Ruchi Doshi – författare

The book offers a critical exploration of the integration of AI, blockchain, and metaverse technology in the hospitality and tourism industry to investigate the potential of these technologies in revolutionizing the industry. This comprehensive work studies, with practical examples, how cutting-edge technologies of Industry 4.0 are transforming luxury industry into a high-touch, hyper-personalized metaverse. It explains how these technologies can be used to improve customer experience and operational efficiency in areas such as guest interaction, supply chain management, payment processing, and virtual stores. The book also discusses the conditions that can promote sustainable development in the hospitality industry using Industry 4.0 technologies.Provides an innovative perspective by blending high-tech trends like AI, blockchain, and metaverse with traditional wellness practicesEmphasis on ethical considerations and potential risks associated with the use of these technologies, providing a balanced perspective on their impactIncludes case studies and practical examples on how businesses can use AI, blockchain, and the metaverse to improve customer experiences and operational efficiencyExplores how the hospitality industry can embrace Industry 4.0 technologies to improve its operations, enhance customer experiences, and contribute to sustainable developmentProvides a roadmap for companies looking to implement these technologies, highlighting potential benefits and pitfalls of each approachThis reference book is for scholars and professionals in computer science who are interested in studying the effect of AI, blockchain, and metaverse in hospitality and tourism industry.

What are the means to create a paradigm shift from conventional to intelligent companies? Industry 6.0: Technology, Practices, Challenges and Applications shows how integrating Industry 6.0 technology with data creates a framework for that shift. The book discusses the limitations, pitfalls, and open research questions in Industry 6.0, as well as the most recent advances, architectures, frameworks, applications, and novel practices, methods, and techniques. These are vital for resolving intelligent Internet of Things issues. There is a special focus on sustainable growth, humanization and environmentally friendly intelligent system applications, and an emphasis on the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP).Features: Presents the latest trends in the fields of intelligent systems, machine intelligence, deep learning, and Industrial Internet of Things for smart environments. Discusses securing the mobile ad hoc network (MANET) by detecting the Intrusions using CSO and XGBoost model. Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains. Focuses on intelligent process manufacturing, automation using robotics, development of robotic appliances, and smart manufacturing. Covers data-driven agriculture, crop disease prediction, drip irrigation systems, pesticide and fertilizer sprinkling using the Industrial Internet of Things, and water estimation systems.With many contemporary articles from both scientists and practitioners working in many fields where intelligent systems and the IIoT can break new ground, the text is assembled to aim at a readership that includes researchers, statisticians, practitioners, scientists, and developers.

What are the means to create a paradigm shift from conventional to intelligent companies? Industry 6.0: Technology, Practices, Challenges and Applications shows how integrating Industry 6.0 technology with data creates a framework for that shift. The book discusses the limitations, pitfalls, and open research questions in Industry 6.0, as well as the most recent advances, architectures, frameworks, applications, and novel practices, methods, and techniques. These are vital for resolving intelligent Internet of Things issues. There is a special focus on sustainable growth, humanization and environmentally friendly intelligent system applications, and an emphasis on the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP).Features: Presents the latest trends in the fields of intelligent systems, machine intelligence, deep learning, and Industrial Internet of Things for smart environments. Discusses securing the mobile ad hoc network (MANET) by detecting the Intrusions using CSO and XGBoost model. Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains. Focuses on intelligent process manufacturing, automation using robotics, development of robotic appliances, and smart manufacturing. Covers data-driven agriculture, crop disease prediction, drip irrigation systems, pesticide and fertilizer sprinkling using the Industrial Internet of Things, and water estimation systems.With many contemporary articles from both scientists and practitioners working in many fields where intelligent systems and the IIoT can break new ground, the text is assembled to aim at a readership that includes researchers, statisticians, practitioners, scientists, and developers.

The book covers the concepts of Python programming language along with mobile application development. Starting from fundamentals, the book continues with the explanation of mobile app development using Kivy framework. All the chapters offer questions and exercises for to better understanding of the subject. At the end of the book some hands-on projects are given to help the readers to improve their programming and project development skills.

This book explains how to use the programming language Python to develop machine learning and deep learning tasks. It provides readers with a solid foundation in the fundamentals of machine learning algorithms and techniques. The book covers a wide range of topics, including data preprocessing, supervised and unsupervised learning, model evaluation, and deployment. By leveraging the power of Python, readers will gain the practical skills necessary to build and deploy effective machine learning models, making this book an invaluable resource for anyone interested in exploring the exciting world of artificial intelligence.

The book covers the concepts of Python programming language along with mobile application development. Starting from fundamentals, the book continues with the explanation of mobile app development using Kivy framework. All the chapters offer questions and exercises for to better understanding of the subject. This second revised and updated edition covers the most recent developments in Kivy since the publishing of the first edition.