Data Analytics and Machine Learning Applications for Remote Management Systems (RMS) In Telecommunications Infrastructure

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This framework improves remote management systems in telecommunications using anomaly detection and cost reduction.

A data-driven framework enhanced remote management systems, resulting in a 40% reduction in mean time to repair.
The anomaly detection module achieved 85% accuracy in identifying abnormal air conditioning unit cycling patterns.
The hybrid machine learning approach effectively detects operational issues, aligning with ISO 25010 standards for system quality.
Historical data was leveraged for root cause analysis, achieving 83.3% accuracy while contributing to sustainability goals.

Yu et al. (2025) studied this question.

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View Full Paper

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Authors

This framework improves remote management systems in telecommunications using anomaly detection and cost reduction.

A data-driven framework enhanced remote management systems, resulting in a 40% reduction in mean time to repair.
The anomaly detection module achieved 85% accuracy in identifying abnormal air conditioning unit cycling patterns.
The hybrid machine learning approach effectively detects operational issues, aligning with ISO 25010 standards for system quality.
Historical data was leveraged for root cause analysis, achieving 83.3% accuracy while contributing to sustainability goals.

Yu et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark