AR Item Filtering for Real-Time Shopping Selection
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Solution Overview
Problem
Consumers face inefficiencies and frustration when selecting items due to large item selections and lack of information about new or unfamiliar items, making it difficult to locate desired or suitable substitutes.
Innovation Solution
An augmented reality system that uses a customized AR filter component to generate an AR display overlaying real-world images with positive and negative item indicators, highlighting high-interest items and obscuring low-interest items, and displaying un-stocked items available elsewhere, based on user preferences and location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If consumers browse items on shelves reading labels to locate desired items, then they can identify item details and make informed selections, but the process becomes time-consuming and inefficient due to the large number of items and varieties on shelves
Solution Approach 1:
The patent replaces the mechanical manual browsing and label-reading process with an automated optical recognition system. Sensors capture images of items on shelves, and image recognition algorithms automatically identify and extract item information, substituting human visual inspection with machine vision technology to reduce selection time while maintaining identification accuracy.
Solution Approach 2:
The system creates digital copies of item information through image capture and recognition. Instead of consumers directly examining physical labels, the system generates digital representations of item data including text, images, and specifications, which can be processed and displayed efficiently to help consumers make quick informed decisions.
2Loss of information
If consumers rely on physical item displays in the store, then they can see available items, but they cannot identify new or unfamiliar items without additional information, and cannot access items not physically present
Solution Approach 1:
The patent introduces an intermediary information system that bridges physical items and consumer knowledge. The system captures images of items, recognizes them through AI algorithms, and retrieves comprehensive information from databases including product specifications, reviews, and availability. This intermediary layer provides consumers with detailed information about new or unfamiliar items without requiring physical examination.
Solution Approach 2:
The system adds a digital information dimension to the physical shopping experience. By overlaying digital images, text descriptions, and availability status onto or alongside physical item displays, consumers gain access to multiple dimensions of item information simultaneously, enabling them to identify and select items beyond what is immediately visible or familiar.
3Adaptability or versatility
If the store maintains a large selection of items across multiple categories and brands, then consumers have more options to choose from, but consumers become overwhelmed and frustrated by the sheer number of items to browse
Solution Approach 1:
The patent applies segmentation by dividing the large item selection into manageable groups based on consumer preferences, purchase history, and item characteristics. The system segments items into relevant categories and prioritizes displays, presenting only the most relevant items to each consumer rather than overwhelming them with the complete inventory. This segmentation maintains variety while improving navigability.
Solution Approach 2:
The system applies local quality by customizing the information display and item prioritization for each consumer's specific needs and context. Different consumers receive different levels and types of information based on their preferences, shopping goals, and past behavior. Items are highlighted or emphasized locally based on their relevance to individual consumers, making the large selection feel personalized and manageable rather than uniform and overwhelming.
Data Source
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AI summary
Examples provide customized augmented reality item filtering. An item filter analyzes item data using selection criteria and user preferences to identify highinterest item(s) and/or low-interest item(s) within a field of view (FOV) of a user device associated with a user. A high-interest item may include an item physically present within a portion of an item selection area or an un-stocked item not physically present within the portion of the item selection area. An augmented reality (AR) generator creates an AR image including a real-world image of the portion of the item selection area overlaid with graphical elements, including positive item indicators associated with high-interest items, negative item indicators associated with low interest items, and/or un-stocked virtual items. The AR image is updated in real-time in response to user input, promotional data associated with one or more filtered item(s), and/or changes associated with the items within the FOV of the user device.