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Practical IoT Edge Computing with Python

Practical IoT Edge Computing with Python

SKU:9789349888258

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ISBN: 9789349888968
eISBN: 9789349888258
Rights: Worldwide
Author Name: Dr. Rajasi Tushar Athawale
Publishing Date: 24-Sep-2025
Dimension: 7.5*9.25 Inches
Binding: Paperback
Page Count: 362

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Description

Build Real-time IoT Solutions Using Python, Edge, and Docker Tools.

Key Features

● Explore real-world IoT use-cases using Python and edge computing.
● Hands-on projects on embedded devices like Raspberry Pi and Jetson Nano.
● Learn edge-cloud integration, Docker, and protocols such as MQTT and CoAP.
● Covers security, streaming data, and future edge computing trends.

Book Description

The Internet of Things (IoT) is reshaping the way the world collects, processes, and responds to data—from smart homes and wearables to autonomous vehicles and industrial automation. As the demand for fast, secure, and intelligent data handling grows, edge computing becomes a key enabler, pushing computation closer to the source and reducing latency, cloud dependency, and security risks.

Practical IoT Edge Computing with Python equips readers with a complete, hands-on roadmap to build robust, real-time IoT systems, using edge devices and Python. You will begin by understanding the core concepts of IoT, and the limitations of traditional cloud-based models. Thus, step by step, you will move through building an IoT data pipeline, integrating edge and cloud, and deploying on devices like Raspberry Pi and Jetson Nano, as well as working with protocols such as MQTT and CoAP.

You will also gain practical experience with data preprocessing, edge intelligence, containerization (Docker/Kubernetes), and security measures like blockchain. Each chapter builds your confidence to design scalable, secure, and responsive IoT systems.

Hence, whether you are a student, developer, or industry professional, this book offers the tools and knowledge to turn IoT concepts into fully functioning edge solutions.

What you will learn

● Understand edge vs. cloud computing in IoT system architectures.
● Build IoT data pipelines including pre-processing and analysis steps.
● Deploy Python-based data processing on embedded edge platforms.
● Use networking protocols (MQTT, CoAP and AMQP) in edge devices.
● Containerize models with Docker/Kubernetes for edge deployment.
● Secure IoT systems with blockchain, and understand privacy challenges.

Who is this book for?

This book is ideal for IoT Engineers, Data Analysts, AI/ML Engineers, Embedded Systems Developers, Network Architects, and Cloud-Edge Integration Specialists. The book will also be useful for undergraduate students, IoT enthusiasts, and professionals with foundational Python and ML skills, as well as intermediate knowledge of OS, databases, and networks.

Table of Contents

1. Introduction to IoT and Edge
2. Conventional Cloud versus Edge
3. Building IoT Data Pipelines
4. Integrating Edge with Cloud in IoT Architecture
5. Exploring Edge Platforms and Devices
6. IoT Data Networking at Edge
7. Pre-Processing Data on Edge Devices
8. Leveraging Edge Intelligence
9. Streaming Data Processing
10. Containerization Technology for Edge Intelligence
11. Data Security and Privacy
12. Future Trends
Index

About Author & Technical Reviewer

Dr. Rajasi Tushar Athawale is a voluntary research associate in Mobile Sensing and Intelligence Security (MoSIS Lab), University of Tennessee, Knoxville, USA, working under Dr. Jian Liu. She also conducts independent research on IoT systems integrating ML/AI and edge computing. Her current research focuses on wearable and contactless gait analysis using multi-task transformer architectures to predict running gait parameters from low-cost IMU data. These models are optimized for real-time deployment on edge devices such as Raspberry Pi 4 and Jetson Nano.

Rajasi completed her Ph.D. in Computer Science and Engineering from Motilal Nehru National Institute of Technology (MNNIT) Allahabad in 2024. Her doctoral dissertation, “Design and Implementation of Edge-based Framework for Smart Monitoring of Public Restrooms in Developing Countries,” presents a Python-based system that adaptively fuses heterogeneous data and user feedback while handling network constraints and power outages. The framework was deployed on Raspberry Pi-based setups and tested using real-world sensor data.

About the Technical Reviewer

Dhiraj Singh Rathod is a seasoned technology leader with over 12 years of experience in designing and developing IoT and IIoT enterprise solutions, with expertise in both on-premises and cloud platforms like AWS and Microsoft Azure. His career spans various industries, including steel, power, and manufacturing, where he has delivered robust systems for applications such as smart milking and water management.

Shashank is a seasoned IIoT Engineer with over 8 years of comprehensive experience in industrial automation, IoT system design, and edge computing implementations. Currently serving as Deputy Manager - Research & Development, he brings a unique blend of theoretical knowledge and practical expertise to the field of Industrial Internet of Things (IIoT) and edge computing.