Ai workflow-based multimodal integrated control method and intelligent resource management system for tco reduction
The intelligent resource management system addresses inefficiencies in infrastructure management by integrating multimodal data processing and AI Workflow for real-time analysis and visualization, enhancing operational efficiency and stability.
KR103000116B1Active Publication Date: 2026-08-05INJE UNIVERSITY INDUSTRY ACADEMIC COOPERATION FOUNDATION
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Patent Information
- Application Number
- KR1020250022919
- Authority / Receiving Office
- KR · KR
- Patent Type
- Patents
- Current Assignee / Owner
- Filing Date
- 2025-02-21
- Publication Date
- 2026-08-05
- Estimated Expiration
- 2045-02-21
AI Technical Summary
Technical Problem
Current infrastructure management systems face inefficiencies due to decentralized management frameworks, lack of responsiveness, and single-modality analysis, leading to increased costs, delayed responses, and reduced operational efficiency.
Method used
An intelligent resource management system integrating a multimodal LLM and AI Workflow engine for real-time data processing, context-aware workflow generation, and 3D visualization to enhance operational efficiency and stability.
Benefits of technology
Enables comprehensive infrastructure management through multimodal data analysis, automated response to exceptions, and intuitive visualization, reducing management costs and improving operational efficiency.
✦ Generated by Eureka AI based on patent content.
Abstract
An AI Workflow-based multimodal integrated control method and an intelligent resource management system for reducing TCO are disclosed. An intelligent resource management system for reducing Total Cost of Ownership (TCO) according to one embodiment may include: a multimodal data integration processing engine that preprocesses multimodal data collected in real time into a form that can be processed by a Large Language Model (LLM); an LLM-based situation analysis engine that generates a situation-adaptive workflow based on situation information interpreted through relationship analysis using a Large Language Model for the preprocessed multimodal data; and a 3D topology visualization engine that visualizes an infrastructure operating environment based on the generated situation-adaptive workflow.
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