Audio-Guided Remodel Planning for Accurate Feature Replacement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for identifying and planning structural remodels are subjective and inaccurate, leading to uneven quality and potential premature wear or damage in structure remodels.
Innovation Solution
An artificial intelligence-based system that processes images and audio of a structure, along with floor plans, to generate a remodel plan using a large language model, providing objective and accurate identification of features to replace and materials needed, with user feedback integration for refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual methods are used to identify and plan structural remodels, then the process allows for human judgment and flexibility, but the accuracy and objectivity of identifying features to replace and materials needed deteriorates
Solution Approach 1:
The patent replaces manual visual inspection and subjective judgment with an AI-based automated inspection system that uses image processing and audio analysis to objectively identify structural features requiring replacement. The system substitutes human expertise with machine learning models that can consistently evaluate structural conditions without fatigue or bias.
Solution Approach 2:
The system enables automated self-assessment of structural conditions by processing images and audio data to generate remodel plans without requiring constant human intervention. The AI model independently identifies features, determines replacement needs, and generates material lists, reducing reliance on manual labor while maintaining high accuracy.
2Manufacturing precision
If traditional manual methods are used to create remodel plans, then the system is simpler to implement, but the quality and consistency of remodel plans deteriorates
Solution Approach 1:
The patent segments the remodel planning process into distinct automated components: image capture, audio recording, feature identification, replacement determination, and material listing. Each component is handled by specialized AI models that process specific types of data independently, then integrate their findings to produce a comprehensive remodel plan with high quality and consistency.
Solution Approach 2:
The system introduces an AI-based intermediary layer between the structural assessment and remodel plan generation. This intermediary automatically processes raw images and audio data, extracts relevant features, and translates them into actionable remodel recommendations, ensuring consistent quality without requiring complex manual coordination.
3Reliability
If manual inspection methods are used, then the process is faster to implement, but the reliability of identifying correct features and materials deteriorates
Solution Approach 1:
The system performs preliminary automated analysis of structural conditions by processing images and audio data before final remodel decisions are made. The AI models pre-identify potential issues, prioritize features requiring attention, and prepare initial material lists, reducing the time needed for manual verification while improving reliability through consistent automated assessment.
Data Source
AI summary
An artificial intelligence-based structural remodel estimation system is described herein that processes audio taken of a walkthrough of the structure, processes floor plans, and uses large language models to generate a remodel plan that identifies features of a structure to replace, that is more objective than humans, and that is more accurate than remodel plans generated solely based on structural images. For example, the remodel plan may identify features of a structure to replace and/or materials that may be involved in completing a feature replacement. The artificial intelligence-based structural remodel estimation system can use an audio-based approach to generate the remodel plan.