Virtual Property Models for Weather Damage Risk Simulation

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Solution Overview

Problem

Traditional methods for assessing the risk of property damage due to weather events rely on historical data and aerial imagery, which fail to account for unique characteristics of individual properties, resulting in inaccurate risk assessments.

Innovation Solution

A computer-implemented method and system that utilize high-resolution virtual models of properties generated from images captured by remote imaging vehicles, combined with simulation environments that model weather systems based on historical data, to predictively assess the risk of damage to specific properties.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional aerial imagery and historical data are used for risk assessment, then the assessment process is simple and fast, but the accuracy of risk assessment deteriorates because unique characteristics of individual properties cannot be captured

Engineering Contradiction:
Improverisk assessment accuracyVSAvoidmodeling complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent creates virtual models (digital twins) that are accurate copies of physical properties, capturing unique characteristics such as building structure, materials, and surrounding environment. These virtual models allow detailed simulation of weather events without requiring physical testing, thereby improving risk assessment accuracy while maintaining manageable complexity through computational rather than physical modeling.

Inventive Principle:
Principle #26Copying

2Measurement precision

If high-resolution virtual models with accuracy of at least 10 cm are created, then the detail and precision of property characteristics improve, but the data processing and simulation complexity increases

Engineering Contradiction:
Improvevirtual model accuracyVSAvoidprocessing time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary actions by creating comprehensive virtual models in advance, capturing all relevant property characteristics before simulation is needed. This pre-modeling effort, though time-consuming initially, enables rapid subsequent simulations and risk assessments, as the detailed geometric and material information is already structured and ready for computational analysis.

Inventive Principle:
Principle #10Preliminary action

3Reliability

If simulation environments are used to model weather systems acting upon properties, then the ability to predict specific property damage improves, but the computational resources and system complexity increase

Engineering Contradiction:
Improvepredictive accuracyVSAvoidsimulation system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces physical testing and mechanical assessment methods with computational simulation. Instead of physically exposing properties to weather events or using complex mechanical measurement systems, the invention uses software-based simulation environments that model weather systems and their interactions with virtual property models, achieving high predictive accuracy through algorithms rather than physical apparatus.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250131512A1Systems and methods for predictive modeling via simulation
Publication Date: 2025.04.24 STATE FARM MUTAL AUTOMOBILE INSURANCE COMPANY
  • US20250131512A1 patent drawing
  • US20250131512A1 patent drawing
  • US20250131512A1 patent drawing

AI summary

Methods, systems, and computer readable media for predictively determining a risk of damage to a property are provided. To determine the risk, a high resolution virtual model of a region that includes the property is obtained. The virtual model is imported into a simulation environment. One or more of the simulation parameters are set based on historic weather data for the region. For example, each parameter may be associated with a probability distribution derived based on the historic weather data that is sampled prior to executing the simulation. One or more simulations are executed in accordance with the sampled inputs to simulate the likely weather patterns the property will experience. The result of the simulation is analyzed to determine the predicted risk of damage to the property.