Scene-based sensor networks

1. A computer-implemented method for specifying and obtaining a variety of sensor data and processed sensor data related to a Scene, the method comprising:

communicating a SceneMode from an application to a sensor-side technology stack via a Scene-based application programming interface (API), the sensor-side technology stack comprising a group of one or more sensor devices; and

receiving SceneData from the sensor-side technology stack via the Scene-based API, in response to the communication of the SceneMode to the sensor-side technology stack, the SceneData organized into SceneShots that are samples of the Scene;

wherein:

the SceneData is generated by the sensor-side technology stack based on a plurality of different types of sensor data captured by the sensor group;

the SceneMode does not specify all of the sensor data captured by the sensor group; but the sensor-side technology stack determines, based on the SceneMode, the sensor data that is not specified by the SceneMode;

the SceneData includes SceneData that results from analysis of the captured sensor data; and

the SceneMode does not specify all of the analysis performed by the sensor-side technology stack; but the sensor-side technology stack determines, based on the SceneMode, the analysis not specified by the SceneMode.

2. The computer-implemented method of claim 1 wherein the SceneMode does not specify all of the sensor-level settings for sensors in the sensor group, but the sensor-side technology stack determines based on the SceneMode the sensor-level settings not specified by the SceneMode.

3. The computer-implemented method of claim 1 wherein the SceneMode does not specify all of the types of sensors used to capture the sensor data, but the sensor-side technology stack determines based on the SceneMode the types of sensors not specified by the SceneMode.

4. The computer-implemented method of claim 1 wherein the SceneMode abstracts away from specific implementation of the analysis, but the sensor-side technology stack determines based on the SceneMode the specific implementation of the analysis.

5. The computer-implemented method of claim 1 wherein the SceneMode is one of Home Surveillance, Baby Monitoring, Large Area Surveillance, Personal Assistant, Smart Doorbell, Face Recognition, Restaurant Camera, Security, Robot, Appliance/IoT (Internet of Things), Health/Lifestyle, Wearables and Leisure SceneModes.

6. The computer-implemented method of claim 1 wherein the SceneMode is defined using CaptureModes, and the CaptureModes are building blocks for the SceneModes but are higher level than sensor data captured by sensors in the sensor group.

7. The computer-implemented method of claim 6 wherein the CaptureModes abstract away from individual sensors in the sensor group.

8. The computer-implemented method of claim 6 wherein the CaptureModes include at least one of High Dynamic Range, Biometric, Kinetic, Multi-focal, Stereo/Array, and Crop CaptureModes.

9. The computer-implemented method of claim 1 wherein the SceneMode is dynamic but does not specify all of the changes to the sensor-level settings for the sensor group as the Scene progresses, and the sensor-side technology stack determines based on the SceneMode changes to the sensor-level settings for the sensor group that are not specified by the SceneMode.

10. The computer-implemented method of claim 1 wherein the Scene-based API is a standard.

11. The computer-implemented method of claim 10 wherein the standard includes a set of predefined SceneModes.

12. The computer-implemented method of claim 1 wherein the SceneData includes CapturedData, which includes at least two different types of sensor data captured by the sensor group, wherein at least one of the types of sensor data includes image data.

13. The computer-implemented method of claim 12 wherein the SceneData further includes ProcessedData created by processing the CapturedData.

14. The computer-implemented method of claim 13 wherein the ProcessedData includes at least one of the following: images created by combining two or more different types of captured images, images with depth information, three-dimensional imagery derived from captured images, local images of interest identified by processing captured images, and imagery with motion information.

15. The computer-implemented method of claim 12 wherein the SceneData further include MetaData for the SceneData, the MetaData including labels for results of analyzing the CapturedData.

16. The computer-implemented method of claim 1 wherein the SceneData includes SceneData that results from an artificial intelligence or a machine learning analysis, and the SceneMode does not specify the artificial intelligence or the machine learning analysis, but the sensor-side technology stack determines the artificial intelligence or the machine learning analysis based on the SceneMode.

17. The computer-implemented method of claim 16 wherein the artificial intelligence or the machine learning analysis is performed by cloud-based services.

18. A system comprising:

a plurality of applications that each consume sensor data;

a sensor-side technology stack comprising a group of one or more sensor devices that capture sensor data;

a Scene-based application programming interface (API) for communication between the applications and the sensor-side technology stack;

wherein the applications communicate SceneModes to the sensor-side technology stack via the Scene-based API; and

wherein the sensor-side technology stack returns SceneData to the application via the Scene-based API in response to the communication of the SceneMode to the sensor-side technology stack, the SceneData organized into SceneShots that are samples of the Scene; and

wherein:

the SceneData is generated by the sensor-side technology stack based on a plurality of different types of sensor data captured by the sensor group;

the SceneMode does not specify all of the sensor data captured by the sensor group; but the sensor-side technology stack determines, based on the SceneMode, the sensor data that is not specified by the SceneMode;

the SceneData includes SceneData that results from analysis of the captured sensor data; and

the SceneMode does not specify all of the analysis performed by the sensor-side technology stack; but the sensor-side technology stack determines, based on the SceneMode, the analysis not specified by the SceneMode.

19. A sensor-side technology stack for capturing and producing a variety of sensor data and processed sensor data related to Scenes for multiple applications, the technology stack comprising:

a group of one or more sensor devices that in the aggregate capture a plurality of different types of sensor data;

a Scene-based application programming interface (API) that is accessible by multiple applications, the API for receiving SceneModes from the applications; and

wherein the sensor-side technology stack returns SceneData to the applications via the Scene-based API in response to the communication of the SceneModes to the sensor-side technology stack and organizes the SceneData into SceneShots that are samples of the Scene; and

wherein:

the SceneData is generated by the sensor-side technology stack based on a plurality of different types of sensor data captured by the sensor group;

the SceneMode does not specify all of the sensor data captured by the sensor group; but the sensor-side technology stack determines, based on the SceneMode, the sensor data that is not specified by the SceneMode;

the SceneData includes SceneData that results from analysis of the captured sensor data; and

the SceneMode does not specify all of the analysis performed by the sensor-side technology stack; but the sensor-side technology stack determines, based on the SceneMode, the analysis not specified by the SceneMode.