This book presents the know-how of the real-time IoT application development activity including a basic understanding of the IoT architecture, use cases, smart computing, and the associated challenges in design and development of the IoT system. All the technical details related to protocol stack, technologies, and platforms used for the implementation are explained. It further includes techniques and case studies that include smart computing on the IoT–Cloud models along with test beds for experimentation purposes. The book aims at setting up the groundwork for the creation of applications that can help make day-to-day tasks simpler by meeting the needs of varied sectors like education, health care, agriculture, and so forth.
Author(s): Parikshit N. Mahalle, Ambritta P. Nancy, Gitanjali Rahul Shinde, Arvind Vinayak Deshpande
Publisher: CRC Press
Year: 2021
Cover
Half Title
Series Information
Title Page
Copyright Page
Table of Contents
Authors
Preface
Acknowledgments
1 Introduction
1.1 Overview of IoT
1.1.1 Technical Building Blocks
1.1.1.1 Radio Frequency Identification (RFID)
1.1.1.2 Wireless Sensor Networks (WSN)
1.1.1.3 Addressing Schemes
1.1.1.4 Data Storage and Analytics
1.1.1.5 Cloud Processing
1.1.1.6 Security
1.1.1.7 Visualization
1.1.2 IoT in Business
1.1.2.1 Intelligent Transportation
1.1.2.2 Smart Homes/Buildings and Monitoring
1.1.2.3 Smart Grids
1.1.2.4 Environment Observation and Forecasting
1.1.2.5 Smart Agriculture and Farming
1.1.2.6 Health Care
1.1.2.7 Education
1.1.2.8 Smart Clothing
1.1.2.9 Internet of Things-Architecture Things-Architecture-(IoT-A)
1.1.2.10 Coordination and Support Action for Global rfid-Related Activities and Standardization (casagras)
1.1.2.11 Magnet and Magnet Beyond
1.1.2.12 Butler
1.1.2.13 Smarter Cities Data Management (SMARTIE)
Functionalities of Iot With Smart Computing
1.2 IoT Architecture: Layered Perspective
1.3 Smart Computing
1.4 IoT Design: Issues and Challenges
1.4.1 Design Issues
1.4.2 Challenges
References
2 Internet of Things Application Development
2.1 Application Development Phases
2.1.1 Principles
2.1.2 C Model
2.2 Wireless Technologies for IoT
2.2.1 Bluetooth, Bluetooth Low Energy, and Bluetooth 5
2.2.2 Zigbee
2.2.3 WiFi
2.2.4 6LowPAN
2.2.5 3G/4G/5G
2.2.6 LoRAWAN
2.2.7 Sigfox
2.3 Protocol Stack
2.3.1 CoAP
2.3.2 MQTT
2.3.3 AMQP
2.3.4 XMPP
2.3.5 Comparison of Application Layer Protocols
2.4 Electronic Platforms
2.4.1 Arduino
2.4.2 Raspberry Pi
2.4.3 Beaglebone
References
3 IoT–Cloud Convergence
3.1 Introduction
3.1.1 Five Quintessential Characteristics of Cloud Computing
3.1.2 Cloud Computing Service Models
3.1.3 Cloud Computing Deployment Models
3.2 Opportunities and Challenges
3.2.1 IoT Requirements to Meet the Future Market Potential
3.2.2 How Cloud Comes in Handy?
3.2.3 Application Areas for Iot–cloud Convergence
3.2.3.1 IoT and Cloud Confluence in Agriculture
3.2.3.2 IoT and Cloud Confluence in Manufacturing
3.2.3.3 IoT and Cloud Confluence in Oil and Natural Gas Rig Safety
3.2.3.4 IoT and Cloud Confluence in the Retail Industry
3.2.3.5 IoT and Cloud Confluence in Supply Chain and Logistics
3.2.4 Challenges that Come With Convergence
3.3 Architecture for Convergence
3.3.1 An Overview of Cloud-Based IoT Services
3.3.1.1 Amazon Web Services (AWS) IoT Services
3.3.1.2 Analytics Services
3.3.1.3 Microsoft Azure IoT Products and Services
3.3.1.4 Google Cloud-Based IoT Services
3.3.2 State of the Art: Convergence Architectures
3.3.3 A Simplified Convergence Model
3.4 Data Offloading and Computation
3.4.1 Data Offloading and Computation: an IoT Perspective
3.4.2 Edge Computing Technologies for an IoT Network Infrastructure
3.4.3 Data Offloading and Computations
3.4.4 Offloading Considerations and Challenges
3.5 Dynamic Resource Provisioning
3.5.1 The Resource Provisioning Activity and Requirements for IoT
3.5.1.1 Resource Provisioning Requirements for an IoT-based Environment
3.5.2 Dynamic Resource Provisioning
3.6 Security Aspects in IoT Cloud Convergence
3.6.1 Enisa’s Categorized Security Challenges in IoT Cloud Convergence
3.6.2 IoT Security Designs Based On Edge Computing
3.7 IoT–Cloud Convergence: Test Beds and Technologies
3.7.1 Overview of Testbeds and Platforms
3.7.1.1 Smartsantander Testbed
3.7.1.2 Unis Testbed
3.7.1.3 KETI Testbed
3.7.1.4 Com4Innov Testbed
References
4 Smart Computing Over IoT–Cloud
4.1 Introduction
4.2 Big Data Analytics and Cognitive Computing
4.2.1 Cognitive Computing Capabilities
4.2.2 Underlying Technologies
4.2.3 Empowering Analytics
4.3 Deep Learning Approaches
4.3.1 Artificial Neural Networks (ANN)
4.3.2 Convolution Neural Network (CNN)
4.3.3 Recurrent Neural Networks (RNN)
4.4 Algorithms, Methods, and Techniques
4.5 Case Studies
4.5.1 Health Care
4.5.2 Smart Home
4.5.3 Manufacturing
4.5.4 Retail Sector
References
5 Conclusion
5.1 Summary
5.2 Issues and Challenges
5.3 Future Outlook
References
Index
