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Advances in Performance Monitoring and Evaluation: Harnessing Machine Learning for Enhanced Insights and Decision-Making

  • Unique Paper ID: 170420
  • Volume: 11
  • Issue: 7
  • PageNo: 1093-1097
  • Abstract:
  • Performance monitoring and evaluation systems play a crucial role in various domains, providing insights into system performance, behavior analysis, and decision-making support. In this abstract, recent advancements in performance monitoring and evaluation systems leveraging machine learning techniques are reviewed. The survey encompasses studies across various domains, including healthcare, manufacturing, IoT, and risk management. Key contributions entail assessing contactless breathing monitors for sleep stage classification, recognizing activities in climbing through sensor-based methods, and validating intrusion detection systems for power systems using machine learning. Additionally, research endeavors delve into physical activity classification with sensorized devices, employing deep learning for fall detection, and applying reinforcement learning for managing blood glucose levels in diabetes. Furthermore, investigations explore machine learning-based file entropy analysis for detecting ransomware, fault monitoring in additive manufacturing, and plant-wide process monitoring within Industry 4.0 contexts. This abstract offers insights into the diverse applications and methodologies in performance monitoring and evaluation systems, underscoring the importance of machine learning in tackling intricate challenges across diverse fields.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 7
  • PageNo: 1093-1097

Advances in Performance Monitoring and Evaluation: Harnessing Machine Learning for Enhanced Insights and Decision-Making

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8.01 (Year 2024)
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Journal no 47859

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