within a defined threshold limit. 13. The computer device of claim 12 , wherein the non-transitory computer executable instructions to minimize a squared error in the measured gravity includes a least squares solution. 14. The computer device of claim 8 , wherein the non-transitory computer executable instructions to generate a pitch angle and a roll angle further cause the one or more processors to: incorporate a rotation matrix definition. 15. A computer readable storage medium comprising non-transitory computer readable instructions stored thereon for determining a driving pattern, the instructions when executed on one or more processors cause the one or more processors to: convert a plurality of telematics data corresponding to a trip of a moving vehicle and originating from a client computing device from a time domain to a spectral domain, wherein the client computing device includes an accelerometer; select data points from the converted telematics data, wherein the selected data points are indicative of the vehicle moving; generate a total spectral power of the data points selected from the converted telematics data; determine that the total spectral power meets a threshold value; identify a primary movement window including the selected data points if the total spectral power of the selected data points does not meet the threshold value, wherein the primary movement window is indicative of the accelerometer being static with
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