Visible Light Sensor Glare Detection for Motorized Shades
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Solution Overview
Problem
Existing load control systems for managing motorized window treatments often inaccurately control shades due to small, high-intensity glare conditions from sources like reflections or raindrops, leading to unnecessary adjustments and energy consumption.
Innovation Solution
A visible light sensor processes images to determine the position of glare sources and adjusts motorized window treatments by comparing pixel luminance to a threshold, accounting for image resolution and grouping pixels with similar intensities to filter out noise and accurately detect glare conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional glare detection systems use simple luminance thresholding, then the system responds quickly to glare conditions, but it produces false positives from small high-intensity glare sources like reflections or raindrops
Solution Approach 1:
The image is divided into multiple pixels, and the detection process is segmented into multiple steps: initial luminance thresholding to identify candidate glare pixels, followed by spatial relationship analysis by comparing each candidate pixel's luminance with its neighboring pixels. This segmentation allows the system to filter false positives without requiring complex processing of the entire image at once.
Solution Approach 2:
The patent applies different detection criteria to different regions of the image. For each candidate glare pixel, the system locally compares luminance values with neighboring pixels to determine if the high luminance represents a true glare source or a false positive from small reflections or raindrops. This local quality assessment improves detection accuracy while maintaining efficiency.
2Object-affected harmful factors
If the system controls motorized window treatments for every detected glare condition, then all glare is prevented, but unnecessary control actions occur due to false positives from small high-intensity glare sources
Solution Approach 1:
The system uses feedback from the spatial relationship analysis to determine whether to activate the motorized window treatments. By comparing each candidate glare pixel's luminance with its neighboring pixels, the system receives feedback that helps distinguish true glare sources from false positives, enabling intelligent decision-making about when to control the window treatments and when to avoid unnecessary energy consumption.
3Measurement precision
If the system uses complex configuration procedures and advanced system controllers to improve glare detection accuracy, then detection precision improves, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically analyzing the spatial relationships between pixels and making its own determination about true glare sources versus false positives. The pixel comparison logic is embedded in the detection algorithm itself, eliminating the need for complex external configuration procedures or advanced system controllers, thereby reducing device complexity while maintaining high detection precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively prevents glare from affecting occupants while minimizing unnecessary control actions, optimizing energy usage and improving comfort by accurately identifying and addressing glare sources.
Implementation Method 1
A visible light sensor and/or system controller may process an image to determine the position of a glare source and control motorized window treatments to prevent the glare source from affecting an occupant of a room. The sensor (e.g., a visible light sensor) and/or system controller may process the pixels of the image to determine whether a glare condition exists.
Data Source
AI summary
A sensor and/or system controller may process an image multiple times at multiple resolutions to detect glare conditions. A glare condition threshold used to determine whether a glare condition exists may be based on the resolution of the image. When the resolution of the image is higher, the glare condition threshold may be higher. The sensor and/or system controller may organize one or more adjacent pixels having similar intensities into pixel groups. The pixel groups may vary in size and/or shape. The sensor and/or system controller may determine a representative group luminance for the pixel group (e.g., an average luminance of the pixels in the group). The sensor and/or system controller may determine a group glare condition threshold, which may be used to determine whether a glare condition exists for the group of pixels and/or may be based on the size of the group.