This book highlights recent advance in the area of Machine Learning and IoT, and their applications to solve societal issues/problems or useful for various users in the society. It is known that many smart devices are interconnected and the data generated is being analyzed and processed with machine learning models for prediction, classification, etc., to solve human needs in various sectors like health, road safety, agriculture, and education. This contributed book puts together chapters concerning the use of intelligent techniques in various aspects related to the IoT domain from protocols to applications, to give the reader an up-to-date picture of the state-of-the-art on the connection between computational intelligence, machine learning, and IoT.
Author(s): Ch. Satyanarayana, Xiao-Zhi Gao, Choo-Yee Ting, Naresh Babu Muppalaneni
Series: Advanced Technologies and Societal Change
Publisher: Springer
Year: 2022
Language: English
Pages: 168
City: Singapore
Preface
Introduction
Contents
About the Editors
1 A Review on Generative Adversarial Networks
Introduction
Basics of GAN
Training Data for Discriminator
Training the Discriminator
The Generator
Using the Discriminator to Train the Generator
Attentional Generative Adversarial Network
Control GAN
DC-GAN
Conditional GAN
Cycle Consistent GAN
FM-GAN
Stack GAN
MirrorGAN
Fusion GAN
Comparison of Different GAN Based on Inception Score
Merits of Generative Adversarial Network
Demerits of Generative Adversarial Network
Future Prospects of GAN
Conclusion
References
2 Integration of Machine Learning in Education: Challenges, Issues and Trends
Introduction
Machine Learning Overview
Opportunities of Machine Learning in Education
Challenges and Issues
Explainability
Accountability
Cultural Bias
Ethical Concerns
Existing Examples
Conclusion
References
3 IoT-Based Continuous Glucose Monitoring System for Diabetic Patients Using Sensor Technology
Introduction
Glucose Measurement Methods
Existing Methods
Internet of Things (IoT)
General IoT-Based Continuous Glucose Measurement Architecture
Internet of Things (IoT)-Enabled Continuous Glucose Monitoring System (CGMS)
Results and Discussion
Conclusion
References
4 Role of Machine Learning and Cloud-Driven Platform in IoT-Based Smart Farming
Introduction
Literature Review
Applications of Machines Learning in a Major IoT-Based Smart Farming Environment
IOT-AI-Cloud in Agriculture—The Need and Implementation
User Domain
IoT Domain
Cloud Domain
Smart Farming Challenges
Conclusion
References
5 Smart Airport System to Counter COVID-19 and Future Sustainability
Introduction
Proposed System
Passenger Registration Using Blockchain
Blockchain for Data Storage
Blockchain Data Storage
Benefits of Storing Data Using Blockchain
Passenger Verification and Reports Management in Hospitals
Passenger Authentication at Airport
Recognizing Faces with CNN
Dataset of Facial Images
MTCNN System for Face Detection
Post-Processing of Images
Facial Feature Extraction
Facial Authentication
Wearable Smart Band
Assessing Risk Level and Acceptance
Maintaining Health and Hygiene
Maintaining Clean and Hygiene Places
Smart Soap Dispensers
Smart Toilet Paper Dispenser
Smart Garbage Bin
Conclusion
References
6 Early Prediction of COVID-19 Using Modified Convolutional Neural Networks
Introduction
Literature Review
Existing System and Their Implementation Details
Existing System
Proposed System
System Design and Implementation
Implementation and Experimentation Details
System Modules
ECNN Algorithm
Results
Evaluation Methods
Conclusions and Future Possibilities
References
7 A Cyber Physical System Model for Autonomous Tolling Booths
Introduction
Problem Definition
Cyber Physical System for Autonomous Toll Booths (CPSATB)
Input Layer of CPSATB
Control Layer of CPSATB
Cloud Model
Output Layer of CPSATB
A Proof of Concept for CPSATB
Conclusion
References
8 Sentiment Extraction from English-Telugu Code Mixed Tweets Using Lexicon Based and Machine Learning Approaches
Introduction
Related Work
Methodology
Experiments and Results
Conclusion and Future Work
References
9 An Integrated Approach for Medical Image Classification Using Potential Shape Signature and Neural Network
Introduction
Methodology
Results and Discussions
Conclusion
References
10 Brain Tumour Segmentation Using Hybrid Approach
Introduction
Related Work
Proposed Methodology
Experimental Results
Conclusions
References
11 Identification of Brain Tumors Using Deep Learning Techniques
Introduction
Literature Study
Proposed Method
Results and Discussions
Conclusion
References
12 Implementation of ANN for Examining the Electrical Parameters of Cadmium Sulfide Solar Cell
Introduction
Working Model of CdS Thin-Film Solar Cell
Artificial Neural Network Modeling of CdS Thin-Film Solar Cell
Results and Discussion
Impact of Hidden Neurons: Modeling of CdS Solar Cell
Conclusion
References
13 Deduplication of IoT Data in Cloud Storage
Introduction
Background and Related Work
Proposed System Model
Results After Experiments Done
Conclusion
References
