Image-Stitched Property Models for Continuous Insurance Policy Updates
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Solution Overview
Problem
Existing insurance policies often fail to adequately cover changes made to insured properties after initial policy determination, such as remodeling or addition of items, due to lack of continuous updating mechanisms.
Innovation Solution
A system that uses image editing technology to create a visual model of a property, digitally stitch images to identify new features, and update insurance policies based on these changes, using machine learning to passively monitor and analyze sensor data without active user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If insurance policies are determined based on initial property data, then policy determination is efficient and straightforward, but the policies fail to reflect subsequent property changes such as remodeling or addition of items
Solution Approach 1:
The system implements continuous monitoring of property changes through periodic image acquisition and comparison. The processor continuously receives images, digitally stitches them, compares against reference images, and updates policies automatically, ensuring the insurance coverage remains accurate without requiring manual user intervention at each change point.
Solution Approach 2:
The system enables automatic self-updating of insurance policies by using the processor to autonomously detect property changes through image analysis and trigger policy updates without requiring user initiation. The notification system then informs users of the automatically generated updates, reducing the need for active user participation in the policy maintenance process.
2Measurement precision
If the system requires active user input for data collection, then data accuracy is high, but user burden and system complexity increase
Solution Approach 1:
The system allows properties to monitor and report their own changes automatically. The processor autonomously acquires images, processes them through digital stitching and comparison algorithms, identifies changes, and generates policy updates without requiring users to manually report changes or provide detailed information about property modifications.
Solution Approach 2:
The system implements a feedback loop where the processor continuously monitors property images, compares them against reference data, and automatically triggers policy updates when changes are detected. The notification system provides feedback to users about the detected changes and generated updates, allowing users to verify accuracy without needing to actively participate in the data collection process.
3Area of stationary object
If multiple images are processed and digitally stitched, then comprehensive property coverage is achieved, but processing complexity and computational resources increase
Solution Approach 1:
The system divides the property monitoring task into segmented image acquisitions rather than requiring a single comprehensive image. The processor receives multiple images from different angles or time points, digitally stitches them together to create a complete property view, and then compares this composite image against reference data. This segmentation approach allows comprehensive coverage while managing processing complexity through modular image handling.
4Reliability
If the system continuously monitors property changes, then policy relevance is maintained, but energy consumption and processing load increase
Solution Approach 1:
The system implements periodic monitoring rather than continuous real-time monitoring. The processor receives images at scheduled intervals, performs digital stitching and comparison operations only at these periodic points, and updates policies based on accumulated changes. This periodic approach maintains policy relevance while significantly reducing energy consumption and processing load compared to continuous monitoring.
Data Source
AI summary
A method may include receiving, via at least one processor, a plurality of images representative of a property and determining whether two or more images of the plurality of images correspond to reference image data associated with the property. The method may then involve combining the images to generate a digitally stitched image that corresponds to the reference image data in response to the images corresponding to the reference image data and comparing the digitally stitched image to the reference image data to identify features associated with the property. The method may also involve updating a model representative of the property based on the features and generating an updated insurance policy associated with the property based on the model. Afterwards, the method may send a notification indicative of the updated insurance policy to a computing device.