Sensor Network Recalibration Using Environment Response Functions

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Solution Overview

Problem

Existing sensor calibration methods are costly, time-consuming, and difficult to scale, especially for remote sensors, and current blind calibration techniques are not effective in the long term due to drift issues.

Innovation Solution

A method and system for sensor calibration that utilizes an environment response function to estimate a current sensor response function, using either semi-blind calibration with controlled perturbations or blind calibration through a two-stage autoencoder network, allowing for autonomous recalibration without the need for reference sensors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional calibration methods are used, then calibration can be performed, but the process is time-consuming and requires specialized knowledge

Engineering Contradiction:
Improvecalibration speedVSAvoidcalibration process complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The calibration system enables sensors to perform self-calibration by automatically comparing their responses with reference sensors and adjusting their own calibration parameters, eliminating the need for manual intervention by specialized personnel

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system pre-configures reference sensors with known calibration parameters and establishes automated comparison protocols before actual calibration is needed, allowing rapid calibration execution when required

Inventive Principle:
Principle #10Preliminary action

2Measurement precision

If manual calibration by specialized personnel is performed, then calibration accuracy can be maintained, but the cost and time requirements increase

Engineering Contradiction:
Improvesensor calibration accuracyVSAvoidcalibration time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system implements automated feedback loops where sensor responses are continuously compared against reference values, and calibration parameters are automatically adjusted based on the comparison results, maintaining accuracy without manual intervention

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

Reference sensors serve as intermediaries with known calibration characteristics, enabling automated comparison and calibration of target sensors without requiring specialized personnel to perform the actual calibration measurements

Inventive Principle:
Principle #24Intermediary (Mediator)

3Reliability

If specialized personnel perform calibration, then proper calibration can be achieved, but the operational complexity and resource requirements increase

Engineering Contradiction:
Improvecalibration reliabilityVSAvoidcalibration operation ease
Core Design Contradiction:
ReliabilityVSEase of operation

Solution Approach 1:

The calibration system enables sensors to perform self-calibration by automatically comparing their responses with reference sensors and adjusting their own calibration parameters, eliminating the need for manual intervention by specialized personnel

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system pre-configures reference sensors with known calibration parameters and establishes automated comparison protocols before actual calibration is needed, allowing rapid calibration execution when required

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentEP4609149B1Method and system of calibration of a sensor or a network of sensors
Publication Date: 2026.05.13 UNIVERSITY OF CAPE TOWN
  • EP4609149B1 patent drawingFigure 1A~1B
  • EP4609149B1 patent drawingFigure 2A
  • EP4609149B1 patent drawingFigure 2B

AI summary

A method and system of calibration of one or more sensors are provided in a given environment. In a reliable calibration phase, in a first time period after calibration of the sensor, the method determines an environment response function based on a known sensor response function. The environment response function is a spatio-temporal response of the environment representing the environmental response operating on the event to result in the measurand field. Subsequently, in an unreliable calibration phase, in a second time period after the first time period, the method estimates a current sensor response function based on the environment response function determined in the reliable calibration phase. The method outputs a calibration function based on the estimated current sensor response function for updating calibration of the sensor.