Augmented Reality Damage Assessment Using Image Recognition
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Solution Overview
Problem
Current methods for assessing damage to insured items are tedious, inaccurate, and time-consuming, leading to inconsistencies in claim payments and potential fraud, as homeowners struggle to accurately inventory valuables and wait for adjusters to assess damage.
Innovation Solution
An augmented reality method using image recognition and artificial intelligence to capture initial and post-damage images of items, automatically detecting differences, determining repair or replacement needs, and estimating costs, thereby streamlining the inventory process and reducing reliance on manual assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inventory forms are used to list valuables, then customers can document their possessions, but the process is tedious and time-consuming leading to inaccurate or incomplete documentation
Solution Approach 1:
The patent replaces the manual mechanical process of filling out inventory forms with an automated image recognition system using machine learning algorithms. The system captures images of possessions and automatically identifies, catalogs, and values items, eliminating the need for manual documentation while improving accuracy through automated object detection and classification.
Solution Approach 2:
The patent creates digital copies (images) of physical possessions and uses these copies to automatically generate inventory information. By capturing images and analyzing them through AI algorithms, the system extracts item details, quantities, and valuation data without requiring physical handling or manual entry, thus saving time while maintaining accuracy.
2Reliability
If adjusters manually assess damage after incidents, then damage evaluation can be performed, but the process is time-consuming and produces inconsistent results due to varying adjuster methods
Solution Approach 1:
The patent replaces the manual mechanical assessment process performed by adjusters with an automated computer vision system. The system captures images of damaged items and uses machine learning models to objectively evaluate damage extent, classify damage types, and estimate repair costs, eliminating human variability and providing consistent, reliable assessments across all claims.
Solution Approach 2:
The patent enables the damage assessment system to evaluate and process claims autonomously without requiring human adjuster intervention for routine assessments. The AI system independently analyzes images, determines damage severity, calculates repair estimates, and generates claims decisions, significantly reducing assessment time while maintaining consistency through standardized algorithmic evaluation criteria.
Data Source
AI summary
A method of automatically detecting damage following a loss causing incident is disclosed. The method includes capturing image information about a group of physical objects in their initial states and comparing these with image information about the group of physical objects in their modified states following a loss causing incident. The method includes detecting discrepancies between the initial and modified states and automatically assesses the degree of damage and/or loss.