Artificial Intelligence Development in Sensors and Computer Vision for Health Care and Automation Application explores the power of artificial intelligence (AI) in advancing sensor technologies and computer vision for healthcare and automation. Covering both machine learning (ML) and deep learning (DL) techniques, the book demonstrates how AI optimizes prediction, classification, and data visualization through sensors like IMU, Lidar, and Radar. Early chapters examine AI applications in object detection, self-driving vehicles, human activity recognition, and robot automation, featuring reinforcement learning and simultaneous localization and mapping (SLAM) for autonomous systems. The book also addresses computer vision techniques in healthcare and automotive fields, including human pose estimation for rehabilitation and ML in augmented reality (AR) for automotive design. This comprehensive guide provides essential insights for researchers, engineers, and professionals in AI, robotics, and sensor technology. Key Features: - In-depth coverage of AI-driven sensor innovations for healthcare and automation. - Applications of SLAM and reinforcement learning in autonomous systems. - Use of computer vision in rehabilitation and vehicle automation. - Techniques for managing prediction uncertainty in AI models.

Metal Complexes: Environmental and Biomedical Applications offers a comprehensive exploration of the role of metal complexes in diverse fields, including biomedicine, energy, and environmental protection. This book provides insights into the synthesis, properties, and applications of metal complexes, covering topics such as their use in therapeutics, diagnostics, energy materials, and catalysis. It also examines their antibacterial, antifungal, and sensor applications. With a systematic approach, the book is ideal for students, researchers, and professionals interested in the growing relevance of metal complexes in scientific and industrial applications. Key Features: - Overview of metal complexes and oxidation states. - Synthesis of metal complexes from N-heterocyclic carbene and Schiff base ligands. - Biomedical applications, including therapeutics and diagnostics. - Use of metal complexes in energy storage and catalysis. - Applications in antibacterial and antifungal treatments. - Metal complexes as sensors and in analytical chemistry.

Artificial Intelligence: A Multidisciplinary Approach towards Teaching and Learning explores the evolving role of AI in education, covering applications in fields such as bioinformatics, environmental science, physics, chemistry, economics, and language learning. Written by experts, this book provides a comprehensive overview of AI's integration into diverse subjects, offering insights into the future of AI in education and its potential to enhance academic research and pedagogy. Targeted at faculty, students, and professionals, the book addresses AI's role in blended learning environments and offers practical tools for educators seeking to incorporate AI into their teaching practices. Key Features: - Multidisciplinary exploration of AI in teaching and learning. - Practical tools and methodologies for educators. - Insights into AI-driven innovations in research. - Relevant to a broad audience, from students to professionals.

Smart Home and Industrial IoT Devices: Critical Perspectives on Cyber Threats, Frameworks and Protocols provides an in-depth examination of the Internet of Things (IoT) and its profound impact on smart homes and industrial systems. The book begins by exploring the significance of IoT in smart homes, followed by an analysis of emerging cyber threats targeting smart homes and cyber-physical systems. It presents AI and machine learning-based frameworks for monitoring water quality and managing irrigation in agriculture, highlighting their role in IoT ecosystems. The text also discusses a framework to mitigate cyber-attacks on robotic systems and introduces a multinomial naive Bayesian classifier for analyzing smart IoT devices. Dataflow analysis and modeling experiments are detailed, along with a comparison of IoT communication protocols using anomaly detection and security assessment. The book concludes with a discussion on efficient, lightweight intrusion detection systems and a unique taxonomy for IoT frameworks. This book is ideal for students, researchers, and professionals seeking to understand and secure IoT environments.

This book demonstrates several use cases of how artificial intelligence (AI) and machine learning (ML) are revolutionizing problem-solving across various industries. The book presents 18 edited chapters beginning with the latest advancements in human-AI interactions and neuromorphic computing, setting the stage for practical applications. Chapters focus on AI and ML applications such as fingerprint recognition, glaucoma detection, and lung cancer identification using image processing. The book also explores the role of AI in professional operations such as UX design, event detection, and content analysis. Additionally, the book includes content that examines AI's impact on technical operations wireless communication, VLSI systems, and advanced manufacturing processes. Each chapter contains summaries and references for addressing the needs of beginner and advanced readers. This comprehensive guide is an essential resource for anyone seeking to understand AI's transformative role in modern problem-solving in professional industries.

This handbook provides a comprehensive understanding of computational linguistics, focusing on the integration of deep learning in natural language processing (NLP). 18 edited chapters cover the state-of-the-art theoretical and experimental research on NLP, offering insights into advanced models and recent applications. Highlights: - Foundations of NLP: Provides an in-depth study of natural language processing, including basics, challenges, and applications. - Advanced NLP Techniques: Explores recent advancements in text summarization, machine translation, and deep learning applications in NLP. - Practical Applications: Demonstrates use cases on text identification from hazy images, speech-to-sign language translation, and word sense disambiguation using deep learning. - Future Directions: Includes discussions on the future of NLP, including transfer learning, beyond syntax and semantics, and emerging challenges. Key Features: - Comprehensive coverage of NLP and deep learning integration. - Practical insights into real-world applications - Detailed exploration of recent research and advancements through 16 easy to read chapters - References and notes on experimental methods used for advanced readers Ideal for researchers, students, and professionals, this book offers a thorough understanding of computational linguistics by equipping readers with the knowledge to understand how computational techniques are applied to understand text, language and speech.

