Handbook of Research on AI and ML for Intelligent Machines and Systems

The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. This handbook bridges the gap by presenting a comprehensive understanding of this fusion and its implications for the field. This book delves into the world of intelligent machines, revealing how they interact autonomously with their environment and adapt seamlessly to new situations. By harnessing the power of AI and ML, these smart devices can accomplish complex tasks such as traffic monitoring, speech recognition, face recognition, and automatic manufacturing, significantly enhancing operational efficiency. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths. Cover Title Page Copyright Page Book Series Mission Coverage Quotes and Testimonials Dedication Preface Organization of Book Acknowledgement Chapter 1: Conceptualising the Role of Intellectual Property and Ethical Behaviour in Artificial Intelligence ABSTRACT INTRODUCTION 1. UNDERSTANDING INTELLECTUAL PROPERTY 2. ETHICAL CONSIDERATIONS AND CHALLENGES IN AI 3. LEGAL PERSPECTIVES, POLICIES, AND CURRENT STRATEGIES OF IP IN AI 4. LEGAL PERSPECTIVES, POLICIES, AND CURRENT STRATEGIES TO PROMOTE ETHICAL AI 5. BALANCING IP RIGHTS AND ETHICAL CONSIDERATIONS IN AI 6. CASE STUDY: INTERPLAY OF IP AND ETHICAL BEHAVIOUR IN AI-DRIVEN HEALTHCARE SECTOR CONCLUSION REFERENCES Chapter 2: Measuring Throughput and Latency of Machine Learning Techniques for Intrusion Detection ABSTRACT INTRODUCTION BACKGROUND MATERIALS AND METHOD RESULTS EVALUATION OF RESULTS CONCLUSION REFERENCES Chapter 3: Securing Digital Ecosystems ABSTRACT INTRODUCTION A FULLY DECENTRALISED ENVIRONMENT CONCLUSION REFERENCES KEY TERMS AND DEFINITIONS Chapter 4: IoT-Based Economic Flame Detection Device for Safety ABSTRACT 1 INTRODUCTION 2 LITERATURE REVIEW 3 PROBLEM STATEMENT AND OBJECTIVE 4 RESEARCH METHODOLOGY 5 RESULTS AND DISCUSSION 6 CONCLUSION 7 FUTURE SCOPE REFERENCES Chapter 5: Human Face Mask Detection Using YOLOv7+CBAM in Deep Learning ABSTRACT INTRODUCTION LITERATURE REVIEW METHODOLOGY RESULT ANALYSIS CONCLUSION REFERENCES Chapter 6: The Role of AI in Improving Interaction With Cultural Heritage ABSTRACT INTRODUCTION BACKGROUND THE ROLE OF AI IN IMPROVING THE INTERACTION WITH USERS WITH CULTURAL HERITAGE EVALUATION MEASURES FOR ARTIFICIAL INTELLIGENCE ALGORITHMS CONCLUSION AND FUTURE DIRECTIONS REFERENCES Chapter 7: Machine Learning Approach for Robot Navigation Using Motor Imagery Signals ABSTRACT INTRODUCTION LITERATURE SURVEY PROPOSED WORK EXPERIMENTAL RESULTS CONCLUSION AND FUTURE WORK REFERENCES Chapter 8: Cloud Solutions for Smart Parking and Traffic Control in Smart Cities ABSTRACT INTRODUCTION SMART CITIES AND URBAN MOBILITY CLOUD COMPUTING IN URBAN MOBILITY SMART PARKING SOLUTIONS INTELLIGENT TRAFFIC CONTROL SYSTEMS INTEGRATION OF CLOUD AND IOT FOR URBAN MOBILITY CHALLENGES AND CONSIDERATIONS FUTURE DIRECTIONS AND TRENDS CONCLUSION REFERENCES LIST OF ACRONYMS Chapter 9: Building Sustainable Smart Cities Through Cloud and Intelligent Parking System ABSTRACT INTRODUCTION SMART CITIES AND SUSTAINABILITY CLOUD COMPUTING IN SMART CITIES INTELLIGENT