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    Advances in Artificial Intelligence Applications in Industrial and Systems Engineering

    AvGavriel (Purdue University) Salvendy,Waldemar (University of Central Florida) Karwowski

    Inbunden, Engelska, 2025

    Del i serien Advances in Industrial and Systems Engineering

    1 258 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Comprehensive guide offering actionable strategies for enhancing human-centered AI, efficiency, and productivity in industrial and systems engineering through the power of AI. Advances in Artificial Intelligence Applications in Industrial and Systems Engineering is the first book in the Advances in Industrial and Systems Engineering series, offering insights into AI techniques, challenges, and applications across various industrial and systems engineering (ISE) domains. Not only does the book chart current AI trends and tools for effective integration, but it also raises pivotal ethical concerns and explores the latest methodologies, tools, and real-world examples relevant to today’s dynamic ISE landscape. Readers will gain a practical toolkit for effective integration and utilization of AI in system design and operation. The book also presents the current state of AI across big data analytics, machine learning, artificial intelligence tools, cloud-based AI applications, neural-based technologies, modeling and simulation in the metaverse, intelligent systems engineering, and more, and discusses future trends. Written by renowned international contributors for an international audience, Advances in Artificial Intelligence Applications in Industrial and Systems Engineering includes information on: Reinforcement learning, computer vision and perception, and safety considerations for autonomous systems (AS)(NLP) topics including language understanding and generation, sentiment analysis and text classification, and machine translationAI in healthcare, covering medical imaging and diagnostics, drug discovery and personalized medicine, and patient monitoring and predictive analysisCybersecurity, covering threat detection and intrusion prevention, fraud detection and risk management, and network securitySocial good applications including poverty alleviation and education, environmental sustainability, and disaster response and humanitarian aid.Advances in Artificial Intelligence Applications in Industrial and Systems Engineering is a timely, essential reference for engineering, computer science, and business professionals worldwide.

    Produktinformation

    • Utgivningsdatum:2025-09-08
    • Mått:193 x 236 x 31 mm
    • Vikt:794 g
    • Format:Inbunden
    • Språk:Engelska
    • Serie:Advances in Industrial and Systems Engineering
    • Antal sidor:400
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394257065

    Utforska kategorier

    • Teknik: allmänt inom Naturvetenskap och teknik
    • Artificiell intelligens inom Data och IT
    • Tillverkningsteknik inom Naturvetenskap och teknik

    Mer om författaren

    WALDEMAR KARWOWSKI is a Pegasus Professor and Chair in the Department of Industrial Engineering and Management Systems at the University of Central Florida. He is an elected member of The Academy of Science, Engineering and Medicine of Florida (ASEMFL). VINCENT DUFFY is a Professor of Industrial Engineering and Agricultural & Biological Engineering at Purdue University and a Fulbright Senior Scholar. GAVRIEL SALVENDY is a University Distinguished Professor at the University of Central Florida, a member of the National Academy of Engineering, and founding Department Head of Industrial Engineering at Tsinghua University in China.

