Localized sensor quality analysis and control
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Solution Overview
Problem
The proliferation of IoT devices with similar functions installed in close proximity leads to inefficiencies in data transmission and quality control, as existing methods rely heavily on cloud-based analysis, consuming significant bandwidth and resources.
Innovation Solution
Implementing a localized sensor quality control system where sensors communicate via short-range protocols to perform calibration and quality analysis among themselves, reducing reliance on Internet-based communications and utilizing nearby sensors' data for accurate calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud-based quality control analysis is used for IoT sensors, then comprehensive quality control can be achieved, but network bandwidth consumption and resource usage increase significantly
Solution Approach 1:
The patent segments the quality control function by dividing sensors into reference sensors and target sensors. Reference sensors perform quality control analysis locally for target sensors in their vicinity, eliminating the need for all sensors to communicate with cloud-based systems. This segmentation reduces network bandwidth consumption while maintaining comprehensive quality control through distributed analysis.
Solution Approach 2:
The patent introduces a spatial dimension to quality control by establishing geographic proximity as a criterion for sensor pairing. Sensors within a defined radius of each other form local quality control groups, adding a spatial organizational layer that reduces reliance on centralized cloud processing and minimizes network bandwidth usage.
2Loss of energy
If localized quality control is implemented using short-range communication, then network bandwidth usage is reduced, but the system complexity increases
Solution Approach 1:
The patent implements self-service by enabling sensors to autonomously perform quality control analysis using their own measurements and those of nearby reference sensors. Sensors automatically determine quality control results without requiring complex external system coordination, thereby reducing overall system complexity while minimizing bandwidth consumption through localized processing.
Solution Approach 2:
The patent merges the functions of measurement and quality control analysis into a single integrated process. Reference sensors use their measurement data to perform quality control analysis on target sensors, combining multiple functions into unified operations that simplify system architecture while reducing network bandwidth requirements.
3Productivity
If cloud-based quality control is used, then centralized management is achieved, but response time and efficiency are reduced
Solution Approach 1:
The patent implements preliminary action by having reference sensors continuously monitor and analyze target sensor data in real-time before issues require cloud intervention. This proactive localized quality control enables immediate detection and response to sensor anomalies, improving efficiency and reducing response time compared to waiting for cloud-based analysis.
Solution Approach 2:
The patent establishes a local feedback loop where reference sensors provide immediate quality control results to target sensors through short-range communication. This real-time feedback mechanism enables rapid adjustment and response without the delays inherent in cloud-based round-trip communication, thereby improving productivity and reducing response time.
Data Source
AI summary
A computer-implemented method comprising capturing measurement data via a first sensor suite, broadcasting the measurement data via short-range communication, receiving, via the short-range communication, a broadcast including a quality control analysis result corresponding to the measurement data and determined by a second sensor suite, acting on the quality control analysis result, and performing quality control analysis for a third sensor suite.