IoT Telemetry Semantic Tagging for Unstructured Data Insights
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Solution Overview
Problem
The unstructured and proprietary nature of IoT telemetry data hinders organizations' ability to derive value and insights due to the lack of a standard schema, limiting the usefulness of the vast amounts of data collected.
Innovation Solution
The solution involves receiving telemetry data, parsing it to identify properties, mapping these properties to a set of semantic tags using a tag library with predetermined relationships, and generating insight data for automatic reporting, thereby providing semantic meaning and enabling dynamic insights without requiring a specific schema change.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If telemetry data is collected from diverse IoT sensors and devices with proprietary formats, then the quantity of data collected increases, but the ease of operation deteriorates due to lack of standard schema
Solution Approach 1:
The patent introduces an intermediary layer (data normalization service) that translates proprietary telemetry formats from diverse IoT devices into a standardized schema. This mediator component receives raw telemetry data in various formats, maps the data to universal concepts and relationships, and outputs normalized data that can be easily analyzed, thereby resolving the contradiction between collecting diverse data and maintaining ease of operation
Solution Approach 2:
The patent transforms the parameters of telemetry data by changing their representation from proprietary formats to a standardized schema. This involves mapping device-specific parameters to universal parameters, transforming data structures, and reformatting values according to a common vocabulary, thereby making the data easier to operate with while preserving the original information
2Ease of manufacture
If proprietary formats specific to each sensor and manufacturer are used, then device complexity is reduced for individual manufacturers, but the adaptability of the system deteriorates
Solution Approach 1:
The patent creates a universal data schema that can accommodate telemetry data from multiple manufacturers and device types. The normalization service implements universal mapping rules and a common data model that works across different proprietary formats, enabling the system to handle diverse data sources with a single unified approach, thereby achieving universality without compromising individual device simplicity
3Productivity
If unstructured telemetry data is collected without standard schema, then the productivity of data collection increases, but the loss of information increases due to inability to derive insights
Solution Approach 1:
The patent applies preliminary action by normalizing and structuring telemetry data immediately upon collection, before analysis or storage. The data normalization service performs schema mapping, validation, and enrichment at the point of data ingestion, ensuring that the data is ready for insight generation without requiring later reprocessing, thereby preventing information loss while maintaining collection productivity
Data Source
AI summary
The disclosure derives insight from telemetry data by receiving telemetry data; parsing the received telemetry data to identify properties, and mapping the identified properties to a set of identified tags based at least on a tag library. Based at least on the mapping, the disclosure generates insight data and a report for the telemetry data. In this manner, the disclosure adds structure to data, thereby providing semantic meaning to internet of things (IoT) telemetry data, regardless of the device class or manufacturer. This, in turn, automatically creates applicable insights. Insights are available with a core tag taxonomy, which can be extended and customized. By applying the tags, a user obtains immediate insights related to usage, performance, and health of a monitored product or service.