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The whole closed loop (intent-based awareness, identification, analysis, decision, execution and evaluation) powered by big data and AI technology effectively speeds up the long-term autonomous capability construction process on base of abundant best practices and case libraries in China.
How to monitor a massive amount of alarms and events from multi-vendor and multi-domain.
How to precisely locate the root cause and start the trouble shooting at the first stage.
Traditional FM systems put more attention to monitor problems rather than solving problems, and focus on locating the network problem rather than making an insight into customer perception.
Passive receiving equipment alarm, lack of network-oriented active perception ability.
The fault location is limited to the network fault itself, and the event-based multidimensional data locating ability is insufficient.
Fault handling is mainly based on order dispatch, and the self-healing ability is insufficient, and lack of event-based closed-loop capability.
The solution performs centralized management on all alarms from network elements. It can trace whole lifecycle of fault and also trigger to create trouble ticket automatically for closed-loop trouble shooting.
The solution is based on big data platform and AI mechanism, with highlights and use case details as:
• Enhance network-oriented perception and fault prediction capabilities
• End-to-end capabilities for perception, cognition, decision-making and handling of events and business scenarios
• Improve the level of intelligence and provide event-based closed-loop capability of the whole process lifecycle
• Realize fast fault diagnosis and cross-domain root cause location.
• Service impact analysis, with AI-based alarm correlation mining to provide full support of customer care