Method of realizing benefits of indoor cleaning system through artificial intelligence generated content
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing indoor air cleaning systems face challenges in optimizing device numbers, layout, performance control, noise reduction, and cost planning to meet clean room requirements, requiring extensive data verification and experimentation.
Innovation Solution
An indoor cleaning system integrated with artificial intelligence generated content (AIGC) optimizes device numbers, layout, performance control, and cost planning by using professionally and user-generated data to generate optimized settings through deep learning, ensuring quick convergence and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to optimize device numbers, layout, and configuration, then extensive data verification and repeated experimentation are required, but this leads to high time consumption and complex planning processes
Solution Approach 1:
The patent replaces traditional mechanical trial-and-error optimization methods with an AIGC-based intelligent system. The system uses large language models to process professional knowledge and user requirements, automatically generating optimized device numbers, layouts, and configurations without requiring extensive physical experimentation or manual data verification.
Solution Approach 2:
The patent introduces an AIGC model as an intermediary between user requirements and system configuration. This intermediary processes natural language inputs, integrates professional knowledge databases, and generates optimized solutions, eliminating the need for direct manual optimization efforts and repeated experimentation.
2Reliability
If manual optimization methods are used for system configuration, then extensive experimentation is required, but this increases device complexity and planning difficulty
Solution Approach 1:
The patent enables the system to perform self-optimization through the AIGC model, which automatically analyzes requirements, queries professional knowledge databases, and generates optimized configurations without external intervention. This self-service capability eliminates the need for complex manual planning processes while ensuring reliable system performance.
Solution Approach 2:
The patent pre-establishes a professional knowledge database containing optimized configuration patterns and best practices. The AIGC model queries this pre-prepared knowledge base to generate reliable configurations, avoiding the need for extensive real-time experimentation and reducing planning complexity.
3Measurement precision
If traditional optimization approaches are used, then repeated experimentation is necessary, but this increases cost planning and reduces ease of operation
Solution Approach 1:
The patent replaces manual optimization operations with automated AIGC-based intelligent optimization. Users simply input their requirements in natural language, and the system automatically generates optimized configurations by querying professional knowledge databases, eliminating the need for users to perform repeated experimentation or complex calculations.
Solution Approach 2:
The AIGC model serves as an intermediary that translates simple user requirements into optimized system configurations. It automatically queries professional knowledge databases and performs the complex optimization work, making the system easy to operate while maintaining high optimization accuracy.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method of realizing benefits of indoor cleaning system (A) through AIGC is disclosed and includes following steps: providing professionally generated data of an indoor cleaning system (A); providing user-generated data of the indoor cleaning system (A); providing an AIGC model (4) and inputting the professionally generated data and the user-generated data for calculating, comparing and identifying to generate an automatically generated data; and providing an integrated benefit correction to promote an ultimate integration of the automatically generated data generated by the AIGC model (4), so as to optimize a deep learning processing data correction, and compare learning and improvement of the automatically generated data, wherein the AIGC model (4) is led to quickly converge in a correct and applicable direction, and the automatically generated data are regressed to a most accurate one, so that the benefits of the indoor cleaning system (A) are optimized for implementing the indoor cleaning system (A).