Data-driven Anomaly Detection in Industrial Processes
This talk presents a model-based anomaly detection framework, along with data-driven process monitoring approaches based on multivariate statistical methods and artificial intelligence techniques.
Overview
Anomaly detection plays a critical role in ensuring the safety, reliability, and operational efficiency of engineering, environmental, and industrial systems. Undetected anomalies can lead to productivity losses, increased operational costs, and serious safety hazards. Model-based and data-driven approaches offer complementary strengths for identifying anomalous conditions and improving system monitoring performance. The proposed methods are illustrated through several real-world applications, including air quality monitoring, fault detection in photovoltaic systems, water desalination, and anomaly detection in wastewater treatment plants.
Presenters
Brief Biography
Dr. Harrou received an M.S. degree in Telecommunications and Networking from the University of Paris VI and a Ph.D. degree in Systems Optimization and Security from the University of Technology of Troyes (UTT), France. He was an Assistant Professor at UTT for one year and was an Assistant Professor at the Institute of Automotive and Transport Engineering, Nevers, France, for one year. He was also a Post-Doctoral Research Associate at the Systems Modelling and Dependability Laboratory, UTT, for one year. He is currently a Senior Research Scientist with the Division of Computer, Electrical, and Mathematical Sciences and Engineering at King Abdullah University of Science and Technology. He is a co-author of "Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications" (Elsevier, 2020) and "Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning" books. And he is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). Harrou is the author of more than 250 refereed journal articles, conference publications, and book chapters. He received two IEEE ECBIOS 2021 Best Paper Awards. Dr. Harrou is featured in Stanford University’s list of the world’s Top 2% scientists for 2020-2025. And he is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
Related People
Related Researchers
Fouzi Harrou
- Senior Research Scientist, Statistics