How a System Scores Your Home's Maintenance and Teaches You
This patent describes a system that uses machine learning to score a home's maintenance, compares it to another property, and then creates personalized learning tips for the user to help them improve their home, especially when moving.
Patent Number
US 12737818
Status
Active
Filing Date
April 23, 2024
Grant Date
September 15, 2026
Expiration
~April 2044 (estimated)
Claims
0
Assignee
—
Inventors
—
Citations
0 forward · 0 backward
What it covers
This system evaluates and gamifies property maintenance for a user. It starts by retrieving data for a user's current home (first property) and a new home they are becoming associated with (second property). Using a trained machine learning model, it calculates maintenance scores for the new home based on its data. Crucially, it detects local environmental differences between the user's old and new properties. Finally, it generates a personalized learning module for the user. This module aims to help the user improve or maintain the new home's maintenance scores, specifically tailoring advice based on the detected environmental differences. For example, if a user moves from a dry desert climate to a humid coastal area, the system might generate a module on preventing mold or managing humidity in their new home.
What it doesn't cover
- —Does not cover systems that only score a single property without comparing it to another property associated with the user.
- —Does not cover systems that do not use a trained machine learning model to calculate home score factors.
- —Does not cover systems that fail to detect local environmental differences between two properties a user is associated with.
- —Does not cover systems that do not generate a personalized learning module for the user based on those environmental differences.
- —Does not cover systems that solely provide generic maintenance advice without considering a user's transition between different properties.
The clever bit
The novelty lies in combining a user's transition between two properties with the detection of environmental differences between those locations. This allows the system to generate highly personalized, proactive maintenance advice, rather than just generic tips, by anticipating new challenges a user might face.
Why it matters
This technology could help homeowners, especially those relocating, understand and adapt to new maintenance needs specific to their new environment. By providing personalized guidance, it could reduce unexpected repair costs and help maintain property value. It also introduces a gamified element to encourage consistent home care.
Real-world examples
- 1.Smart home assistant apps
- 2.Real estate platforms offering homeowner resources
- 3.Home insurance company portals
- 4.Property management software for individual homeowners
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US 12737818 · 2026