This book covers a wide range of topics related to the integration of Artificial Intelligence, Big Data, Io T, and Blockchain: From Concepts to Applications. It begins by establishing a solid foundation and introducing the concepts and principles of each technology. The subsequent chapters delve into the various applications and use cases, providing readers with real-world examples of how AI, Io T, and Blockchain can be leveraged to address key challenges in Smart Environments. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science, Artificial Intelligence, and Smart Environments inspire novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. This book reviews the state of the art of big data analysis, Artificial Intelligence, and Smart Environments. It includes issues that pertain to signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. The papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart cities in particular. The authors hope that this book serves as a valuable resource and guide for readers, empowering them to navigate the intricate landscape of Artificial Intelligence, Io T, and Blockchain in Smart Environments. Let the authors embark on this transformative journey together, as the authors explore the concepts and applications that hold the potential to shape the future of Smart Environments. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers, as well as anyone interested in big data analysis and Artificial Intelligence.
Table of Content
Chapter 1. An Extension to Single Events of the Mongo DB Atlas Trigger Scheduling Mechanism.- Chapter 2. Proposed Architecture for Smart Irrigation System: Leveraging Io T and Lo Ra WAN.- Chapter 3. Digitalization’s Influence on Audit: Examining the Implications of Big Data and Blockchain Technology.- Chapter 4. Artificial Intelligence for Auditing.- Chapter 5. Enhancing Query Processing in Big Data: Scalability and Performance Optimization.- Chapter 6. Customer Behavior Tracing And Prediction Using Genetic Algorithm: Review of Literature.- Chapter 7. Combining NLP and Generative Models for Predicting Incident Category and Incident Routing in Incidents Management Systems.- Chapter 8. Artificial Intelligence as a Lever for Optimizing Well-Being at Work.- Chapter 9. The digitalization of social influence practices in Morocco and its effect on attitudinal change and purchase behavioral intention.- Chapter 10. Performance improvement of internet of things by using fuzzy logic.- Chapter 11. Digitalization, Connectivity, and Smart Cities: The case of Romania.- Chapter 12. Innovation Strategies and Performance in the Enterprise: An Analysis of Digital Marketing Role.- Chapter 13. Drivers of EPS Adoption: Exploring the Influence of Environmental Consciousness, Risk Perception, and Trust.- Chapter 14. Deep Learning-Based Predictive Analytics for Anomaly Detection in Big Data Environments.- Chapter 15. XAI for cardiovascular risk prediction.- Chapter 16. Impact Of The Perceived Congruence Between The Dominant Color Of The Ad Banner And The Message On Consumer Attitude Towards The Brand.- Chapter 17. Transforming hospitality: harnessing artificial intelligence for enhanced guest experience and operational efficiency.- Chapter 18. Theoretical approach of the contribution of artificial intelligence systems in value creation in the B2C sales funnel.- Chapter 19. Understanding and Designing Turing Machines with innovative applications to Computing.- Chapter 20. Genomic Insights Revealed: Multiclass DNA Sequence Classification Using Optimized Naive Bayes Modeling.- Etc…
About the author
Yousef FARHAOUI is a Professor at Moulay Ismail University, Faculty of sciences and Techniques, Morocco. He is the Chair of IDMS Team and the Director of STI Laboratory. He obtained his Ph.D. degree in Computer Security from Ibn Zohr University of Science. His research interests include learning, AI, e-learning, computer security, big data analytics, and business intelligence. Farhaoui has three books in computer science. He is a coordinator and member of the organizing committee and member of the scientific committee of several international congresses. He is also a member of various international associations. He has authored 15 books and several book chapters with Springer and IGI. He has served as a Reviewer for IEEE, IET, Springer, Inderscience and Elsevier Journals. He is also the Guest Editor of several journals like Wiley, Springer, Inderscience, and others. He has been the General Chair, Session Chair, and Panelist in several conferences. He is Senior Member of IEEE, IET, ACM and EAI.
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