AI Automation Profile Generator for Reliable System Updates
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Solution Overview
Problem
Traditional automation techniques lack precision and reliability due to a lack of prior knowledge of system and application conditions, and fail to consider processing load, making it challenging to automate tasks effectively.
Innovation Solution
A computerized method utilizing artificial intelligence to determine system automation profiles, construct AI-based learning mechanisms, and create portable automation criteria libraries that can be applied to new systems with comparable profiles, ensuring reliable and fault-tolerant automation by analyzing processing power, load, and performance attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional automation techniques are used, then automation can be implemented, but precision and reliability are limited due to lack of prior knowledge of system conditions
Solution Approach 1:
The system performs preliminary scanning of the application to extract data on processing power, load, footprint, and performance attributes before automation execution. This preliminary action builds an automation profile that contains prior knowledge of system conditions, enabling reliable and precise automation without needing real-time intervention.
2Productivity
If automation speed is increased, then productivity improves, but processing load management becomes insufficient affecting reliability
Solution Approach 1:
The system changes automation parameters dynamically based on extracted system data. By analyzing processing power, load, footprint, and performance attributes, the system adjusts automation speed and timing parameters to optimize both productivity and reliability, ensuring tasks complete successfully without overwhelming the system.
3Reliability
If automation is customized for each system, then reliability improves, but device complexity and implementation time increase
Solution Approach 1:
The system creates a universal automation profile generator that can scan and profile any application by extracting common attributes (processing power, load, footprint, performance). This multi-functional approach enables reliable automation across different systems without requiring system-specific customization, reducing overall complexity.
Solution Approach 2:
The system creates a portable automation profile that can be copied and applied to new systems with comparable characteristics. By extracting and storing system attributes in a reusable profile format, the system enables rapid deployment of reliable automation without re-scanning or re-configuring each time.
4Adaptability or versatility
If automation criteria are updated continuously, then adaptability to system changes improves, but processing time and computational load increase
Solution Approach 1:
The system performs self-updating by automatically scanning for application changes and updating automation profiles without external intervention. The profile generator continuously monitors system attributes and updates automation criteria autonomously, maintaining adaptability while minimizing manual processing time.
Data Source
AI summary
This invention generally relates to a process, system and computer code for updating of computer applications based on collecting automation information related to a current application such as processing power, load, footprint, and performance attributes, determining a system automation profile; using an artificial intelligence based modeler for analyzing data, applying the data to an artificial intelligence model for training and predicting performance, adjusting the artificial intelligence model to achieve an updated automation criteria with optimal values, wherein the optimal values provide input to an automation criteria library for storing and updating a prior automation criteria, and exporting the upgraded automation criteria values for incorporation in a computer-to-be-updated, to achieve a reliable automatic update.