Gaurav Dhiman – författare

This book is a comprehensive overview of advancements in artificial intelligence (AI) and how it can be applied in the field of air quality management. It explains the linkage between conventional approaches used in air quality monitoring and AI techniques such as data collection and preprocessing, deep learning, machine vision, natural language processing, and ensemble methods. The integration of climate models and AI enables readers to understand the relationship between air quality and climate change. Different case studies demonstrate the application of various air monitoring and prediction methodologies and their effectiveness in addressing real-world air quality challenges.FeaturesA thorough coverage of air quality monitoring and prediction techniques.In-depth evaluation of cutting-edge AI techniques such as machine learning and deep learning.Diverse global perspectives and approaches in air quality monitoring and prediction.Practical insights and real-world case studies from different monitoring and prediction techniques.Future directions and emerging trends in AI-driven air quality monitoring.This is a great resource for professionals, researchers, and students interested in air quality management and control in the fields of environmental science and engineering, atmospheric science and meteorology, data science, and AI.

This book is a comprehensive overview of advancements in artificial intelligence (AI) and how it can be applied in the field of air quality management. It explains the linkage between conventional approaches used in air quality monitoring and AI techniques such as data collection and preprocessing, deep learning, machine vision, natural language processing, and ensemble methods. The integration of climate models and AI enables readers to understand the relationship between air quality and climate change. Different case studies demonstrate the application of various air monitoring and prediction methodologies and their effectiveness in addressing real-world air quality challenges.FeaturesA thorough coverage of air quality monitoring and prediction techniques.In-depth evaluation of cutting-edge AI techniques such as machine learning and deep learning.Diverse global perspectives and approaches in air quality monitoring and prediction.Practical insights and real-world case studies from different monitoring and prediction techniques.Future directions and emerging trends in AI-driven air quality monitoring.This is a great resource for professionals, researchers, and students interested in air quality management and control in the fields of environmental science and engineering, atmospheric science and meteorology, data science, and AI.

Taking a broad, multidisciplinary approach to the ethical, legal, and practical dimensions of developing AI, the book puts key issues such as bias, transparency, accountability, and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. This book can be read as a resource for those who want to be able to guide the development and deployment of responsibly controlled AI systems.

The book explores the intersection between IoT technologies and responsible practices across four vital dimensions. It looks into the latest advancements in IoT, encompassing hardware, software, and cutting-edge communication protocols, while also highlighting trends like edge computing, IoT security, and energy-efficient IoT devices. The next part of the book showcases real-world applications and success stories across diverse sectors such as healthcare, manufacturing, smart cities, and agriculture. The next part addresses the vital role of data analytics and artificial intelligence in harnessing the potential of IoT, covering real-time data analysis, predictive maintenance, and data visualization. The last part focuses on the essential aspect of safeguarding IoT devices and data, exploring authentication, encryption, vulnerability assessment, and the ethical and regulatory considerations surrounding IoT. The book serves as a resource for professionals, researchers, and policymakers, offering valuable insights, best practices, and responsible strategies for leveraging IoT in an increasingly connected and data-driven industrial world while prioritizing ethical, security, and privacy concerns.

The rapid advances in technology have revolutionized healthcare and assisted living, and given rise to Ambient Assisted Living (AAL). As healthcare is transitioning from healthcare 4.0 to healthcare 5.0, the integration of AI, IoT, Blockchain, 5G, and Fog Computing is enabling innovative solutions for personalized care, remote monitoring, and intelligent decision-making.This book delves into cutting-edge AAL technologies, including AI-driven gait analysis for diagnosing and classifying disorders like Parkinson's disease, assistive robotics to enhance daily living, and Blockchain-based token incentive systems for transparency and engagement. It also explores AI-powered diet management for diabetes patients, NLP applications in clinical decision-making, and large language models for healthcare analytics. The book highlights GAN-based solutions for emergency staffing and resilient scheduling, demonstrating AI's role in optimizing healthcare operations. The book also examines multisensory rooms for engaging children with disabilities, emphasizing inclusive technology design. Ethical concerns in AAL, ensuring that innovation aligns with societal values and patient dignity are also addressed. With insights into practical applications, challenges, and future directions, the book serves as a guide for researchers, practitioners, and policymakers, offering a comprehensive vision of how technology can revolutionize healthcare and empower individuals.