We are at the moment on the cusp of the fourth industrial revolution (4IR) or Industry 4.0, which is poised to reshape the financial system and society with unprecedented depth and breadth. Emerging applied sciences together with complicated group and programs, sensible sensing, industrial robotics, industrial wi-fi communications, industrial Internet-of-Things (IIoT), Internet-of-Moving-Things (IoMT), industrial cloud, huge information and cyber-physical programs (CPS) have change into the hotspots of analysis and innovation globally. In the previous few years, these rising applied sciences have change into mainstream and industrially-relevant on account of steady developments in digitalization, synthetic intelligence (AI), superior analytics, huge computing energy, cheap reminiscence, and the big volumes of information collected.
The course of industries are in a singular place to learn from Industry 4.0, as they’ve the best infrastructure and personal huge quantities of heterogeneous industrial information. Industry 4.Zero is poised to supply financial and aggressive benefits within the face of ever-increasing calls for on vitality, setting, and high quality by offering automation and effectivity by no means seen earlier than. Process industries have been utilizing information analytics (e.g., principal part evaluation (PCA), partial least squares (PLS), canonical variate evaluation (CVA), and time-series strategies for modeling) in numerous varieties for greater than three many years. Recent developments in AI, machine studying, and superior analytics present a brand new opening for leveraging industrial information for fixing complicated programs engineering issues.
Building upon the success of the primary particular problem on Machine studying and Advanced Data Analytics in Control Engineering Practice, we’re completely satisfied to launch the Call-for-Papers (CfP) for the second particular problem on the identical subject. The second particular problem intends to proceed to curate novel advances within the improvement and utility of machine studying methods to handle ever-present challenges of coping with complicated and heterogeneous industrial information in course of programs engineering and past. Practical contributions are invited on matters that embrace, however should not restricted to:
Data analytics and machine studying strategies for modeling, management, and optimization;
Reinforcement-learning/deep-learning strategies for modeling and management;
Advanced strategies for course of information visualization;
Natural language processing/computer-vision/speech-recognition within the course of industries;
Adaptive strategies for autonomous studying within the course of industries;
Video and image-based soft-sensors;
Mobile and cloud computing within the trade; and
Routine and predictive upkeep.
Control Engineering Practice is a premier journal that publishes papers with direct purposes of profound management idea and its supporting instruments in all doable areas of automation. Through this particular problem, we hope to draw extra tutorial researchers and industrial practitioners to work and form this new, fascinating and important space.
Aditya Tulsyan, Amgen Inc., USA, email@example.com
Jong Min Lee, Seoul National University, South Korea, firstname.lastname@example.org
Zhiqiang Ge, Zhejiang University, China, email@example.com
Zhongliang Li, Aix-Marseille University, France, firstname.lastname@example.org
Biao Huang, University of Alberta, Canada, email@example.com
Submission opens: Immediately
Submission deadline: Dec 31, 2020
Target remaining acceptance notification: August 1, 2021