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The convergence of AI and the Internet of Things (IoT) is rapidly transforming the landscape of intelligent devices. As AI algorithms become more sophisticated and embedded in everyday objects, devices are empowered to learn from data and operate with minimal human intervention. This integration not only enhances operational efficiency and user experience but also paves the way for innovative applications across all sectors. Exploring AI advancements in IoT reveals the transformative potential and emerging challenges of a future shaped by intelligent, interconnected systems. AI Advancements in Internet of Things, Smart Healthcare, and Intelligent Devices presents a comprehensive exploration of the powerful convergence between AI, machine learning, and IoT, with a strong emphasis on their integration into intelligent devices. It not only explores foundational concepts but also addresses the practical challenges and opportunities in deploying intelligent systems at scale. Covering topics such as cloud computing, predictive maintenance, and software testing, this book is an excellent resource for academicians, researchers, students, engineers, technologists, policymakers, and more.

Muneer Khan is an accomplished professional innovator in the field of Electrical Engineering, with a strong background in both academia and industry. He holds a Master of Science in Electrical Engineering from Columbia University, specializing in intelligent and connected devices, sensors, Embedded AI, semiconductor physics, and integrated photonics. Khan has extensive experience in research and applied science, having worked as a Research Assistant at Columbia University’s Laboratory of Unconventional Electronics. He has completed internships in France and India. His work spans advanced technologies, including PCB design, machine learning algorithms, hardware inspection, and robotic sensors. In addition to his academic and research roles, Khan is a successful entrepreneur, having founded Cadre Technologies Services. His venture focuses on AI, machine learning, and assistive technologies. He has been recognized for his contributions to science and technology with numerous awards, including the Distinguished Young Scientist Award from the Government of India, the Engineering for Humanity Award in New York for his outstanding innovation for blind individuals, and multiple accolades from academic institutions. He won the First Position at the Wearable Innovation Forum 2025 at Cambridge University, UK, for his groundbreaking work in wearable assistive technology. Khan’s work has led to several patents, publications, and major funding, including the Engineering for Humanity Award 2025 for his startup. His technical skills span programming, circuit design, and advanced testing, and he continues to lead innovative projects and product developments worldwide.

Shantanu Awasthi has an extensive academic background, holding a Ph.D. in Mathematics from North Dakota State University, an M.S. in Mathematics from Virginia State University, and a B.Tech in Electronics and Communication Engineering from Maharaja Agrasen Institute of Technology. His professional experience spans several academic and industry roles, including positions as an Assistant Professor of Data Analytics at Missouri Southern State University and Data Science roles at various institutions, such as Sense 360 and the University of North Dakota. His research interests focus on stochastic processes, machine learning, and deep learning, with publications in journals like the Journal of Safety Research and the Journal of Stochastic Analysis. In addition to his research, Shantanu has presented his work at notable conferences, including the North American Meetings of the Regional Science Association International and the SIAM Northern States Section Student Chapter Conference. His teaching experience covers data science, statistics, and mathematics courses at multiple universities. He has also earned several honors, including a Graduate Student Travel Grant and a Department Research Award. Furthermore, he holds certifications in actuarial sciences, SAS programming, and deep learning.

Dr. Mohd Sakib is an Assistant Professor in the School of Computer Science at UPES University, Dehradun, India. He earned his Ph.D. in Computer Science from Aligarh Muslim University, specializing in ensemble learning, deep learning, and time-series analysis. Before joining UPES, he served as an Assistant Professor at Madanapalle Institute of Science & Technology (MITS), Andhra Pradesh, where he coordinated student holistic activities, NBA documentation, and national initiatives such as AICTE PARAKH. He has taught and supervised projects in areas including artificial intelligence, deep learning, and data science at both undergraduate and postgraduate levels. His research focuses on developing intelligent AI-driven models for forecasting, anomaly detection, and smart-energy systems. He has published widely in reputed Q1, SCI/SCIE, and Scopus-indexed journals and presented his work at IEEE international conferences. He actively contributes as a reviewer and technical-committee member for journals and conferences and serves on the editorial board of IGI Global. He has also edited and published two edited volumes with IGI Global. He is a Life Member of the Indian Society for Technical Education (ISTE) and regularly delivers invited talks and organizes faculty-development programs.

Mohammad Vaseem khan (B.Tech in ECE), M.Tech (Electronics) from University of Mumbai-Maharashtra, Gate-2004,2005,2014 Qualified), is a distinguished academician and researcher with over 16 years of experience in Electronics and Communication Engineering. Currently serving as Associate Professor at Bansal Institute of Engineering and Technology, Lucknow(UP,India), he has previously held key position including Head of Department and Assistant Controller of Examination in reputed institutions and Dean Academics at Rajkiya Engineering college Kannauj(UP,India). With expertise in signal processing, basic Electronics, signal systems, Electronics devices and circuits, robotics and IoT. He has significantly contributed to the field through his research on signal processing and IoT. His work has been published in prestigious international journals like IRJET and IJRASET. Beyond academia, his leadership in organizing technical events, state level competitions. A passionate educator and lifelong learner, He continue to inspire students and professionals with his initiative teaching methods.