Data Driven Applications for Industry 4.0 and Beyond

Nazmul Siddique, M Shamim Kaiser, KM Azharul Hasan, Mohammad Shamsul Arefin, K.M. Azharul Hasan, M. Shamim Kaiser

• Publisher: Chapman and Hall/CRC
• Year: 2025
• eBook ISBN: 9781040424636
• Topic: Computer Science
• Subtopic: Data Mining
• Index: Computer Science

The increasing reliance on automation and data-driven decision-making is transforming industries. As technology advances, the need for more intelligent and efficient systems is growing. This book explores how data-driven approaches are being applied in various fields to solve real-world challenges.

With contributions from researchers and professionals, the chapters discuss practical applications of modern computational techniques. Topics range from optimizing industrial processes to improving predictive systems in different sectors. The book also emphasizes the importance of responsible and interpretable technology to ensure fairness and transparency.

This book is a valuable resource for students, researchers, and professionals looking to understand the evolving role of data in industry. It provides insights into emerging trends and encourages further exploration in the field of intelligent systems and automation.

Table of contents

• Cover Page
• Half-Title Page
• Title Page
• Copyright Page
• Dedication Page
• Contents
• Preface
• Contributors
• Editors
• Chapter 1 A System That Analyzes Bengali Text on Facebook Posts Using Machine Learning to Spot Suspicious Content
• Chapter 2 A Reversible Transformer Based Bangla Conversational Agent
• Chapter 3 URL Based Website Classification Using Deep Learning and Word-Based Multiple N-gram Models
• Chapter 4 Gait Recognition from Occluded to Reconstructed Gait Cycle Using Deep Learning
• Chapter 5 RiceNet: Accurate Classification of Rice Varieties Using Convolutional Neural Networks
• Chapter 6 Vehicle Name Plate Detection and Blurring from Social Media Images Using Image Processing and Deep Learning
• Chapter 7 DCNN-SMD: A Deep Convolutional Neural Network Model to Diagnosis, Prognosis, and Characterise Sperm Morphology
• Chapter 8 Muslim Salat Gesture Recognition Framework: Integrating Deep Transfer Learning and Machine Learning
• Chapter 9 BHSGR-Net: A Light-Weight Convolutional Neural Architecture for Recognition of Bengali Hand Sign Gestures
• Chapter 10 Can Machine Learning Help Identify Suicidal Tweets? An Ensemble Classifier Approach
• Chapter 11 An Interpretable Systematic Review of Machine Learning Models for Predictive Maintenance of Aircraft Engine
• Chapter 12 Multichannel Attention Networks with Ensembled Transfer Learning to Recognize Bangla Handwritten Character
• Chapter 13 Development of a Deep Learning Classification Model for Improved Rainfall Prediction in Ireland
• Chapter 14 Defect Detection of Casting Products Using Deep Learning: A Method Based on Convolutional Neural Networks
• Chapter 15 OLD-TL: Offensive Language Detection in Gaming Live Stream Using Transfer Learning
• Chapter 16 Predicting Stress in Bangladeshi University Students: A LIME-Interpretable Machine Learning Approach
• Chapter 17 Early Detection of System Failure Using Machine Learning Techniques
• Chapter 18 Churn Prediction Using Machine Learning in the Tours and Travel Industry
• Index