This book presents the overall technology spectrum in artificial intelligence (AI) and the Fourth Industrial Revolution, which is set to revolutionize the world. It discusses their various aspects and related case studies from industry, academics, administration, law, finance, and accounting as well as educational technology. The contributors, who are experts in their respective fields and from industry and academia, focus on a gesture-recognition prototype for specially abled people; jurisprudential approach to AI and legal reasoning; automated chatbot for autism spectrum disorder using AI assistance; Big Data analytics and Internet of Things (IoT); role of AI in advancement of drug discovery; development, opportunities, and challenges of the Fourth Industrial Revolution; legal, ethical, and policy implications of AI; Internet of Health Things for smart healthcare and digital wellbeing; machine learning and computer vision; computer vision-based system for automation and industrial applications; AI-IoT in home-based healthcare; and AI in super-precision human brain and spine surgery. Buttressed with comprehensive theoretical, methodological, well-established, and validated empirical examples, the book covers the interests of a broad audience from basic science to engineering and technology experts and learners. It will be greatly helpful for CEOs, entrepreneurs, academic leaders, researchers, and students of engineering, biomedicine, and master’s programs in science as well as the vast workforce and students with technical or non-technical backgrounds. It also serves common public interest by presenting new methods to improve the quality of life in general, with a better integration into society.
Author(s): Utpal Chakraborty, Amit Banerjee, Jayanta Kumar Saha, Niloy Sarkar, Chinmay Chakraborty
Publisher: Jenny Stanford Publishing
Year: 2022
Language: English
Pages: 311
City: Singapore
Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Section I: AI in Industry 4.0
Chapter 1: Computer Vision–Based System for Automation and Industrial Applications
1.1: Introduction
1.2: Previous Research
1.3: AOI System Application on a Scanning Machine
1.3.1: Detecting Rubber Keypads Defects on a Scanning Machine
1.3.2: Theoretical Framework, Materials, and Methods
1.3.2.1: Mobile image processing unit
1.3.2.2: Image calibration
1.3.2.3: Image segmentation
1.3.2.4: Automatic defect detection algorithm
1.3.2.5: Results and discussion
1.4: AOI System Application on Electronic Boards
1.4.1: Detecting Defects on Electronic Boards
1.4.2: Theoretical Framework, Materials, and Methods
1.4.2.1: Mobile image processing unit
1.4.2.2: Image calibration
1.4.2.3: Editing and automatic defect detection algorithm
1.4.2.4: Result and discussion
1.5: Conclusions
Chapter 2: Opportunities and Challenges of the Fourth Industrial Revolution
2.1: Introduction
2.2: Evolving Fields in the Fourth Industrial Revolution
2.3: Artificial Intelligence: Technology Driving Change
2.4: Relationship between Artificial Intelligence, Deep Learning, and Machine Learning
2.4.1: Machine Learning
2.4.1.1: Types of machine learning
2.4.1.2: Types of reinforcement learning
2.4.1.3: Applications of reinforcement learning
2.4.2: Deep Learning
2.4.2.1: Role of deep learning in big data
2.4.2.2: Deep learning applications for big data analytics
2.5: AI Challenges by Potential Environmental Areas
2.5.1: Climate Modeling
2.5.2: Clean Oceans
2.5.3: Water Preservation
2.5.4: Weather and Disaster Management
2.6: Emerging Technologies
2.6.1: Key Drivers
2.6.1.1: Digitization/integration of value chains
2.6.1.2: Digitization of product and service offerings
2.6.1.3: Digital business models and customer access
2.7: The Role of Robotics in the 4IR
2.7.1: Applications of AI and Robotics
2.8: Conclusion
2.9: Future Scope
Chapter 3: Role of AI in the Advancement of Drug Discovery and Development
3.1: Introduction
3.2: Artificial Intelligence
3.3: Machine Learning and Deep Learning in Artificial Intelligence
3.4: Application of Machine Learning in Pharmaceutical Science
3.4.1: Disease Identification and Diagnosis
3.4.2: Drug Discovery and Manufacturing
3.4.3: Smart Electronic Health Records
3.5: Building an AIF
3.6: Classification of Artificial Intelligence
3.6.1: Type 1
3.6.2: Type 2
3.7: General Aspects of AI
3.7.1: AI Use in Drug Development: R&D Proficiency
3.7.2: Application of AI in Drug Designing
3.7.2.1: Protein-protein interaction modeling
3.7.2.2: Virtual screening
3.7.2.3: Quantitative structure-activity relationship
3.7.2.4: Assessment of ADME
3.7.2.5: Drug repurposing/drug reposing
3.7.2.6: De novo drug design
3.8: Challenges and Limitations of AI