    Innehållsförteckning

    • About the Editors xxiiiPreface xxv1 Introduction to Industrial Artificial Intelligence 1Dai-Yan Ji, Hanqi Su, Takanobu Minami, and Jay Lee, USA1.1 Fundamental Problems in Industry 11.2 The Purpose of Industrial AI 21.3 Difference Between AI and Industrial AI 41.4 Definition and Meaning of Industrial AI 51.5 Key Elements in Industrial AI: ABCDE 71.6 CPS Framework for Industrial AI 81.7 Technological Elements of CPS Framework 91.8 Developing Industrial AI Talents 101.9 Training Industrial AI Talents Using Open-source Datasets 101.10 Issues in Industrial AI 141.11 Conclusion 162 Autonomous Systems and Intelligent Agents 19Babak Ebrahimi Soorchaei, Arash Raftari, and Yaser Fallah, USA2.1 Definitions and Scopes 192.2 Core Concepts and Components 212.3 Applications and Case Study: Autonomous Vehicle 272.4 Challenges and Future Directions 373 Natural Language Processing for Industrial and Systems Engineering 43Daniel Braun, Germany3.1 Introduction 433.2 Advances and Trends in NLP 443.3 Domain-specific Challenges in ISE 473.4 Applications of NLP in ISE 503.5 Outlook 524 Smart Manufacturing, Robotics, and AI Systems 61Xifan Yao, Huifeng Yan, Jiajun Zhou, Yongxiang Li, and Hongnian Yu, China/UK4.1 Introduction to Smart Manufacturing 614.2 Smart Manufacturing System Integration and Interoperability 634.3 Robotics in Manufacturing 674.4 AI in Manufacturing 705 Artificial Intelligence in Healthcare 79Vinita Gangaram Jansari, USA5.1 History of Artificial Intelligence in Healthcare 795.2 New Age of Healthcare with the Use of AI 815.3 AI-enabled Medical Devices 855.4 Explainable AI for Healthcare 865.5 Medical Decision Support Systems 875.6 Precision/Personalized Medicine Using AI 885.7 Smart Healthcare 895.8 Healthcare 5.0 905.9 Ethics, Bias, and Fairness Constraints 945.10 Concluding Remarks 965.11 Future Directions 966 Artificial Intelligence in Cybersecurity for Industrial and Systems Engineering 111Robin Yeman, Hasan Yasar, Suzette Johnson, and Tracy Bannon, USA6.1 Introduction to Cybersecurity and Artificial Intelligence for Industrial and Systems Engineering 1116.2 Cyber Threat Landscape for CPS 1136.3 AI in Cybersecurity for CPS 1136.4 Risk Assessment, Compliance, and Regulatory Considerations 1156.5 Threat Detection and Prevention 1166.6 Incident Response and Management 1186.7 Anti-phishing 1206.8 Dependable Authentication 1206.9 Behavior Analytics 1216.10 Conclusion 1217 Artificial Intelligence in Defense 125Dylan Schmorrow, Robert Sottilare, Jack Zaientz, John Sauter, Randolph Jones, Charles Newton, Joseph Cohn, Jon Sussman-Fort, Robert Bixler, Brice Colby, Victor Hung, Jeffrey Craighead, Le Nguyen, and Ullice Pelican, USA7.1 Introduction 1257.2 Ethical Considerations and Challenges 1267.3 AI-driven Innovations in C2 Systems 1297.4 AI Applications in Uncrewed Systems 1327.5 Application of AI to Cyber Operations 1347.6 AI-enabled Training and Simulation Systems 1377.7 AI-enabled HMI Technologies 1437.8 Integrating Machine Reasoning and Explanation for Dynamic Decision-making 1467.9 Responsible AI in Predictive Systems and Medical/Defense Health Readiness 1487.10 Future Directions 1507.11 Conclusion 1548 AI-Driven Management and Modeling Decision Optimization as a Timely Opportunity at the US Department of Defense 159Link Parikh, USA8.1 Why Act Now and Why Engineering Lifecycle and AI? 1598.2 Who Needs to Make Changes in the Ecosystem? 1638.3 How to Implement the AI-driven Ecosystems Management and Modeling Regime 1678.4 Key Elements of AI-driven Ecosystem Management and Modeling 1698.5 Enhance Workforce Development and Mentorship 1788.6 When Can We Acquire Dramatic Speed and Precision? 1798.7 Which Elements Exist in "AI Ecosystem Management and Modeling?" 1798.8 Sample Applications of Dramatic Speed and Precision 1918.9 AI-driven Ecosystem Management and Modeling Solution and Toolset 1928.10 Summary 1949 Enhancing Cryptocurrency Market Forecasting: Advanced Machine Learning Techniques and Industrial Engineering Contributions 197Jannatun Nayeem Pinky and Ramya Akula, USA9.1 Introduction 1979.2 Background 1999.3 Methods 2019.4 Dataset 2249.5 Evaluation 2369.6 Limitations 2539.7 Future Recommendations 2549.8 Conclusion 25710 Artificial Intelligence in Aviation 263Dr. Dimitrios Ziakkas, USA10.1 Introduction to Artificial Intelligence in Aviation 26310.2 AI in Flight Operations and Training 26410.3 AI in Air Traffic Management 26710.4 AI in Airport Operations 26810.5 AI in Customer Experience and Service 27010.6 AI in Maintenance and Technical Support 27210.7 Human Factors and AI Integration 27410.8 Ethical and Regulatory Challenges 27510.9 AI Case Studies and Future Prospects 27610.10 The Future of AI in Aviation 27811 Enhancing Engineering Education: A Multimodal Approach to Personalization and Adaptation Using Artificial Intelligence in Game-based Learning 281Roger Azevedo, Daryn Dever, and Megan Wiedbusch, USA11.1 Context: Challenges in Engineering Education 28111.2 GBLEs for Engineering Education: Are They Effective? 28311.3 Personalization and Adaptivity in GBLEs 28411.4 Personalization and Adaptivity in GBLEs for Engineering Education: Are They Effective? 28411.5 Augmenting Personalization and Adaptivity in GBLEs in Engineering Education with Multimodal Trace Data28611.6 AI Techniques for Handling Multimodal Approaches to Individualization and Adaptation 28811.7 Essential SRL Processes from Multimodal Trace Data with GBLEs in Engineering Education 28911.8 Open Questions, Future Directions, and Conclusions 29712 Securing Artificial Intelligence Systems in the Era of Large Language Models 307Carmen-Gabriela Stefanita, USA12.1 The Need for an Artificial Intelligence Risk Management Framework in an Evolving Artificial Intelligence Landscape 30712.2 Security for AI Threat Model 31312.3 Implementing a Security for AI Framework 31712.4 Conclusion 32313 Responsible Artificial Intelligence Applications for Social Good 327Ozlem Garibay and Brent Winslow, USA13.1 Introduction 32713.2 Ethical Aspects of AI for Social Good Applications 32813.3 AI Applications for Healthcare 33113.4 AI for Environmental Sustainability 33513.5 AI for Education and Accessibility 33813.6 AI in Humanitarian Efforts and Disaster Response 34013.7 Conclusion 34214 Future Directions and Applications of Artificial Intelligence 355Ivan Garibay, Clayton Barham, Sina Abdidizaji, Chathura Jayalath, USA14.1 Introduction 35514.2 Emerging Trends of AI for Industrial Engineering 35614.3 Recent Applications 36014.4 Future Directions: Explainable AI for Industrial Engineering 36114.5 Case Study 365References 366Index 371