Applied AI and Machine Learning for Real-World Systems

Artificial intelligence (AI) and machine learning (ML) have rapidly evolved from specialized research domains into transformative technologies that are reshaping nearly every aspect of modern society. Across industries, governments, healthcare systems, educational institutions, and research organizations, AI-driven solutions are increasingly being used to solve complex problems, improve decision-making, automate processes, and drive innovation. As these technologies continue to mature, their influence extends beyond technical efficiency, raising important questions about transparency, accountability, fairness, trustworthiness, and human oversight. As AI becomes embedded in critical sectors, successful implementation requires collaboration to develop systems that are transparent, inclusive, and responsive to human needs. Applied AI and Machine Learning for Real-World Systems explores the practical application of intelligent technologies while emphasizing the human dimensions that accompany their deployment. This book brings together contemporary research, innovative methodologies, emerging frameworks, and real-world case studies that demonstrate how AI and ML can be designed and implemented to address pressing challenges across multiple sectors. Covering topics such as open mapping, digital identity, and adaptive image encryption, this book is an indispensable academic resource for graduate and doctoral students, AI developers, software engineers, data scientists, technology practitioners, digital innovation professionals, policymakers, and more.

Jingyuan Zhao obtained her PhD in Management Science and Engineering from University of Science and Technology of China. She completed four postdoctoral programs respectively in Mathematical and Computational Science with University of Toronto Mississauga, in Innovation and Governance with University of Toronto, in Management of Technology with Université du Québec à Montréal, and in Technological Economics with Harbin Institute of Technology. Dr. Zhao's research expertise includes management of technology innovation, innovation and entrepreneurship, behaviour and information technology, human-computer interaction, and science and technology policy. She has teaching experience of 15 years at the graduate and undergraduate level. Research portfolio includes peer-reviewed articles in highly regarded journals, authored books, multiple book chapters, and conference presentations. Dr. Zhao also has extensive industry experience and provides consulting services to major corporations, such as China Mobile. She serves as editor-in-chief of International Journal of e-Collaboration (IJeC).

V. Vinoth Kumar is an Associate Professor in the Department of Computer Science and Engineering in MVJ College of Engineering, Bangalore, India. He is a highly qualified individual with around 8 years of rich expertise in teaching, entrepreneurship, and research and development with specialization in computer science engineering subjects. He has been a part of various seminars, paper presentations, research paper reviews, and conferences as a convener and a session chair, a guest editor in journals and has co-authored several books and papers in national, international journals and conferences. He is a professional society member for ISTE, IACIST and IAENG. He has published more than 15 articles in National and International journals, 10 articles in conference proceedings and one article in book chapter. He has filed Indian patent in IoT Applications. His Research interest includes Mobile Adhoc Networking and IoT.