Selecting a window treatment fabric

• US 10,043,132 B2
• Filed: 04/02/2015
• Issued: 08/07/2018
• Est. Priority Date: 04/02/2014
• Status: Active Grant

• Current Assignee: Lutron Technology Company LLC
• Original Assignee: Lutron Electronics Company Incorporated (Lutron Electronics)
• Inventors: Blair, Edward J., Chambers, Samuel F., Gabriel, Laura M., Greene, Michelle L., Lawler, Andrew J., Parks, Joseph Roy, Protzman, Brent, Quirk, Staci L.
• Primary Examiner(s): Smith, Paulinho E
• Application Number:
  US14/677,939
• Publication Number:
  US 20150286940A1
• Time in Patent Office: 1,223 Days
• Field of Search: None
• CPC Class Codes: E06B 2009/6809 Control
• CPC Class Codes: E06B 2009/6818 using sensors
• CPC Class Codes: E06B 2009/6827 sensing light
• CPC Class Codes: E06B 9/24 Screens or other constructions affording protection against light, especially against sunshine; Similar screens for privacy or appearance; Slat blindsoperating, guiding or securing devices or arrangements for roll-type closures E06B9/56; free-hanging flexible screens A47H23/00
• CPC Class Codes: E06B 9/32 Operating, guiding, or securing devices therefor operation of tilting bars E06B9/307
• CPC Class Codes: E06B 9/68 Operating devices or mechanisms, e.g. with electric drive
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: Y02T 10/82 Elements for improving aerodynamics

Abstract

A fabric selection tool provides an automated procedure for recommending and/or selecting a fabric for a window treatment to be installed in a building. The recommendation may be made to optimize the performance of the window treatment in which the fabric may be installed. The recommended fabric may be selected based on performance metrics associated with each fabric in an environment. The fabrics may be ranked based upon the performance metrics of one or more of the fabrics. One or more of the fabrics, and/or their corresponding ranks, may be displayed to a user for selection. The recommended fabrics may be determined based on combinations of fabrics that provide performance metrics for various façades of the building. Using the ranking system provided by the fabric selection tool, the user may obtain a fabric sample and/or order one or more of the recommended fabrics.

Claims

1. A method to assist user selection of a fabric of a window treatment for at least one window of an interior space, the method comprising:

computing, for each fabric option of a plurality of fabric options, associated scores based on values of at least two predicted performance metrics, wherein the values of the at least two predicted performance metrics depend on characteristics of daylight entering the interior space when at least one of the fabric options for the window treatment is used as the window treatment for the at least one window; and

communicating, to a user, information that is based on an extent to which the computed associated scores together satisfy at least one predefined window-treatment-recommendation criteria;

wherein the values of the at least two predicted performance metrics are based on input data defining at least one environmental characteristic of the interior space and at least one fabric characteristic of the fabric option.

2. The method of claim 1, further comprising:

determining a ranking of the plurality of fabric options based upon the extent to which the computed associated scores together satisfy the at least two predicted performance metrics.

3. The method of claim 2, wherein the at least two predicted performance metrics are at least a daylight glare probability value of the interior space, a spatial daylight autonomy value of the interior space, and a view rating of the interior space.

4. The method of claim 1, wherein the associated scores comprise at least two scores, and wherein the information is communicated by displaying a ranking of each of the fabric options based on the at least two scores corresponding to each of the fabric options.

5. The method of claim 4, wherein the information is communicated by displaying the at least two scores of each of the fabric options adjacent to each other on a visual display.

6. The method of claim 1, further comprising:

computing, for each fabric option of the plurality of fabric options, predicted performance metrics that correspond to environmental characteristics of the interior space.

7. The method of claim 1, wherein the information is based on the at least two predicted performance metrics.

8. The method of claim 1, further comprising:

installing a fabric option of the plurality of fabric options on a fabric roller tube that is selected as the window treatment for the at least one window of the interior space, wherein the fabric option is selected for being installed based on the associated scores.

9. The method of claim 1, wherein at least one of the at least two predicted performance metrics is a direct glare score of each of the plurality of fabric options or a spatial daylight autonomy value of the interior space.

10. The method of claim 1, further comprising:

determining a ranking of each fabric option of the plurality of fabric options, wherein the ranking is based on the computed associated scores, and wherein the at least two predicted performance metrics comprise a tolerance of an openness factor of each fabric option of the plurality of fabric options or a visual transmittance of each fabric option of the plurality of fabric options; and

displaying the ranking in a visual display.