This book explores the intersection of the Internet of Things (IoT) and Artificial Intelligence (AI) in sustaining a green environment, sustainable societies, and thriving industries. It offers a comprehensive exploration of how these technologies intersect and transform various sectors to enhance environmental conservation, societal well-being, and industrial progress. The book features a diverse array of case studies, methodologies, and notes on technological advancements. Readers will gain valuable insights into the impact of AI and IoT on sustainable initiatives through real-world examples, research findings, and discussions on future directions. Key themes AI in complex and versatile scenarios: Chapters 1 and 4 explore AI applications in combatant identification and COVID-19 monitoring IoT for efficiency and data-driven decision-making: Chapters 2, 3, and 7 focus on IoT implementations in battery monitoring for electric vehicles, healthcare systems, and precision farming AI for diagnostics and computer vision: Chapters 5, 9, and 13 highlight AI-driven solutions for plant disease detection, fetal spine disorder detection, and defect detection Industry applications: Chapters 6, 8, 10, 11, 12, 14, 15, 16, and 17 cover AI and IoT in healthcare, transportation, supply chain management, endangered species protection, crop management, and pollution detection, showcasing their transformative potential across various domains. This book is ideal for readers with multidisciplinary backgrounds, including researchers, academics, professionals, and students interested in IoT, AI, environmental sustainability, healthcare, agriculture, smart technologies, and industrial innovation.

Artificial Intelligence, Machine Learning and User Interface Design is a forward-thinking compilation of reviews that explores the intersection of Artificial Intelligence (AI), Machine Learning (ML) and User Interface (UI) design. The book showcases recent advancements, emerging trends and the transformative impact of these technologies on digital experiences and technologies. The editors have compiled 14 multidisciplinary topics contributed by over 40 experts, covering foundational concepts of AI and ML, and progressing through intricate discussions on recent algorithms and models. Case studies and practical applications illuminate theoretical concepts, providing readers with actionable insights. From neural network architectures to intuitive interface prototypes, the book covers the entire spectrum, ensuring a holistic understanding of the interplay between these domains. Use cases of AI and ML highlighted in the book include categorization and management of waste, taste perception of tea, bird species identification, content-based image retrieval, natural language processing, code clone detection, knowledge representation, tourism recommendation systems and solid waste management. Advances in Artificial Intelligence, Machine Learning and User Interface Design aims to inform a diverse readership, including computer science students, AI and ML software engineers, UI/UX designers, researchers, and tech enthusiasts.

Stay informed about recent trends and groundbreaking research driving innovation in the AI-IoT landscape. AI, a simulated form of natural intelligence within machines, has revolutionized various industries, simplifying daily tasks for end-users. This book serves as a handy reference, offering insights into the latest research and applications where AI and IoT intersect. The book includes 12 edited chapters that provide a comprehensive exploration of the synergies between AI and IoT. The contributors attempt to address engineering opportunities and challenges in different fields. Key Topics: AI and IoT in Smart Farming: Explore how these technologies enhance crop yield and sustainability, revolutionizing agricultural practices. AIoT (Artificial Intelligence of Things): Understand the amalgamation of AI and IoT and its applications, particularly focusing on smart cities and agriculture. Smart Healthcare and Predictive Disease Analysis: Uncover the crucial role of AI and IoT in early disease prediction and improving healthcare outcomes. Applications of AI in Various Sectors: Explore how AI contributes to sustainable development, sentiment analysis, education, autonomous vehicles, fashion, virtual trial rooms, and more. Each chapter has structured sections with summaries and reference lists, making it an invaluable resource for researchers, professionals, and enthusiasts keen on understanding the potential and impact of these technologies in today's rapidly evolving world.

This book explains different applications of supervised and unsupervised data engineering for working with multimedia objects. Throughout this book, the contributors highlight the use of Artificial Intelligence-based soft computing and machine techniques in the field of medical diagnosis, biometrics, networking, automation in vehicle manufacturing, data science and automation in electronics industries. The book presents seven chapters which present use-cases for AI engineering that can be applied in many fields. The book concludes with a final chapter that summarizes emerging AI trends in intelligent and interactive multimedia systems. Key features: - A concise yet diverse range of AI applications for multimedia data engineering - Covers both supervised and unsupervised machine learning techniques - Summarizes emerging AI trends in data engineering - Simple structured chapters for quick reference and easy understanding - References for advanced readers This book is a primary reference for data science and engineering students, researchers and academicians who need a quick and practical understanding of AI supplications in multimedia analysis for undertaking or designing courses. It also serves as a secondary reference for IT and AI engineers and enthusiasts who want to grasp advanced applications of the basic machine learning techniques in everyday applications.