Shopper Intent Analysis via Acceleration and Image Data Fusion
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Solution Overview
Problem
Retail stores face challenges in accurately tracking shopper interest in products, especially in environments with complex or numerous products, as existing methods lack the ability to effectively combine physical movement data from acceleration sensors with visual data from image capture devices to determine shopper intentions.
Innovation Solution
A computer-implemented method that receives acceleration information from sensors attached to products and combines it with images from image capture devices to determine shopper movements, using machine learning models to analyze skeletal structures and suggest actions based on the data, thereby improving real-time shopper service and product placement strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acceleration sensors and image capture devices are used to track shopper movements, then the ability to determine shopper interest and product comparison is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent combines acceleration sensors attached to products with image capture devices positioned in the store. The acceleration sensors detect product movements while the image capture devices record shopper movements and behaviors. By merging these two data sources, the system achieves comprehensive tracking of both product and shopper interactions, enabling accurate determination of shopper interest and product comparisons without requiring complex individual sensor systems.
2Reliability
If multiple sensors and image capture devices are deployed throughout the store, then the coverage and data quality for analyzing shopper behavior is improved, but the cost and complexity of the system increases
Solution Approach 1:
The image capture devices serve multiple functions: they capture images of shoppers, track shopper movements, identify products of interest, and detect shopper behaviors such as picking up and comparing products. This multi-functionality reduces the need for separate specialized sensors for each task, thereby improving reliability of shopper behavior tracking while limiting the increase in system complexity and cost.
3Productivity
If real-time analysis of acceleration and image data is performed, then the ability to provide real-time shopper service and product recommendations is improved, but the processing time and computational resources increase
Solution Approach 1:
The system continuously collects and pre-processes acceleration data from sensors and image data from capture devices, organizing it into structured formats ready for analysis. By performing preliminary data organization and filtering before actual shopper behavior analysis, the system enables faster real-time processing when shopper interactions occur, reducing the computational time required for immediate service responses while maintaining high productivity.
Data Source
AI summary
A method includes receiving, by a computing device, acceleration information from an acceleration sensor attached to a product; receiving, by the computing device, from an image capture device an image of a prospective purchaser of the product; determining, by the computing device, a movement of the prospective purchaser based on the acceleration information and the image, the movement being in relation to a movement of the product; and sending, by the computing device, display information to a digital display, the display information including information related to the product. The movement of the product is based on the acceleration information.