Shelf Sensor Triggering Camera for Product Recognition
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Solution Overview
Problem
Current shelf monitoring systems either accurately count products or identify them, but not both, due to integration and cost issues when combining counting and recognition systems.
Innovation Solution
An apparatus and method that integrates sensors and cameras on shelves to detect thresholds, triggering image capture and product identification, enabling both counting and recognition, with a server for accurate inventory management and planogram generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If smart shelves based on resistive, capacitive, or light sensors are used to count products and track positions, then counting accuracy is improved, but object identification capability deteriorates
Solution Approach 1:
The patent combines sensor-based counting systems with image capture systems into a unified shelf monitoring apparatus. The sensor system counts products and tracks positions while the image capture system identifies products, merging the advantages of both approaches to achieve both accurate counting and object identification simultaneously.
Solution Approach 2:
The shelf monitoring system is designed with multi-functionality to perform both counting and object identification tasks. The apparatus includes sensors for counting, image capture devices for identification, and a processor that handles both counting data and image analysis, making the system universal for comprehensive shelf monitoring.
2Difficulty of detecting and measuring
If shelf monitoring robots and fixed cross-aisle cameras are used to capture images for product identification, then object recognition is improved, but counting accuracy deteriorates
Solution Approach 1:
The system segments the shelf monitoring function into distinct modules: sensor-based counting for quantitative data and image capture for qualitative identification. This segmentation allows each module to specialize in its strength while the integrated processor combines results for comprehensive monitoring.
Solution Approach 2:
The patent merges image capture systems with sensor-based counting systems to create a complementary monitoring approach. The image capture system provides product identification while the sensor system provides accurate counting, and their results are integrated to overcome the limitations of either system alone.
3Adaptability or versatility
If both counting systems and object recognition systems are deployed together, then complete shelf arrangement is improved, but system complexity and cost increase
Solution Approach 1:
The shelf monitoring apparatus is designed as a universal system that performs both counting and object recognition functions through integrated hardware and software. The processor handles both counting data processing and image analysis, reducing the need for separate independent systems.
Solution Approach 2:
The processor acts as an intermediary that receives data from both the sensor system and image capture system, processes and integrates this information to generate complete shelf arrangement data. This intermediary approach simplifies the overall system architecture by centralizing data processing.
4Difficulty of detecting and measuring
If continuous image capture is performed for product identification, then recognition accuracy is improved, but energy consumption and unnecessary captures increase
Solution Approach 1:
The sensor system performs preliminary detection to identify when changes occur on the shelf, such as products being added or removed. This preliminary action triggers the image capture system only when necessary, avoiding continuous capturing and reducing energy consumption while maintaining recognition accuracy.
Solution Approach 2:
The system uses feedback from the sensor system to control the image capture system. When sensors detect changes in shelf conditions, they trigger image capture to update product identification. This feedback mechanism ensures images are captured only when needed, optimizing energy usage.
Data Source
AI summary
Systems and methods for triggering object recognition and planogram generation via shelf sensors are disclosed herein. An example apparatus may comprise a shelf, at least one sensor affixed to the shelf, at least one camera affixed to the shelf, and at least one server communicatively coupled to the at least one camera and the at least one sensor. The apparatus may be configured such that the at least one sensor is configured to detect that at least one threshold has been met, and the at least one sensor is further configured to trigger an image to be taken by the least one camera; wherein the at least one camera is configured to capture at least one image based on the met threshold, and the at least one server is configured to identify at least one product identifier based on the at least one captured image.