Industry 4.0 refers to automation and data exchange in manufacturing technologies. From innovative research, challenges, solutions and strategies to real-world case studies, the aim of this edited book is to focus on the nine pillars of technology that are supporting the transition to Industry 4.0 and smart manufacturing. The nine pillars include the internet of things, cloud computing, autonomous and robotics systems, big data analytics, augmented reality, cyber security, simulation, system integration, and additive manufacturing. A key role is played by the industrial IoTs and state-of-the-art technologies such as fog and edge computing, advanced data analytics, innovative data exchange models, artificial intelligence, machine learning, mobile and network technologies, robotics and sensors.
This book is a useful resource for an audience of academic and industry researchers and engineers, as well as advanced students in the fields of information and communication technologies, robotics and automation, big data analytics and data mining, machine learning, artificial intelligence, AR/VR/ER, cybersecurity, cyber physical systems, sensing and robotics with a focus on Industry 4.0, and smart manufacturing.
Chuah, Joon Huang: -
Joon Huang Chuah lectures at the Department of Electrical Engineering, University of Malaya, Malaysia and is the Head of VLSI and Image Processing (VIP) Research Group. He specialises in artificial intelligence, image processing and integrated circuit design. He is the Principal Journal Editor of the Institution of Engineers, Malaysia. He received his B.Eng. from the Universiti Teknologi Malaysia, M.Eng. from the National University of Singapore, MPhil in Technology Policy from the Cambridge Judge Business School, and PhD from the University of Cambridge.
Leong, Wai Yie: -
Wai Yie Leong is the Chairperson of The Institution of Engineering and Technology (Malaysia Local Network) and Vice President of The Institution of Engineers, Malaysia (IEM). She specializes in sensing and wireless communications and medical signal processing research including wireless sensor networks, wireless communications, and brain signal processing for signal conditioning and classification in various EEG-based mental tasks. She received the Women Engineer of the Year award in 2018, the IEM Presidential of Excellence Award in 2016, and ASEAN Meritorious Award in Science and Technology 2017. She holds a Ph.D. in Electrical Engineering from The University of Queensland, Australia.
Tee, Boon Tuan: -
Boon Tuan Tee is an Associate Professor at the Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka, Malaysia. His research focuses on energy management system and green technology. He is a Professional Technologist (Green Technology) registered under Malaysia Board of Technologists. His other professional certifications include Certified Energy Manager under ASEAN Energy Management System (AEMAS) and Certified Professional in Measurement & Verification from Malaysia Greentech. He has been a member of the IET since 2015. He holds a Ph.D. degree in Engineering from University of Cambridge, UK.
