AI Prioritization of Wireless Network Issue Tickets
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Solution Overview
Problem
Current telecommunication networks lack the ability to prioritize user-reported issues effectively, as they do not have information on the level of importance or urgency perceived by users, leading to inefficient allocation of resources for issue resolution.
Innovation Solution
A system and method that dynamically and automatically determine the priority of user-reported issues based on historical data, including user behavior and network performance, using AI to assess the probability of users disengaging from the network if issues are not resolved quickly, thereby prioritizing tickets for the engineering team.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a default priority is assigned to all issue tickets, then the ticketing system is simple and easy to operate, but the engineering team cannot effectively prioritize issues based on user importance levels
Solution Approach 1:
The system automatically determines issue priority by analyzing user-reported symptoms and comparing them against a knowledge base of known issues and their impacts, eliminating the need for manual priority assignment by the engineering team while capturing critical information about user importance levels
Solution Approach 2:
The manual mechanical process of engineering team members reviewing and assigning priorities is replaced with an automated computer-based system that uses symptom matching and impact analysis to determine priority levels, improving both efficiency and information accuracy
2Measurement precision
If the engineering team manually reviews all issue tickets to determine priority, then accurate priority assessment is achieved, but the process becomes time-consuming and reduces productivity
Solution Approach 1:
The system performs preliminary analysis of issue symptoms and automatically determines priority levels before tickets reach the engineering team, so that when engineers do review tickets, the priority is already established based on objective criteria, maintaining accuracy while speeding up the overall process
Solution Approach 2:
The system uses a knowledge base that is continuously updated with information about known issues, their symptoms, and their impacts on users, creating a feedback loop where resolved issues improve future priority determination accuracy without requiring manual engineering review for each new ticket
Data Source
AI summary
The disclosed system and method obtain a report of an issue reported by a user of the wireless telecommunication network, and historical information associated with the user and the wireless telecommunication network. The historical information includes multiple issues reported by users similar to the user, and multiple user statuses associated with the users similar to the user. The user status among the multiple user statuses includes active and inactive, indicating whether the user is an active member of the telecommunication network or has left the network. The system provides the historical information to an AI model, and obtains from the AI model a priority associated with the issue experienced by the user. The system causes a resolution of the issue based on the priority.