Proximity-based navigational mode transitioning
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Solution Overview
Problem
Current methods for monitoring product placement in retail stores are inefficient and lack continuous monitoring capabilities, leading to nonuniform compliance with product-related guidelines due to reliance on manual checks that do not account for dynamic changes in displays.
Innovation Solution
The implementation of systems and methods that utilize image processing and sensors to capture, analyze, and compare actual product placement with desired placement, triggering alerts for disparities and enabling automated monitoring of retail spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual monitoring methods are used to check product placement, then device complexity is reduced, but productivity and measurement precision deteriorate due to inefficiency and inability to detect dynamic changes
Solution Approach 1:
The patent replaces manual mechanical monitoring with an automated image processing system using cameras and computer vision algorithms. The system captures images of product shelves, automatically identifies product placements, and compares them against desired configurations, eliminating the need for manual inspection while significantly improving monitoring efficiency and productivity.
Solution Approach 2:
The system enables self-service monitoring by automatically capturing images, processing visual data, identifying products, and generating compliance reports without human intervention. The automated nature of the system allows continuous monitoring of product placements, detecting dynamic changes in real-time and improving productivity while maintaining simplicity through automation.
2Measurement precision
If continuous automated monitoring is implemented, then measurement precision and reliability improve, but device complexity and cost increase
Solution Approach 1:
The patent employs image processing technology and computer vision algorithms to replace manual measurement methods. The system uses cameras to capture high-resolution images of product shelves, applies image processing techniques to identify product placements with high precision, and automatically compares them against desired configurations, achieving superior measurement accuracy while maintaining manageable system complexity through software-based solutions.
Solution Approach 2:
The system introduces an intermediary layer of image processing and pattern recognition algorithms between the physical product placement and the monitoring function. This intermediary processing layer enables precise detection of product placements by analyzing visual patterns, colors, shapes, and positions in captured images, improving measurement precision while keeping the overall system architecture relatively simple and modular.
3Loss of time
If manual monitoring is used, then ease of operation is maintained, but loss of time and productivity increase due to non-uniform compliance monitoring
Solution Approach 1:
The patent implements continuous automated monitoring that operates without interruption, continuously capturing images, analyzing product placements, and detecting compliance issues in real-time. This continuous operation eliminates the time loss associated with periodic manual checks and enables immediate detection of placement discrepancies, significantly reducing monitoring time while the automated nature handles the complexity, maintaining ease of operation through minimal human intervention required.
Solution Approach 2:
The system incorporates feedback mechanisms that automatically compare detected product placements against desired configurations and provide real-time alerts or reports when discrepancies are found. This automated feedback loop eliminates the time loss of manual re-checking and ensures consistent compliance monitoring, reducing overall monitoring time while the systematic feedback process manages operational complexity.
Data Source
AI summary
A non-transitory computer-readable medium includes instructions that when executed by a processor cause the processor to perform a method for providing visual navigation assistance in retail stores, which may include receiving a first indoor location of a user within a retail store; receiving a target destination; and providing first navigation data to the user through a first visual interface. The method may also include, after providing the first navigation data, receiving a second indoor location of the user within the retail store; determining that the second indoor location is within a selected area around the target destination, with the selected area not including the first indoor location; and, in response to the determination that the second indoor location is within the selected area around the target destination, providing second navigation data to the user through a second visual interface, where the second visual interface differs from the first visual interface.