Electronic Shelf Label Guidance for Camera-Verified Planograms
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Solution Overview
Problem
Existing electronic shelf label systems lack efficient methods for guiding stock associates in rearranging products on shelves to align with planograms, considering real-time inventory changes and labor costs, leading to suboptimal product placement and increased operational time.
Innovation Solution
An electronic shelf label system with a display screen, input mechanism, camera, and optimization module that generates step-by-step instructions and graphical depictions to guide associates in rearranging products based on planograms, using real-time feedback and minimizing labor and time required for restocking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual product arrangement methods are used, then associates have flexibility in restocking, but product placement does not align with optimal planograms and operational time increases
Solution Approach 1:
The system uses cameras to capture images of products on shelves and compares them with planogram data, providing real-time feedback to associates about correct product placement. This feedback loop enables associates to adjust their restocking actions to achieve precise alignment with planograms while maintaining operational efficiency
Solution Approach 2:
The patent replaces manual visual inspection and physical arrangement methods with an automated image recognition system that uses computer vision algorithms to detect product positions and verify planogram compliance, thereby improving placement accuracy without increasing operational time
2Productivity
If frequent planogram updates are implemented, then product placement optimality improves, but system complexity and update time increase
Solution Approach 1:
The system pre-processes and stores planogram data in a standardized format before it is needed for restocking operations. This preliminary preparation allows for rapid updates and deployment of new planograms without increasing system complexity during actual restocking operations
Solution Approach 2:
The planogram system is divided into modular components including planogram definition modules, data storage modules, and comparison modules. This segmentation allows individual components to be updated independently, reducing overall system complexity while enabling frequent planogram updates
3Manufacturing precision
If real-time camera monitoring is used, then product placement accuracy is verified, but energy consumption and operational time increase
Solution Approach 1:
Instead of continuous monitoring, the system uses periodic camera captures at key moments during restocking operations. This periodic action maintains verification accuracy while significantly reducing energy consumption compared to continuous monitoring
Solution Approach 2:
The image recognition system is integrated into the existing shelf label infrastructure, allowing the system to verify product placement using already-deployed hardware resources. This self-service approach minimizes additional energy consumption while maintaining verification capabilities
Data Source
AI summary
An electronic shelf label (ESL) system is discussed. An ESL affixed to a shelf facing assists stock associates in managing products on the shelf. More particularly, the ESL may receive and display step-by-step instructions and/or graphical depictions on a display screen of the ESL that are received from a computing device-executed optimization module. The instructions may be generated to minimize the number of required actions by the stock associate and guide the associate in arranging products on the shelf. The displayed instructions may be determined based on a planogram. The planogram may be generated from a range of criteria including historical profit and loss data, inventory data, supply and demand data and/or labor cost data.