UE Grouping System Using Relational Data and Multi-Mode Communication
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Solution Overview
Problem
Existing social network services fail to accurately reflect real-world social relations and physical distances among users, limiting their ability to enhance real-world activities and online interactions.
Innovation Solution
A grouping method and system that transmits relational data from User Equipment (UE) to a server using multiple communication modes, prioritizing connections based on proximity, and generates groups based on real-world social relations and physical distances, allowing for the creation of new groups and web page access for content sharing and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple communication modes are used for device connection, then communication reliability is improved, but device complexity increases
Solution Approach 1:
The system dynamically switches between different communication modes (first communication mode for normal operation, second communication mode for fallback) based on connection status. This dynamic adaptation allows the system to maintain communication reliability while managing device complexity through conditional logic rather than permanent multi-mode infrastructure.
Solution Approach 2:
The system changes communication parameters by switching between different communication modes. When the first communication mode becomes unusable, the system transitions to the second communication mode, effectively changing the communication parameters to maintain connectivity. This parameter switching resolves the contradiction by adapting to different operational conditions.
2Measurement precision
If groups are generated based on both physical distance and social relations, then measurement precision of user relationships is improved, but device complexity increases
Solution Approach 1:
The system segments user relationship data into distinct categories: physical distance information and social relation data. By separating these data types and processing them independently before combining them for group generation, the system achieves precise measurement of user relationships while managing device complexity through modular data handling.
Solution Approach 2:
The server performs multiple functions: it receives and processes both physical distance data and social relation data, generates groups based on combined analysis, and manages communication between devices. This multi-functionality at the server level allows precise relationship measurement without increasing individual device complexity.
Data Source
AI summary
A grouping method of User Equipment (UE) is provided. The grouping method includes transmitting, to a server, relational data stored in the UE using a first communication mode, and receiving, from the server, generated group information based on relational data of a plurality of UEs, wherein, in response to the first communication mode being unusable, communication is performed using a second communication mode.