Internet of Drone Things

Architectures, Approaches, and Applications

1st Edition - October 1, 2024
Authors: Amartya Mukherjee, Debashis De, Nilanjan Dey
Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 1 5 9 0 0 - 8
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 1 5 9 0 1 - 5

Internet of Drone Things: Architectures, Approaches, and Applications includes fundamental information related to IoDT architecture design and features and reviews the state-of-… Read more

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Internet of Drone Things: Architectures, Approaches, and Applications includes fundamental information related to IoDT architecture design and features and reviews the state-of-the-art in hardware and software platforms to deploy, connect, and control drones or swarms of drones. It also covers the latest developments in innovative drone-facilitated applications and services that can significantly improve efficiency, productivity, and sustainability of various operations in modern society and a growing number of its industries. Finally, experimental modeling and simulations are accompanied by prototyping examples, which are set to become the benchmark of next-level automation in the field.

This book is, therefore, an invaluable resource for engineering students, researchers, and professionals as well as sector experts who work to develop new drone standards or to identify new drone technology use and commercialization areas on an international level.

1: Internet of Drone Things: Architecture Design

1.1 Internet of Drone Things: a concept

1.2 Fundamental architecture of IoDT

1.3 Application scenarios and challenges

1.4 Internet of Drone Things services

1.4.1 oneM2M systems

1.4.2 Cognitive IoT-based services

1.4.3 Cloud-based management systems

1.5 Communication protocol standard for IoDT

1.6 Conclusion References

2: Internet of Drone Things: Deployment Strategies

2.1 Introduction

2.2 Classification of UAVs

2.3 Classification of Internet of Drone Things

2.3.1 Architectural features for deployment

2.3.2 Software approach for deployment

2.3.3 Simulation roadmap

2.3.4 3D realization of the simulation

2.3.5 UAV swarming

2.4 IoDT deployment strategies: state-of-the-art

2.4.1 User off-load selection and drone positioning

2.4.2 Contemporary perspective of drone in wireless networks

2.4.3 Multi-tier drone architecture

2.5 Application perspective

2.5.1 Agriculture applications

2.5.2 Environment monitoring applications

2.5.3 Industrial applications

2.6 Conclusion References

3: Routing and Mission Planning

3.1 Introduction

3.2 Related research

3.3 Layered network architecture design

3.4 Ad-hoc routing methodology

3.5 Opportunistic routing for drones

3.6 Routing under cellular network

3.7 Flying ad-hoc network scenario

3.8 Node mobility design

3.8.1 3D Gauss-Markov mobility model

3.8.2 Randomized mobility

3.8.3 Shortest path map-based mobility

3.9 IoDT mission control

3.9.1 Low altitude flight control

3.9.2 IoDT node maneuverability

3.10 Design of mission critical IoDT applications

3.10.1 Disaster response applications

3.10.2 Emergency healthcare applications

3.10.3 Crowded sensing applications

3.11 Conclusion References

4: Modeling and Simulation of IoDT

4.1 Introduction

4.2 UAV simulators

4.3 Network simulators

4.4 Mission planner: a case study

4.5 Conclusion Reference

5: Hardware Platforms and API Specification for IoDT Development

5.1 Introduction

5.2 Sensor node specification

5.2.1 Sensor interfacing using the Arduino platform

5.2.2 Inter-node communication using ESP8266

5.3 On-board cloud service deployment

5.3.1 Setup of a Raspberry Pi Node-RED IoT service

5.3.2 MQTT service and Raspberry Pi

5.3.3 Flow deployment in Node-RED

5.4 IoDT node deployments

5.4.1 Stationary nodes

5.4.2 Vehicular nodes

5.4.3 Flying nodes

5.4.4 Autopilot setup

5.4.5 Mission planning

5.4.6 Telemetry logging and analysis

5.4.7 Navigation algorithm analysis

5.5 Conclusion References

6: Effective Framework of IoDT for Smart-City Scenarios

6.1 Introduction

6.2 Flying ad-hoc network scenario

6.3 Edge and dew computing for Internet of Drone Things

6.4 Implementation of drones as a service

6.5 Software-defined drone networks

6.6 Airborne fog computing and mobile cloud scenario

6.7 Energy management policy

6.8 Quality of service

6.9 Data collection, analytics, processing, and delivery

6.9.1 Using drones in smart cities

6.10 Energy management for IoDT

6.10.1 Usage of renewable energy

6.10.2 Energy harvesting

6.11 Conclusion References

7: Intelligence in IoDT

7.1 Introduction

7.2 Remote sensing and intelligent decision-making

7.3 Cloud-based intelligent navigation

7.4 Demand side load forecasting using a drone-based Internet of Thing infrastructure

