Industrial Data Platform Using BIDTs for Contextualized Asset Data
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Solution Overview
Problem
Industrial automation systems face challenges in collecting and formatting data from distributed industrial devices into meaningful presentations for users, as much of the data is unstructured and lacks context, burdening developers to define its meaning.
Innovation Solution
The implementation of Basic Information Data Types (BIDTs) within industrial devices, which are structured data types representing rates, states, and events, along with user-configurable metadata, and a gateway device that references these BIDTs in asset models to generate contextualized data presentations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If unstructured data is collected from distributed industrial devices, then data collection coverage is improved, but data usability and contextual meaning deteriorate
Solution Approach 1:
The patent applies parameter changes by transforming unstructured industrial data into structured data with defined parameters. Basic Information Data Types (BIDTs) are implemented to standardize data representation, converting raw unstructured data into organized data structures with specific parameters such as rates, states, and events. This transformation maintains data quantity while recovering contextual meaning through standardized parameter definitions.
Solution Approach 2:
The patent introduces an intermediary layer (gateway device or server) that mediates between distributed industrial devices and users. This intermediary collects unstructured data from multiple devices, applies BIDT-based structuring, and presents contextualized information. The intermediary recovers lost contextual meaning by interpreting raw data through standardized data types and relationships before presenting it to users.
2Loss of information
If developers manually define data meaning for unstructured data, then data contextual accuracy is improved, but system complexity and development burden increase
Solution Approach 1:
The patent applies universality by creating a universal data framework (BIDTs) that can handle multiple types of industrial data through a common structure. Instead of requiring custom definitions for each data type, the universal BIDT framework provides standardized templates for rates, states, events, and other data categories. This reduces system complexity by eliminating the need for developers to manually define data meaning for each individual data point.
Solution Approach 2:
The patent changes the parameter structure from unstructured free-form data to structured parameters defined by BIDTs. By imposing a standardized parameter framework, the system automatically recovers contextual accuracy without requiring manual intervention for each data element. The parameter changes transform the data organization from developer-dependent to system-standardized.
3Loss of information
If structured data types are implemented in industrial devices, then data usability is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the data structuring function into discrete, manageable BIDT components. Instead of implementing a complex monolithic data structure, the system segments data organization into standardized types (rates, states, events, etc.). Each BIDT represents a segmented, self-contained data category that can be independently implemented and understood, reducing the perceived complexity while improving data usability.
Data Source
AI summary
A cloud-based industrial data services (IDS) architecture leverage smart tags, asset models, and data service applications to facilitate secure transaction and exchange of contextualized factory data between different parties as part of a combined technology and commerce platform, or to perform provide asset owners with insights into operation of their industrial assets. The IDS platform supports a set of services that connect providers of smart industrial devices to plant floor and systems owned by the end users of these devices. The cloud-based platform allows asset providers to publish data service applications for purchase and use by end users of their assets, and allows equipment owners to control remote access to selected sets of their industrial data via the cloud platform.