AR Product Overlay System for Weighted Social and Environmental Evaluation
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Solution Overview
Problem
Current systems do not effectively enable users to consider social and environmental factors when making product purchase decisions, lacking a straightforward and quick method to incorporate these important factors into their evaluations.
Innovation Solution
A computer-implemented system and method that creates user profiles with weighted purchasing decision factors, retrieves product profiles based on user-input product identifiers, and evaluates products in real-time, providing display data that overlays relevant information on the product, allowing users to make informed decisions based on social and environmental considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional product evaluation methods are used, then the purchase decision process is simple, but users cannot effectively consider social and environmental factors
Solution Approach 1:
The system segments the product evaluation into multiple independent factors including social factors, environmental factors, and traditional factors. Each factor is weighted separately based on user preferences, allowing comprehensive evaluation without overwhelming complexity. The AR interface further segments information display into overlay layers that present different factors independently.
Solution Approach 2:
The patent creates a universal evaluation framework that can assess any product across multiple dimensions (social, environmental, traditional factors). The system multi-functionalizes by combining product information retrieval, factor analysis, weighting calculations, and AR visualization into a single integrated platform that adapts to various product types and user preferences.
2Measurement precision
If comprehensive product factor analysis is performed, then better-informed decisions are enabled, but the evaluation process becomes time-consuming
Solution Approach 1:
The system performs preliminary actions by pre-collecting and organizing product information and factors before the user makes a purchase decision. Product profiles are pre-analyzed for relevant social and environmental factors, and user preferences are pre-weighted, so that when evaluation is needed, the system can quickly retrieve and process pre-prepared data rather than gathering everything from scratch.
Solution Approach 2:
The patent replaces manual information gathering and analysis with an automated computer-based system that retrieves product data, analyzes factors, calculates weighted scores, and generates evaluations automatically. This substitution of mechanical human analysis with automated computational processes dramatically reduces evaluation time while maintaining or improving precision.
3Productivity
If real-time product evaluation is provided, then quick decision-making is enabled, but system computational requirements increase
Solution Approach 1:
The system extracts only the most relevant product factors and evaluation data needed for the user's specific decision context, rather than processing all possible product information. By identifying and extracting key social, environmental, and traditional factors based on user preferences, the system reduces computational load while maintaining evaluation quality and enabling real-time results.
Data Source
AI summary
A computer-implemented system and method are provided for obtaining and providing product information to a user. The method comprises creating, with a processor of a purchase evaluation system, a user profile comprising a plurality of purchasing decision factors with each having a respective weight. The method further comprises receiving a product identifier that identifies a product being considered for purchase by a user, and then building or retrieving, in real-time, a product profile based on the product identifier that contains a plurality of product factors corresponding to the purchasing decision factors, each of which contain a value representing a score of the product's relationship to the respective product factor. The method then evaluates the product based on a function that incorporates the purchasing decision factors and the product factors, and creates display data for displaying the identified product and the product evaluation on a display.


