Media volume control system

• US 8,897,905 B2
• Filed: 10/07/2011
• Issued: 11/25/2014
• Est. Priority Date: 10/07/2011
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Inventors: Harber, Dustin, Oguchi, Kentaro
• Primary Examiner(s): Kuntz, Curtis
• Assistant Examiner(s): MAUNG, THOMAS H
• Application Number:
  US13/269,102
• Publication Number:
  US 20130090751A1
• Time in Patent Office: 1,145 Days
• Field of Search: 382/104
• US Class Current: 700/94
• CPC Class Codes: H03G 3/3005 in amplifiers suitable for low-frequencies, e.g. audio amplifiers H03G3/32, H03G3/34 take precedence
• CPC Class Codes: H03G 3/3089 Control of digital or coded signals

Abstract

A system and method for regulating media volume is disclosed. The system comprises a prediction engine and a regulation module. The prediction engine collects sensor data and scene category data. The scene category data includes data describing an environment in which the media volume is regulated. The prediction engine predicts a workload for a user based at least in part on the scene category data and the sensor data and generates a predicted workload value for the predicted workload. The regulation module adjusts the media volume based at least in part on the predicted workload value.

Claims

1. A computer-implemented method for regulating media volume, the method comprising:

collecting sensor data measuring one or more operational conditions related to a vehicle;

capturing one or more images of an operating environment external to the vehicle;

generating scene category data from the one or more images that classifies the operating environment using one or more scene categories, the one or more scene categories including a weather condition and an overall scene type;

predicting a workload for a user based at least in part on the scene category data and the sensor data;

generating a predicted workload value for the predicted workload; and

adjusting the media volume based at least in part on the predicted workload value.

2. The method of claim 1, wherein predicting the workload for the user further comprises:

aggregating the scene category data and the sensor data to form a prediction feature vector, the prediction feature vector including one or more of brake data, velocity data, steering data, wiper data, light data, and temperature data, the prediction feature vector further including a combination of (1) one or more of weather data and scene type data and (2) one or more of traffic data and road type data; and

predicting the workload for the user based at least in part on the prediction feature vector.

3. The method of claim 1 further comprising:

receiving one or more sensor signals from one or more sensors; and

generating the sensor data based at least in part on the one or more sensor signals.

4. The method of claim 1, wherein the scene category data further classifies the operating environment using at least (1) one or more of the weather condition and the overall scene type and (2) one or more of a road type and a traffic condition.

5. The method of claim 1, wherein the scene category data includes one or more of weather data, road type data, traffic data and scene type data.

6. The method of claim 1, wherein the sensor data includes one or more of brake data, velocity data, steering data, wiper data, light data and temperature data.

7. The method of claim 1, wherein adjusting the media volume further comprises:

determining a current level of the media volume in which media content is being played;

determining a current workload value associated with the current level of the media volume;

determining a predicted level of the media volume associated with the predicted workload value;

comparing the predicted workload value to the current workload value; and

decreasing the media volume from the current level to the predicted level if the predicted workload value is greater than the current workload value.

8. A system for regulating media volume, the system comprising:

a prediction engine collecting sensor data and scene category data, the sensor data measuring one or more operational conditions related to a vehicle, the scene category data generated from one or more images of an operating environment external to the vehicle and classifying the operating environment using one or more scene categories, the one or more scene categories including a weather condition and an overall scene type, the prediction engine predicting a workload for a user based at least in part on the scene category data and the sensor data, the prediction engine generating a predicted workload value for the predicted workload; and

a regulation module communicatively coupled to the prediction engine, the regulation module adjusting the media volume based at least in part on the predicted workload value.

9. The system of claim 8, wherein the prediction engine is further configured to:

aggregate the scene category data and the sensor data to form a prediction feature vector, the prediction feature vector including one or more of brake data, velocity data, steering data, wiper data, light data, and temperature data, the prediction feature vector further including a combination of (1) one or more of weather data and scene type data and (2) one or more of traffic data and road type data; and

predict the workload for the user based at least in part on the prediction feature vector.

10. The system of claim 8 further comprising:

a communication module receiving one or more sensor signals from one or more sensors; and

a sensor module communicatively coupled to the communication module and the prediction engine, the sensor module generating the sensor data based at least in part on the one or more sensor signals, the sensor module sending the sensor data to the prediction engine.

11. The system of claim 8 further comprising:

a communication module receiving one or more images from a camera; and

a scene module communicatively coupled to the communication module and the prediction engine, the scene module processing the one or more images to generate the scene category data, the scene module sending the scene category data to the prediction engine.

12. The system of claim 8, wherein the scene category data further classifies the operating environment using at least (1) one or more of the weather condition and the overall scene type and (2) one or more of a road type and a traffic condition.

13. The system of claim 8, wherein the sensor data includes one or more of brake data, velocity data, steering data, wiper data, light data, and temperature data.

14. The system of claim 8, wherein the regulation module is further configured to:

determine a current level of the media volume in which media content is being played;

determine a current workload value associated with the current level of the media volume;

determine a predicted level of the media volume associated with the predicted workload value;

compare the predicted workload value to the current workload value; and

decrease the media volume from the current level to the predicted level if the predicted workload value is greater than the current workload value.

15. A computer program product comprising a non-transitory computer readable medium encoding instructions that, in response to execution by a computing device, cause the computing device to perform operations comprising:

collecting sensor data measuring one or more operational conditions related to a vehicle;

capturing one or more images of an operating environment external to the vehicle;

generating scene category data from the one or more images that classifies the operating environment using one or more scene categories, the one or more scene categories including a weather condition and an overall scene type;

predicting a workload for a user based at least in part on the scene category data and the sensor data;

generating a predicted workload value for the predicted workload; and

adjusting the media volume based at least in part on the predicted workload value.

16. The computer program product of claim 15, wherein predicting the workload for the user further comprises:

aggregating the scene category data and the sensor data to form a prediction feature vector, the prediction feature vector including one or more of brake data, velocity data, steering data, wiper data, light data, and temperature data, the prediction feature vector further including a combination of (1) one or more of weather data and scene type data and (2) one or more of traffic data and road type data; and

predicting the workload for the user based at least in part on the prediction feature vector.

17. The computer program product of claim 15, wherein the instructions encoded in the computer readable medium when executed cause the computing device to perform operations further comprising:

receiving one or more sensor signals from one or more sensors; and

generating the sensor data based at least in part on the one or more sensor signals.

18. The computer program product of claim 15, wherein the scene category data further classifies the operating environment using at least (1) one or more of the weather condition and the overall scene type and (2) one or more of a road type and a traffic condition.

19. The computer program product of claim 15, wherein the scene category data includes one or more of weather data, road type data, traffic data and scene type data.

20. The computer program product of claim 15, wherein the sensor data includes one or more of brake data, velocity data, steering data, wiper data, light data and temperature data.