Mobile Light Sensor Display Calibration Automation
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Solution Overview
Problem
Display devices require manual calibration to correct calibration errors, which is a burdensome and error-prone process for users, as each device displays content differently despite standard calibration.
Innovation Solution
A mobile device with a light sensor and calibration data stores device-specific settings to normalize sensor values, allowing it to adjust output signals for media devices to match display standards by detecting light properties and positioning instructions for accurate calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration is performed by the user, then calibration errors can be corrected, but the process becomes burdensome and error-prone
Solution Approach 1:
The system performs self-calibration by automatically comparing the display output against stored reference data and adjusting parameters without requiring user intervention. The processor executes calibration algorithms and modifies display settings autonomously, eliminating the need for manual user calibration while maintaining high accuracy.
Solution Approach 2:
Reference calibration data stored in memory acts as an intermediary standard against which the display output is compared. This reference data serves as a mediator between the display device and the calibration process, enabling automated adjustment by providing a benchmark for accuracy verification and parameter optimization.
2Stability of the object's composition
If each display device is calibrated to the same standard, then consistency is achieved, but slight variations still occur in visual presentation
Solution Approach 1:
The system applies localized calibration adjustments specific to each display device's characteristics. By measuring the actual output of each device and comparing it against reference data, the system determines device-specific parameter modifications that compensate for individual variations, ensuring each display achieves accurate presentation tailored to its unique properties.
Solution Approach 2:
The calibration process dynamically adjusts display parameters such as color temperature, brightness, and gamma based on measured deviations from reference standards. The processor modifies these parameters in real-time based on comparison results, enabling precise control over display output characteristics to achieve uniform visual presentation across different devices.
3Productivity
If a mobile device is used for calibration, then the process becomes quick and convenient, but device-specific sensor variations must be normalized
Solution Approach 1:
Device-specific calibration data for the light sensor is stored in advance in the mobile device's memory. This preliminary calibration establishes a baseline that accounts for individual sensor variations, enabling the sensor readings to be normalized and compared against display output without requiring real-time adjustment for each measurement.
Solution Approach 2:
The system implements a feedback loop where the mobile device's light sensor measures the display output, compares it against reference calibration data, and provides information back to the processor for parameter adjustment. This closed-loop feedback ensures that sensor variations are compensated and that the calibration process achieves accurate results despite differences in individual sensor characteristics.
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
Enables quick and accurate calibration of media device signals for display on specific devices by automating the calibration process, ensuring consistent and standardized visual output.
Implementation Method 1
The mobile device then detects properties of light emitted by the display device during a presentation to obtain sensor values related to light emitted by the display device during the presentation
Data Source
AI summary
In some implementations, a mobile computing device may participate in the calibration of an output signal of a media device. This calibration process includes storing device-specific calibration data which is related to properties of a light sensor of the mobile device. The mobile device then detects of properties of light emitted by the display device during a presentation to obtain sensor values related to light emitted by the display device during the presentation. The calibration process may also ensure that the mobile device is proximate to the display device prior to obtaining the sensor values. The collected sensor values are adjusted using device-specific calibration data stored to the mobile device to normalize the sensor values relative to a baseline. These normalized sensor values are sent to the media device for use in adjusting the output signal based on the normalized sensor values.