Retail Shelf Image Analysis Triggered by Infrared Engagement Sensing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Image analysis in retail environments is expensive and lacks sufficient detail and accuracy for efficient store management, particularly in large-scale settings.
Innovation Solution
Utilizing a combination of infrared and vibration sensors to analyze engagement with retail shelves, triggering image processing based on sensor data to determine inventory, facings data, and planogram compliance, and employing image analysis to assess shelf states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image analysis is performed continuously on all retail shelves, then detailed and accurate inventory information is obtained, but operational costs and processing time increase significantly
Solution Approach 1:
The system performs preliminary actions by continuously monitoring infrared sensor data to detect customer engagement with shelves before triggering image analysis. This preliminary detection allows the system to prepare for selective image processing only when relevant events occur, avoiding continuous expensive image analysis while maintaining accurate inventory tracking.
Solution Approach 2:
The patent replaces continuous mechanical image analysis with a sensor-driven triggering system using infrared sensors and vibration sensors. This substitution uses lower-cost, lower-power sensors to monitor shelf conditions and only activates the more expensive and computationally intensive image analysis system when actual customer interaction is detected, thereby improving operational efficiency while maintaining measurement precision.
2Measurement precision
If multiple types of sensors are deployed to monitor shelf engagement, then detection accuracy improves, but device complexity increases
Solution Approach 1:
The system merges multiple sensor types (infrared sensors for detecting body heat, vibration sensors for detecting shelf movement, and image sensors for visual confirmation) into a unified monitoring system. These sensors work together synergistically, where each sensor type compensates for the limitations of others, improving overall engagement detection accuracy while sharing common processing infrastructure to manage complexity.
Solution Approach 2:
The sensor system is designed with multi-functionality where the same sensor array serves multiple purposes: infrared sensors detect both customer presence and engagement, vibration sensors monitor both shelf interaction and product movement, and the system can adapt its analysis based on different sensor triggers. This universal design reduces overall system complexity by using a single versatile sensor platform rather than separate specialized systems.
Data Source
AI summary
A method for image processing based on image data analysis may include mounting on a first retail shelving unit a first housing comprising an image capture device that is directed to a second retail shelving unit. A second housing comprising a processor is also mounted on the first retail shelving unit at location spaced apart from the first housing. A data conduit is extended between the first housing and second housing, wherein images captured by the image capture device in the first housing are transmitted to the second housing. At least some of the captured images are then transmitted from the second housing to a remote server configured to determine planogram compliance relative to the second retail shelving unit.