Granted Patent B2

US 11,787,413 · App. 16/794,114 · Granted Oct 17, 2023

Inventors: Evaline Shin-Tin Tsai (Cupertino, CA); Kieran K. Gupta (San Francisco, CA); Margaret Irene Finch (San Francisco, CA); Matthew Lee Basham (Oakland, CA); Bodecker John DellaMaria (San Francisco, CA); Brian Tuan (Cupertino, CA); James Chen (San Francisco, CA); Jason Noah Laska (San Francisco, CA); Jason Frederic Symons (Dublin, CA); John Charles Bicket (San Francisco, CA); Kavya Joshi (San Francisco, CA); Ryan Reading (San Francisco, CA); Sabrina Quinn Shemet (San Francisco, CA); Sean Kyungmok Bae (San Francisco, CA); Ishaan Kansal (San Francisco, CA)

Assignee: Samsara Inc.

B60W40/04G06V10/82G06V20/46G06V20/56G06F18/214G06V20/44G06V20/582G06V20/597

Abstract

Claims (75)

1. A method comprising:

detecting a start of a trip;

accessing a sensor data stream generated by a sensor device in response to the detecting the start of the trip, the sensor data stream comprising image data;

generating baseline data based on a first portion of the image data that corresponds with a predetermined distance traveled from the start of the trip;

performing a comparison of the baseline data to a second portion of the image data from the sensor data stream;

detecting an event based on the comparison, the event comprising attributes;

identifying one or more client devices based on the attributes of the event, responsive to detecting the event; and

causing a notification at the one or more client devices based on the event.

2. The method of claim 1 , wherein the detecting the start of the trip includes:

accessing accelerometer data; and

detecting the start of the trip based on the accelerometer data.

3. The method of claim 1 , wherein the detecting the start of the trip includes:

accessing geolocation data; and

detecting the start of the trip based on the geolocation data.

4. The method of claim 1 , wherein the sensor device includes a dash-cam, and the image data comprises a set of image features that depict a gaze and a head pose.

5. The method of claim 1 , wherein the method further comprises:

identifying a user account based on the image data from the sensor data stream; and

associating the baseline value to the user account.

6. The method of claim 5 , wherein the start of the trip is a first start of a first trip, and the method further comprises:

detecting a second start of a second trip;

identifying the user account based on the image data from the sensor device; and

retrieving the baseline value in response to the identifying the user account based on the image data.

7. The method of claim 1 , wherein the generating the baseline data based on the first portion of the image data from the sensor data stream includes:

generating a training data set based on the baseline data; and

training a machine-learned model based on the training data set.

8. A system comprising:

at least one sensor device to generate sensor data comprising a plurality of data streams;

a memory; and

at least one hardware processor to perform operations comprising:

detecting a start of a trip;

accessing a sensor data stream generated by a sensor device in response to the detecting the start of the trip, the sensor data stream comprising image data;

generating baseline data based on a first portion of the image data that corresponds with a predetermined distance traveled from the start of the trip;

performing a comparison of the baseline data to a second portion of the image data from the sensor data stream;

detecting an event based on the comparison, the event comprising attributes;

identifying one or more client devices based on the attributes of the event, responsive to detecting the event; and

causing a notification at the one or more client devices based on the event.

9. The system of claim 8 , wherein the detecting the start of the trip includes:

accessing accelerometer data; and

detecting the start of the trip based on the accelerometer data.

10. The system of claim 8 , wherein the detecting the start of the trip includes:

accessing geolocation data; and

detecting the start of the trip based on the geolocation data.

11. The system of claim 8 , wherein the sensor device includes a dash-cam, and the image data comprises a set of image features that depict a gaze and a head pose.

12. The system of claim 8 , wherein the operations further comprise:

identifying a user account based on the image data from the sensor data stream; and

associating the baseline value to the user account.

13. The system of claim 12 , wherein the start of the trip is a first start of a first trip, and the operations further comprise:

detecting a second start of a second trip;

identifying the user account based on the image data from the sensor device; and

retrieving the baseline value in response to the identifying the user account based on the image data.

14. The system of claim 8 , wherein the generating the baseline data based on the first portion of the image data from the sensor data stream includes:

generating a training data set based on the baseline data; and

training a machine-learned model based on the training data set.

15. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:

detecting a start of a trip;

accessing a sensor data stream generated by a sensor device in response to the detecting the start of the trip, the sensor data stream comprising image data;

generating baseline data based on a first portion of the image data that corresponds with a predetermined distance traveled from the start of the trip;

performing a comparison of the baseline data to a second portion of the image data from the sensor data stream;

detecting an event based on the comparison, the event comprising attributes;

identifying one or more client devices based on the attributes of the event, responsive to detecting the event; and

causing a notification at the one or more client devices based on the event.

16. The non-transitory machine-readable storage medium of claim 15 , wherein the detecting the start of the trip includes:

accessing accelerometer data; and

detecting the start of the trip based on the accelerometer data.

17. The non-transitory machine-readable storage medium of claim 15 , wherein the detecting the start of the trip includes:

accessing geolocation data; and

detecting the start of the trip based on the geolocation data.

18. The non-transitory machine-readable storage medium of claim 15 , wherein the sensor device includes a dash-cam, and the image data comprises a set of image features that depict a gaze and a head pose.

19. The non-transitory machine-readable storage medium of claim 15 , wherein the operations further comprise:

identifying a user account based on the image data from the sensor data stream; and

associating the baseline value to the user account.

20. The non-transitory machine-readable storage medium of claim 19 , wherein the start of the trip is a first start of a first trip, and the operations further comprise:

detecting a second start of a second trip;

identifying the user account based on the image data from the sensor device; and

retrieving the baseline value in response to the identifying the user account based on the image data.

Assignments (2)

Continuity (2)

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