System and method for remote calibration of an air-quality sensor device
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Solution Overview
Problem
Legacy building management systems are inefficient in managing high-volume data, lack modern functionalities, and require manual calibration of sensors and regulators, failing to provide optimized wellness, comfort, and energy solutions for large commercial and industrial buildings.
Innovation Solution
A method and system for remote calibration of air-quality sensor devices, involving data analysis to identify statistically-significant drifts, computation of re-calibration updates, and transmission to adjust sensor readings within expected ranges, utilizing a network system with a command and control server, bridge devices, and sensor devices for cloud-level administration and data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration of sensor devices is performed, then measurement precision is maintained, but loss of time and productivity deteriorate due to prohibitively large outlay of time and effort
Solution Approach 1:
The sensor device performs self-calibration by automatically comparing its readings against reference values stored in its memory. The processor detects drift by analyzing sensor data against these references and adjusts calibration parameters without human intervention, enabling the system to maintain measurement precision while eliminating manual calibration time
Solution Approach 2:
Reference calibration values are pre-stored in the sensor device's memory during manufacturing. These preliminary stored values serve as the basis for ongoing automated drift detection and calibration adjustments, allowing the system to maintain accuracy without requiring repeated manual calibration operations
2Measurement precision
If manual calibration of sensor devices is performed, then measurement precision is maintained, but productivity deteriorates due to intensive manual adjustment requirements
Solution Approach 1:
The sensor device autonomously monitors its own calibration status by comparing current readings against stored reference values. When drift is detected, the device automatically adjusts its calibration parameters, eliminating the need for building management personnel to perform manual calibration tasks and thereby improving overall productivity
Solution Approach 2:
The system continuously monitors sensor readings and compares them against reference values to detect drift. This feedback mechanism triggers automatic recalibration when needed, ensuring measurement precision is maintained while freeing building management personnel to focus on higher-value tasks
3Device complexity
If legacy building management systems are used, then device complexity is reduced, but adaptability deteriorates due to lack of cloud-processing and interconnectivity features
Solution Approach 1:
The sensor device integrates multiple functions including environmental sensing, automated calibration, data processing, and cloud communication capabilities. This multi-functional design enables the device to operate autonomously while maintaining connectivity to building management systems and cloud platforms, enhancing adaptability without proportionally increasing complexity
Solution Approach 2:
The calibration and data processing functions are segmented into the sensor device itself, while cloud-based analytics and centralized management are separated into remote servers. This segmentation allows the device to remain relatively simple while gaining access to powerful cloud-based adaptability and intelligence
Data Source
AI summary
A system and method for remote calibration of an air-quality sensor device. The method includes receiving sensor data from at least one sensor device; analyzing the received sensor data to identify at least statistically-significant values indicating on at least drift from initial calibrated values of each of the at least one sensor device; for each identified drifted sensor device, computing re-calibration updates, wherein the re-calibration updates adjust the initial calibrated values such that readings of the respective drifted sensor device fall within a range of expected values; and transmitting the re-calibration updates to the respective drifted sensor device, wherein the respective drifted sensor device upon receiving the re-calibration updates is configured to update its calibration parameters.