Remote Sensor Damage Measurement for Automated Insurance Claims
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Solution Overview
Problem
Existing insurance claim settlement systems lack efficiency and accuracy, particularly in parametric insurance where damage assessment is often delayed or subjective, leading to inefficiencies and potential disputes.
Innovation Solution
A system utilizing remote sensors and machine-learning models to automatically measure damage by comparing pre- and post-triggering event sensor data, such as images and other telemetry, to calculate insurance payouts based on objective damage assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual damage assessment methods are used, then subjective judgment and potential disputes occur, but automation and objectivity are reduced
Solution Approach 1:
The patent replaces manual mechanical assessment processes with automated sensor-based systems. Remote sensors capture images and telemetry data, while machine learning models automatically analyze damage, substituting human subjectivity with objective computational analysis. This resolves the contradiction by maintaining high measurement precision through automated means rather than manual inspection.
Solution Approach 2:
The system enables self-service damage assessment where the sensors and machine learning models autonomously evaluate damage without human intervention. The automated comparison of pre- and post-event sensor data allows the system to independently determine damage extent, improving both objectivity and automation while eliminating subjective human judgment.
2Measurement precision
If detailed manual inspection is performed, then assessment accuracy improves, but time consumption increases
Solution Approach 1:
The system performs preliminary damage assessment automatically using pre-captured sensor data and machine learning models. By having sensors continuously monitor and store data before events occur, and automatically analyzing damage when events happen, the system eliminates time-consuming manual inspection while maintaining accurate measurement through automated comparison of pre- and post-event data.
Solution Approach 2:
Manual inspection processes are replaced with automated image analysis and telemetry data processing. Machine learning models rapidly evaluate sensor images and data to determine damage extent, achieving both high measurement precision and rapid claim settlement by substituting slow manual processes with fast computational analysis.
3Productivity
If automated sensor systems are deployed, then claim processing speed increases, but system complexity increases
Solution Approach 1:
The patent employs multi-functional sensor systems that perform multiple assessment tasks. Remote sensors capture various types of data (images, telemetry) that serve multiple purposes: monitoring conditions before events, documenting damage after events, and providing data for machine learning analysis. This universal approach increases productivity while managing complexity by having one system perform multiple functions rather than requiring separate specialized systems.
Solution Approach 2:
The system introduces an intermediary layer of machine learning models that process and interpret sensor data. These models act as mediators between the complex sensor hardware and the simple claim settlement output, automatically translating diverse sensor inputs into objective damage assessments. This intermediary approach enables rapid automated processing while managing system complexity through intelligent data interpretation.
Data Source
AI summary
Provided herein is a system for settling insurance claims. The system includes a computer; one or more remote sensors configured to generate sensor data for at least one dwelling and communicate the sensor data to the computer; and monitoring software configured to run on the server. The sensor data includes a first set of sensor data collected at a first time point and a second set of sensor data collected at a second time point. The monitoring software is configured to process the sensor data; compare the first set of sensor data to the second set of sensor data; and measure damage to the at least one dwelling based upon the comparison of the first set of sensor data to the second set of sensor data. Also provided are a method of settling insurance claims using the system and a non-transitory, processor-readable medium storing instructions for executing the method.