Multi-Agent Media Generation for Construction Project Data
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Solution Overview
Problem
Construction management software applications face inefficiencies in synthesizing and presenting construction project data, leading to time-consuming information gathering and potential errors, which can result in delays and inefficiencies in project management.
Innovation Solution
A software-based AI architecture utilizing multiple AI agents to synthesize construction project data into automatically generated media content, including a planner agent, knowledge agent, QA agent, visual agent, speech agent, and production agent, to create accurate and relevant media content such as documents, images, and videos, with accompanying audio narration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If construction project data is manually synthesized and presented using traditional software applications, then users can access project information, but the process is time-consuming and prone to errors
Solution Approach 1:
The system enables self-service by automatically synthesizing construction project data through AI agents that independently gather, process, and present project information without requiring manual user intervention for data compilation and presentation creation
Solution Approach 2:
The patent replaces manual mechanical processes of data gathering and presentation creation with an automated AI-based system that uses machine learning models to synthesize project data, eliminate human error, and deliver results instantly
2Reliability
If traditional software applications are used to manage construction projects, then project data can be stored and accessed, but the synthesis and presentation of data requires manual effort and is error-prone
Solution Approach 1:
The AI agents perform self-service by automatically retrieving, validating, and synthesizing project data from multiple sources, ensuring accuracy through automated processes while eliminating the need for manual data processing efforts
Solution Approach 2:
The system implements feedback mechanisms where AI agents continuously validate and cross-check project data against established criteria and historical project information, automatically correcting errors and improving data reliability through iterative refinement
3Productivity
If manual methods are used to create media content from construction data, then content can be generated, but the process is inefficient and delays project management
Solution Approach 1:
The content creation process is segmented into distinct AI agent responsibilities: data retrieval agents gather information, synthesis agents process and organize data, and presentation agents generate final media content, allowing parallel processing and improved efficiency
Solution Approach 2:
The AI system provides universal functionality by handling multiple types of construction project data (drawings, specifications, schedules, budgets) and generating various media formats (reports, presentations, visualizations) through a single integrated platform
Data Source
AI summary
A computing platform configured to perform functionality that involves (i) receiving an indication of a request for media content related to a given construction project, (ii) utilizing a planner agent to generate a sequence of tasks to be performed by other agents to generate the requested media content, (iii) utilizing a knowledge agent to perform a first subset of the sequence of tasks to obtain a set of project data for use in generating the requested media content, (iv) utilizing a production agent to perform a second subset of the sequence of tasks to generate the requested media content, and (v) causing the generated media content to be presented via a client device.