Mobile Gas Sensor Blind Drift Calibration via Peer Device Communication
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Solution Overview
Problem
Mobile gas sensors, particularly chemo resistive sensors, experience signal drift over time, leading to reduced accuracy in air quality measurements, and existing recalibration methods are not feasible in mobile applications without reference sensors.
Innovation Solution
A device and method for blind drift calibration, where mobile devices communicate directly via a wireless path to share measurement information, allowing for recalibration of gas concentration measurements without a central server or reference sensor, using a calibration module to revise calibration information based on received data from nearby devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If gas sensors are used in mobile applications, then the device size and cost are reduced, but the sensor signal drifts over time leading to reduced measurement accuracy
Solution Approach 1:
The patent implements a feedback mechanism where mobile devices exchange concentration measurements with nearby devices via wireless communication. Each device uses received measurements from other devices to recalibrate its own sensor readings, creating a distributed feedback loop that compensates for drift without requiring external reference sensors or centralized infrastructure.
Solution Approach 2:
The calibration system is self-service in that each mobile device independently recalibrates its own sensor using measurements from peer devices. No external calibration equipment, reference sensors, or centralized calibration server is needed - the devices collectively perform mutual calibration through direct wireless communication, making the system autonomous and suitable for mobile applications.
2Measurement precision
If recalibration techniques are implemented to maintain measurement accuracy, then measurement precision is improved, but hardware resources and computational power are required
Solution Approach 1:
Instead of each device performing complex independent calibration algorithms, the system copies concentration measurements from nearby devices and uses these copied values for mutual calibration. This approach reduces computational requirements compared to full recalibration algorithms, as devices primarily need to exchange and compare measurement data rather than perform extensive signal processing.
3Adaptability or versatility
If blind calibration without reference sensors is used, then device independence is improved, but calibration accuracy may be compromised
Solution Approach 1:
The patent merges measurements from multiple mobile devices to achieve calibration. By combining concentration data from several peer devices that are spatially close, the system creates a collective calibration reference that is more reliable than single-device measurements, maintaining calibration accuracy without requiring external reference sensors or centralized infrastructure.
Data Source
AI summary
A device for determining a concentration of a target gas in a mobile application comprises a measurement module for obtaining measurement information about a concentration measurement of a target gas; a communication module for communicating with at least one further device via a direct wireless communication path, wherein the communication module receives information about a further concentration measurement of the target gas from the further device; and a calibration module for using calibration information for determining a calibrated measurement value on the basis of the measurement information, and for revising the calibration information by using the received information about the further concentration measurement.