Sensor Calibration via Networked Data Exchange
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Solution Overview
Problem
Conventional methods for calibrating sensors distributed across different devices are impractical, especially when sensors are integrated into wearable items or in environments with interference, as they require user intervention like 'figure 8' motions or moving to known locations, which may not be feasible.
Innovation Solution
A method and system that collect sensor data from multiple devices to determine calibration values, allowing for remote calibration and compensation of sensors, using network servers to analyze data and send calibration commands to ensure accurate readings without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional calibration methods (e.g., figure 8 motion, moving to known locations) are used, then sensor calibration can be performed, but user intervention is required which may not be feasible in wearable devices or environments with interference
Solution Approach 1:
The system enables self-service calibration by allowing sensors to automatically calibrate themselves using data from other sensors in the network. Each sensor acts as both a client (requesting calibration) and a server (providing calibration data), eliminating the need for user intervention while maintaining calibration accuracy through peer-to-peer data exchange.
Solution Approach 2:
The patent introduces intermediary components including calibration servers and coordination mechanisms that mediate between sensors needing calibration and those providing calibration data. These intermediaries manage the calibration process, match sensors based on proximity and data quality, and coordinate the exchange of calibration information without requiring direct user action.
2Adaptability or versatility
If sensors are integrated into wearable items or small devices, then device portability and integration are improved, but conventional calibration methods become impractical
Solution Approach 1:
The system creates a universal calibration network where any sensor in the network can serve multiple functions - acting as both a client needing calibration and a server providing calibration data. This multi-functionality allows small, integrated sensors to calibrate themselves through the network rather than requiring device-specific calibration mechanisms.
Solution Approach 2:
The patent transitions calibration from a single-device, user-operated process to a multi-device, automated networked process. By adding the network dimension, sensors in wearable devices can access calibration data from other devices in the environment, making calibration feasible without physical manipulation of the small integrated sensors.
3Measurement precision
If sensor calibration is performed manually, then calibration can be done, but it requires user presence and action which reduces automation
Solution Approach 1:
The system implements feedback mechanisms where sensors continuously monitor their own calibration status and the quality of calibration data from other sensors. Calibration requests are automatically generated when drift is detected, and calibration results are verified through feedback loops, enabling fully automated calibration while maintaining accuracy through continuous monitoring and adjustment.
Solution Approach 2:
The patent employs preliminary action by having sensors continuously collect and store calibration data in advance, and by pre-establishing the calibration network infrastructure. When calibration is needed, the system can immediately retrieve and apply pre-collected calibration data without requiring real-time user action, thus maintaining both automation and accuracy.
Data Source
AI summary
Sensors in one or more remote devices provide sensor output to a device having a controller. The controller analyzes the sensor data to determine the accuracy of the sensors outputting the sensor data. Based on the analysis, the controller calculates a calibration value to utilize in calibrating one or more of the sensors in the remote devices, or in one or more other devices.