Emerging Trends in TinyML

From Algorithms to Applications
1. Auflage 2027
ISBN: 978-1-041-27777-4
Verlag: Taylor & Francis

Buch, Englisch, 306 Seiten, Format (B × H): 156 mm x 234 mm

Tiny Machine Learning (TinyML) is an emerging field of artificial intelligence that allows machine learning models to be executed directly on resource-constrained devices like microcontrollers, sensors and embedded systems. Unlike traditional cloud-based approaches, TinyML brings real-time intelligence to the edge with minimal computational and energy requirements. This capability makes TinyML a key enabler of sustainable edge AI by reducing latency, enhancing data privacy through local processing, and minimizing dependence on centralized cloud infrastructure.

This book explores how TinyML is transforming sectors such as agriculture, environmental science, healthcare, urban planning, and industrial automation by enabling intelligent data processing without reliance on cloud infrastructures. These edge-centric applications dramatically reduce energy consumption and latency, contributing to both environmental sustainability and enhanced user experience. Bridging theory and practice, this volume compiles cutting-edge research, methodologies, and case studies that highlight the design, deployment, and optimization of TinyML systems. Emphasis is placed on low-power hardware, domain-specific constraints, privacy-preserving AI, and ethical considerations.

Intended for academic researchers, engineers, data scientists, and graduate students, this book offers foundational insights and advanced approaches that are crucial for developing sustainable AI models at the edge.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Narisetty, Nirmala Jyothi

Dhulipalla, Ramya Krishna

Bhattacharyya, Debnath

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Verteilte Systeme (Netzwerke)
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Über Autor(innen)

Nirmala Jyothi Narisetty is an Associate Professor in the Computer Science & Engineering Department at Koneru Lakshmaiah Education Foundation, Hyderabad, India. With over a decade of academic experience, her research focuses on cloud computing, machine learning, and data analytics. She has made significant contributions to the field, publishing 22 research papers in esteemed international journals. In addition to her expertise in data mining, deep learning, and cloud computing, she actively engages with the academic community as a member of IEEE, and is a reviewer for several prestigious journals.

Ramya Krishna Dhulipalla obtained a BTech degree from JNTU, Kakinada, in 2010 and a MTech from the same university in 2012. She obtained a PhD in 2025 from Vellore Institute of Technology University, Andhra Pradesh, India. She is currently an Assistant Professor in the Department of Computer Science and Engineering at Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad, India. Her areas of research interest include Deep Learning, Computer Vision, Image Processing, and Drone Technology. She has a strong academic background and is actively involved in research, having published more than 10 research papers in reputed national and international journals. She is also passionate about guiding students and participating in innovative research project.

Debnath Bhattacharyya is a Professor at Department of Information Technology, Aditya Institute of Technology and Management, Tekkali, Andhra Pradesh, India. He was an Invited International Professor of Lincoln University College, Kuala Lumpur, Malaysia, and a Foreign Professor, Department of Multimedia Engineering, Hannam University, South Korea. Currently, he is the Visiting Professor at University of Johannesburg, South Africa and UCSI University, Kuala Lumpur, Malaysia. He completed his PhD (Tech, CSE) from the University of Calcutta, Kolkata. He did his MTech (CSE) from West Bengal University of Technology, Kolkata, India. Dr Bhattacharyya is the Senior Member of IEEE, Senior Member of ACM, ACM SIGKDD, OWASP, Life Member of CSI, India, Senior Member of IACSIT, Singapore and Senior Member of IAENG, Hong Kong. He serves as an editor for several reputed journals (indexed by Scopus, SCI, and WoS). He has published 300 Scopus indexed articles and 160 WoS (Core) indexed papers. His research interests include Security Engineering, Pattern Recognition, Biometric Authentication, Multimodal Biometric Authentication, Data Mining and Image Processing. He has also published 6 books in Computer Science and Engineering.