Automated Troubleshooting System for User Devices
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Solution Overview
Problem
Existing systems fail to efficiently diagnose and troubleshoot user devices without customer care executive intervention, leading to delayed and ineffective resolution of user issues in communication services.
Innovation Solution
An automated troubleshooting method and system that receives user queries, identifies intents, determines corresponding tags and events, and performs actions on user devices for troubleshooting, including contextual, informative, and actionable events, without requiring customer care executive involvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated troubleshooting system is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The automated troubleshooting system is divided into distinct functional modules: a natural language processing module for intent identification, a knowledge base module for storing troubleshooting procedures, an execution module for performing actions, and a feedback module for learning. This segmentation allows each module to specialize in specific tasks, improving overall troubleshooting efficiency while managing system complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary knowledge base that acts as a mediator between user queries and troubleshooting actions. The knowledge base stores structured troubleshooting procedures and serves as a bridge, translating natural language intents into executable troubleshooting steps. This intermediary layer simplifies the interaction between the complex NLP module and the execution module, resolving the contradiction between productivity improvement and system complexity.
2Loss of time
If manual customer care executive intervention is used, then device complexity is reduced, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing troubleshooting procedures in the knowledge base before actual troubleshooting incidents occur. Natural language intents and corresponding troubleshooting steps are identified and structured in advance, allowing the system to quickly retrieve and execute appropriate actions during actual troubleshooting without requiring complex real-time analysis, thus reducing troubleshooting time while managing complexity through advance preparation.
Solution Approach 2:
The automated troubleshooting system enables self-service by allowing the system to independently analyze user queries, identify intents, select appropriate troubleshooting procedures from the knowledge base, and execute actions without human intervention. This self-service capability eliminates the time loss associated with manual customer care executive intervention while the modular architecture keeps system complexity manageable through standardized interfaces and protocols.
Data Source
AI summary
Embodiments of the present disclosure relate to automated troubleshooting of at least one user device and accordingly perform at least one action on the at least one user device, wherein the at least one action is performed for troubleshooting of the at least one user device. In an embodiment, the automated troubleshooting system receives at least one query from the user of the at least one user device and identifies at least one intent from said at least one query. Thereafter, said system determines at least one tag corresponding to the at least one intent and processes the at least one tag to determine at least one event corresponding to the at least one action to be performed. Finally, said system performs the at least one action on the at least one user device based on the at least one event.