Three University academics have made a significant contribution to a book published by Springer, an American publishing company specialising in academic journals and books across nursing, gerontology, psychology, social work, counselling, public health, and rehabilitation. The book, ‘Measurement, Automation, and Control in Artificial Intelligence and Machine Learning’, with 13 chapters, is edited by two MUT academics from the Department of Electrical Engineering: Professor Puramanathan (Ralph) Naidoo and Matthew Sibanda. Sibanda said the book is a guidebook for the “smart factories” and automated systems of the future. “Think of it as a roadmap for making machines not just active, but aware and adaptive,” Sibanda said.
The book explains how traditional industrial systems are being “upgraded” with AI: Measurement (the Senses): “Instead of a sensor just reporting a number, like it is 100 degrees, AI allows it to understand what that number means for the future, predicting if a machine is about to break before it actually does,” said Sibanda.
He said Automation (the Action) is about moving beyond “if this, then that” rule. The book describes systems that can learn from their own past mistakes and adjust their own work without a human having to reprogramme them. Sibanda also explained the role of ‘Control (the Strategy)’. “It introduces Integrative Process Automation and Control Engineering (IPACE). This is just a fancy way of saying all these smart parts, which are the sensors, robots, and software, are unified into one “nervous system” that manages everything from manufacturing to energy use”, he highlighted.
Sibanda said they invited a diverse group of professionals to collaborate in this book to bridge the gap between traditional engineering and the rapid rise of Industry 4.0.
“Our decision was driven by three primary motivations: breaking down silos in traditional industries since departments such as finance, production, and maintenance often operate in silos. The editors wanted to showcase IPACE, a new approach that unifies these fields through a single “nervous system” of the Industrial Internet of Things (IIoT) and AI. By inviting specialists from different sectors, we could demonstrate how these technologies work together as a fully integrated system,” Sibanda said.
The editors brought in professionals who have implemented “these systems in diverse fields, including transportation and smart homes, renewable energy and agriculture, as well as cybersecurity and management. This broad expertise ensures the book serves as a practical roadmap for practitioners, not just an academic text”.
Some of the higher education institutions from which the professionals were from are Chuka University, Kenya; Moi University School of Engineering, Kenya; Technical University Kenya, Kenya; Rajiv Gandhi College of Engineering Research and Technology, India; Cape Peninsula University of Technology, RSA; and International University of Management, Windhoek, Namibia. Dr Kavita Behari, a Lecturer in the Department of Electrical Engineering, together with daughter, Shriya Behara, wrote a chapter called ‘Explainable Artificial Intelligence in Dermatology: Overview of Data Scarcity for Skin Cancer Detection in Black Skin’. The chapter examines the application of artificial intelligence in dermatology, with a particular focus on skin cancer detection in Black skin and other Skin of Colour populations. “While AI has shown considerable promise in improving diagnostic accuracy, a major limitation remains the scarcity and underrepresentation of darker skin tones in dermatological datasets. This can lead to biased models and inequitable clinical outcomes,” said Dr Behara. Shriya is a final-year medical student at the University of the Witwatersrand (WITS). In addition to editing the book, Professor Naidoo published two chapters.