Machine Learning and the Internet of Things in Education: Models and Applications (Studies in Computational Intelligence, 1115)

✍ Scribed by John Bush Idoko (editor), Rahib Abiyev (editor)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 280
• Category: Library

✦ Synopsis

This book is designed to provide rich research hub for researchers, teachers, and students to ease research hassle/challenges. The book is rich and comprehensive enough to provide answers to frequently asked research questions because the content of the book touches several disciplines cutting across computing, engineering, medicine, education, and sciences in general. The rich multidisciplinary contents of the book promise to leave all users satisfied. The valuable features in the book include but not limited to: demonstration of mathematical expressions for implementation of machine learning models, integration of learning techniques, and projection of future AI and IoT technologies. These technologies will enable systems to be simulative, predictive, and self-operating smart systems. The primary audience of the book include but not limited to researchers, teachers, and postgraduate and undergraduate students in computing, engineering, medicine, education, and science fields.

✦ Table of Contents

Preface
Contents
About the Editors
Introduction to Machine Learning and IoT
1 Artificial Intelligence (AI)
2 Internet of Things
3 Conclusion and the Future of AI and IoT
References
Deep Convolutional Network for Food Image Identification
1 Introduction
2 CNN Architecture
3 Design of FRCNN System
3.1 Food-101 Dataset
3.2 Model Architecture
3.3 Simulations
4 Conclusion
References
Face Mask Recognition System-Based Convolutional Neural Network
1 Introduction
1.1 Objectives and Scope
1.2 Significance of Real-Time Face Mask Detection
2 Literature Review
3 Data Preprocessing
4 Proposed Model (CNN)
4.1 Splitting of the Data into Training and Test Sets
4.2 Activation Function
4.3 Convolutional Layers
4.4 Fully-Connected Layers
4.5 Face Detection and Cropping
4.6 Blob from Image (RGB Mean Subtraction)
4.7 The Architecture of the Application
4.8 Training of the Face Mask Detection Model
4.9 Simulation of the Proposed Model
5 Conclusion and Future Work
References
Fuzzy Inference System Based-AI for Diagnosis of Esophageal Cancer
1 Introduction
2 Related Literature Review
3 Materials and Methods
4 Results and Discussion
5 Conclusion and Recommendation
References
Skin Detection System Based Fuzzy Neural Networks for Skin Identification
1 Introduction
2 Review of Related Study
3 Proposed Algorithm
3.1 Structure of the System
3.2 Fuzzy Neural System for Skin Detection
3.3 Cross Validation
3.4 Parameter Updates and Fuzzy Classification
3.5 Learning Using Gradient Descent
4 Simulation Studies
5 Conclusions
References
Machine Learning Based Cardless ATM Using Voice Recognition Techniques
1 Introduction
1.1 Machine Learning
1.2 The Purpose of Using Voice Recognition in an ATM and Its Advantages
2 Related Works
3 Proposed System
3.1 System Classifier
3.2 Simulation and Result
4 Conclusion
References
Automated Classification of Cardiac Arrhythmias
1 Introduction
2 Review of Existing Works
3 Dataset Analysis
3.1 Feature Selection Method
4 Cardiac Arrhythmia Classification
4.1 Fuzzy Neural Network for Classification of Cardiac Arrythmia
4.2 Naïve Bayes Based Machine Learning Technique
4.3 Radial Basis Function Networks (RBFN) Technique
4.4 Experimental Result Comparison of the Proposed Algorithms
5 Conclusion and Future Work
References
A Fuzzy Logic Implemented Classification Indicator for the Diagnosis of Diabetes Mellitus in TRNC
1 Introduction
2 Methodology
2.1 Database
3 Classification
3.1 Fuzzy Logic
3.2 Fuzzy Logic Solution Approach
3.3 Reasons for Preference of Fuzzy Logic
3.4 Fuzzy Sets
3.5 MF (Membership Functions)
3.6 Variables of Linguistic
3.7 Classification Results
4 Implementation
4.1 System Design
5 Experimental Results
5.1 Rules of Fuzzy
5.2 GUI System Design
5.3 Accuracy Checking
6 Conclusion
References
Implementation and Evaluation of a Mobile Smart School Management System—NEUKinderApp
1 Introduction
2 Proposed Method
2.1 NEUKinderApp Architecture
2.2 Material Design and Optimization
2.3 Backend Customization
3 Result Analysis
3.1 Explored Devices
3.2 Response Times
3.3 Comparative Result Analysis
4 Conclusion
References
The Emerging Benefits of Gamification Techniques
1 Introduction
1.1 Artificial Intelligence (AI), and Implementation of Gamification
2 Methods of Gamification and Engineering Design
3 Conclusion
References
A Comprehensive Review of Virtual E-Learning System Challenges
1 Introduction
2 Related Works
3 Challenges Encountered During Covid-19 Pandemic with E-Learning System
4 Research Methodology
5 Discussion
6 Recommendations
7 Conclusion
References
A Semantic Portal to Improve Search on Rivers State’s Independent National Electoral Commission
1 Introduction
2 Literature Review
3 The Research Methods Used in This Report
3.1 The Study Philosophy
3.2 The Research Approach
3.3 System Analysis, Design, and Architecture
3.4 System Specifications (Domain of the System)
3.5 Ontology Processing
3.6 System Design
3.7 The Election Ontology
3.8 How the System Works
4 Evaluation and Testing
4.1 Analyzing and Evaluation Results of the Proposed and Baseline System
5 Conclusion, Limitation, and Recommendations
References
Implementation of Semantic Web Service and Integration of e-Government Based Linked Data
1 Introduction
1.1 The Open Government Data (OGD)
1.2 Linked Open Data (LOD)
2 Methodology
2.1 System Description
2.2 System Analysis
2.3 The Proposed System
3 System Implementation and Evaluation
3.1 Brief Description of the United Kingdom (UK) Government
3.2 SPARQL Endpoint for Linked Data
3.3 System Evaluation and Discussion
4 Conclusion
References
Application of Zero-Trust Networks in e-Health Internet of Things (IoT) Deployments
1 Introduction
2 E-Health Security Challenges
3 Proposed Model
4 Results
5 Conclusion
References
IoT Security Based Vulnerability Assessment of E-learning Systems
1 Introduction
2 E-learning Vulnerabilities
3 E-learning Vulnerability Assessment
4 Vulnerability Risk Space and Threat Landscape of E-learning system
5 Conclusion
References
Blockchain Technology, Artificial Intelligence, and Big Data in Education
1 Introduction
2 Extent of Past Work
3 Materials and Procedures
4 Results and Discussion
5 Conclusion
References
Sustainable Education Systems with IOT Paradigms
1 Introduction
2 Scope of Previous Works
3 Methodology
4 Results and Discussion
4.1 Methods Using Relational Ontology
4.2 Relationship-Based Epistemologies
4.3 Ethical Methods Based on Relationships
5 Conclusions
References
Post Covid Era-Smart Class Environment
1 Introduction
2 Educational Sensors
3 Ubiquitous Learning
4 Learning Management Systems (LMS)
5 Unified Learning
6 Virtual Classrooms
7 Cloud-Based Smart Classroom
8 Education and the Covid-19 Era
9 Artificial Intelligence in Education
9.1 Intelligent Tutoring Systems
9.2 Smart Classrooms: Good or Bad?
10 Conclusion
References