Computer Vision Proof of Work Verification
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Solution Overview
Problem
Current methods for verifying proof of work, such as time on site, are inaccurate, leading to over or under compensation of employees, wasting resources and failing to provide proper incentives for efficient work.
Innovation Solution
A compliance platform using computer vision and machine learning to process image data from wearable devices to identify verifiable content, determining the likelihood of an individual being in a work environment and calculating verifiable hours worked, thereby correcting wage payments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional time on site methods are used to verify proof of work, then the verification process is simple to implement, but the accuracy of hours worked determination is poor leading to over or under compensation
Solution Approach 1:
The patent replaces manual time tracking methods with automated computer vision and machine learning systems. Image capture devices and processing algorithms automatically verify work completion, substituting human judgment and simple time clocks with intelligent automated systems that analyze visual evidence of work performed.
Solution Approach 2:
The patent introduces an intermediary verification system that processes image data between the worker and the compensation determination. This intermediary layer captures, analyzes, and validates work evidence through content recognition techniques, providing an objective bridge that improves measurement accuracy while maintaining systematic control.
2Reliability
If automated image processing is used to verify proof of work, then the accuracy of work verification is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by capturing images at scheduled intervals during work periods and pre-processing this data. By having image data ready and pre-analyzed before final verification is needed, the system reduces real-time processing requirements and enables faster reliability checks when compensation determination is required.
Solution Approach 2:
The patent uses partial action by selecting specific keyframes or representative images from captured data for detailed analysis, rather than processing every single image frame. This selective approach maintains high reliability in verification while significantly reducing the computational burden and processing time required.
Data Source
AI summary
A device receives image data associated with an environment of an individual and identifies verifiable content by processing the image data. The device processes the verifiable content to determine a likelihood that the individual is an employee or agent of an organization and to determine a set of likelihoods of the environment being a work environment. The device determines, based on the likelihood and the set of likelihoods, a number of verifiable hours worked by the individual during a given time period. The device identifies wages data that specifies a number of hours worked that has been credited to the individual for the given time period, determines that an amount of wages paid to the individual is an incorrect amount of wages, and provides an alert to another device that indicates that the amount of wages paid to the individual is the incorrect amount of wages.