Edge-Computing UAVs for Property Inspection and Cost Estimation
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Solution Overview
Problem
Current methods for home inspection, commercial property inspection, and insurance claims processing are time-consuming, costly, and inefficient, often requiring manual data collection and multiple iterations, with potential safety risks and inaccuracies due to remote or hazardous locations and limited network connectivity.
Innovation Solution
Implementing an edge-computing system on unmanned autonomous vehicles (UAVs) and field vehicles for real-time data collection, analysis, and processing, using machine learning to determine assessment characteristics, costs, and generate quotes, allowing for decentralized and automated processing without reliance on central servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data collection and central processing is used, then data accuracy can be maintained through human review, but processing time and costs increase significantly
Solution Approach 1:
The patent replaces manual mechanical data collection and analysis with automated UAV-based data collection and AI/ML-based analysis. The system uses computer vision algorithms and machine learning models to automatically inspect properties, identify damage, and generate assessments, eliminating the need for manual human review while maintaining high accuracy through algorithmic precision.
Solution Approach 2:
The system enables self-service through autonomous UAVs that automatically navigate, capture data, and perform inspections without human intervention. The AI models automatically analyze the collected data and generate assessments, allowing the system to serve itself in completing the entire inspection workflow without requiring manual processing at each stage.
2Reliability
If multiple data collection efforts are conducted over time, then comprehensive data can be gathered, but productivity and efficiency decrease
Solution Approach 1:
The patent implements continuous data collection through automated UAV inspections that can operate continuously without interruption. The system captures comprehensive data in a single continuous operation rather than requiring multiple separate data collection efforts, maintaining data completeness while significantly improving productivity through uninterrupted automated inspection processes.
Solution Approach 2:
The system performs preliminary data collection and analysis automatically before human review is needed. UAVs pre-inspect properties and collect all necessary data in advance, and AI models perform preliminary analysis to identify key findings, so that when human reviewers do examine the data, comprehensive information is already available, eliminating the need for multiple follow-up data collection trips.
3Measurement precision
If manual assessment workflows are used, then local costs and conditions can be considered, but the process becomes expensive and time-consuming
Solution Approach 1:
The patent changes the parameters of the assessment process by transitioning from manual human-based assessment to automated AI-based assessment. The system maintains accuracy by using machine learning models trained on local cost data and conditions, automatically adjusting assessment parameters based on geographic location, material costs, and labor rates without requiring manual intervention to consider these factors.
Solution Approach 2:
The system creates a universal assessment platform that automatically adapts to different locations and conditions. The AI models are designed to universally handle various property types, damage conditions, and geographic regions by incorporating local cost data and conditions into a single automated workflow, eliminating the need for separate manual assessment processes for different scenarios.
4Measurement precision
If inspectors work in remote or hazardous locations, then on-site data can be collected, but safety risks increase
Solution Approach 1:
The patent introduces UAVs as intermediaries between inspectors and hazardous locations. The UAVs fly into dangerous or remote areas to collect data, acting as a mediator that eliminates the need for human inspectors to physically enter unsafe environments. The system maintains on-site data quality by capturing high-resolution images and sensor data directly from the location through the UAV's onboard cameras and sensors.
Data Source
AI summary
Methods, computer-readable media, software, and apparatuses may receive, at a field vehicle, field data from one or more unmanned autonomous vehicles, where the field data may be indicative of an item for assessment. Edge-computing, based on machine learning techniques, may be performed at the field vehicle to identify one or more characteristics of the assessment, and a projected cost may be determined. An estimate may be sent to a consumer. In some aspects, the projected costs may be based on local data related to a geographical location of the item. In another aspect, underwriting tasks may be performed at the field vehicle, and a quote may be sent to a consumer.