Virtual Shelf Verification Using Aisle Video and AI Comparison
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Solution Overview
Problem
There is a lack of digital/virtual product placement verification systems that can remotely provide services similar to in-person product placement verification, which is essential for online shopping and delivery services.
Innovation Solution
A product placement verification system utilizing a server, user computing devices, and business computing devices to remotely capture and analyze product placement through image/video data, generate reports, and provide compensation to users for their contributions, leveraging gig economy practices and AI for image comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in-person product placement verification is used, then accurate product placement data can be obtained, but travel time and operational costs increase
Solution Approach 1:
The patent uses digital copies (photos and videos) of product placement taken by users at stores to replace physical in-person verification. The system captures images of products on shelves and uses AI image recognition to verify placement accuracy, eliminating the need for verification personnel to travel to each store while maintaining verification accuracy through digital documentation.
Solution Approach 2:
The patent replaces the mechanical system of physical travel and manual verification with an automated digital system. Users capture images using their devices, and AI-based image recognition algorithms automatically analyze the photos to verify product placement, substituting physical presence with computational analysis.
2Measurement precision
If in-person product placement verification is used, then accurate product placement data can be obtained, but operational costs increase
Solution Approach 1:
The system uses digital copies of product placement (photos and videos) submitted by users to replace expensive in-person verification services. The AI image recognition system processes these digital submissions to verify placement accuracy, dramatically reducing operational costs while maintaining verification quality.
Solution Approach 2:
The patent implements a self-service model where users (shoppers or employees) capture product placement images themselves during their regular activities. This eliminates the need for dedicated verification personnel to travel to stores, as the verification data is collected automatically by the user community as part of their normal shopping or work routines.
3Loss of time
If remote digital verification system is implemented, then travel time and costs are reduced, but system complexity increases
Solution Approach 1:
The patent introduces a centralized server as an intermediary that coordinates the entire verification process. The server manages user registrations, distributes verification tasks, receives and stores submitted images, and triggers AI analysis. This centralized intermediary simplifies the overall system architecture by providing a single point of control despite the distributed nature of image collection across multiple users and locations.
Solution Approach 2:
The patent replaces complex manual coordination of in-person verification with automated digital processes. The system uses electronic communications, database storage, and AI image recognition algorithms to handle what would otherwise require complex human logistics coordination, thereby reducing system complexity despite the remote verification model.
4Productivity
If AI image recognition is used for verification, then verification speed increases, but measurement precision may be affected
Solution Approach 1:
The patent implements a feedback mechanism where the AI image recognition system analyzes submitted photos and provides verification results back to the platform. The system can identify whether products are correctly placed according to specified parameters (such as shelf position, orientation, and visibility), and this feedback loop ensures that verification accuracy is maintained while enabling rapid processing of multiple images.
Data Source
AI summary
Described is a product placement verification system. The system includes a server having a memory storing store information, including at least one shelving video or photography of travel up and down aisles of a store recorded by a camera system. The system also includes a user computing device coupled to the server. The system allows a user to virtually navigate aisles in a store through the user computing device accessing the system and the stored shelving video or photography. The user may select items and the system determine location of the selected item within the store, including shelf height and slot width. The server may be programmed to provide a product placement report to the user computing device.