International Journal of Power Electronics Controllers and Converters

Unlocking Insights, Optimizing Processes: A Review Of Machine Learning In Action

  1. Sneha Raj M. P.
  2. Farsana Muhammed

Abstract

Machine learning (ML) has become a disruptive technology with applications in many different fields and sectors. Machine learning techniques are transforming the way data is examined, patterns are found, and decisions are made in a variety of industries, including healthcare, finance, manufacturing, and transportation. ML is improving drug discovery, treatment strategies, and diagnostics in the healthcare industry. In the financial sector, this means maximizing risk mitigation, credit scoring, and fraud detection. Machine learning (ML) enables process optimization, quality control, and predictive maintenance in manufacturing. ML is useful for transportation in the areas of route planning, autonomous vehicles, and logistics. These uses highlight machine learning's ability to increase productivity, cut expenses, and spur creativity, making it a vital component of contemporary technological developments. Machine learning (ML) is a rapidly evolving field with immense potential to revolutionize various aspects of our lives. This review explores the diverse applications of ML across various sectors like finance, health care, transportation, autonomous industries, manufacturing, data security and analyzing its impact and future potential. It also discusses ML's role in industrial sensing and control, addressing challenges and offering practical perspectives on process monitoring, fault detection, and control optimization. The paper gives an idea about the machine learning techniques performed in various applications and can analyze that which of the techniques are suitable for each application. This comprehensive review provides a valuable resource for researchers, practitioners, and policymakers interested in understanding the transformative power of ML across diverse industries.

Keywords:  Machine Learning (ML), Applications, Optimization, unlocking, Application Programming Interface, Support Vector Regression.

Keywords

References (10)

  1. Shamout, T. Zhu and D. A. Clifton. Machine Learning for Clinical Outcome Prediction. IEEE Reviews in Biomedical Engineering. 2021; vol. 14, pp. 116-126.
  2. Ma, H. Ge, Y. Liu, et al. A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms. IEEE Access, 2019; vol. 7, pp. 21235-21245.
  3. Shafi et al. Tackling Food Insecurity Using Remote Sensing and Machine Learning-Based Crop Yield Prediction. IEEE Access. 2023; vol. 11, pp. 108640-108657.
  4. Krummenacher, C. S. Ong, S. Koller, et al. Wheel Defect Detection With Machine Learning. IEEE Transactions on Intelligent Transportation Systems. 2018; vol. 19, no. 4, pp. 1176-1187.
  5. Meiners, M., Mayr, A., Thomsen, M, et al. Application of machine learning for product batch oriented control of production processes. Procedia CIRP. 2020; vol. 93, pp. 431-436.
  6. Lawrence, N. P., Damarla, S. K., Kim, J. W, et al. Machine learning for industrial sensing and control: A survey and practical perspective. Control Engineering Practice. 2024; vol. 145, pp.
  7. M. Rooney and M. K. Hinders. Machine Learning for Medium Access Control Protocol Recognition in Communications Networks. IEEE Access.2021; vol. 9, pp. 110762-110771.
  8. Elkateb, S., Métwalli, A., Shendy, A., et al. Machine learning and IoT–Based predictive maintenance approach for industrial applications. Alexandria Engineering Journal, 2024; vol. 88, pp. 298-309.
  9. Cerar, H. Yetgin, C. Fortuna, et al. Machine Learning for Wireless Link Quality Estimation: A Survey. IEEE Communications Surveys & Tutorials. 2021; vol. 23, no. 2, pp. 696-728.
  10. O. Alsrehin, A. F. Klaib and A. Magableh. Intelligent Transportation and Control Systems Using Data Mining and Machine Learning Techniques: A Comprehensive Study. IEEE Access.2019; vol. 7, pp. 49830-49857.

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