Edge Computing With Python
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Edge Computing with Python
Author: Abhinandan Bhadauria
language: en
Publisher: BPB Publications
Release Date: 2022-10-13
Deep Dive into Edge Computing and its Implementations KEY FEATURES ● Numerous real-world examples are provided to help readers grasp essential facets of Edge Computing. ● Apply a wide range of Python libraries, frameworks, and libraries to build intuitive IoT solutions. ● Exclusive coverage of the working of the Siemens Industrial Edge Computing Platform. DESCRIPTION The success of IoT and Industry 4.0 depends on edge computing and better network performance. The book, ‘Edge Computing with Python,’ intends to provide a fully-connected embedded environment in which readers can experience the applications of edge computing and IoT in a professional context. In this book, readers will learn what edge computing is, what its possible applications are, and how advantageous it is. This book provides thorough instructions for using Python to build every potential edge application. The book begins by configuring the programming environment with tools like VS Code, Python, and several popular libraries like SciPy, NumPy, and Pandas. Then, the book explains gaining access to IO devices, data handling, data storage, cloud connectivity, and hosting ready and pre-trained machine learning models step by step. The book delves into sophisticated ideas such as Docker Containers, MQTT, and FIWARE and how one can use them to construct Edge applications. In addition, the book details the Siemens Edge computing platform and how to use it for rapidly developing Edge applications. After reading this book, knowledge of Edge Computing's architecture, its benefits, and drawbacks will give readers a competitive advantage in the market. WHAT YOU WILL LEARN ● In-depth knowledge of Edge Computing and its strong ties with the Cloud, IoT, and IIoT. ● Illustrations of numerous Python packages and simulations for device interfaces. ● Explanation of multiple data gathering methods, including HTTP/REST, Serial Port, and ZeroMQ. ● Explanation of aspects of AI/ML, including model training, loading, and execution in the context of Edge Computing. ● Security threats and countermeasures, including SSL/TLS, Nginx, secure code, etc. ● Building full-fledged Edge applications using Docker, MQTT, FIWARE, and the Siemens Industrial Edge Platform. WHO THIS BOOK IS FOR Readers interested in embedded programming, system programming, edge device programming, electronics hobbyists, Internet of Things (IoT) engineers, microcontroller programming, and networking will find this book boost their career development. Knowledge of Docker, Containers, and REST is an added advantage. TABLE OF CONTENTS 1. Understanding Edge Computing 2. Up and Running with Edge Architectures 3. Challenges for Developers 4. Setting Up Edge Computing Environment 5. Data Acquisition and Processing 6. Data Storage and Cloud Connectivity 7. Executing AI/ML Models 8. Security and Protection 9. Applying Advanced Tools and Techniques 10. Developing End-to-End Edge Applications 11. Edge Platforms at a Glance
IoT and Edge Computing for Architects
Create scalable IoT and edge computing solutions with practical architectural strategies, robust communication protocols, and integrated analytics support for informed decision-making Key Features Build robust IoT and edge computing systems using real-world architectural strategies Explore a comprehensive range of technologies—from sensors and RF to cloud infrastructure and analytics Gain the insights needed to make informed technical decisions across communication protocols, security, and system design Book DescriptionIndustries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices. IoT and Edge Computing for Architects, 2E encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the book explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. The book wraps up the analytics portion with the application of statistical analysis, complex event processing, and deep learning models. The book then concludes by providing a holistic view of IoT security, cryptography, and shell security in addition to software-defined perimeters and blockchains.What you will learn Understand the role and scope of architecting a successful IoT deployment Scan the landscape of IoT technologies, from sensors to the cloud and more See the trade-offs in choices of protocols and communications in IoT deployments Become familiar with the terminology needed to work in the IoT space Broaden your skills in the multiple engineering domains necessary for the IoT architect Implement best practices to ensure reliability, scalability, and security in your IoT infrastructure Who this book is for This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, technologies, and trade-offs, and develop a 50,000-foot view of IoT architecture. An understanding of the architectural side of IoT is necessary.
IoT Data Analytics using Python
Harness the power of Python to analyze your IoT data KEY FEATURES ● Learn how to build an IoT Data Analytics infrastructure. ● Explore advanced techniques for IoT Data Analysis with Python. ● Gain hands-on experience applying IoT Data Analytics to real-world situations. DESCRIPTION Python is a popular programming language for data analytics, and it is also well-suited for IoT Data Analytics. By leveraging Python's versatility and its rich ecosystem of libraries and tools, Data Analytics for IoT can unlock valuable insights, enable predictive capabilities, and optimize decision-making in various IoT applications and domains. The book begins with a foundation in IoT fundamentals, its role in digital transformation, and why Python is the preferred language for IoT Data Analytics. It then covers essential data analytics concepts, how to establish an IoT Data Analytics environment, and how to design and manage real-time IoT data flows. Next, the book discusses how to implement Descriptive Analytics with Pandas, Time Series Forecasting with Python libraries, and Monitoring, Preventive Maintenance, Optimization, Text Mining, and Automation strategies. It also introduces Edge Computing and Analytics, discusses Continuous and Adaptive Learning concepts, and explores data flow and use cases for Edge Analytics. Finally, the book concludes with a chapter on IoT Data Analytics for self-driving cars, using the CRISP-DM framework for data collection, modeling, and deployment. By the end of the book, you will be equipped with the skills and knowledge needed to extract valuable insights from IoT data and build real-world applications. WHAT YOU WILL LEARN ● Explore the essentials of IoT Data Analytics and the Industry 4.0 revolution. ● Learn how to set up the IoT Data Analytics environment. ● Equip Python developers with data analysis foundations. ● Learn to build data lakes for real-time IoT data streaming. ● Learn to deploy machine learning models on edge devices. ● Understand Edge Computing with MicroPython for efficient IoT Data Analytics. WHO THIS BOOK IS FOR If you are an experienced Python developer who wants to master IoT Data Analytics, or a newcomer who wants to learn Python and its applications in IoT, this book will give you a thorough understanding of IoT Data Analytics and practical skills for real-world use cases. TABLE OF CONTENTS 1. Necessity of Analytics Across IoT 2. Up and Running with Data Analytics Fundamentals 3. Setting Up IoT Analytics Environment 4. Managing Data Pipeline and Cleaning 5. Designing Data Lake and Executing Data Transformation 6. Implementing Descriptive Analytics Using Pandas 7. Time Series Forecasting and Predictions 8. Monitoring and Preventive Maintenance 9. Model Deployment on Edge Devices 10. Understanding Edge Computing with MicroPython 11. IoT Analytics for Self-driving Vehicles