TV Power State Detection With Auto-Calibrated Thresholds
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Solution Overview
Problem
Existing methods for detecting the ON/OFF state of advanced televisions, such as smart TVs, are inaccurate due to their complex power draw scenarios and require time-consuming manual recalibration when settings change, leading to incorrect media exposure measurements.
Innovation Solution
Implementing a meter with multiple thresholds that are automatically calibrated through an ongoing process, including an initial learning phase and periodic recalibration, to accurately determine the ON/OFF state of televisions by analyzing power draw patterns and excluding outlier conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual calibration methods are used for detecting TV ON/OFF state, then the detection can be implemented with simple apparatus, but the detection accuracy deteriorates due to complex power draw scenarios of smart TVs
Solution Approach 1:
The system dynamically adapts to changing TV power draw characteristics by implementing continuous learning and automatic recalibration. The detection thresholds are not fixed but evolve over time to match the TV's actual power consumption patterns, resolving the contradiction between simple apparatus and accurate detection for smart TVs with complex power scenarios.
Solution Approach 2:
The detection system performs self-calibration by automatically learning the TV's power draw characteristics during an initial learning phase and subsequent periodic recalibration. This eliminates the need for manual calibration while maintaining high detection accuracy, allowing simple apparatus to achieve precise measurement through autonomous adaptation.
2Measurement precision
If manual recalibration is performed when TV settings change, then the detection accuracy can be maintained, but the time consumption and operational complexity increase
Solution Approach 1:
The system implements periodic automatic recalibration at predetermined intervals without requiring manual intervention. This maintains detection accuracy by regularly updating the power draw thresholds while eliminating the time loss and operational complexity associated with manual recalibration processes.
Solution Approach 2:
The system continuously monitors power draw patterns and uses feedback from the initial learning phase and ongoing operation to automatically adjust calibration parameters. This feedback mechanism maintains high detection accuracy while eliminating manual recalibration time, as the system self-adjusts based on observed power consumption changes.
3Ease of operation
If single threshold detection is used, then the system operation is simple, but the reliability deteriorates due to outlier conditions and complex power draw patterns
Solution Approach 1:
The detection system segments the power draw range into multiple thresholds (first, second, and third thresholds) rather than using a single threshold. This segmentation allows the system to reliably distinguish between different TV states (OFF, standby, ON) and filter out outlier conditions, maintaining operational simplicity while significantly improving detection reliability for complex smart TV power scenarios.
Data Source
AI summary
Methods and apparatus are disclosed to determine a power state of a device. An example method includes determining respective counts for a plurality of measurements during a calibration period, the measurements indicative of an amount of power drawn by the device, determining a first threshold and a second threshold based on at least one of the counts, the first threshold determined using most frequently logged measurement values, the most frequently logged measurement values based on counts performed after expiration of the calibration period, comparing a measurement to the first threshold and to the second threshold, and outputting a positive indication when the measurement is within an acceptable difference range, the acceptable difference range based on the amount of power drawn by the device.