Sensor Metadata Matching Apparatus for IoT Networks
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Solution Overview
Problem
Existing sensor network technologies face challenges in efficiently matching sensor-side metadata with application-side metadata due to non-uniform terminology, leading to reduced matching precision and opportunities, resulting in unnecessary sensor extraction and network congestion.
Innovation Solution
A matching apparatus that calculates relevancy between terms in sensor-side and application-side metadata using related terms, adjusts the range of relevancy, and corrects relevancy based on co-occurrence and contract frequency to enhance matching precision and opportunities, while reducing network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If matching is performed using only exact term matching between sensor-side metadata and application-side metadata, then matching precision is maintained, but the number of matching opportunities is reduced due to non-uniform terminology
Solution Approach 1:
The patent changes the parameter of term matching from exact matching to relevancy-based matching. It introduces a relevancy calculation mechanism that computes similarity scores between terms using statistical methods (co-occurrence frequency, TF-IDF), allowing the system to match terms with different expressions while maintaining controlled precision through threshold settings.
Solution Approach 2:
The patent introduces an intermediary relevancy calculation layer between sensor-side metadata and application-side metadata. This intermediary mechanism uses related terms and statistical analysis to bridge the terminology gap, enabling matches between non-identical terms while maintaining precision through controlled relevancy thresholds.
2Productivity
If the relevancy range is widened to increase matching opportunities, then more sensors can be matched, but matching precision is reduced due to extraction of unnecessary sensors
Solution Approach 1:
The patent implements dynamic adjustment of the relevancy threshold based on the specific matching context. The system can adaptively set the threshold level to balance between recall (number of matches) and precision (quality of matches), allowing flexible control over the trade-off between matching opportunities and precision.
Solution Approach 2:
The patent changes the parameter of relevancy threshold to be adjustable and context-dependent. By modifying this parameter, the system can optimize the balance between increasing matching opportunities and maintaining precision, extracting only necessary sensors rather than all potentially related ones.
3Measurement precision
If extensive metadata matching and analysis is performed to improve matching precision, then matching quality increases, but system complexity and processing time increase
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing relevancy scores between terms in a thesaurus or lookup table. This pre-processing step reduces the complexity of real-time matching operations, as the system can directly query pre-computed relevancy values rather than performing complex statistical analysis during matching.
Solution Approach 2:
The system uses self-service mechanisms by automatically building and updating the relevancy database from historical data and co-occurrence patterns. This reduces manual configuration complexity and allows the system to improve its own matching precision automatically over time.
Data Source
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AI summary
A matching apparatus (1) includes: a sensor-side metadata acquisition unit (11) that acquires sensor-side metadata; an application-side metadata acquisition unit (12) that acquires application-side metadata; a matching unit (13) that performs matching between the sensor-side metadata and the application-side metadata in which a first related term that is related to a term in the acquired sensor-side metadata and a second related term that is related to a term in the acquired application-side metadata are in common with each other, and extracts a sensor candidate; and a dataflow control command instruction unit (14) that transmits a dataflow control command that includes information that specifies the sensor extracted by the matching unit (13) and an application.