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This book aims to provide state-of-the-art knowledge in the field of Intelligence of Things to both academic and industrial readers. In particular, undergraduate, graduate, and researchers may find valuable information to drive their future research. This book is considered a reference for numerous courses such as artificial intelligence, Internet of Things, intelligent systems, and mobile networks. In the industrial area, this book provides information on recent studies in applying AI to IoT developments, which help to align and shorten R&D processes to introduce new classes of intelligent IoT products.
List of contents
1.Development of a Smart Crib System Using IoT and AI Technologies for Infant Safety Monitoring.- 2.Toward Robust Speech Emotion Recognition: A Hybrid EMix-Based Augmentation Approach.- 3.Reinforcement Learning for RAN Intelligent Controller: A Case Study on Traffic Steering.- 4.Optimizing Email Filtering Systems: Addressing Challenges from AI-Generated Spam and Phishing.- 5.A Deep Learning Approach For Segmenting Wire Conductor of Power Transmission Systems.- 6.Integrating graph features for social bot detection.- 7.Smart Glove for Word-Level Sign Language Recognition Using Flex Sensors, Accelerometer Sensors, and Long-Short Term Memory Model.- 8.Optimizing Beamforming for Cell-Free MIMO ISAC Systems with Low-Resolution ADCs.- 9.APMR-CNN: A Photonic Convolutional Neural Network Based on Cascaded All-Pass Microring Resonators.- 10.A Large-Scale Real-Time Camera Analysis AI System for the Retail Industry.- 11.An IoT-Based Intelligent Hyperlocal Sky Condition Forecasting System for Astronomical Observatories Using Deep Learning.- 12.Low-Complexity Variable Bandpass Filter with Simplified Stability Guarantee.- 13.Detecting Windows malware using machine learning.- 14.A novel 1D convolutional neural network architecture for improved Pumpkin seed classification.- 15.GPMHA: Gaussian Projected Quantum Multi-Head Attention for Sentiment Analysis.- 16.Face and Voice Recognition Using a Shared CoAtNet Framework: From Unimodal to Multimodal.- 17.Blockchain Performance Benchmarking in Industrial Supply Chains: Empirical Evidence from Coal Mining.- 18.Multimodal Deep Learning for Phishing Detection: HTML and Visual Features.- 19.Secrecy Performance Analysis of Precoded STBC and Beamforming for Next-Generation Networks.- 20.Phi-3-Code: Fine Tuning a Small Size Language Model for Coding Generation.- 21.Coverage-Aware Sensor Clustering for Network Lifetime Maximization in Smart Cities.- 22.Region-Aware Multispectral Satellite Image Compression for Precision Agriculture.- 23.A Weather-Enhanced Deep Learning Approach for Bus Passenger Demand Forecasting in Smart Bus Systems.- 24.Benchmarking Common Machine Learning Algorithms on an Enhanced UAV Fault Dataset.- 25.Deploying Lightweight Federated Learning on Edge Devices for Smart Healthcare.- 26.Federated Swarm Intelligence: A Novel Framework for Collaborative Anomaly Detection in Decentralized IoT Network.- 27.Balancing Accuracy and Efficiency: Post-Training vs Quantization-Aware Training for Multispectral Remote Sensing Models.
Summary
This book aims to provide state-of-the-art knowledge in the field of Intelligence of Things to both academic and industrial readers. In particular, undergraduate, graduate, and researchers may find valuable information to drive their future research. This book is considered a reference for numerous courses such as artificial intelligence, Internet of Things, intelligent systems, and mobile networks. In the industrial area, this book provides information on recent studies in applying AI to IoT developments, which help to align and shorten R&D processes to introduce new classes of intelligent IoT products.
