Retail Loss Prevention via Visual Code and RFID Cross-Validation
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Solution Overview
Problem
Retail environments face significant losses due to shoplifting, mispricing, and employee collusion, where customers or employees manipulate prices by swapping tags or concealing items, leading to revenue loss and difficulty in detecting discrepancies at the point of sale.
Innovation Solution
Implementing a system that combines visual code identifiers, RFID tags, and image analytics using neural networks to detect and compare merchandise information, transmitting alerts when discrepancies are found between scanned and imaged items, ensuring accurate pricing and preventing losses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional point-of-sale scanning systems are used, then transaction speed is maintained, but merchandise discrepancy detection capability is insufficient
Solution Approach 1:
The patent combines multiple identification technologies (visual code scanning, RFID reading, and image recognition) into a unified loss prevention system. The system merges data from these different sources and compares them against each other to detect discrepancies, thereby improving detection precision while managing complexity through integration rather than separate systems
Solution Approach 2:
The patent introduces an intermediary comparison mechanism that acts as a mediator between the different identification methods. This intermediary system cross-references visual code data, RFID data, and image-recognized merchandise to detect discrepancies, enabling accurate detection without requiring complete system redesign
2Measurement precision
If multiple identification methods (visual code, RFID, image recognition) are combined, then merchandise detection accuracy is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary action by capturing images and reading RFID tags simultaneously with or before visual code scanning occurs. This parallel data collection approach ensures that all identification methods are executed concurrently rather than sequentially, improving accuracy without significantly increasing processing time
Solution Approach 2:
The system maintains continuity of useful action by processing multiple identification data streams in parallel and continuously comparing them. The real-time comparison mechanism ensures that discrepancy detection occurs without interruption to the transaction flow, maintaining processing efficiency while improving detection accuracy
3Reliability
If real-time discrepancy detection and alerting is implemented, then loss prevention effectiveness is improved, but system complexity increases
Solution Approach 1:
The patent implements feedback mechanisms by continuously monitoring comparison results from multiple identification methods and providing real-time alerts when discrepancies are detected. This feedback loop enables immediate response to potential loss events, improving loss prevention effectiveness while managing complexity through automated alerting rather than manual monitoring
Solution Approach 2:
The system performs self-service by automatically comparing data from different identification methods and generating alerts without requiring manual intervention. The automated discrepancy detection and alerting mechanism reduces the need for additional personnel or complex manual monitoring systems, improving reliability while keeping system complexity manageable
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively reduces revenue loss by accurately identifying merchandise and pricing discrepancies in real-time, enabling timely alerts to store personnel, thereby enhancing loss prevention and security.
Implementation Method 1
a RFID reader 112 that reads the content of the RFID tag 104
Implementation Method 2
A visual code scanner 106 scans a visual code 108
Data Source
AI summary
Aspects of the present disclosure include methods, systems, and non-transitory computer readable media that perform the steps of receiving a visual code identifier associated with a transaction of one or more transaction merchandises, receiving a radio frequency identification (RFID) identifier associated with the transaction, analyzing the image, determining at least one of one or more detected merchandises, a number of the one or more detected merchandises, and a price of the one or more detected merchandises based on information in the RFID identifier and the analyzed image, determining a merchandise discrepancy, a number discrepancy, or a price discrepancy, and transmitting, in response to determining the at least one of the merchandise discrepancy, the number discrepancy, or the price discrepancy, an alert.