ALLIANCE — Dr. Thuan Do, assistant professor of computer and electrical engineering at the University of Mount Union, has published a new book exploring Tiny Machine Learning (TinyML), an emerging area of artificial intelligence that brings machine learning capabilities directly to low-power embedded devices and Internet of Things systems. 
 
Tiny Machine Learning: Design Principles and Applications provides a comprehensive discussion of TinyML concepts, design principles, enabling technologies and real-world applications. The book examines how machine learning can be implemented on resource-constrained microcontrollers through system-algorithm co-design, allowing smart devices to process data locally with limited memory, computing power and energy consumption. 
 
“TinyML creates new opportunities to bring artificial intelligence directly into low-power smart devices,” said Do. “By enabling machine learning models to run on microcontrollers and embedded systems, our Mount Union students can develop faster, lightweight, more energy-efficient and more responsive Internet of Things applications.”  
 
Topics covered in the book include TinyML paradigms, anomaly detection, lightweight machine learning frameworks, power consumption and memory optimization and some applications such as real-time and environmental applications, and security and privacy for embedded AI systems. The reference book also explores ultralow-power smart Internet of Things devices and practical TinyML research focused on microcontrollers for data processing, extraction and synthesis.  
 
Designed for researchers, engineers, faculty and undergraduate students, the book reflects Do’s teaching in Mount Union’s computer and electrical engineering and applied AI programs, along with his research interests in embedded systems, artificial intelligence applications, robotics and the Internet of Things. His work highlights the growing role of TinyML in developing intelligent devices for applications such as healthcare, environmental monitoring, industrial automation, robotics, wearable technology and smart systems.