Applied Intelligence for Industry 4.0

Nazmul Siddique, Mohammad Shamsul Arefin, M Shamim Kaiser, ASM Kayes, Nazmul Siddique, Mohammad Shamsul Arefin, M Shamim Kaiser, ASM Kayes

• Publisher: Chapman and Hall/CRC
• Year: 2023
• eBook ISBN: 9781000804270
• Topic: Computer Science
• Subtopic: Business Intelligence
• Index: Computer Science

We are all aware that artificial intelligence (AI) has brought a change in our lives, driven by a new form of interaction between man and machine. We are in the era of the fourth Industrial Revolution (IR) where AI plays vital roles in human development by enabling extraordinary technological advances making fundamental changes to the way we live, work and relate to one another. It is an opportunity to help everyone, including leaders, policymakers and people from all income groups and nations, to harness converging technologies in order to create an inclusive, human-centered future. We need to prepare our graduates as well as researchers to conduct their research with 4.0 IR-related technologies. We need to develop policies and implement those policies to focus on the components of 4.0 IR for sustainable developments. Applied Intelligence for Industry 4.0 will cover cutting edge topics in the fields of AI and industry 4.0. The text will appeal to beginners and advanced researchers in computer science, information sciences, engineering and robotics.

Features

• Discusses advance data mining, feature extraction and classification algorithms for disease detection, cyber security detection and prevention, soil quality assessment and other industrial applications
• Includes the parameter optimization and explanation of intelligent approaches for business applications
• Presents context-aware smart insights and energy efficient and smart computing for the next-generation of smart industry

Table of contents

• Cover Page
• Half-Title Page
• Title Page
• Copyright Page
• Dedication Page
• Contents
• Preface
• Contributors
• Editors
• Chapter 1 Multi-labelled Bengali Public Comments Sentiment Analysis with Bidirectional Recurrent Neural Networks (Bi-RNNs)
• Chapter 2 Machine Learning and Blockchain-based Privacy-aware: Cognitive Radio Internet of Things
• Chapter 3 Machine Learning-based Models for Predicting Autism Spectrum Disorders
• Chapter 4 Implementing Machine Learning Using the Neural Network for the Time Delay SIR Epidemic Model for Future Forecasting
• Chapter 5 Prediction of PCOS Using Machine Learning and Deep Learning Algorithms
• Chapter 6 Malware Detection: Performance Evaluation of ML Algorithms Based on Feature Selection and ANOVA
• Chapter 7 An Efficient Approach to Assess the Soil Quality of Sundarbans Utilizing Hierarchical Clustering
• Chapter 8 A Machine Learning Approach to Clinically Diagnose Human Pyrexia Cases
• Chapter 9 Prediction of the Dengue Incidence in Bangladesh Using Machine Learning
• Chapter 10 Detecting DNS over HTTPS Traffic Using Ensemble Feature-based Machine Learning
• Chapter 11 Development of a Risk-Free COVID-19 Screening Algorithm from Routine Blood Tests Using Ensemble Machine Learning
• Chapter 12 A Transfer Learning Approach to Recognize Pedestrian Attributes
• Chapter 13 TF-IDF Feature-Based Spam Filtering of Mobile SMS Using a Machine Learning Approach
• Chapter 14 Content-based Spam Email Detection Using an N-gram Machine Learning Approach
• Chapter 15 AI Poet: A Deep Learning-based Approach to Generate Artificial Poetry in Bangla
• Chapter 16 Document Level Comparative Sentiment Analysis of Bangla News Using Deep Learning-based Approach LSTM and Machine Learning Approaches
• Chapter 17 Employee Turnover Prediction Using a Machine Learning Approach
• Chapter 18 A Dynamic Topic Identification and Labeling Approach for COVID-19 Tweets
• Chapter 19 Analyzing the IT Job Market and Classifying IT Jobs Using Machine Learning Algorithms
• Index