11. The method of claim 1, wherein the values of the at least two predicted performance metrics correspond to at least one environmental characteristic of a building in which the window treatment is to be installed;

and wherein the at least one environmental characteristic of the building comprises at least one of a location of the building, an orientation of the building, at least one faç

ade of the building on which the window treatment is to be installed, a buffer zone between a window in the building and an occupant'"'"'s work space, a window size associated with the window in the building, a glass type associated with the window in the building, a room color, a depth of a room, or a type of space in the building in which at least one of the fabric options is to be installed.

12. The method of claim 1, wherein the associated scores comprise at least one of a glare score that indicates a predicted amount of glare resulting in a building from use of the fabric in the window treatment, a view score that indicates an occupant'"'"'s predicted amount of view out of the at least one window when the window treatment is installed, or a daylight score that indicates a predicted amount of daylight resulting in the interior space from the use of the fabric in the window treatment.

13. The method of claim 1, wherein a value of at least one other predicted performance metric comprises a spatial daylight autonomy value, wherein the spatial daylight autonomy indicates an amount of floor space in a building where daylight alone may provide light over a period of time.

14. The method of claim 1, wherein the values of the at least two predicted performance metrics comprise at least two of a daylight glare probability, a spatial daylight autonomy, or a view preservation, and

wherein the daylight glare probability indicates a maximum daylight glare intensity over a period of time, the spatial daylight autonomy indicates an amount of floor space in a building where daylight alone may provide light over a period of time, and the view preservation indicates an amount of the at least one window that may be unobstructed by the window treatment.

15. A network device for selecting fabric comprising:

a processor configured to;

compute, for each fabric option of a plurality of fabric options, associated scores based on values of at least two predicted performance metrics, wherein the values of the at least two predicted performance metrics depend on characteristics of daylight entering an interior space when at least one of the fabric options for a window treatment is used as the window treatment for at least one window; and

communicate, to a user, information that is based on an extent to which the computed associated scores together satisfy at least one predefined window-treatment-recommendation criteria,

wherein the values of the at least two predicted performance metrics are based on input data defining at least one environmental characteristic of the interior space, and at least one fabric characteristic of the fabric option.

16. The network device of claim 15, further comprising:

a visual display;

wherein the processor is configured to communicate the information by displaying the information on the visual display.

17. The network device of claim 16, wherein the processor is configured to display a ranking of each fabric option of the plurality of fabric options on the visual display, and wherein the ranking is based on a tolerance of an openness factor of each fabric option of the plurality of fabric options or a visual transmittance of each fabric option of the plurality of fabric options.

18. The network device of claim 16, wherein the processor is configured to display the associated scores of each of the fabric options adjacent to each other on the visual display.

19. The network device of claim 15, wherein the processor is configured to communicate the information by transmitting the information to a second network device.

20. The network device of claim 19, wherein the second network device has a visual display for displaying the information.

21. The network device of claim 15, wherein the processor is configured to determine a ranking of the plurality of fabric options based upon the extent to which the computed associated scores satisfy the at least two predicted performance metrics.

22. The network device of claim 21, wherein the at least two predicted performance metrics are at least a daylight glare probability value of the interior space, a spatial daylight autonomy value of the interior space, and a view rating of the interior space.

23. The network device of claim 15, wherein the processor is configured to compute, for each fabric option of the plurality of fabric options, predicted performance metrics that correspond to environmental characteristics of the interior space.

24. A method to assist user selection of a fabric of a window treatment for at least one window of an interior space, the method comprising:

computing, for each fabric option of a plurality of fabric options, a view score based on values of at least one predicted performance metric, wherein the values of the at least one predicted performance metric depend on characteristics of daylight entering the interior space when at least one of the fabric options for the window treatment is used as the window treatment for the at least one window; and

communicating, to a user, information that is based on an extent to which the computed view score satisfies at least one predefined window-treatment-recommendation criteria,

wherein the values of the at least one predicted performance metric are based on input data defining at least one environmental characteristic of the interior space, and at least one fabric characteristic of the fabric option.

25. The method of claim 24, wherein the information includes a view rating, a visual representation of a recommended fabric, a family characteristic, a warning, a star rating, a recommended fabric, or a fabric characteristic.

26. The method of claim 25, wherein the fabric characteristic is a visual light transmittance value associated with the fabric or a solar heat reflectance value of the fabric.

27. The method of claim 24, wherein the view score for each fabric option is based on a view preservation rating that indicates an amount of a window view that may be unobstructed by the fabric when in a window treatment installed in an environment that is associated with a building or a location in the building.

28. The method of claim 27, wherein the view preservation rating of each fabric option is based on a view clarity rating that indicates an amount of visibility available through the fabric.

29. The method of claim 24, further comprising:

computing, for each fabric option of the plurality of fabric options, a glare score based on the values of the at least one predicted performance metric, wherein the values of the at least one predicted performance metric depend on characteristics of daylight entering the interior space when the at least one of the fabric options for the window treatment is used as the window treatment for the at least one window, and wherein the computed view score and the computed glare score satisfy the at least one predefined window treatment recommendation criteria.

