AR Task Compliance Detection via Machine Learning Object Processing

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Solution Overview

Problem

Existing augmented reality systems rely on users formulating correct queries to receive relevant information, leading to inefficiencies and potential frustration due to the presentation of irrelevant information.

Innovation Solution

A computer system utilizing a machine learning-based object processing scheme to determine the compliance of a predefined task by identifying a first object and a second object involved in the task, and assessing the state of the first object based on user manipulation using the second object.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If a user formulates a query to obtain information in an augmented reality system, then the user can receive relevant information displayed in the field of view, but the user may spend excessive time browsing irrelevant information or formulating incorrect queries

Engineering Contradiction:

Improverelevance of informationVSAvoidtime to formulate query and browse information

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system automatically determines the user's task compliance by analyzing images of objects and actions captured by the augmented reality device, without requiring the user to manually query or search for information. The system serves itself by autonomously processing visual data and providing compliance feedback.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system provides automatic feedback to the user about task compliance by comparing the determined state of objects with expected task outcomes. This feedback loop allows the user to adjust their actions in real-time without needing to search for guidance information.

Inventive Principle:

Principle #23Feedback

2Productivity

If the system automatically determines task compliance using machine learning, then the user receives immediate feedback without manual querying, but the system complexity increases due to machine learning processing requirements

Engineering Contradiction:

Improvetask completion efficiencyVSAvoidmachine learning processing capability

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system replaces manual information querying and analysis with automated machine learning-based image processing. The machine learning model automatically identifies objects, determines their states, and assesses task compliance without requiring manual intervention or complex user queries.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The machine learning model acts as an intermediary between the captured images and the compliance determination. It processes the visual data and translates it into meaningful task compliance assessments, bridging the gap between raw image data and actionable feedback.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12322082B2Method and system for compliance determination

Publication Date: 2025.06.03 WIRETRONIC AB

AI summary

The present disclosure generally relates to a computer system adapted to determine how well user manipulation of a first object using a second object is complying with a predefined task to be performed in relation to the first object. This in line with the present disclosure achieved by applying a machine learning based object processing scheme to determine a state of the first object when the user has manipulated the first object using a second object, and compare this state with data defining processing steps to be performed for completing the predefined task. The present disclosure also relates to a corresponding computer implemented method and a computer program product.