Application of artificial intelligence (AI) and machine learning for proactive network troubleshooting and fault prediction (case study ZETDC HARARE)

Author
Mapiku Trish
Title
Application of artificial intelligence (AI) and machine learning for proactive network troubleshooting and fault prediction (case study ZETDC HARARE)
Abstract
ABSTRACT
Zimbabwe Electricity Transmission and Distribution Company (ZETDC) is rooted in the dynamic landscape of the electricity industry in Zimbabwe. As the primary electricity distribution and transmission utility in the country, ZETDC faces a confluence of challenges and opportunities. This study is geared toward exploring strategies and solutions that will bolster the reliability, efficiency, and sustainability of electricity distribution and transmission, ensuring that ZETDC continues to play a vital role in Zimbabwe's economic and social development while meeting the expectations of its diverse customer base. The integration with the existing network infrastructure enables real-time data processing, allowing the AI models to analyze incoming network data for anomaly detection and fault prediction. The system generates alerts for network administrators upon detecting anomalies, providing insights into potential issues before they impact operations. The user interface offers intuitive dashboards for monitoring network health and responding to alerts, while fault prediction capabilities empower administrators to take preemptive actions. Rigorous testing ensures the system's accuracy and reliability, leading to a gradual rollout into the production network environment with training provided to administrators. The model's performance, with precision at 87% and recall at 91%, indicates a promising level of effectiveness in its predictive capabilities for positive classes. These results suggest that the model is adept at making accurate positive predictions while also capturing a substantial portion of the actual positive cases.
Date
JUNE 2024
Publisher
BUSE
Keywords
Zimbabwe Electricity Transmission and Distribution Company (ZETDC), bolster the reliability, efficiency, and sustainability of electricity distribution and transmission,
Supervisor
NIL
Item sets
Department of Computer Science
Media
Mapiku Trish

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