RFID Tag Grouping for User Behavior Pattern Generation
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Solution Overview
Problem
Current RFID systems lack the capability to generate and utilize behavior patterns based on user belongings with attached RFID tags to provide relevant information to users, limiting their application in enhancing user experiences.
Innovation Solution
An apparatus and method that identify and group RFID tags attached to user belongings, collect behavior information, and generate patterns to store and provide related information to user devices, enabling personalized insights and notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If RFID tags are attached to user belongings to track behavior, then user behavior patterns can be generated and personalized information can be provided, but the system complexity increases due to the need to identify, group, and analyze multiple RFID tags and their associated behavior information
Solution Approach 1:
The system segments the overall behavior analysis task into distinct components: RFID tag identification, behavior information collection, pattern generation, and information provision. This modular segmentation allows each component to be processed independently, reducing system complexity while enabling personalized information delivery based on aggregated behavior patterns.
2Measurement precision
If behavior information is collected and analyzed from multiple RFID tags, then accurate behavior patterns can be generated, but the time required for data collection and processing increases
Solution Approach 1:
The system performs preliminary actions by pre-identifying and grouping RFID tags before behavior information collection. This preliminary organization of tags allows for more efficient subsequent processing of behavior information, as the system already has a structured framework for analyzing the data, thereby reducing overall processing time while maintaining accurate behavior pattern generation.
Data Source
AI summary
A method for generating a behavior pattern based on information from radio frequency identification tags is disclosed. The method includes identifying a plurality of radio frequency identification tags, generating a radio frequency identification group that corresponds to the plurality of radio frequency identification tags, receiving behavior information that corresponds to the radio frequency identification group from a user device, matching the radio frequency identification group with the behavior information, generating a behavior pattern corresponding to the matched radio frequency identification group and the behavior information, and storing the behavior pattern in a database.