Digital Twin Telemetry Processing via User-Defined Functions
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Solution Overview
Problem
Managing and processing vast amounts of data from IoT devices is challenging due to difficulties in intuitively managing and grouping devices, controlling user access, and efficiently processing sensor data linked to the physical environment.
Innovation Solution
A method involving user-defined functions and matchers within a digital twins object model, where data is parsed to identify metadata, and user-defined functions are executed based on matching conditions, stored in a spatial intelligence graph, allowing for efficient data processing and customization of telemetry processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data processing methods are used for IoT devices, then device management and data processing can be performed, but it becomes increasingly difficult to manage devices and their users, control user access, and efficiently process data as the number of devices proliferates
Solution Approach 1:
The patent introduces a digital twin intermediary layer that mediates between physical IoT devices and the processing system. Each physical device has a corresponding digital twin that stores metadata, properties, and relationships. This intermediary enables efficient querying and processing by allowing the system to work with digital representations rather than directly managing complex device connections, thus improving productivity while managing system complexity.
Solution Approach 2:
The patent creates digital copies (digital twins) of physical IoT devices and their data. These digital twins contain metadata, properties, and relationship information that replicate the physical devices' characteristics. By working with these copies, the system can efficiently process and analyze device data without the complexity of directly managing the physical devices, thereby improving data processing efficiency while maintaining manageable system complexity.
2Loss of information
If vast amounts of telemetry data from IoT devices are collected, then comprehensive monitoring and analysis are enabled, but it becomes difficult to manage, access, and link the data to the physical environment
Solution Approach 1:
The digital twin serves as an intermediary between raw telemetry data and the physical environment representation. It stores structured metadata, properties, and relationships that link device data to physical contexts. This intermediary layer enables accurate data linkage by providing a structured framework that connects telemetry data to physical devices and their environments, preventing information loss while maintaining manageable data complexity.
Solution Approach 2:
The patent segments the data management system into distinct components: digital twins for device representation, metadata for device characteristics, properties for specific attributes, and relationships for contextual connections. This segmentation organizes vast amounts of telemetry data into manageable, structured units that can be efficiently linked to the physical environment, reducing data management complexity while ensuring accurate information linkage.
3Adaptability or versatility
If user-defined functions are implemented for telemetry processing, then customization and efficiency are improved, but system complexity increases
Solution Approach 1:
The patent stores user-defined functions as digital objects within the digital twin framework. These function definitions are copied and associated with relevant digital twins, allowing customization without creating complex standalone processing systems. The functions are integrated into the existing digital twin structure, enabling adaptable telemetry processing while maintaining manageable system complexity through reuse of the established framework.
Solution Approach 2:
The digital twin framework provides a universal platform that can accommodate various user-defined functions for different telemetry processing needs. Rather than creating separate complex systems for each customization requirement, the system uses a multi-functional digital twin structure that can handle diverse processing tasks through a unified approach, thereby improving adaptability while controlling system complexity.
Data Source
AI summary
Described herein is a system and method of processing data of a digital twins object model. Data associated with a node of the digital twins object model is parsed to identify metadata associated with the node. The data can comprise telemetry data received from an IoT device associated with the node. User-defined function(s) are determined that match the identified metadata. The data and metadata can be provided to the user-defined function(s). The determined user-defined function(s) are executed. Also described herein is a method of creating a user-defined function for processing data of a digital twins object model. Information regarding business logic is received from a user defining a user-defined function. Information regarding telemetry condition(s) to which the user-defined function applies is received defining a matcher. The user-defined function and matcher are stored as objects within a spatial intelligence graph associated with the digital twins object model.