Cloud coverage estimation by dynamic scheduling of a distributed set of cameras

Patent metadata

Field	Value
Publication number	US-10114149-B2
Application number	US-201615172566-A
Country	US
Kind code	B2
Filing date	Jun 3, 2016
Priority date	Jun 3, 2016
Publication date	Oct 30, 2018
Grant date	Oct 30, 2018

Abstract

Methods, systems, and computer program products for cloud coverage estimation by dynamic scheduling of a distributed set of cameras are provided herein. A computer-implemented method includes transmitting one or more instructions to each of multiple spatially-distributed cameras in a pre-determined geographic area, wherein the one or more instructions cause each of the spatially-distributed cameras to change a context from (i) a pre-determined task to (ii) capturing one or more spatio-temporal measurements of cloud coverage; tracking the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras; obtaining one or more meteorological measurements from one or more non-camera sources; and generating a cloud coverage forecast for the pre-determined geographic area based on (i) the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras and (ii) the one or more meteorological measurements from the one or more non-camera sources.

First claim

What is claimed is:

1. A computer-implemented method, comprising:
transmitting one or more instructions to each of multiple spatially-distributed cameras in a pre-determined geographic area, wherein the one or more instructions cause each of the spatially-distributed cameras to change a context from (i) a pre-determined task to (ii) capturing one or more spatio-temporal measurements of cloud coverage;
tracking the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras;
obtaining one or more meteorological measurements from one or more non-camera sources; and
generating a cloud coverage forecast for the pre-determined geographic area based on (i) the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras and (ii) the one or more meteorological measurements from the one or more non-camera sources;
wherein the steps are carried out by at least one computing device.

2. The computer-implemented method of claim 1 , wherein the one or more instructions are based on an opportunity cost arising from changing the context of a given one of the cameras from (i) the pre-determined task of the given camera to (ii) capturing the one or more spatio-temporal measurements of cloud coverage.

3. The computer-implemented method of claim 2 , wherein the opportunity cost comprises the potential impact on the pre-determined task as a result of the context change to capturing the one or more spatio-temporal measurements of cloud coverage.

4. The computer-implemented method of claim 2 , wherein the opportunity cost comprises the potential benefit to capturing the one or more spatio-temporal measurements of cloud coverage as a result of the context change from the pre-determined task.

5. The computer-implemented method of claim 4 , wherein the potential benefit to capturing the one or more spatio-temporal measurements of cloud coverage comprises projected improvement in cloud coverage forecast accuracy.

6. The computer-implemented method of claim 1 , wherein the one or more instructions are based on availability of a given one of the cameras to change the context from (i) the pre-determined task of the given camera to (ii) capturing the one or more spatio-temporal measurements of cloud coverage.

7. The computer-implemented method of claim 1 , wherein the one or more instructions are based on one or more configuration parameters derived from each of the multiple spatially-distributed cameras.

8. The computer-implemented method of claim 7 , wherein the one or more configuration parameters comprise positioning of a given camera, camera type of the given camera, and/or one or more constraints corresponding to the given camera.

9. The computer-implemented method of claim 1 , wherein the multiple spatially-distributed cameras comprise one or more traffic cameras, one or more agriculture crop cameras, and/or one or more astronomical cameras.

10. The computer-implemented method of claim 1 , wherein said tracking comprises aggregating the one or more spatio-temporal measurements from the spatially-distributed cameras.

11. The computer-implemented method of claim 1 , wherein the one or more non-camera sources comprise one or more solar panel mechanisms.

12. The computer-implemented method of claim 1 , wherein the one or more non-camera sources comprise one or more solar pumps.

13. The computer-implemented method of claim 1 , wherein the one or more instructions are based on the one or more measurements obtained from the one or more non-camera sources.

14. The computer-implemented method of claim 1 , wherein the one or more meteorological measurements comprises one or more items of satellite data.

15. The computer-implemented method of claim 1 , wherein the one or more meteorological measurements comprises one or more global weather models.

16. The computer-implemented method of claim 1 , wherein the one or more meteorological measurements comprises one or more historical meteorological measurements.

17. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to:
transmit one or more instructions to each of multiple spatially-distributed cameras in a pre-determined geographic area, wherein the one or more instructions cause each of the spatially-distributed cameras to change a context from (i) a pre-determined task to (ii) capturing one or more spatio-temporal measurements of cloud coverage;
track the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras;
obtain one or more meteorological measurements from one or more non-camera sources; and
generate a cloud coverage forecast for the pre-determined geographic area based on (i) the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras and (ii) the one or more meteorological measurements from the one or more non-camera sources.

18. The computer program product of claim 17 , wherein the one or more instructions are based on an opportunity cost arising from changing the context of a given one of the cameras from (i) the pre-determined task of the given camera to (ii) capturing the one or more spatio-temporal measurements of cloud coverage.

19. A system comprising:
a memory; and
at least one processor coupled to the memory and configured for:
transmitting one or more instructions to each of multiple spatially-distributed cameras in a pre-determined geographic area, wherein the one or more instructions cause each of the spatially-distributed cameras to change a context from (i) a pre-determined task to (ii) capturing one or more spatio-temporal measurements of cloud coverage;
tracking the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras;
obtaining one or more meteorological measurements from one or more non-camera sources; and
generating a cloud coverage forecast for the pre-determined geographic area based on (i) the one or more spatio-temporal measurements of cloud coverage captured by the multiple spatially-distributed cameras and (ii) the one or more meteorological measurements from the one or more non-camera sources.

20. A computer-implemented method, comprising:
communicating with each of multiple pre-engaged and spatially-distributed cameras in a pre-determined geographic area to determine one or more configuration parameters for each of the cameras;
transmitting one or more instructions to each of the cameras, wherein the one or more instructions are based on the one or more configuration parameters determined for each of the cameras, and wherein the one or more instructions cause each of the cameras to change a context from (i) a pre-determined task to (ii) capturing one or more spatio-temporal measurements of cloud coverage;
collecting images captured by the cameras in connection with said capturing one or more spatio-temporal measurements of cloud coverage;
tracking the one or more spatio-temporal measurements of cloud coverage based on the collected images;
obtaining one or more meteorological measurements from one or more non-camera sources in the pre-determined geographic area; and
generating a cloud coverage forecast for the pre-determined geographic area based on (i) the one or more spatio-temporal measurements of cloud coverage and (ii)

Assignees

• IBM

Inventors

• Bharadwaj Samarth
• Kota Ramachandra
• Dayama Pankaj
• Kalyanaraman Shivkumar
• Kumar Pratyush

Classifications

• H04N23/90

  Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums · CPC title

• H04N23/662

  by using camera arrangements where one camera controls another camera to affect the control of camera image capture, e.g. placing the camera in a desirable condition to capture a desired image · CPC title

• G06V20/13

  Satellite images · CPC title

• G01W1/10 Primary

  Devices for predicting weather conditions (computers per se G06; display devices G09) · CPC title

• H04N5/247

  Electricity · mapped topic