Visual Sensor System for Automated Virtual Transaction Compilation
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Solution Overview
Problem
Current retail environments face challenges in efficiently managing transactions and inventory due to the need for traditional checkout processes and lack of real-time data on customer interactions and inventory levels, which can lead to inefficiencies and increased operational costs.
Innovation Solution
Implementing a system with visual sensors networked to a controller that monitors interactions between customers and items, allowing for the compilation of virtual transactions in real-time, eliminating the need for checkout lanes and providing data on inventory, employee performance, and customer interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional checkout processes are used, then transaction accuracy is maintained, but operational efficiency decreases and operational costs increase
Solution Approach 1:
The system enables self-service shopping where customers automatically complete transactions by simply picking items and leaving. Visual sensors automatically detect item removal from shelves and compile virtual transactions without requiring customer action at checkout, eliminating the need for manual scanning and traditional checkout lanes.
Solution Approach 2:
The patent replaces mechanical checkout systems (manual scanning, cash handling, bagging) with an automated visual sensing system. Cameras and image processing algorithms automatically track items, identify customers, and process transactions, substituting physical checkout infrastructure with optical detection and computational processing.
2Loss of information
If visual sensors are deployed throughout the environment, then real-time monitoring capability is improved, but system complexity and implementation cost increase
Solution Approach 1:
The visual sensor system performs multiple functions simultaneously: it monitors customer behavior, tracks inventory levels, identifies products being removed, and processes transactions. This multi-functionality reduces the need for separate specialized systems for each task, simplifying the overall infrastructure despite the distributed sensor network.
Solution Approach 2:
The controller acts as an intermediary that receives data from multiple visual sensors, processes the information, and coordinates the response. This central processing unit simplifies the complexity by providing a single point of coordination rather than requiring direct peer-to-peer communication between numerous sensors and multiple system components.
3Ease of operation
If manual scanning and checkout lanes are eliminated, then customer convenience is improved, but transaction verification accuracy may worsen
Solution Approach 1:
The system continuously monitors customer actions through visual sensors and provides real-time feedback by updating virtual transactions. The controller tracks item removal, customer identification, and transaction compilation continuously, ensuring accuracy is maintained throughout the shopping process rather than only at the end at checkout.
Solution Approach 2:
The system performs preliminary verification by continuously tracking items as they are removed from shelves and associating them with customers in real-time. This ongoing verification process ensures transaction accuracy is established during shopping rather than relying solely on final checkout verification, maintaining reliability while enabling convenient leave-and-pay functionality.
Data Source
AI summary
A method, computer program product, and system are disclosed for compiling a virtual transaction for a person within an environment having a plurality of items. The method includes acquiring, using at least one visual sensor, first image information including a person. The method further includes identifying the at least one person from the first image information by classifying the person into a class. The method also includes acquiring second image information including the person and an item. The method further includes identifying a behavior of the person relative to the item, and updating, based on the identified behavior, the virtual transaction.