Ambient Light Calculation Using Weighted Image Sensor Pixels
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Solution Overview
Problem
Existing ambient light sensors lack spatial information, providing only rough estimations of light levels in a space, which limits their ability to accurately regulate lighting conditions in homes and offices, leading to inefficient energy use.
Innovation Solution
The use of an image sensor with an array of pixels to analyze a scene and calculate ambient light by detecting non-representative pixels and assigning weights to pixel values, allowing for a more accurate mapping of light conditions in a space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a photodiode or photodetector is used to measure ambient light, then the device complexity is reduced and ease of manufacture is improved, but measurement precision deteriorates due to lack of spatial information
Solution Approach 1:
The patent segments the ambient light measurement task into multiple spatial samples using an array of pixels in an image sensor. Each pixel measures light at a specific location, and these segmented measurements are then integrated to provide comprehensive spatial information about ambient light distribution in the space.
Solution Approach 2:
The patent transitions from a single-point measurement approach (0D/1D) to a two-dimensional spatial measurement approach by using an image sensor array. This adds the spatial dimension to ambient light measurement, enabling the system to capture light distribution across the entire field of view rather than at a single location.
2Measurement precision
If an image sensor with array of pixels is used to capture spatial light information, then measurement precision is improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent extracts only the necessary information from the full image data captured by the sensor array. Instead of processing all pixel data equally, the system identifies and processes only representative pixels that provide sufficient ambient light information, reducing computational energy consumption while maintaining measurement precision.
Solution Approach 2:
The patent uses partial action by selecting a subset of pixels from the full array for ambient light calculation. Rather than utilizing all pixels, the system identifies representative pixels that provide adequate spatial sampling, reducing processing requirements while maintaining adequate measurement accuracy.
3Measurement precision
If all pixels in the image are used to calculate ambient light, then measurement precision is improved, but loss of information increases due to inclusion of non-representative pixels
Solution Approach 1:
The patent applies local quality by treating different pixels differently based on their representativeness. Instead of uniform weighting of all pixels, the system identifies pixels located in regions that are representative of the overall ambient light conditions and gives these pixels appropriate weight in the calculation, while reducing or excluding non-representative pixels.
Solution Approach 2:
The patent changes the weighting parameter for different pixels based on their spatial location and representativeness. By dynamically adjusting the weight assigned to each pixel's contribution to the ambient light calculation, the system optimizes measurement precision while filtering out non-representative data.
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 enables more precise control of lighting, providing the most convenient conditions by accurately determining ambient light levels, thereby reducing energy consumption and improving lighting efficiency.
Implementation Method 1
obtaining an image of the space from an array of pixels
Data Source
AI summary
Calculating ambient light in a space by obtaining a top view image of the space from an array of pixels, and identifying an object in the image and assigning weights to pixels from the array of pixels based on locations of the pixels relative to the identified object in the image, where object may include a reflective surface, where ambient light in the space is calculated based on the weighted pixels.