Smart Manufacturing with AIoT: Signal Processing, Computer Vision, and Data Analytics [Hardcover]

Chapter 1: Deep Learning-Based Improved Gait Recognition Using 3D Skeletal Data for Smart Surveillance Systems, Chapter 2: IoT-Based Automated Fog Detection System Using kNN and Real-Time Meteorological Data Analytics, Chapter 3: Intelligent Waste Classification Framework Based on Machine Learning and Deep Learning for Smart City Application, Chapter 4: AI-Powered Data Analytics for Optimizing Tea Tourism: An Investigation on Determinants and Destination Information, Chapter 5: Substation Level Short-Term Load Forecasting Using Graph-Based Signal Processing and Machine Learning Algorithms, Chapter 6: AI-Based Histopathological Image Analysis for Breast Cancer Diagnosis Using Deep and Machine Learning Algorithms, Chapter 7: AI-Optimized Active Cell Balancing Technique Using Single Inductor for Intelligent Battery Management in IoT-Enabled Energy Systems, Chapter 8: Integrated Simulation and Hardware-in-the-Loop Analysis of ISO15118-Based Smart EV Charging Communication Systems, Chapter 9: AI-Driven Analysis of Air Gap Eccentricity Effects in PMSM for Condition Monitoring in Smart Industrial Systems,?Chapter 10: Deep Convolutional Neural Network-Based Smart Diagnostic System for Enhanced Breast Cancer Detection

As industries move toward intelligent, adaptive, and efficient manufacturing processes, the integration of (artificial intelligence) AI, (Internet of Things) IoT, signal processing, and computer vision is crucial. This book serves as a comprehensive guide for professionals, researchers, and academics seeking to leverage the power of cuttingedge technologies in the field of smart manufacturing.

Smart Manufacturing with AIoT: Signal Processing, Computer Vision, and Data Analytics is a comprehensive guide that focuses on practical implementation, bridging the gap between theoretical concepts and realworld applications. Each chapter of this book explores a different aspect of thelè