Читать книгу Green Internet of Things and Machine Learning - Группа авторов - Страница 2
Table of Contents
Оглавление1 Cover
4 Preface
5 1 G-IoT and ML for Smart Computing 1.1 Introduction 1.2 Machine Learning 1.3 Deep Learning 1.4 Correlation Between AI, ML, and DL 1.5 Machine Learning–Based Smart Applications 1.6 IoT 1.7 Green IoT 1.8 Green IoT–Based Technologies 1.9 Life Cycle of Green IoT 1.10 Applications 1.11 Challenges and Opportunities for Green IoT 1.12 Future of G-IoT 1.13 Conclusion References
6 2 Machine Learning–Enabled Techniques for Reducing Energy Consumption of IoT Devices 2.1 Introduction 2.2 Internet of Things (IoT) 2.3 Empowering Tools 2.4 IoT in the Energy Sector 2.5 Difficulties of Relating IoT 2.6 Future Trends 2.7 Conclusion References
7 3 Energy-Efficient Routing Infrastructure for Green IoT Network 3.1 Introduction 3.2 Overview of IoT 3.3 Perspectives of Green Computing: Green IoT 3.4 Routing Protocols for Heterogeneous IoT 3.5 Machine Learning Application in Green IoT 3.6 Conclusion References
8 4 Green IoT Towards Environmentally Friendly, Sustainable and Revolutionized Farming 4.1 Introduction 4.2 How is Machine Learning Used in Agricultural Field? 4.3 What is IoT? How Can IoT Be Applied in Agriculture? 4.4 What is Green IoT and Use of Green IoT in Agriculture? 4.5 Conclusion: Risks of Using G-IoT in Agriculture References
9 5 CIoT: Internet of Green Things for Enhancement of Crop Data Using Analytics and Machine Learning 5.1 Introduction 5.2 Motivation 5.3 Review of Literature 5.4 Problem with Traditional Approach 5.5 Tool Requirement 5.6 Methodology 5.7 Conclusion References
10 6 Smart Farming Through Deep Learning 6.1 Introduction 6.2 Literature Review 6.3 Deep Learning in Agriculture 6.4 Smart Farming 6.5 Image Analysis of Agricultural Products 6.6 Land-Quality Check 6.7 Arduino-Based Soil Moisture Reading Kit 6.8 Conclusion 6.9 Future Work References
11 7 Green IoT and Machine Learning for Agricultural Applications 7.1 Introduction 7.2 Green IoT 7.3 Machine Learning 7.4 Conclusion References
12 8 IoT-Enabled AI-Based Model to Assess Land Suitability for Crop Production 8.1 Introduction 8.2 Literature Survey 8.3 Conclusion References
13 9 Green Internet of Things (GIoT): Agriculture and Healthcare Application System (GIoT-AHAS) 9.1 Introduction 9.2 Relevant Work and Research Motivation for GIoT-AHAS 9.3 Conclusion References
14 10 Green IoT for Smart Transportation: Challenges, Issues, and Case Study 10.1 Introduction 10.2 Challenges of IoT 10.3 Green IoT Communication Components 10.4 Applications of IoT and Green IoT 10.5 Issues of Concern 10.6 Challenges for Green IoT 10.7 Green IoT in Smart Transportation: Case Studies 10.8 Conclusion References
15 11 Green Internet of Things (IoT) and Machine Learning (ML): The Combinatory Approach and Synthesis in the Banking Industry 11.1 Introduction 11.2 Research Objective 11.3 Methodology 11.4 Result and Discussion 11.5 Conclusion References
16 12 Green Internet of Things (G-IoT) Technologies, Application, and Future Challenges 12.1 Introduction 12.2 The Internet of Thing (IoT) 12.3 Elements of IoT 12.4 The Green IoT: Overview 12.5 Green IoT Technologies 12.6 Green IoT Applications 12.7 IoT in 5G Wireless Technologies 12.8 Internet of Things in Smart City 12.9 Green IoT Architecture for Smart Cities 12.10 Advantages and Disadvantages of Green IoT 12.11 Opportunities and Challenges 12.12 Future of Green IoT 12.13 Conclusion References
17 Index
