3D Model Visualization Database System for Automated Data Management
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Solution Overview
Problem
The existing methods for building and managing three-dimensional massive model visualization data sets for complex objects like aircraft are time-consuming and require significant user expertise, leading to inefficiencies in data management and processing.
Innovation Solution
A method and apparatus that utilize a data set manager to automatically create, distribute, and update three-dimensional massive model visualization data sets across a network of repositories and client devices, allowing for efficient management and visualization of complex models without the need for extensive user knowledge or processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually locate and build three-dimensional massive model visualization data sets on their own computers, then the data sets can be created and visualized, but the process becomes time-consuming and requires significant user expertise and computing resources
Solution Approach 1:
A centralized server system acts as an intermediary between the user and the three-dimensional model data. The server automatically locates, retrieves, and processes the required model data from multiple storage locations, eliminating the need for users to manually search and assemble data sets. Users simply request visualizations through a user interface, and the server handles all data collection and processing automatically.
Solution Approach 2:
The system pre-loads and caches three-dimensional model data into memory on the server before users need it. By anticipating data requirements and preparing data sets in advance, the system eliminates time-consuming data retrieval operations when users initiate visualization requests, significantly reducing wait times.
2Reliability
If all three-dimensional model data is processed and stored on user computers, then complete visualization capability is achieved, but significant computing resources and storage capacity are required on user devices
Solution Approach 1:
The system separates computation and data storage from the user device. Heavy processing, data storage, and resource-intensive operations are performed on a centralized server with adequate computing resources. The user device only handles lightweight tasks such as displaying visualizations and capturing user input, dramatically reducing local computing and energy requirements.
Solution Approach 2:
Instead of requiring users to possess complete three-dimensional model data sets locally, the system creates and maintains data sets on the server, then transmits only the necessary visualization data to user devices. This copying approach allows users to access complete data sets remotely without duplicating large amounts of data locally, saving storage space and reducing the need for powerful local hardware.
3Loss of information
If three-dimensional model data is retrieved from multiple storage locations, then comprehensive data availability is achieved, but the locating and processing becomes challenging and time-consuming
Solution Approach 1:
The server system provides a universal interface for accessing three-dimensional model data regardless of the original storage location or format. It automatically handles data retrieval from multiple sources, format conversion, and standardization, presenting a unified data access mechanism to users and eliminating the complexity of managing multiple storage locations.
Solution Approach 2:
The server system automatically manages the complexity of retrieving and processing data from multiple storage locations without user intervention. It self-services by implementing automated data location algorithms, retrieving data from distributed sources, and processing it into usable formats, thereby eliminating the need for users to understand or manage the underlying data infrastructure complexity.
Data Source
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AI summary
A method and system for managing three-dimensional massive model visualization data sets. The method comprises compiling a vehicle list of vehicles for which the three-dimensional massive model visualization data sets are to be built. The method automatically builds the three-dimensional massive model visualization data sets for vehicles in the vehicle list using a computer system. The method stores the three-dimensional massive model visualization data sets in a group of repositories. The method distributes the three-dimensional massive model visualization data sets for displaying massive model visualizations for the vehicles using the three-dimensional massive model visualization data sets on client devices. The method may selectively update a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date.