Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing industries, reshaping the way we interact with technology, and driving innovation across multiple disciplines. Advancements in Artificial Intelligence and Machine Learning is a comprehensive exploration of the latest developments, applications, and challenges in AI and ML, offering insights into cutting-edge research and real-world implementations.
This book is a collection of twelve chapters, each exploring a distinct application of Artificial Intelligence (AI) and Machine Learning (ML). It begins with an overview of AI’s transformative role in Next-Gen Mechatronics, followed by a comprehensive review of key advancements and trends in the field. The book then examines AI’s impact across diverse sectors, including energy, digital communication, and security, with topics such as AI-based aging analysis of power transformer oil, AI in social media management, and AI-driven human detection systems.
Further chapters address sentiment analysis, visual analysis for image processing, and the integration of AI in smart grid networks. The volume also covers AI applications in hardware security for wireless sensor networks, drone robotics, and crime prevention systems. The final set of chapters highlights AI’s role in healthcare and automation, including an AI-assisted system for women’s safety in India and the use of EfficientNet B0 CNN architecture for brain tumor detection and classification.
Together, these chapters showcase the versatility and growing influence of AI and ML across critical modern industries.
Key Features:
- A multidisciplinary approach covering AI applications in robotics, cybersecurity, healthcare, and digital transformation in 12 organized chapters.
- A focus on contemporary challenges and solutions in AI and ML across industries.
- Research-driven insights from experts and practitioners in the field.
- Practical discussions on AI-driven automation, security, and intelligent decision-making systems.
Table of Contents
Chapter 1: Next-Gen Mechatronics: The Role of Artificial Intelligence
- Introduction
- Overview of Artificial Intelligence
- Machine Learning (ML)
- Deep Learning (DL)
- Natural Language Processing (NLP)
- Computer Vision
- Robotics
- Expert Systems
- Data Science
- Explainable AI
- Applications of AI in Mechatronics
- Robotics
- Self-Driving Vehicles
- Smart Manufacturing
- Healthcare
- Challenges in AI-Mechatronics Integration
- Multidisciplinary Coordination
- Handling Complexity
- Real-Time Processing
- Sensor Fusion
- Robustness and Adaptability
- Safety and Reliability
- Data Efficiency and Privacy
- Integration With Legacy Systems
- Data Availability
- Safety and Reliability
- Ethical Considerations
- Future Prospects
- Explainable AI
- Cognitive Mechatronics
- Swarm Robotics
- Conclusion
- References
Chapter 2: Advancements and Applications of Artificial Intelligence And Machine Learning: A Comprehensive Review
- Introduction
- Background
- Objectives
- Structure of the Paper
- Evolution of Artificial Intelligence
- Early Developments
- Emergence of Machine Learning
- Deep Learning Revolution
- Principal Concepts in Artificial Intelligence
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Deep Learning Architectures
- Natural Language Processing
- Computer Vision
- Recent Advancements in AI and Ml
- Recent Advancements in NLP and Computer Vision
- Applications of Ml in AI
- Applications of AI in Healthcare
- AI in Finance
- Transportation and Autonomous Systems
- AI in Entertainment and Gaming
- Challenges and Ethical Considerations
- Future Directions and Opportunities
- Conclusion
- References
Chapter 3: AI-Based Aging Analysis of Power Transformer Oil
- Introduction
- Properties of Transformer Oil
- Electrical Properties
- Electrical Breakdown Voltage (BDV)
- Resistivity
- Dielectric Dissipation Factor (Tan Delta)
- Physical Properties
- Water Content
- Interfacial Tension
- Flash Point
- Viscosity
- Pour Point
- Chemical Properties
- Neutralization Value
- Corrosive Sulphur
- Basics of “Ann” and “Anfis” Methods
- Development of Ann Model for Age Prediction of Oil
- Simulation Results of “Ann Model
- Development of “Anfis” Model for Age Prediction of Oil
- Simulation Results of “Anfis” Model
- Comparison of “Ann” and “Anfis” Model
- Conclusion
- References
Chapter 4: Artificial Intelligence and Social Media: Strength, Management and Responsibility
- Introduction
- Communication and Connectivity
- Information Dissemination
- Cultural Impact
- Political Impact
- Economic Influence
- Mental Health
- Privacy and Security
- The Role of Social Media and Its Impact on Societies
- Different Ways Through Which Societies Can Be Manipulated
- Social Media and Online Platforms
- Stories and Edited Video Content
- Political Interference
- Dissemination of False Information
- Manipulation Through Deepfakes
- Monetary Policies
- Essential Characteristics of Manipulation
- Deception
- Control
- Exploitation
- Planning With a Strategic Approach
- Exerting An Impact on Emotions
- Manipulation and AI
- Addressing Digital Manipulation
- Critical Thinking and Media Literacy
- Verify Information
- Check URLs and Sources
- Be Skeptical of Emotional Appeals
- Update Privacy Settings
- Use Strong Passwords and Enable Two-Factor Authentication
- Stay Informed About Digital Threats
- Disinformation Detection and Combating Disinformation
- Ethical Obligations and Societal Responsibilities of AI
- Developers
- Transparency and Responsibility
- Equity and Impartiality
- Privacy
- Security
- Empowering Users
- Evaluation of Societal Repercussions
- Ongoing Observation and Enhancement
- Cooperation and the Exchange of Knowledge
- Societal Responsibilities of Regulatory Bodies
- Implementation of Criteria
- Safeguarding the Rights and Interests of Consumers
- Ensuring the Safety of the Public
- Ethical Reflections
- Promotion of Knowledge and Consciousness
- Engagement With Global Organizations
- Conclusion
- References
Chapter 5: Recent Trends in AI-Driven Human Detection Tactics
- Introduction
- Classification of Human Detection Techniques
- Classifiers
- Naive Bayes Classifier (Generative Learning Model)
- Nearest Neighbor
- Logistic Regression (Predictive Learning Model)
- Decision Trees
- Random Forest
- Neural Network
- Datasets for Human Detection
- Future Research Opportunities
- Exploring Fuzzy Logic in Human Detection
- Neutrosophic Deep Learning Architectures for Multimodal Human Detection
- Adaptive Fusion of Fuzzy and Neutrosophic Techniques
- Explainable AI for Human Detection
- Cross-Domain Transfer Learning With Fuzzy and Neutrosophic Models
- Combating Cyber Attacks in Human Detection Systems
- Conclusion
- References
Chapter 6: A Review of Sentiment Analysis Opinion Mining and Using Machine Learning
- Introduction
- Sentiment Analysis
- Sentiment Analysis Applications
- Role of Machine Learning in Sentiment Analysis
- Review of Literature
- Comparative Analysis
- Methods and Approaches Used for Sentiment Analysis
- Machine Learning Techniques
- Naïve Bayes (NB)
- Support Vector Machine (SVM)
- Decision Tree (DT)
- Dataset Domain
- Challenges of Sentiment Analysis
- Conclusion and Future Scope
- References
Chapter 7: State-Of-The-Art Techniques in Visual Analysis for Image Processing and Pattern Recognition: A Systematic Review
- Introduction
- Overview of Image Processing and Pattern Recognition
- Importance
- Applications
- Fundamentals of Image Processing
- Basics of Digital Images
Author
- Asif Khan
- Mohammad Kamrul Hasan
- Naushad Varish
- Mohammed Aslam Husain
