AI Network Quality Index for User-Centric Performance Evaluation
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Solution Overview
Problem
Conventional Internet performance evaluation methods rely heavily on isolated key performance indicators (KPIs) that lack contextual insight and fail to integrate objective data from network monitoring systems with subjective customer feedback, limiting the ability of service providers to enhance operational decision-making and customer satisfaction.
Innovation Solution
An AI-driven platform that integrates objective wireless connection metrics with subjective customer feedback using large language models to generate a Mean Quality Index (MQI) score, combining throughput, latency, and packet loss with sentiment analysis from textual sources to provide a holistic understanding of network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If isolated key performance indicators (KPIs) are used for network performance evaluation, then measurement simplicity is maintained, but contextual insight and comprehensive evaluation capability are lost
Solution Approach 1:
The patent merges multiple isolated KPIs (download speed, upload speed, latency, packet loss) with subjective customer feedback data into a unified Mean Quality Index (MQI) score. This combination allows the system to maintain measurement simplicity while gaining comprehensive contextual insight through the integration of both objective metrics and subjective perceptions.
Solution Approach 2:
The MQI score serves multiple functions simultaneously: it quantifies network performance, incorporates customer sentiment, provides contextual insight, and enables proactive service management. This multi-functional approach resolves the contradiction by making the evaluation method both simple (single score) and comprehensive (multiple data sources).
2Measurement precision
If objective network metrics are collected and analyzed, then measurement precision is improved, but the ability to reflect user experience is limited
Solution Approach 1:
The system combines objective network metrics (download speed, upload speed, latency, packet loss) with subjective user feedback data to create a comprehensive MQI score. This merging allows the measurement to be both precise (objective data) and adaptable to user experience (subjective feedback).
Solution Approach 2:
The MQI score acts as an intermediary that translates both objective metrics and subjective feedback into a unified representation of network quality from a user perspective. This intermediary mechanism allows precise measurement to reflect user experience without requiring direct correlation between technical metrics and user perceptions.
3Ease of manufacture
If conventional KPI collection methods are used, then data collection simplicity is maintained, but the ability to provide holistic network performance understanding is reduced
Solution Approach 1:
The patent merges multiple data sources (objective KPIs from network monitoring systems and subjective feedback from customer reviews, support transcripts, and social media) into a single holistic understanding through the MQI score. This maintains ease of data collection while achieving comprehensive performance understanding.
Solution Approach 2:
The MQI score provides multiple functions: it summarizes network performance, incorporates customer sentiment analysis, identifies service quality issues, and guides proactive management decisions. This multi-functionality achieves holistic understanding without complicating the data collection process.
Data Source
AI summary
An approach for collecting network (e.g., Internet) performance metrics from an end-user perspective is disclosed. The approach comprises collecting, by at least one objective agent, a plurality of connection parameters relating to network service quality, wherein the plurality of collected connection parameters include throughput measurements relating to download speed and upload speed. The approach also comprises determining a mean quality index (MQI) score based on the plurality of collected connection parameters, wherein the MQI score is indicative of the network service quality from a user perspective.