Mobile Image Recognition for Property Maintenance Reporting
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Solution Overview
Problem
Managing property maintenance and compliance is a daunting task due to the complexity of tracking items that require periodic attention, repairs, and compliance with various regulations, as existing methods lack efficient tracking and reporting mechanisms.
Innovation Solution
A method using image recognition on a mobile device to capture and analyze images of a property environment, identifying objects of interest, and generating reports that include maintenance plans and compliance information, which can be customized based on the condition, size, and location of the objects, and suggesting professionals for maintenance and compliance services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual tracking methods are used to monitor property maintenance items, then property owners can keep track of maintenance tasks, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The patent replaces manual mechanical tracking methods with an automated image recognition system using machine learning algorithms. The system captures images of property items, automatically identifies them, retrieves maintenance information from databases, and generates reports without human intervention, thereby substituting manual labor with automated computational processes.
Solution Approach 2:
The system enables self-service by allowing property owners to simply capture images with their mobile devices, and the system automatically performs identification, information retrieval, and report generation. This eliminates the need for owners to manually track and manage maintenance tasks, as the system serves itself through automated processing.
2Reliability
If comprehensive maintenance tracking is implemented to monitor all property items, then maintenance needs are identified, but the complexity of managing and organizing information increases
Solution Approach 1:
The patent segments the complex maintenance tracking system into distinct functional modules: image capture, image recognition, database querying, and report generation. Each module handles a specific aspect of the process, reducing overall system complexity while maintaining comprehensive tracking capabilities through modular architecture.
Solution Approach 2:
The system introduces an intermediary database that stores maintenance information for various property items. This database acts as a mediator between the image recognition system and the report generation process, organizing and managing comprehensive maintenance data without requiring complex direct connections between all system components.
3Loss of information
If detailed maintenance plans are generated for each identified object, then comprehensive maintenance information is provided, but the time and resources required to process and deliver information increase
Solution Approach 1:
The system performs preliminary actions by pre-populating a database with maintenance information for various property items before they are scanned. When an item is identified through image recognition, the system can quickly retrieve pre-existing maintenance plans and specifications without needing to process or analyze the item in real-time, thereby reducing information processing time while maintaining completeness.
Data Source
AI summary
Image recognition and report generation is described. A camera component of a mobile device captures image frames of a physical environment. Each frame is run through an image recognition library to identify object(s) of interest. An object of interest is determined and it is an item associated with periodic maintenance. An identification of the identified object of interest is transmitted to a server. The mobile device receives information about the identified object of interest from the server that is based on a location of the mobile device, the information including a maintenance plan for the identified object of interest.