Intelligence of Things: AI-IoT Based Critical-Applications and Innovations (AIoT Innovation)

✍ Scribed by Fadi Al-Turjman (editor), Anand Nayyar (editor), Ajantha Devi (editor), Piyush Kumar Shukla (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 244
• Category: Library

✦ Synopsis

This book presents recent technologies that explore artificial intelligence (AI) and its scope in Internet of Things (IoT) enabled areas for productivity and the betterment of society. The book aims at targeting audiences of several disciplines to share research, suggest solutions, and future trends in the field of AI using IoT. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both aspects to give a holistic understanding of the AI paradigm for IoT. The book focuses on timely topics related to the field of AI enabled IoT applications at large. The book consists of four major parts: fundamentals, theoretical discussion, critical applications, and the learning algorithms. These contents shall include the basics, types, tools, and techniques of AI. Finally, applications of AI enabled IoT in several areas are presented including health, security, climate change, agricultural engineering, bioinformatics, biomedicine, smart applications, natural language processing, social and economic implications of AI enabled IoT, as well as robotics, sustainability, risk management, seismic data processing, smart grid management, text analysis, security, privacy, and ethics.

✦ Table of Contents

Preface
Contents
About the Authors
Applications of Internet of Things (IoT) in Green Computing
1 Introduction
2 Internet of Things (IoT)
3 Green Computing and Green IoT
3.1 Principles of Green IoT
4 IoT in Green Computing
4.1 Applications of IoT Green Computing Based on Policies
4.1.1 IoT-Based Green Campus
4.1.2 Green Agriculture and Green Health Care
4.1.3 Intelligent Automobiles
4.1.4 Intelligent Houses
4.1.5 Intelligent Protection/Security
4.2 IoTGC Applications Based on Software
4.2.1 Cloud Computing
4.2.2 Edge Computing
4.2.3 Fog Computing
4.2.4 Telecommuting
4.2.5 Based on Data Center
4.2.6 Virtualization Based
4.3 Hardware-based IoTGC Applications
4.3.1 RFID Based
4.3.2 Based on Integrated Circuit
4.3.3 Based on Processor
4.3.4 Based on Sensor
4.4 Applications of IoT Green Computing Based on Awareness
4.4.1 Usefulness of Ambient Notification
4.4.2 Proper Visualization of Information in Public Sectors
4.5 IoTGC Applications Based on Recycling
5 A Case Study on the Influence of Smartphones on the Environment
5.1 Minimization of the Drastic Change in the Environment
5.1.1 Hazardous Materials of Smartphone
5.1.2 Recycling
5.1.3 Selection of Right Design of Repair and Disassembly
5.1.4 Development of Smartphones using Green Materials
5.1.5 Energy-Saving Smartphone Batteries
5.1.6 Reduce Packaging and Accessories Requirements
5.2 Assessment of Smartphones using Life Cycle Assessment (LCA)
5.3 Selling and Emission Rate of the Smartphone
6 Discussion on Case Study
7 Conclusion
References
Vehicular Intelligence System: Time-Based Vehicle Next Location Prediction in Software-Defined Internet of Vehicles (SDN-IOV) ...
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Proposed (ERS-SDN-IOV) Routing Protocol
3.2 Prediction Neural Network
4 Experimental Results
4.1 Simulation Parameters
4.2 Simulation Scenario
4.3 Simulation Results
5 Conclusion
References
An Enhanced Cloud-IoMT-based and Machine Learning for Effective COVID-19 Diagnosis System
1 Introduction
2 Application of Cloud Computing and IoMT to Combat COVID-19 Pandemic
3 Related Works
4 The Proposed Cloud-IoMT-Based Architecture for Early Diagnosis of COVID-19 Outbreak
4.1 Data Capture and Collection of Symptoms Layer
4.2 Isolation/Quarantine Layer
4.3 Computers and AI Data Analysis Center
4.4 Healthcare Experts
4.5 Cloud-IoT-based Storage Database
4.6 Gateway
5 Applicability of the Proposed Model
5.1 Preprocessing
5.2 Diagnosis Models, Parameters, and Metrics
6 Results and Discussion
6.1 Confusion Matrix
6.2 ROC Curves
7 Conclusion
References
AIIoT for Development of Test Standards for Agricultural Technology
1 Introduction
1.1 Artificial Intelligence-Internet of Things (AIIoT)
1.1.1 Internet of Things (IoT)
Architecture of IoT
Applications of IoT
1.1.2 Artificial Intelligence (AI)
1.1.3 Machine Learning (ML)
2 Internet of Things Using Artificial Intelligence
2.1 Advantages of AIIoT
2.2 Applications of AIIoT
3 Role of AI and IoT in Agriculture
3.1 Role of IoT in Agriculture
