AI Virtual Representations for AEC Smart Constructs
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Solution Overview
Problem
Conventional software solutions in the Architecture, Engineering, and Construction (AEC) field fail to comprehend dynamic variations, provide real-time decision-making, and adapt to diverse inputs, leading to inefficiencies in project management and construction processes.
Innovation Solution
An AI-based system that determines user intent, computes knowledge units, and generates virtual representations of AEC smart constructs through computational simulations, integrating historical and factual data with human cognitive factors to optimize project objectives such as cost, time, and sustainability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional software solutions are used for AEC project management, then basic design and planning functions can be performed, but the system fails to comprehend dynamic variations and provide real-time decision-making capabilities
Solution Approach 1:
The patent replaces conventional mechanical/software-based decision-making systems with an AI-based system that uses machine learning models, natural language processing, and computational simulations to comprehend dynamic variations and provide real-time decision-making capabilities in AEC project management
Solution Approach 2:
The AI system performs self-learning and self-adjustment by processing historical and factual data to automatically update its models, enabling it to adapt to dynamic project conditions without requiring manual reconfiguration or external intervention for each variation
2Adaptability or versatility
If conventional rule-based software is used, then standardized processes can be maintained, but the system cannot adapt to diverse inputs or provide meaningful insights
Solution Approach 1:
The patent implements feedback mechanisms where the AI system continuously processes feedback from diverse inputs (text, images, data streams) to refine its understanding and generate more accurate insights, creating a closed-loop system that learns from each interaction
Solution Approach 2:
The AI-based system is designed to handle multiple types of inputs (textual, visual, numerical) and perform various functions (analysis, prediction, decision-making) through a single unified platform, replacing the need for multiple specialized software tools
3Productivity
If manual and rule-based approaches are used for design, then control over design processes is maintained, but the system cannot provide real-time optimization or follow-up validation
Solution Approach 1:
The patent performs preliminary actions by pre-training AI models on historical AEC data and pre-configuring computational simulations to evaluate design options, enabling rapid real-time optimization when new design requirements arise without requiring complex on-demand system configuration
Data Source
AI summary
A system for generating virtual representations of architecture, engineering, and construction (AEC) smart constructs is disclosed. The system includes a controller that determines user intent based on an analysis of a user input and further determines project objective constraints based on an evaluation of project objectives. Knowledge units are computed based on a plurality of nodes and a plurality of interdependencies of a computational graph. The plurality of nodes corresponds to the user intent, and the plurality of interdependencies is established based on the project objectives. Based on the knowledge units, computational simulations for the user intent are performed. Further, virtual representations of the AEC smart constructs in a digital environment are generated based on the computational simulations. The computational simulations meet a defined criteria associated with the project objectives.