Automated Property Surveying with Unmanned Vehicles
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Solution Overview
Problem
Property surveying is a costly, labor-intensive, and time-consuming process prone to human errors, which can have significant consequences for land usage, and there is a need for improved methods and systems for processing and categorization of media assets based on location.
Innovation Solution
The use of unmanned vehicles equipped with sensors to capture digital media assets, such as images, videos, and environmental data, which are automatically categorized and stored based on location, device type, and subject matter, allowing for efficient tracking and analysis of property features and defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional property surveying methods are used, then human operators can perform detailed analysis and decision-making, but the process becomes costly, labor-intensive, and time-consuming with higher risk of human error
Solution Approach 1:
The system enables autonomous operation where the unmanned vehicle automatically captures media assets, tracks its own location via positioning receiver, and the computing device automatically generates location-based categories without human intervention. This self-service approach eliminates human error while maintaining high accuracy through automated processing.
Solution Approach 2:
The patent replaces manual mechanical surveying operations with an automated system comprising unmanned vehicles, sensors, positioning receivers, and computing devices. This substitution of mechanical human labor with automated technological systems resolves the contradiction by providing both high reliability through consistent automated processing and high productivity through parallel operation capabilities.
2Loss of information
If manual processing and categorization of media assets is performed, then detailed human judgment can be applied, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The computing device automatically generates location-based categories by processing location data from positioning receivers and media assets from multiple unmanned vehicles. This automated computational process replaces manual categorization, eliminating time loss while maintaining accuracy through systematic algorithmic processing that consistently applies categorization criteria without human fatigue or error.
Solution Approach 2:
The system enables continuous automated processing where the computing device constantly receives location data and media assets from unmanned vehicles and continuously generates and updates location-based categories. This continuous automated action eliminates the intermittent nature of manual processing, reducing time loss while maintaining high categorization accuracy through uninterrupted systematic processing.
3Loss of information
If comprehensive media assets are captured from multiple locations, then complete property documentation is achieved, but the complexity of processing and organizing the data increases
Solution Approach 1:
The computing device automatically generates location-based categories that segment the comprehensive property data into organized groups based on geographic locations. This segmentation principle divides the large volume of media assets from multiple unmanned vehicles into manageable location-based subsets, reducing processing complexity while maintaining complete property documentation through systematic organization.
Solution Approach 2:
The computing device performs multiple functions simultaneously: it receives location data from positioning receivers, processes media assets from multiple unmanned vehicles, generates location-based categories, and organizes comprehensive property documentation. This multi-functionality reduces overall system complexity by consolidating diverse processing tasks into a single integrated system rather than requiring separate specialized systems for each function.
Data Source
AI summary
Digital media assets depicting or otherwise representing portions of a property are captured via a media capture device, such as an unmanned vehicle, at various locations about a property. A positioning receiver tracks the location of the media capture device when each digital media asset is captured. A computing device associated with either the media capture device itself or a network-connected server automatically generates location-based categories—such as “front side” or “rear side” or “living room”—automatically based on the plurality of locations so that each location-based category is associated with multiple digital media assets and their corresponding locations.