Theory and Application of Automation, Intelligence and Big Data Technology in Complex Production Process

Introduction: With the rapid development of computer and artificial intelligence technology, its application in industry, agriculture, medical health and other fields has been widely used. This call for papers aims to explore the theoretical research and practical applications of automation, data science, and artificial intelligence techniques in complex process industries, discrete industries, and modern smart farm environments. Intelligent and automated technologies have made significant progress in industry and agriculture in various scenarios. From intelligent detection, monitoring, environmental regulation to planning and scheduling and optimal control, intelligent and automated technology is completely changing the mode of modern industrial and agricultural production. Therefore, it is of great significance to study and explore the theory and application technology of automation and intelligent technology in complex production processes (such as complex industry, power grid, and modern agriculture) to promote the upgrading of industrial and agricultural industries. Other areas of interest include automation and intelligent technology in complex environmental state monitoring, intelligent regulation of modern farm microclimate, theoretical and practical exploration of intelligent detection of key parameters in complex production processes, and environmental perception based on multi-source data. We welcome submissions that explore these and other related topics. Topics can include, but are not limited to, the following:

1. Advanced artificial intelligence algorithms are applied to the modeling and optimization of complex power grid processes.
2. Application research of big data technology in modern agricultural environment.
3. Artificial intelligence in abnormal condition detection of complex production processes.
4. Advanced perception technology based on artificial intelligence.
5. Challenges and future prospects of automation and intelligence in complex production processes.

 

Organizers:

	Dayu Tan, Anhui University, China Dayu Tan is the Associate Professor, Master’s Supervisor at the Key Laboratory of Computational Intelligence and Signal Processing (Ministry of Education), Anhui University. He received the Ph.D. degree in control science and engineering from the School of Information Science and Engineering from East China University of Science and Technology, Shanghai, China, in 2021. He was a visiting Ph.D. student of School of Engineering Practice and Technology, McMaster University, Hamilton, ON, Canada, for the period from Sep. 2019 to Oct. 2020. In September 2021, he joined the Anhui University, Hefei, China. His research interests include machine learning, computer vision, and data mining. He has been responsible for 1 project of the Youth Foundation of the National Natural Science Foundation of China, 2 provincial and ministerial-level funds, and 2 school-level talent projects. Dr. Tan has published over 30 SCI/EI academic papers in renowned international and domestic journals, including IEEE TNNLS, IEEE TCYB, IEEE TII, IEEE TETCI, IEEE TCDS, IEEE JBHI, BIB, Neurocomputing, CIS.
	Haojie Huang, Fuzhou University, China Haojie Huang received the B.S. degree and Ph.D. degree in control science and engineering in 2017 and 2023 from the East China University of Science and Technology, Shanghai, China, respectively. He is an Assistant Professor with Fuzhou University. His current research interests include machine learning, especially Gaussian process regression and explainable machine learning.
	Dan Yang, Hunan University of Science and Technology, China Dan Yang received the B.S. degree in control science and engineering from the East China University of Science and Technology, Shanghai, China, in 2019, and the Ph. D degree from the Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, in 2024, in control science and engineering. From 2022-2023, she was a visiting Ph.D student with the University of Duisburg-Essen, Duisburg, Germany. She is currently a lecture with Hunan University of Science and Technology, Xiangtan, China. Her current research interests include intelligent modeling of industrial processes.

Submission Guideline:

Please submit your manuscript via Online Submission System: https://easychair.org/conferences/?conf=rcae2026
Please choose "Special Session 6"