PARKING SYSTEMS INTEGRATING CLOUD AND INTELLIGENT PARKING SYSTEMS ADVANTAGES FOR SUSTAINABLE SMART CITIES FUTURE TRENDS AND PROSPECTS CONCLUSION REFERENCES APPENDIX: GLOSSARY OF TERMS Chapter 10: A Study on AI and Blockchain-Powered Smart Parking Models for Urban Mobility ABSTRACT INTRODUCTION SMART PARKING: A NECESSITY IN MODERN CITIES FOUNDATIONS OF AI IN SMART PARKING BLOCKCHAIN TECHNOLOGY FOR PARKING INTEGRATION OF AI AND BLOCKCHAIN IN SMART PARKING EXPERIMENTAL FRAMEWORK RESULTS AND INSIGHTS CASE STUDY: STREAMLINING URBAN PARKING WITH AI AND BLOCKCHAIN IN CITY CHALLENGES AND FUTURE DIRECTIONS CONCLUSION REFERENCES APPENDIX Chapter 11: Machine Learning and Deep Learning for Intelligent Systems in Small Aircraft Applications ABSTRACT INTRODUCTION MACHINE LEARNING FOUNDATIONS DEEP LEARNING ESSENTIALS SMALL AIRCRAFT AUTOPILOT SYSTEMS AUTOMATION IN AVIATION ENHANCED NAVIGATION AND GUIDANCE SYSTEMS FAULT DETECTION AND PREDICTIVE MAINTENANCE PILOT ASSISTANCE AND HUMAN-MACHINE INTERACTION SUMMARY REFERENCES Chapter 12: Machine Learning in E-Health and Digital Healthcare ABSTRACT INTRODUCTION MACHINE LEARNING E-HEALTH AND DIGITAL HEALTHCARE LANDSCAPE DIGITAL HEALTHCARE TECHNOLOGIES THE ROLE OF DATA IN HEALTHCARE TRANSFORMATION APPLICATIONS OF MACHINE LEARNING IN HEALTHCARE PRACTICAL STRATEGIES FOR IMPLEMENTATION CASE STUDIES Challenges and Ethical Considerations FUTURE TRENDS AND INNOVATIONS SUMMARY REFERENCES List of Abbreviations Chapter 13: Unsupervised Learning Techniques for Vibration-Based Structural Health Monitoring Systems Driven by Data ABSTRACT INTRODUCTION FEATURE EXTRACTION TECHNIQUES SHM UNSUPERVISED LEARNING BASED ON ARTIFICIAL NEURAL NETWORKS NOVELTY DETECTION TECHNIQUES FUTURE CHALLENGES AND DISCUSSIONS CONCLUSION REFERENCES Chapter 14: Convergence of Data Science-AI-Green Chemistry-Affordable Medicine ABSTRACT INTRODUCTION DATA SCIENCE AND AI IN DRUG DISCOVERY GREEN CHEMISTRY PRINCIPLES IN PHARMACEUTICAL PRODUCTION CHALLENGES AND OPPORTUNITIES IN AFFORDABLE MEDICINE INTEGRATION OF DATA SCIENCE, AI, AND GREEN CHEMISTRY FOR AFFORDABLE DRUG DEVELOPMENT PERSONALIZED MEDICINE AND AFFORDABILITY GLOBAL COLLABORATION AND REGULATORY CONSIDERATIONS FUTURE TRENDS AND EMERGING TECHNOLOGIES CONCLUSION REFERENCES ABBREVIATION LIST Chapter 15: Intelligent Machines, IoT, and AI in Revolutionizing Agriculture for Water Processing ABSTRACT INTRODUCTION SIGNIFICANCE OF INTELLIGENT MACHINES, IOT, AND AI IN AGRICULTURE CHAPTER OBJECTIVES WATER RESOURCES IN AGRICULTURE INTELLIGENT MACHINES IN AGRICULTURE INTERNET OF THINGS (IOT) IN AGRICULTURE ARTIFICIAL INTELLIGENCE (AI) IN AGRICULTURE BENEFITS AND CHALLENGES CHALLENGES AND SOLUTIONS CASE STUDIES CONCLUSION REFERENCES APPENDIX: LIST OF ABBREVIATIONS Chapter 16: A Mixture Model for Fruit Ripeness Identification in Deep Learning ABSTRACT INTRODUCTION RELATED WORK METHODOLOGY RESULTS CONCLUSION REFERENCES Chapter 17: YOLO Models for Fresh Fruit Classification From Digital Videos ABSTRACT INTRODUCTION RELATED WORK OUR WORK RESULT ANALYSIS MAJORITY VOTE ALATION STUDY CONCLUSION REFERENCES Compilation of 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