Developing AI monitoring systems to upgrade industrial intelligence ― Lingnan President S. Joe Qin and the research team take second prize at Liaoning Provincial Science and Technology Awards

The research, conducted jointly by Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science at Lingnan University, and the research team from Northeastern University, has won Second Prize at the Liaoning Provincial Science and Technology Awards. Their project, “Low-quality heterogeneous big data-driven monitoring theory and methods for complex dynamic systems”, is a breakthrough in the field of AI-driven automation, able to systematically address data monitoring challenges in complex dynamic systems, particularly in industrial systems and automation technologies, thus providing crucial technical support for the future development of industrial intelligence.

Breaking traditional boundaries: Innovative data monitoring theory and methods

Traditional industrial monitoring systems face numerous problems, including a wide variety of data types, inconsistent quality, rapidly changing system status, and difficulties in immediate detection abnormalities. Supported by the Major Program of the National Natural Science Foundation of China (NSFC), Prof Qin and the research team conducted innovative in-depth systematic studies in key national areas such as intelligent manufacturing, which revealed the spatial structure and geometric properties of traditional data monitoring models. Based on these findings, the team proposed a novel algorithm, “Dual time-scale hierarchical joint monitoring theory and method”, which enables rapid analysis and early warning in traditional models, thereby enhancing flexibility and accuracy.

This breakthrough not only supports AI-driven automation research, but also the development of control science and engineering disciplines, providing essential guarantees for the safe and reliable operation of industrial systems, and helping enterprises make quicker and more effective decisions in complex environments. Related findings have been published in prestigious international journals such as IEEE Transactions on Industrial Informatics and IEEE Transactions on Automation Science and Engineering (T-ASE).

Industry-academia integration: Promoting the application of big data and AI technologies in industrial scenarios

Prof Qin said, “It is an honour to collaborate with such a highly respected research team from Northeastern University on this groundbreaking project, and our achievement is a testament to the team’s intelligence and dedication. This recognition not only affirms our research outcomes, but also highlights the important role of data science in improving industrial artificial intelligence. Moving forward, the University will continue to promote in-depth integration of AI technology with the real economy, and to contribute to the progress of intelligent manufacturing and sustainable development.”

An internationally renowned data scientist with a background in automation and engineering systems, President Qin is dedicated to advancing the application of big data and AI in the industrial sector. He is the only recipient from the Greater China region of the prestigious international IEEE Control Systems Society Transition to Practice Award, which recognises his outstanding contributions to scientific collaboration and interaction between industry, research laboratories, and academia.