AI & Automation

Harnessing AI to Improve Network Reliability

Proactive and AI-Driven Network Event Prediction for Improved Service Health and Network Reliability in Outside Plant Maintenance 

  • Developing a framework for proactive event prediction in outside plant maintenance
  • Leveraging AI techniques to analyze telemetry data and interaction events across multiple customer channels
  • Incorporating the use of deep learning models to capture complex relationships within the data and enhance prediction and accuracy

Alexis Hwang
Manager, Data Science
Cox Communications

Smart Network: Graph-Based Network Analysis, Event Detection, and Outage Simulation 

  • Understanding the importance of real-time end-to-end visibility of the network footprint to monitor the health of the network and traffic flow
  • Creating a blueprint by combining network topology with real-time device telemetry
  • Exploring how to leverage graph algorithms to enhance the robustness, scalability, and intelligence of the network infrastructure

Nivedhitha Sridhar
Data Scientist 

Predictive Framework for Enhanced Wireline Network Reliability: Unveiling Anomalies and Streamlining Maintenance          

  • Enhancing network reliability and performance by developing a framework to predict wireline network failures
  • Creating a tool with actionable insights to prioritize node maintenance and facilitate field maintenance technicians
  • Evaluating operational benchmarks and KPIs to conducting root cause analysis and predict the future state of the network
  • Using the framework to enable the effective allocation of resources and enhance overall efficiency of network operations

Madiha Sahar
Rogers Telecommunications Inc.

Damian Poltz
Senior Vice President, Wireline Networks
Rogers Communications

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