Impact of LoRA and 5G on Smart Manufacturing from Automation Perspective


  • Muhammad Ayoub Kamal 1Malaysian Institute of Information Technology (MIIT), Universiti Kuala Lumpur, Malaysia ,2Institute of Business and Management. Karachi, Sindh, Pakistan
  • Muhammad Mansoor Alam Malaysian Institute of Information Technology (MIIT), Universiti Kuala Lumpur, Malaysia, 2 Riphah International University, I-14/3 Islamabad, Pakistan
  • Aznida binti Abu Bakar Sajak Malaysian Institute of Information Technology (MIIT), Universiti Kuala Lumpur, Malaysia
  • Mazliham Mohd Su’ud Malaysian France Institute (MFI), Universiti Kuala Lumpur, Malaysia



LoRA, 5G, Industrial IoT, Automation, Long Range, Fifth Generation, Industry 4.0


The Industrial Internet of Things (IIoT), also known as Industry 4.0, is a forward-thinking industrial era in which numerous developing technologies are combined to produce digital solutions. In industrial enterprises, Industry 4.0 technologies are separated into base and front-end technologies. Cloud computing, IoT, analytics, and big data are all essential technologies. In this article, we evaluate the current landscape of factory automation and the influence of 5G and LoRA communication on smart manufacturing automation, while front-end technologies are split into four categories: smart goods, smart working, smart manufacturing, and smart supply chain. First, we looked at the idea of Industry 4.0, as well as the four front-end dimensions and four basic technological components. Second, we spoke about smart industrial automation and the influence of 5G and LoRA communication. The broad use of front-end technology, of which Smart Manufacturing is a crucial component, is required for Industry 4.0 to succeed. However, the implementation of the foundation technologies is difficult. Current automation standards will serve as a solid foundation for future smart manufacturing systems. The distribution, adoption, and development of relevant morality in a requirement-driven process may result in faster, deeper, and bigger implementation of smart industrial automation.


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Author Biographies

Muhammad Ayoub Kamal, 1Malaysian Institute of Information Technology (MIIT), Universiti Kuala Lumpur, Malaysia ,2Institute of Business and Management. Karachi, Sindh, Pakistan

Muhammad Ayoub Kamal, pursing PhD in (Information Technology), from the Malaysian Institute of Information Technology University Kuala Lumpur, Kuala Lumpur, Malaysia. He received his Master of Engineering degree in Information Technology and Bachelor of Engineering degree in Computer System Engineering from Mehran University of engineering and Technology in 2015, 2012 respectively. He is working as a lecturer in Computer Science Department of IoBM. He has seven years of experience in fieldwork and academic institutions, five years of experience as IT Manager in EKTA construction company, and he has one year of experience as Lecturer Computer Science in ILMA University. He has published 9 research articles in national and international research journals. His areas of research are wireless sensor network (WSN), long range technology (LoRA), internet of things (IoT), machine to machine communication (M2M), machine learning (ML) and artificial intelligence (AI).

Muhammad Mansoor Alam, Malaysian Institute of Information Technology (MIIT), Universiti Kuala Lumpur, Malaysia, 2 Riphah International University, I-14/3 Islamabad, Pakistan

Muhammad Mansoor Alam holds a PhD Degree in computer engineering, a PhD Degree in electrical and electronic engineering, the M.E degree in system engineering, and degree in computer science. He is a Professor of Computer Science in riphah international university. He is also working as an adjunct professor in UniKL. He is an active researcher in the field of Computer Science. He has authored more than 160 research articles published in ISI indexed journals, as book chapters, and in peer-reviewed conferences. He is also an author of the book “Study guide of Network Security” copyrighted by Open University Malaysia and Open University Hong Kong.

Aznida binti Abu Bakar Sajak, Malaysian Institute of Information Technology (MIIT), Universiti Kuala Lumpur, Malaysia

Aznida binti Abu Bakar Sajak Graduated from University of Liverpool in 2005 with Masters of Science (Engineering) in Telecommunications and Microelectronics System. Loves Liverpool so much that she decided to pursue her PhD at the same university sponsored by the Islamic Development Bank, Saudi Arabia. Aznida Abu Bakar Sajak was in Digi Telecommunications, a mobile service provider in Malaysia owned by Telenor ASA of Norway for almost six years before joining UniKL in 2011. Holds a PhD in Electrical Engineering and Electronics from the University of Liverpool in 2019. A member of Board of Engineers Malaysia, The Institution of Engineers, Malaysia and The Institution of Engineering and Technology, UK.

Mazliham Mohd Su’ud, Malaysian France Institute (MFI), Universiti Kuala Lumpur, Malaysia

Mazliham Mohd Su’ud received a PhD in Computational Intelligence & Decision, from University De La Rochelle, France 2007. He received his Postmaster Degree in Electronics, from University De Montpellier II France and master’s degree in electrical and electronics engineering from the University of Montpellier II, in 1993, and since 2013. He has been a President/Chief Executive Officer of Universiti of Kuala Lumpur, Malaysia. He is an active researcher in the field of machine learning algorithms. He has authored more than 70 research articles published in ISI indexed journals, as book chapters, in peer-reviewed conferences, and Scopus journals.


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