Automated Building Inspection Workflow for Code Compliance Verification
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Solution Overview
Problem
Building inspections are time-consuming and prone to human error due to complex, jurisdiction-specific requirements in diverse formats, lacking unified systems to automate the interpretation and documentation of compliance.
Innovation Solution
A computer-implemented system and method that imports and interprets inspection requirements, generates task lists, and utilizes AI models to automate tool usage, integrating large language models and tool libraries for real-time compliance verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used, then inspectors can verify requirements, but the process is time-consuming and prone to human error
Solution Approach 1:
The patent replaces manual mechanical inspection processes with an automated computer vision system that uses machine learning models to detect and verify building code requirements. The system automatically captures images, processes them through trained models, and generates compliance reports, eliminating human manual verification while improving both speed and accuracy.
Solution Approach 2:
The inspection system performs self-verification by automatically comparing detected features against building code requirements stored in the database. The system independently validates compliance without requiring human inspectors to manually check each requirement, enabling the system to serve itself in the verification process.
2Productivity
If inspectors manually document compliance, then requirements can be recorded, but the process is repetitive and detail-oriented
Solution Approach 1:
The patent replaces manual documentation processes with automated computer vision and natural language processing systems. The system automatically generates structured compliance reports from processed images and detected features, eliminating repetitive manual typing and formatting while ensuring consistent accuracy through algorithmic validation against building codes.
Solution Approach 2:
The system creates digital copies of inspection data directly from captured images and sensor readings, automatically structuring and storing them in standardized formats. This eliminates the need for manual transcription and reduces errors associated with manual copying and data entry.
3Adaptability or versatility
If requirements are stored in nonstandard formats, then diverse sources can be accommodated, but machine readability and databasing are challenging
Solution Approach 1:
The patent introduces an intermediary processing layer that converts various nonstandard requirement formats from different sources into a unified standardized database structure. This intermediary translation layer handles PDFs, Word documents, web pages, and other formats, converting them into machine-readable structured data without requiring changes to the source formats or complicating the core database system.
Solution Approach 2:
The system employs a universal import and processing framework that can handle multiple document formats and data sources through a single standardized interface. This multi-functional capability allows the system to accommodate diverse requirement sources while maintaining a consistent internal data structure, reducing overall system complexity.
4Reliability
If inspectors verify multiple interrelated measurements, then compliance can be confirmed, but the process requires complex coordination
Solution Approach 1:
The patent merges multiple measurement verification tasks into a single integrated computer vision processing pipeline. The system simultaneously detects and correlates multiple features and measurements from captured images, automatically verifying interrelated requirements in one unified process rather than requiring separate manual checks for each measurement.
Solution Approach 2:
The system implements automated feedback loops where detection results from one measurement inform subsequent verification steps. The machine learning models use feedback from initial detections to adjust and refine subsequent measurements and compliance assessments, automatically coordinating complex interrelated verifications without increasing operational complexity.
Data Source
AI summary
A computer-implemented system and method for automating building inspections are disclosed herein. This system and method expedites interpretation and inspection against documented requirements, improves accuracy in measurement and other calculations, as well as securely stores documentation against said requirements. The system includes a device with a user interface, an extraction engine running a server, a classifier engine running on the server, a database, a large language model running on the server, and a tool library on the device.