3.1.1 Applications of IoT in Agriculture
3.2 Role of AI in Agriculture
3.2.1 Applications of AI in Agriculture
3.3 Future Aspects of IoT and AI in Agriculture
4 Testing
4.1 Software Testing in Agriculture
5 Test Standards in Agriculture
6 The International Organization for Standardization (ISO)
6.1 Case Study
7 Conclusion
References
Study and Analysis of 5G Enabling Technologies, Their Feasibility and the Development of the Internet of Things
1 Introduction
2 Background
3 Definition of the Problem
4 Objectives of the Research Problem
4.1 General Objective
4.2 Specific Objectives
5 Hypothesis
6 Research Methodology
7 Evolution of Mobile Networks from 0G to 5G: Basic Mobile Broadband Concept
8 Mobile Broadband Evolution: First Generations
9 Digital Generation
10 Multiple Accesses by Code Division
11 Third Generation
12 Long Term Evolution (LTE)
13 Essential Technologies for 5G Network Deployment
13.1 Millimeter Waves
14 Heterogeneous Networks
15 Massive MIMO
16 Beam Forming
17 Device to Device Communication (D2D)
18 NOMA Access Technology
19 Full Duplex
20 5G Architecture
21 NG-RAN
22 Internet of Things, Basic Principles, and Architecture
23 Internet of Everything
24 Industrial Internet of Things
25 Infrastructure and IoT Technologies
26 Convergence of the Physical and Virtual World
27 General Structure of the IoT
28 IoT Protocols
29 IoT Networks
30 Edge Computing
31 5G Security
32 IoT Use Cases
33 Public IoT
34 IoT in Industry
35 IoT at Home
36 Conclusions and Suggestions
37 Recommendations
References
Automated Methods for the Detection of Green Land in Satellite Images
1 Introduction
2 Literature Survey
3 The U-NET Method
4 Skip-U-NET Model
4.1 System Model
4.2 Architecture and Working
5 Experimentation and Analysis
5.1 Experimentation Platform
5.2 DSTL Dataset
5.3 Data Transformation
5.4 Data Augmentation
5.5 Performance Metrics
5.5.1 Jaccard Index
5.5.2 Loss Function
5.6 Segmentation Results
5.7 Analysis
6 Conclusion
References
Artificial Cyber Espionage Based Protection of Technological Enabled Automated Cities Infrastructure by Dark Web Cyber Offender
1 Introduction
1.1 Using AI to Prevent Cybercrime Targeting Technological Enabled Colonies on the DW
1.1.1 How Technological Enabled Colonies Are Using Artificial Cyber Espionage
1.1.2 What AI and ML can do for Automated City?
2 WEBNET Can Be Hacked Through Automated Light Bulb
2.1 Automated City Surveillance Issues
2.2 Seclusion and Surveillance
2.3 Information Bias
3 Solving Urban Issues with AI and ML
3.1 Technological Enabled Colonies Peril
3.1.1 Perpetrator Eavesdrop Threat
3.1.2 Dossier and Identity Thievery by Gadget Hijacking
3.1.3 Network Information Flooding Threat
Securing Technological Enabled Colonies
Firmware Integrity and Impregnable Boot
Mutual Testament
Surveillance Contemplating and Analysis
Surveillance Lifecycle Governance
Root of Credible
Protocol Engines
Provisioning and Key Governance
4 IOT Architectural View
4.1 Automated Gadget/Sensing Chips Tiers
4.2 Gateways and Webnet
4.3 Governance Liturgy Tiers
4.4 IOT Conceptual View
4.4.1 Equate Tiers
4.4.2 Access Tiers
4.4.3 Abstraction Tiers
4.4.4 Service Tiers
5 Conclusion and Future Scope
References
Role of Artificial Intelligence and IoT in Next Generation Education System
1 Introduction
2 Boons of AI in the Education System
3 AI-Based Technologies for Education
4 AI-Based Educational Solutions: Current Scenario
5 Development of AI-Enabled Online Learning Platforms
6 IoT Applications in Education
6.1 Smart Infrastructure
6.1.1 Computer Resource Allocation in Schools
6.1.2 Multimedia Classrooms
6.1.3 Digital Resource for Schools
6.2 Students Attendance Management
6.3 Safety Measures to the Institutional Infrastructure
6.4 Technological Advancement as a Learning Privilege to the Disabled Students
6.4.1 Mobility Assistance
6.4.2 Reading Surroundings
6.4.3 Improvement in Autonomy
7 Potential Use of AI and IoT in Education Sector
8 Conclusion
8.1 Future Scope
References
Social Media Data Analysis: Rough Set Theory Based Innovative Approach
1 Introduction
1.1 Terminologies
1.2 Social Data Analysis-Mathematical Perspective
1.2.1 Structure of the Chapter
2 Rough Sets: Foundations
2.1 Terminologies of Rough Sets
3 Rough Sets: Data Analysis Techniques
3.1 Rule Discovery on Rough Set Theory
4 Rough Graph
4.1 Discernibility Matrix for Rough Graph
4.2 Reduct Calculation Using Graph Approximation
5 Experimental Analysis
6 Conclusions and Future Work
References
Index