3.9: Conclusion
Section II: Internet of Medical Things (IoMT)
Chapter 4: Internet of Health Things: Opportunities and Challenges
4.1: Introduction: Health System
4.1.1: Health Information Revolution
4.1.2: Health Workforce and Task Shifting
4.1.3: Digitization: Hope, Hype, and Harm
4.2: Internet of Health Things
4.2.1: Opportunities
4.2.2: Applications
4.2.3: Describing a Maternal Health Use Case
4.2.4: Challenges
4.2.5: Limitations
4.3: Modeling an IoHT
4.3.1: Service Implementation
4.3.2: Electric Power Module
4.3.3: Networking Module
4.3.4: Server Architecture
4.3.5: Application Module
4.3.6: User Journey
4.4: Conclusion and Future Perspective
Chapter 5: Internet of Things for Smart Healthcare and Digital Well-Being
5.1: Introduction
5.2: Internet of Things
5.3: Technologies behind IoT
5.3.1: Cloud Computing
5.3.2: Sensors
5.3.3: Location
5.3.4: Communication
5.3.5: Identification
5.4: Healthcare and the Internet of Things
5.5: Internet of Things for Health
5.5.1: Digital Wellness
5.5.2: Continuous Health Monitoring
5.5.3: Easy Way of Continuous TREWS
5.6: Integration of Different Disciplines of Science toward Better Application of AI and IOT
5.7: AI: Major Areas of Application in the Health Field
5.8: Present Applications of AI in Healthcare
5.9: Conclusion and Future Work
Chapter 6: Automated Chatbots for Autism Spectrum Disorder Using AI Assistance
6.1: Introduction to Autism
6.1.1: Need to Study Autism
6.1.2: Identification Symptoms
6.1.3: Challenges Faced in a Community
6.1.3.1: Challenges in verbal communication
6.1.3.2: Challenges in nonverbal communication
6.2: Behavior of Autistic Children
6.2.1: Reasons for Autism
6.2.2: Other Reasons That Contribute to ASD
6.2.3: Negligence during Pregnancy
6.2.4: Formative Screening Assessment
6.2.5: Exhaustive Diagnostic Evaluation
6.2.6: Associated Medical and Mental Health Conditions
6.3: Financial Burden on the Families and Effect on the Economy of a Country
6.3.1: World Status on Autism
6.4: Artificial Intelligence and Machine Learning
6.4.1: Machine Learning
6.4.2: Interchange of AI and Machine Learning
6.5: Autism, AI, and Machine Learning
6.5.1: JIBO-Human ROBO
6.5.2: Autism Study Using ROBO
6.5.3: Autism Prediction Using ML Algorithms
6.5.4: Chatbot
6.5.4.1: Algorithm to create a simple chatbot
6.5.4.2: Process to create a chatbot
6.5.4.3: Framework of the chatbot
6.5.5: Role of AI Chatbots
6.5.6: Chatbot Model
6.5.6.1: Creating a chatbot for diagnosis
6.5.6.2: Creating a simple text chat
6.5.6.3: Creating a dashboard and a 3D chatbot model
6.6: Conclusion
6.7: Future Scope
Chapter 7: Emergence of Artificial Intelligence and Its Legal Impact
7.1: Introduction
7.2: What Is Artificial Intelligence?
7.3: Why Artificial Intelligence Is Necessary for Study?
7.3.1: Jurisprudence Analysis of Artificial Intelligence
7.3.2: AI Technologies and Liability
7.4: Rights, Duties, and Liabilities of the AI Inventor
7.4.1: Ethical Responsibilities
7.4.2: Criminal, Civil, and Constitutional Responsibility of the Inventor and AI
7.5: Civil Remedies under the Law of Torts
7.5.1: Principle of Res Ipsa Loquitur
7.5.2: Compensation under the Law of Tort
7.5.2.1: General damages
7.5.2.2: Special damages
7.5.2.3: Common principles for the contemplation of damages
7.5.2.4: Standard principles for granting any damages
7.6: Liability under Criminal Law
7.7: Challenges Ahead
7.8: Conclusion
Chapter 8: Jurisprudential Approach to Artificial Intelligence and Legal Reasoning
8.1: Introduction
8.2: History and Origin of Artificial Intelligence and Law
8.3: Types of Nonhuman Computational Capabilities
8.4: Introduction of Artificial Intelligence to Law
8.5: Do We Have Any International Regulation on Artificial Intelligence?
8.6: Should Artificial Intelligence Be Taught to Law Students?
8.7: Story of IBM’s Watson and Law Firms
8.8: ROSS: A New Venture of AI
8.9: Law Practicum and Artificial Intelligence
8.10: Methods of Computation for Developing Reasoning with Legal Rules and Cases
8.11: Scheme of Argument and Legal Reasoning
8.12: Reasoning with Open-Textured Texts
8.13: Reasoning with Cases, Hypothetical Situations, and Precedence Citing
8.14: MOOCs: Is It an Example of an Intelligent Tutorial System Coupled with Ethics?
8.15: What Future Do We See of Legal Reasoning Associated with Artificial Intelligence?
8.16: Conclusion
Chapter 9: Legal Ethical and Policy Implications of Artificial Intelligence
9.1: Introduction
9.2: Genesis and Concept of AI
9.3: Ethics and Artificial Intelligence
9.4: AI and Its Challenges
9.5: Issues of Human Rights, Governance, and AI
9.6: Destiny of Humanity in the World of AI
9.7: Laws and Policies Related to AI
9.8: Concluding Remarks
Index
