Sensor Calibration Using Cloud-Based Reference Data
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Solution Overview
Problem
Existing sensors for detecting environmental parameters face challenges in maintaining accuracy over their service life due to high calibration efforts and expenses, leading to degradation from dirt and contamination, especially with low-cost sensors lacking routine calibration acceptance.
Innovation Solution
A sensor system utilizing cloud-based data for calibration, where adjustment data can be stored in the sensor or on a server, allowing for offline adjustments and improved signal quality through characteristic value assignment, enabling accurate measurements with reduced technical effort and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used to improve measurement accuracy, then sensor accuracy is improved, but calibration effort and expense increase substantially
Solution Approach 1:
The sensor system performs self-calibration by automatically comparing its measurements with cloud-based reference data from other sensors. The adjustment device autonomously determines calibration values and adjusts measurement data without requiring manual intervention, expensive calibration equipment, or specialized personnel, thereby maintaining accuracy while eliminating substantial calibration efforts and expenses
Solution Approach 2:
A cloud-based server acts as an intermediary between sensors, storing and processing measurement data from multiple sensors. The server provides reference data that enables individual sensors to calibrate themselves by comparison, replacing traditional direct calibration methods with indirect cloud-based calibration that reduces effort and expense
2Measurement precision
If routine calibration is performed to maintain measurement accuracy, then measurement quality is maintained, but user acceptance is low due to effort and cost
Solution Approach 1:
The automated self-calibration system eliminates the need for users to manually perform calibration routines. The sensor autonomously accesses cloud-based reference data, determines calibration values, and adjusts its measurements automatically, transforming a complex user task into a transparent background process that users do not need to understand or execute
Solution Approach 2:
The system performs calibration actions automatically and continuously in the background before users need the measurements. By pre-calibrating and maintaining accuracy automatically, the system ensures measurement quality is already optimized when users access the data, eliminating the perception of calibration as a burdensome routine task
3Ease of manufacture
If low-cost sensor elements are used to reduce sensor cost, then economic cost is reduced, but accuracy and reliability deteriorate
Solution Approach 1:
The system implements continuous feedback calibration by comparing each sensor's measurements against cloud-based reference data from multiple sensors. This feedback loop automatically identifies and corrects drift or inaccuracies in low-cost sensor elements, maintaining measurement precision without requiring expensive high-precision sensor hardware
Solution Approach 2:
The cloud-based server acts as an intermediary that aggregates data from multiple low-cost sensors and provides reference measurements. This intermediary processing enables individual low-cost sensors to achieve higher effective accuracy by leveraging the collective data from the network, compensating for the inherent limitations of inexpensive sensor elements
4Device complexity
If cloud-based calibration is implemented to reduce calibration effort, then calibration expense is reduced, but dependency on cloud access increases
Solution Approach 1:
The system performs preliminary calibration by accessing cloud-based reference data when cloud connectivity is available. Calibration values and adjustment parameters are determined in advance during periods of cloud access, enabling the sensor to operate with pre-calibrated settings during offline periods, thus reducing cloud dependency while maintaining accuracy
Data Source
AI summary
The invention relates to a sensor (1) for detecting environmental parameters, comprising a transmission device (3) by means of which an output signal of the sensor (1) can be emitted, and a correction device (4) by means of which the sensor measurement value can be corrected for the emission of a correct output signal, which sensor is to be easy to produce, and wherein only a small output is to be required for a method for calibrating a sensor of this type. According to the invention, the sensor is calibrated by means of the correction device thereof, on the basis of cloud-based data.