Camera White Balance for Low-Power Blue Light Estimation
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Solution Overview
Problem
Measuring blue light exposure in user environments consumes significant power, shortening battery life and degrading user experience in computing devices.
Innovation Solution
A user computing device with a camera and ambient light sensor estimates blue light exposure by determining a target exposure time, capturing image data, applying automatic white balance, and discarding unnecessary image processing steps to reduce power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the camera captures image data and processes it through automatic white balance to estimate blue light exposure, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent extracts only the essential processing step (automatic white balance) from the complete image processing pipeline to estimate blue light exposure. By discarding full image processing and keeping only the white balance algorithm, the system achieves adequate measurement precision while dramatically reducing power consumption and computational requirements.
Solution Approach 2:
The system performs partial image processing by applying only the automatic white balance algorithm rather than complete image processing. This partial action provides sufficient information for blue light exposure estimation without the excessive energy consumption of full processing, achieving an optimal balance between measurement accuracy and power usage.
2Adaptability or versatility
If the camera captures image data for blue light exposure measurement, then measurement capability is improved, but device complexity increases
Solution Approach 1:
The patent makes the existing camera module multi-functional by using it for both standard photography and blue light exposure measurement. The automatic white balance algorithm, originally designed for color correction in images, is repurposed to extract blue light exposure information, eliminating the need for dedicated blue light sensors and reducing overall device complexity.
Solution Approach 2:
The system uses its own existing image processing capabilities (automatic white balance algorithm) to perform blue light exposure measurement without requiring external specialized components. The camera module serves itself by leveraging its built-in processing algorithms for dual purposes: image capture and environmental light measurement.
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
Accurately estimates blue light exposure with minimal power usage, enabling additional functionality without increasing device cost, and providing real-time exposure values to users.
Implementation Method 1
capturing, using a camera module of the user computing device, image data by exposing a sensor of a camera to light for a time determined based on the target exposure time
Data Source
AI summary
The present disclosure provides computer-implemented methods, systems, and devices for estimation of a user's blue light exposure using the camera of a user computing device. A user computing device captures, using an ambient light sensor, information associated with a light environment of a user computing device. The user computing device determines a target exposure time. The user computing device captures, using a camera, image data by exposing a sensor of the camera to light for a time based on the target exposure time. The user computing device calculates white balance values for the captured image data using an automatic white balance algorithm. The user computing device discards the captured image data. The user computing device generates, based on the automatic white balance values, a blue light exposure value.