AI and IoT in Engineering, Life Science, and Healthcare presents an integrated, application-focused exploration of how intelligent algorithms and connected sensing systems are jointly designed, deployed, and evaluated to solve real-world challenges across engineering workflows, biological research, and clinical practice.
Readers will gain a clear, practice-oriented understanding of how to build end-to-end solutions―from data acquisition with IoT devices to model development, deployment, and validation―supported by concise explanations, case studies, and reproducible workflows. The book explains how to select appropriate sensors, design data pipelines, apply learning models, and assess performance using relevant metrics, while addressing interoperability, scalability, and reliability. It also covers implementation considerations such as edge versus cloud processing, system integration, and lifecycle management. By combining conceptual clarity with step-by-step examples and applied scenarios, the book enables readers to move from theory to working prototypes and informed decision-making.
This book is intended for senior undergraduate and postgraduate students in engineering, biomedical sciences, and health informatics, as well as researchers, practitioners, and professionals seeking to apply connected intelligent systems in applied settings. It is also suitable for educators and industry engineers looking for a structured reference that bridges disciplines and emphasizes practical deployment.
Key Features:
• End-to-end coverage from IoT data acquisition to model deployment and evaluation
• Cross-disciplinary case studies spanning engineering systems, life sciences, and healthcare
• Practical workflows with implementation guidance for edge and cloud environments
• Emphasis on system integration, scalability, and real-world constraints
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Chadi Altrjman received his Bachelor of Engineering from the University of Waterloo, Ontario, Canada, and is working as an associate researcher with Near East University, Cyprus. And now, he is involved in several smart projects via which he is expanding his practical skills. His research interests include AI and machine learning, wireless sensor networks, chemical sensors, sustainable and renewable energy integration, distributed power generation, and smart engineering applications.
Sinem Alturjman worked as a lecturer and research associate at Middle East Technical University, North Cyprus, and at Antalya Bilim University, Antalya, Turkey. She is working in the area of Intelligent Internet of Things and AI-driven solutions. Mrs. Alturjman obtained her bachelor’s degree in Mathematical Science from Akdeniz University, Antalya, Turkey, in 2014. She also obtained her master’s degree in information systems engineering from Near East University, Mersin 10, Turkey. She is very interested in teaching math-related and computing courses. She has taken advanced courses in computing, mathematics, statistics, cryptography, and cutting-edge technologies and has sufficient academic knowledge in handling the academic departmental demands. In addition, she has sufficient expertise with YÖK academics and students’ registration systems such as Moodle and others. Her research interests span a variety of applied math applications and AI-driven techniques toward realizing smart environments and intelligent information systems.
Zuheir N. Khlaif is an accomplished educational technology researcher specializing in emerging technologies, including generative AI and immersive extended reality, with a focus on their application in teaching, assessment, and professional development. He serves as Deputy Editor-in-Chief for An-Najah University Journal – Humanities, indexed in Scopus, and has authored over 50 academic papers and seven books published by renowned publishers. Dr. Khlaif is a seasoned educator and trainer, having led workshops and training sessions for faculty in the Global South on AI integration in education and assessment. He is dedicated to advancing quality education, aligning his research with sustainability goals and fostering innovation in higher education.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. AI and IoT in Engineering, Life Science, and Healthcare presents an integrated, application-focused exploration of how intelligent algorithms and connected sensing systems are jointly designed, deployed, and evaluated to solve real-world challenges across engineering workflows, biological research, and clinical practice.Readers will gain a clear, practice-oriented understanding of how to build end-to-end solutionsfrom data acquisition with IoT devices to model development, deployment, and validationsupported by concise explanations, case studies, and reproducible workflows. The book explains how to select appropriate sensors, design data pipelines, apply learning models, and assess performance using relevant metrics, while addressing interoperability, scalability, and reliability. It also covers implementation considerations such as edge versus cloud processing, system integration, and lifecycle management. By combining conceptual clarity with step-by-step examples and applied scenarios, the book enables readers to move from theory to working prototypes and informed decision-making.This book is intended for senior undergraduate and postgraduate students in engineering, biomedical sciences, and health informatics, as well as researchers, practitioners, and professionals seeking to apply connected intelligent systems in applied settings. It is also suitable for educators and industry engineers looking for a structured reference that bridges disciplines and emphasizes practical deployment.Key Features: End-to-end coverage from IoT data acquisition to model deployment and evaluation Cross-disciplinary case studies spanning engineering systems, life sciences, and healthcare Practical workflows with implementation guidance for edge and cloud environments Emphasis on system integration, scalability, and real-world constraints AI and IoT in Engineering, Life Science, and Healthcare presents an integrated, application-focused exploration of how intelligent algorithms and connected sensing systems are jointly designed, deployed, and evaluated to solve real-world challenges across engineering workflows, biological research, and clinical practice. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781041076438
Quantité disponible : 1 disponible(s)
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. AI and IoT in Engineering, Life Science, and Healthcare presents an integrated, application-focused exploration of how intelligent algorithms and connected sensing systems are jointly designed, deployed, and evaluated to solve real-world challenges across engineering workflows, biological research, and clinical practice.Readers will gain a clear, practice-oriented understanding of how to build end-to-end solutionsfrom data acquisition with IoT devices to model development, deployment, and validationsupported by concise explanations, case studies, and reproducible workflows. The book explains how to select appropriate sensors, design data pipelines, apply learning models, and assess performance using relevant metrics, while addressing interoperability, scalability, and reliability. It also covers implementation considerations such as edge versus cloud processing, system integration, and lifecycle management. By combining conceptual clarity with step-by-step examples and applied scenarios, the book enables readers to move from theory to working prototypes and informed decision-making.This book is intended for senior undergraduate and postgraduate students in engineering, biomedical sciences, and health informatics, as well as researchers, practitioners, and professionals seeking to apply connected intelligent systems in applied settings. It is also suitable for educators and industry engineers looking for a structured reference that bridges disciplines and emphasizes practical deployment.Key Features: End-to-end coverage from IoT data acquisition to model deployment and evaluation Cross-disciplinary case studies spanning engineering systems, life sciences, and healthcare Practical workflows with implementation guidance for edge and cloud environments Emphasis on system integration, scalability, and real-world constraints AI and IoT in Engineering, Life Science, and Healthcare presents an integrated, application-focused exploration of how intelligent algorithms and connected sensing systems are jointly designed, deployed, and evaluated to solve real-world challenges across engineering workflows, biological research, and clinical practice. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781041076438
Quantité disponible : 1 disponible(s)