7.5 IoDT as a component in medical cyber-physical systems

7.6 Artificial Intelligence in IoDT: operations and autonomy

7.7 Artificial intelligence in IoDT: traffic management

7.8 Machine learning and deep learning algorithms for IoDT

7.9 Conclusion References

8: Blockchain-secured Internet of Drone Things

8.1 Introduction

8.2 Fundamentals of blockchain

8.3 Edge computing paradigm

8.4 Edge-enabled blockchain architecture for Internet of Drone Things

8.5 Smart contracts and consortium blockchains for drone-enabled consumer applications

8.6 Lightweight blockchain solutions for IoDT applications

8.7 Conclusion Reference

9: IoDT Applications in Industry 4.0

9.1 Fog computing architecture for Internet of Drone Things

9.2 Dew computing approach in IoDT

9.3 Software-defined networking for drones

9.4 Edge as a service for drones in smart communities

9.5 Conclusion Reference

10: Open research issues

10.1 Enhanced cellular coverage using IoT-enabled drones

10.2 Cloud and big data technologies for drone networks

10.3 Implementation and deployment of real-time test beds for 5G/6G drones

10.4 Distributed caching and security protocols for inter-drone communications

10.5 Advanced caching and content delivery technologies for IoDT

10.6 Content dissemination and named data networks for smart communities

10.7 Security, integrity, and privacy solutions for IoDT

10.8 Energy-aware and sustainable solutions for inter-drone communications

10.8.1 Energy-efficient computing, processing, and analysis in an IoDT ecosystem

10.8.2 Energy harvesting and wireless energy transfer for drones

10.9 Trust management and collaborative solutions for IoDT

10.10 Software-defined networks and network service chaining for IoDT

10.11 Mobility management and channel modeling in IoDT

10.12 Conclusion Reference

Amartya Mukherjee

Amartya Mukherjee received his M.Tech from NIT Durgapur and is presently pursuing a PhD from Maulana Abul Kalam Azad University of Technology, Kalyani. He is currently the head of the Department of Computer Science & Engineering (AIML). He has over 14 years of teaching experience in the field of Computer Science. He has written numerous books and research articles in the field of IoT, embedded application development, wireless communication, and smart systems for various renowned publishing companies, like IEEE, Elsevier, Springer, Taylor & Francis, and World Scientific Press. His Embedded Systems & Robotics with Opensource Tools is one of the bestselling books in embedded application development. His research interests include flying ad-hoc networks, IoT, IoDT, intelligent systems, 5G and 6G communication, and machine learning.

Affiliations and expertise

Department of Computer Science and Engineering (AIML), Institute of Engineering and Management, Salt Lake, Kolkata, India.

Debashis De

Debashis De received his MTech degree from the University of Calcutta in 2002. He obtained his PhD in Engineering from Jadavpur University in 2005. He is a senior member of IEEE and a member of the International Union of Radio Science. He was awarded the prestigious BOYSCAST Fellowship by the Department of Science and Technology, Govt. of India to work at the Herriot-Watt University, Scotland. He was also given the Endeavour Fellowship Award (2008-2009) by DEST Australia to work at the University of Western Australia. He received the Young Scientist award both in 2005 in New Delhi and in 2011 in Istanbul, Turkey, from the International Union of Radio Science Headquarters, Belgium. His research interests include location and handoff management, mobile cloud computing, traffic forecasting, green mobile networks, and low power nanodevice design for mobile applications. He has published more than 60 peer-reviewed articles in international journals, 50 conference papers, 2 research monographs, and 10 books.

Affiliations and expertise

Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kalyani, West Bengal, India.

Nilanjan Dey

Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He also holds a position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence , IGI Global, USA. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (SpringerNature), Data-Intensive Research(SpringerNature), Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier). He was an associate editor of IET Image Processing and editorial board member of Complex & Intelligent Systems, Springer Nature. He is an editorial board member of Applied Soft Computing, Elsevier. He is having 35 authored books and over 300 publications in the area of medical imaging, machine learning, computer aided diagnosis, data mining, etc. He is the Fellow of IETE and Senior member of IEEE.

Affiliations and expertise

Associate Professor, Department of Computer Science and Engineering, Techno International New Town, Kolkata, India