Multi-Sensor Group Calibration for Air Quality Monitoring
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Solution Overview
Problem
Existing air quality monitoring systems face challenges in delivering high accuracy measurements at low cost, particularly in mobile applications where obtaining a high-quality air sample is difficult, especially for highly reactive or trace gases.
Innovation Solution
The system employs multi-sensor groups with co-located sensors that share calibration information to improve data accuracy. Each group includes a first sensor and additional sensors, with calibration information obtained from a database to correct sensor data, ensuring that variations in temperature, pressure, and humidity are accounted for.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single sensors are used for air quality monitoring, then device complexity is reduced, but measurement precision deteriorates due to inability to account for environmental variations
Solution Approach 1:
The system divides the monitoring function into multiple co-located sensors, each measuring different parameters (target gas, temperature, pressure, humidity). This segmentation allows independent measurement of environmental factors that affect sensor accuracy, enabling correction of measurement errors without requiring a single complex sensor
Solution Approach 2:
The sensor group serves multiple functions simultaneously: primary gas detection, environmental parameter monitoring, and self-calibration. The same sensor group infrastructure supports both measurement and correction functions, making the system multi-functional without proportionally increasing complexity
2Measurement precision
If calibration information is stored locally in each sensor group, then measurement precision improves through immediate correction, but device complexity increases due to database management requirements
Solution Approach 1:
A centralized calibration database serves as an intermediary between sensor groups and correction algorithms. The database stores pre-computed calibration information that mediates between raw sensor readings and corrected measurements, eliminating the need for complex real-time calculations at each sensor group while maintaining high measurement precision
Solution Approach 2:
Calibration information is pre-computed and stored in the database based on environmental conditions and sensor characteristics. This preliminary action allows the system to apply simple look-up corrections during operation rather than performing complex real-time calibration calculations, improving both precision and computational efficiency
3Measurement precision
If multiple co-located sensors are deployed, then measurement precision improves through environmental compensation, but manufacturing cost increases
Solution Approach 1:
The system uses multiple copies of sensors measuring the same target gas, with each sensor in the group providing redundant measurement capability. This copying approach allows statistical averaging and cross-validation of readings, improving measurement reliability while using standard off-the-shelf sensor components rather than custom expensive sensors
Solution Approach 2:
The system corrects measurements by applying parameter changes based on environmental conditions (temperature, pressure, humidity) obtained from the sensor group. These parameter-based corrections improve measurement precision without requiring expensive specialized sensors, as standard sensors can be compensated through mathematical adjustment of their readings
Data Source
AI summary
A method and system for processing signals from a plurality of groups of sensors are described. Each group includes a first sensor and at least one additional sensor. A first sensor identifier and first sensor data are received from the first sensor. At least one additional sensor identifier and additional sensor data are also received from the additional sensor(s). The first sensor and the additional sensor(s) of each group are co-located. The first sensor identifier is associated with the additional sensor identifier(s) for each group. Calibration information for the first sensor is obtained based on the first sensor identifier and the additional sensor identifier(s). The calibration information is specific to the first sensor having the first sensor identifier. Corrected first sensor data for each of the groups is provided based on the first sensor data, the additional sensor data and the calibration information.