IPBX Server Missed Call Prioritization via Cross-Correlation
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Solution Overview
Problem
IPBX systems face challenges in effectively identifying and prioritizing missed VoIP calls, as existing solutions lack comprehensive methods to determine call priorities and respond to unreturned calls efficiently.
Innovation Solution
An IPBX server generates call summary metrics and uses a processing circuit to evaluate these metrics, cross-correlate with secondary data sources to identify missed calls, and determine priorities based on criteria such as caller and callee lists, spam probability, and user status, storing data for higher and lower priority calls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive call monitoring and analysis is implemented to identify missed calls, then call identification accuracy is improved, but system complexity increases
Solution Approach 1:
The system divides call monitoring into separate functional modules: call event message reception, call summary metric generation, missed call identification, and priority determination. Each module handles a specific aspect of call analysis, improving identification accuracy while managing system complexity through functional segmentation.
Solution Approach 2:
Call summary metrics serve as an intermediary data structure that aggregates raw call event messages into processed information. This intermediary layer simplifies the complexity by pre-processing call data before it reaches the missed call identification logic, reducing the computational burden on the main system.
2Measurement precision
If multiple criteria are used to determine call priorities, then call prioritization accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-defining priority criteria and categories (e.g., high-priority contacts, spam probability thresholds) before call analysis. When a missed call is identified, the system quickly matches it against pre-established criteria rather than evaluating all possible factors in real-time, thus improving prioritization accuracy without excessive processing time.
Solution Approach 2:
The system changes parameters by assigning different priority levels (high, medium, low) based on multiple criteria including caller identity, time of day, and spam probability. These parameter changes enable accurate prioritization while maintaining efficient processing through discrete priority categories rather than continuous evaluation.
3Speed
If real-time call analysis is performed to improve responsiveness, then call response time is improved, but computational load increases
Solution Approach 1:
The system implements periodic action by analyzing call events at specific intervals rather than continuously processing every call event in real-time. Call summary metrics are generated periodically from accumulated call events, enabling responsive call identification while reducing computational load through time-based sampling rather than continuous analysis.
Data Source
AI summary
Apparatuses and methods concerning routing and processing of calls in a server are disclosed, and involving a processing circuit communicatively coupled to a server that routes calls (e.g., data communications) for a plurality of end-users and generates call event messages for the routed calls. The processing circuit generates call summary data and evaluates the call summary data to identify a set of incoming calls to the server that were missed and have not been returned by the end-users. Certain of the calls are checked relative to a secondary data source and respective priorities for the set of incoming calls are ascribed for further processing, and some having a higher priority.