3D Roof Scanning for Consistent Shingle Damage Assessment
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Solution Overview
Problem
Insurance companies face inconsistent and unreliable roof damage assessments due to subjective human evaluations, which are hazardous and influenced by environmental conditions, leading to inaccurate and variable results.
Innovation Solution
An automated method using a 3D scanner to generate point clouds of roofs, compare them to model shingles, and identify damage through objective analysis, eliminating the need for human estimators to physically inspect the roof.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a human estimator physically inspects the roof to assess damage, then the assessment can be performed with human judgment and experience, but the results are inconsistent and unreliable due to subjective assessment and environmental conditions
Solution Approach 1:
The patent replaces the human estimator's mechanical inspection process with an automated optical scanning system. A 3D scanner captures point cloud data of the roof, and software algorithms automatically analyze the data to identify damage patterns. This substitution eliminates human subjectivity and environmental influences, providing consistent and reliable damage assessments across different estimators and conditions.
Solution Approach 2:
The patent creates a digital copy (point cloud) of the physical roof structure. This virtual representation allows for repeated analysis without physical re-inspection, enabling multiple estimators or algorithms to evaluate the same data objectively. The digital model preserves all structural details while removing the variability inherent in human visual assessment.
2Ease of operation
If a human estimator climbs onto the roof to perform inspection, then direct visual assessment is possible, but the estimator is exposed to dangerous conditions including risk of falling and adverse weather
Solution Approach 1:
The patent introduces a 3D scanning device as an intermediary between the estimator and the roof. The scanner captures data from the ground or a safe position, transferring the inspection function without requiring physical contact with the hazardous environment. This intermediary device performs the dangerous function of close proximity inspection while keeping the human operator safe.
Solution Approach 2:
The system enables self-service inspection where the roof itself provides the data through its reflection of light or other physical properties. The 3D scanner passively captures information about the roof's condition without requiring an estimator to physically interact with or approach dangerous areas, making the inspection process inherently safer.
3Adaptability or versatility
If multiple estimators with different experience levels perform assessments, then diverse perspectives are available, but the results vary significantly due to lack of repeatability
Solution Approach 1:
The patent creates a standardized digital copy of the roof that serves as the sole basis for assessment. All estimators, regardless of experience level, analyze the identical point cloud data using the same software algorithms. This eliminates the variability introduced by different human perspectives while maintaining the ability to handle diverse roof types and damage patterns through programmable analysis methods.
Solution Approach 2:
The patent transforms the assessment from a subjective human judgment process to an objective parameter-based analysis. The software evaluates specific measurable parameters from the point cloud data, such as surface deviations, pattern disruptions, and geometric anomalies. This parameterization ensures consistent application of assessment criteria across all estimators and situations.
Data Source
AI summary
A damage assessment module operating on a computer system automatically evaluates a roof, estimating damage to the roof by analyzing a point cloud of a roof. The damage assessment module identifies individual shingles from the point cloud and detects potentially damaged areas on each of the shingles. The damage assessment module then maps the potentially damaged areas of each shingle back to the point cloud to determine which areas of the roof are damaged. Based on the estimation, the damage assessment module generates a report on the roof damage.