30. The method of claim 24, further comprising:

determining, based on the computed view score, a ranking of the plurality of fabric options, wherein the ranking of the plurality of fabric options indicates an ascending or descending order of performance of the fabric options in the window treatment when installed in an automated window treatment control system in an environment that is associated with a building or a location in the building.

31. The method of claim 24, wherein a ranking of the plurality of fabric options is based on at least one of a glare score that indicates a predicted amount of glare resulting in a building from use of the at least one of the fabric options in the window treatment or a daylight score that indicates a predicted amount of daylight resulting in the interior space from the use of the at least one of the fabric options in the window treatment.

32. A method to assist user selection of a fabric of a window treatment for at least one window of an interior space, the method comprising:

computing, for each fabric option of a plurality of fabric options, a direct glare score based on values of at least one predicted performance metric, wherein the values of the at least one predicted performance metric depend on characteristics of daylight entering the interior space when at least one of the fabric options for the window treatment is used as the window treatment for the at least one window, and

communicating, to a user, information that is based on an extent to which the computed direct glare score satisfies at least one predefined window-treatment-recommendation criteria,

wherein the values of the at least one predicted performance metric are based on input data defining at least one environmental characteristic of the interior space, and at least one fabric characteristic of the fabric option.

33. The method of claim 32, wherein the computed direct glare score is based on a glare score that indicates a predicted amount of glare resulting in a building from the use of the at least one of the fabric options in the window treatment, and wherein the at least one predicted performance metric comprises a daylight glare probability value that indicates a maximum daylight glare intensity over a period of time.

34. The method of claim 32, wherein the computed direct glare score is based on a direct glare adjustment value.

35. The method of claim 34, wherein the direct glare adjustment value is based on a direct visual light transmittance value associated with the fabric option.

36. The method of claim 32, wherein the information includes a view rating, a visual representation of a recommended fabric, a family characteristic, a warning, a star rating, a recommended fabric, or a fabric characteristic.

37. The method of claim 36, wherein the fabric characteristic is the visual light transmittance value associated with the fabric option or a solar heat reflectance value of the fabric option.

38. The method of claim 32, wherein the extent to which the computed direct glare score satisfies the at least one predefined window-treatment-recommendation criteria comprises the extent to which the computed direct glare score does not satisfy at least one predefined window-treatment-recommendation.

39. The method of claim 32, wherein the computing the direct glare score is based on establishing the at least one predicted performance metric for the plurality of fabric options that correspond to environmental characteristics of an environment of the plurality of environments that is associated with a building or a location in the building in which a recommended fabric is to be installed as the window treatment.

40. The method of claim 32, further comprising:

determining a ranking of each fabric option of the plurality of fabric options, wherein the ranking is based on a tolerance of each fabric option of the plurality of fabric options, wherein the tolerance of each fabric option of the plurality of fabric options is based on the computed direct glare score; and

displaying the ranking and the tolerance in a visual display.

41. The method of claim 32, wherein an amount of the daylight is a percentage of the daylight that gets through the fabric and the at least one window.

42. The method of claim 32, wherein the at least one predicted performance metric includes a minimum sun angle, and wherein the direct glare score is based on the minimum sun angle.

43. The method of claim 32, further comprising:

decreasing the direct glare score when a glare score is outside of a predefined range.

44. The method of claim 32, further comprising:

displaying a warning when the direct glare score is outside of a predefined range.

45. A method to assist user selection of a fabric of a window treatment for at least one window of an interior space, the method comprising:

computing, for each fabric option of a plurality of fabric options, an associated score based on at least two values of at least one predicted performance metric, wherein the at least two values of the at least one predicted performance metric are determined based on a tolerance of an openness factor of the fabric option; and

communicating, to a user, information that is based on an extent to which the computed associated score satisfies at least one predefined window-treatment-recommendation criteria;

wherein the at least two values of the at least one predicted performance metric are based on input data defining at least one environmental characteristic of the interior space and at least one fabric characteristic of the fabric option.

46. The method of claim 45, wherein communicating the information comprises displaying the information on a visual display.

47. The method of claim 45, wherein communicating the information comprises transmitting the information to a network device having a visual display.

48. The method of claim 45, wherein the information includes a view rating, a visual representation of a recommended fabric, a family characteristic, a warning, a star rating, a recommended fabric, or a fabric characteristic.

49. The method of claim 45, determining, based on the computed associated score, a ranking of the plurality of fabrics options, wherein the ranking of the plurality of fabrics indicates an ascending or descending order of performance of the fabric options in the window treatment when installed in an automated window treatment control system in an environment that is associated with a building or a location in the building.