Intersection of Artificial Intelligence, Data Science, and Cutting-Edge Technologies: From Concepts to Applications in Smart Environment: ICAISE2024, [Paperback]

This book explores the integration of AI, data science, and emerging technologies to create innovative, practical solutions for smart environments. This book offers a comprehensive framework that combines theoretical concepts with real-world applications, focusing on how these technologies intersect to transform various domains such as healthcare, urban planning, and sustainable development.

The book's novel approach emphasizes interdisciplinary methods and problem-solving in dynamic, data-driven environments, with case studies illustrating practical impacts and advancements in smart city infrastructure, IoT, and predictive analytics. It is designed for researchers, practitioners, and advanced students interested in AI and data science applications within smart systems, as well as professionals seeking actionable insights to apply these technologies in complex environments.

Enhancing Customer Segmentation with Unsupervised Deep Learning.- Development of an EEG Controlled Soft Robotics-Based Active Hand Prosthesis for Enhanced Functionality.- RCSF & IOT In Monitoring of Obstructive Sleep Apnea.- Artificial Intelligence full potential yet attained in the e participation.- Recognition of American Sign Language using hard voting.- Smart Intrusion Detection System in Cloud Computing : A Systematic Review.- Enhancing last mile delivery efficiency through connected vehicle technology and collaborative logistics A systematic literature review.- A Review of some Semantics Methods for Translating Moroccan Text to Moroccan Sign Language.- Analysis of Depressed Patients' Sentiments towards Treatment AI Approach for Healthcare Professionals.- Understanding AI and Google's broader efforts in AI.- Integration of Generative AI and Multimodal Deep Learning for Early Detection of Chemotherapy Induced Cardiotoxicity.- Optimizing Workforce Stability Machine Learning Approaches for Predicting Employee Attrition.- XAI Driven l3ú