GPS Data Image Asset Association Financial Application
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Solution Overview
Problem
Financial software applications face challenges in automatically associating images of assets with their corresponding assets, requiring manual upload and recognition, which is time-consuming and prone to errors.
Innovation Solution
A method and system that utilize GPS data from images captured with GPS-enabled devices to determine geographic locations, perform recognition analysis, and automatically associate objects in images with assets within financial applications, leveraging geotagging and computer processing to streamline this process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual upload and recognition methods are used to associate images with assets, then system complexity is reduced, but productivity and time efficiency deteriorate
Solution Approach 1:
The system performs preliminary actions by embedding GPS data in images at the time of capture, and pre-processing these images to extract geographic location information before the actual association task. This allows the recognition system to work with pre-prepared data, improving efficiency without proportionally increasing complexity
Solution Approach 2:
The patent introduces GPS data and geographic location information as intermediary elements between the image and the asset association process. These intermediaries enable automatic recognition by providing objective spatial references that can be processed computationally, bridging the gap between simple image upload and intelligent asset matching
2Extent of automation
If manual upload methods are used, then automation extent is reduced, but measurement precision requirements are lowered
Solution Approach 1:
The patent replaces manual mechanical operations (manual upload and association) with automated computational processes. GPS data extraction, geographic location determination, and image recognition are all performed automatically through software algorithms, eliminating manual intervention while maintaining precision through systematic processing
3Loss of time
If manual recognition is used to associate images with assets, then automation is reduced, but processing time increases
Solution Approach 1:
The system enables self-service by allowing images to automatically associate with assets through their embedded GPS data. The geographic location information in the image enables the system to autonomously perform recognition and matching without human intervention, making the process self-sufficient and dramatically reducing time consumption
Data Source
AI summary
The invention relates to a method for associating an object in an image with an asset of a number of assets in a financial application. The method includes receiving the image of the object comprising global positioning system (GPS) data, where the image is captured using an image-taking device with GPS functionality and processing the image to generate processed GPS data. The method further includes determining, using the processed GPS data, a geographic location of the object in the image, and identifying, using the geographic location, the object by performing a recognition analysis of the image. The method further includes associating, based on the recognition analysis, the object in the image with the asset of the assets of an owner in the financial application, and storing, in the financial application, the image of the object associated with the asset of the assets of the owner.