Automated Rental Property Inspection via Lease-Video Feature Matching
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Solution Overview
Problem
Documenting the state of a rental property is time-consuming and inefficient, as video or photo documentation by tenants may not clearly capture all features, especially when specific lease provisions are involved, leading to difficulties in storing and retrieving relevant information for future disputes.
Innovation Solution
A computer-implemented method and system that analyzes a lease document to identify specific features, guides users through video and audio documentation of a rental property using a mobile app, and uses machine learning to tag and categorize important features, ensuring comprehensive and retrievable evidence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a tenant uses manual video or photo documentation to record the rental property condition, then the documentation can be created, but the documentation may not clearly capture all lease features and is time-consuming
Solution Approach 1:
The patent replaces manual mechanical documentation processes with automated computer vision and machine learning systems. The system automatically captures images, identifies lease features through image recognition, and documents property conditions without requiring manual review, thereby improving both clarity and efficiency
Solution Approach 2:
The system enables self-service documentation by allowing tenants to capture images and automatically generating structured documentation that identifies lease features. The automated processing eliminates the need for professional inspection services while maintaining documentation quality
2Loss of information
If a tenant captures comprehensive video footage of all property features, then all features may be documented, but the footage becomes difficult to store and retrieve efficiently
Solution Approach 1:
The patent segments comprehensive video footage into individual frames and identifies specific lease features within each frame. By breaking down continuous video into discrete analyzable units and tagging them with identified features, the system enables efficient storage and retrieval without losing documentation completeness
Solution Approach 2:
The system introduces an intermediary processing layer that analyzes video frames, identifies lease features, and creates structured metadata. This intermediary step transforms unstructured video data into organized, searchable information while preserving the original comprehensive documentation
3Productivity
If manual inspection and documentation processes are used, then the process can be completed, but it is frustrating and inefficient for both tenants and landlords
Solution Approach 1:
The patent replaces manual inspection processes with automated image recognition and lease feature matching systems. The system automatically analyzes captured images, identifies relevant lease features, and generates documentation, dramatically improving efficiency and eliminating the frustration of manual processes
Solution Approach 2:
The system provides feedback by automatically identifying which lease features have been captured in the documentation and highlighting any missing features. This feedback mechanism guides users to ensure complete coverage while streamlining the overall process
Data Source
AI summary
A system and method that guides a user to record initial and final walkthrough videos, along with audio, of their rental property is disclosed. The embodiments also provide a system that can scan a lease for the rental property, as well as audio from a user's narration of the video, and extract and tag particular features of the video for efficient querying at a later time. The system can interpret portions of the lease that are relevant to particular items or components in the apartment (for example, major appliances) and guide the user to perform a comprehensive inspection of the items mentioned in the lease.