Presence Information Value-Added Charging Analysis
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Solution Overview
Problem
Current systems charge for presence information based on data volume or number of messages, which does not reflect the user-experienced value, leading to non-service-based charging.
Innovation Solution
A method to analyze presence data from user terminals for modified presence information, identifying value-added updates and charging accordingly, allowing for differentiated billing based on user-experienced value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If presence information is charged based on transmitted data volume or number of messages, then charging implementation is simple, but the charging does not reflect user experienced value
Solution Approach 1:
The presence information is segmented into different types (status updates, value-added information, etc.), and charging is applied differently to each type. This allows the system to move from a single undifferentiated charging model to a multi-tiered model that reflects actual user value while maintaining implementation feasibility through clear categorization rules.
Solution Approach 2:
The charging parameters are changed from simple metrics (data volume, message count) to composite metrics that include information type, user engagement level, and service value. This transformation enables more precise measurement of user experienced value while still using quantifiable parameters that can be implemented in existing charging systems.
2Quantity of substance
If all presence status updates are tracked and charged uniformly, then charging coverage is complete, but it fails to differentiate between value-added and standard presence information
Solution Approach 1:
Different charging rates and policies are applied to different types of presence information based on their local characteristics. Standard status updates (online/offline) receive one charging treatment, while value-added information (detailed status, custom messages, multimedia) receives different treatment. This local differentiation maintains comprehensive coverage while adapting to the specific value of each information type.
Solution Approach 2:
The charging system becomes dynamic by adjusting rates based on the type and value of presence information being transmitted. Rather than a static uniform rate, the system adapts charging parameters in real-time based on information classification, allowing both complete coverage and differentiated pricing to coexist.
3Measurement precision
If presence information charging is based on detailed analysis of modification types, then user experienced value is reflected accurately, but system complexity increases
Solution Approach 1:
The system performs preliminary classification of presence information into predefined categories before charging is applied. By establishing clear classification rules in advance (e.g., status updates vs. value-added information), the system reduces the complexity of real-time analysis while still achieving accurate value-based charging through pre-categorized information types.
Data Source
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AI summary
The present solution relates to a method for providing an enhanced communication service in a communications system (S). In the method, if it is detected in a network apparatus (PS1, IPX proxy, PS2) that presence data received from a user terminal (UE1) comprises modified presence information related to the user terminal (UE1), the method comprises analysing the type of the modification. If it is detected that the presence data comprises a predetermined type of modified presence information, the method comprises indicating that the presence data received from the user terminal (UE1) comprises value-added presence information related to the user terminal (UE1).