Cloud AI Configuration Reuse for Device Monitoring
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Solution Overview
Problem
Existing systems for monitoring process equipment with artificial intelligence require separate AI algorithms and models for each type of equipment, necessitating new data preparation and system development whenever new equipment is added, making it inconvenient to apply AI analysis efficiently.
Innovation Solution
An AI configuration system that allows users to select existing AI configurations and learning data from similar devices, enabling the generation of suitable AI configurations without developing a new system, by storing device type information, AI configuration data, and sensing information, and using this data for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a separate AI algorithm and model are developed for each new device, then the AI analysis accuracy for that specific device is improved, but the system complexity and development time increase significantly
Solution Approach 1:
The patent implements a universal AI configuration storage that stores AI algorithms and models applicable to multiple device types. When a new device is added, the system retrieves and applies pre-stored configurations that can be reused across similar devices, eliminating the need to develop separate AI models for each device while maintaining analysis accuracy.
Solution Approach 2:
The system performs preliminary actions by pre-storing AI algorithms and models in the AI configuration storage before new devices are added. This allows rapid deployment of AI analysis capabilities when new devices are introduced, as the configurations are already prepared and can be directly applied without time-consuming development processes.
2Reliability
If new AI learning data is prepared and a new AI model is trained for each new equipment, then the AI analysis reliability is improved, but the time and resources required for model training increase
Solution Approach 1:
The patent implements a copying mechanism where existing AI configurations and learning data from previously analyzed devices are stored and reused for new devices. Instead of creating new models from scratch, the system copies proven configurations that have demonstrated reliability, significantly reducing training time while maintaining analysis reliability through validated models.
Solution Approach 2:
The system performs preliminary actions by pre-preparing and storing AI learning data and trained models in the AI configuration storage before new devices are added. This allows the system to immediately apply reliable, pre-trained models to new equipment without undergoing time-consuming training processes, thus maintaining reliability while minimizing time loss.
3Adaptability or versatility
If a new system is developed to connect new equipment data to AI models, then the adaptability to new device types is improved, but the development effort and system complexity increase
Solution Approach 1:
The patent implements a universal AI configuration storage designed to handle multiple device types through a single system architecture. The storage structure is designed to accommodate AI algorithms and models for various device categories (manufacturing equipment, medical devices, consumer electronics, etc.), providing broad adaptability without requiring separate development efforts for each device type.
Solution Approach 2:
The system performs preliminary actions by pre-establishing the AI configuration storage infrastructure and populating it with reusable configurations before new devices are introduced. This preliminary setup enables rapid adaptation to new device types through simple configuration retrieval and application, eliminating the need for complex system development and integration work when new equipment is added.
4Measurement precision
If AI configurations are customized for each specific device, then the analysis precision for that device is improved, but the ease of operation and configuration process deteriorate
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically retrieves and applies appropriate AI configurations from the storage when new devices are added, without requiring manual customization. The configuration management unit automatically matches devices with suitable pre-stored AI models, maintaining high analysis precision while eliminating complex manual configuration processes for users.
Solution Approach 2:
The patent implements a universal AI configuration storage that contains pre-configured AI algorithms and models applicable to multiple device types. This universal repository allows the system to maintain high analysis precision across different devices by selecting appropriate pre-configured models, while users benefit from simplified operation as no manual customization is required.
Data Source
AI summary
An artificial intelligence configuration system and an artificial intelligence configuration method include a device type information storage unit configured to store device type information for a plurality of device types to be monitored; an artificial intelligence configuration information storage unit configured to store one or more pieces of artificial intelligence configuration information for each of the device types; a device information storage unit configured to store device information for each actual device of each of the device types; an artificial intelligence configuration unit; a device configuration unit; and a sensing data analysis unit, and an artificial intelligence configuration method.