AR Repair Guidance for Safe Home and Vehicle Diagnostics
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Solution Overview
Problem
Users often struggle to identify and repair malfunctioning home appliances or vehicle components, leading to potential health and safety risks due to delayed or improper repairs.
Innovation Solution
A computer-implemented method and system that uses sensor data and machine learning to identify malfunctioning components, provide augmented reality overlay displays for repairs, and determine the safety of DIY repairs, guiding users through the repair process or recommending professional assistance when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users attempt to repair malfunctioning components themselves, then cost savings and timely repairs may be achieved, but safety risks and potential for improper repair increase
Solution Approach 1:
The system introduces an AI diagnostic assistant as an intermediary between the user and the repair process. The assistant analyzes sensor data, identifies malfunctioning components, and provides guided repair instructions through augmented reality, mediating between the user's repair attempts and the actual repair execution to ensure safety and correctness
Solution Approach 2:
The system enables users to perform self-diagnosis and self-repair of vehicle and home components by providing them with expert-level diagnostic capabilities through AI analysis of sensor data and step-by-step repair guidance, allowing ordinary users to service their own equipment safely and effectively
2Productivity
If users wait until components deteriorate severely before seeking repair, then maintenance costs may be reduced, but health and safety concerns arise
Solution Approach 1:
The system continuously monitors sensor data from vehicles and home appliances to detect early signs of component malfunction before they deteriorate into critical failures. By identifying issues in advance and alerting users proactively, the system enables preventive maintenance that avoids severe deterioration while controlling costs
Solution Approach 2:
The system implements continuous feedback loops where sensor data is constantly analyzed, diagnostic results are communicated to users, and repair outcomes are tracked. This feedback mechanism allows the system to learn from patterns and improve its predictive capabilities, enabling users to maintain components optimally without premature or delayed repairs
3Measurement precision
If detailed diagnostic and repair guidance is provided to users, then repair accuracy and safety improve, but system complexity and information processing requirements increase
Solution Approach 1:
The system segments the complex diagnostic and repair process into distinct modules: sensor data collection, AI analysis, malfunction identification, repair plan generation, and augmented reality guidance. Each module handles a specific aspect of the process, making the overall complex system manageable and maintainable while providing comprehensive diagnostic accuracy
Solution Approach 2:
The system replaces manual diagnostic procedures and expert knowledge with automated AI analysis of sensor data. Machine learning models process sensor readings to identify malfunctions, substituting the need for human experts to physically inspect and diagnose components, thereby reducing system complexity from the user side while maintaining high diagnostic accuracy
Data Source
AI summary
Systems and methods for providing augmented reality overlay displays related to repairs may include obtaining sensor data associated with a home or vehicle and analyzing the sensor data associated to identify a vehicle component and/or home appliance that is not functioning properly. Repairs for the vehicle component and/or home appliance that is not functioning properly may be identified, and a determination may be made as to whether it is safe for a vehicle operator and/or home resident to perform the repair. If so, an augmented reality overlay display may be presented upon images/video of the vehicle/home captured in real time, identifying vehicle/home components that must be manipulated in order to perform the repair. If not, the augmented reality display may identify portions of the vehicle or home of which the vehicle operator must capture images in order to request a professional repair or submit an insurance claim.