Book Image

IoT and Edge Computing for Architects - Second Edition

By : Perry Lea
Book Image

IoT and Edge Computing for Architects - Second Edition

By: Perry Lea

Overview of this book

Industries 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, Second Edition 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.
Table of Contents (17 chapters)
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The value of an IoT system is not a single sensor event, or a million sensor events archived away. A significant amount of the value of IoT is in the interpretation of data and decisions based on that data.

While a world of billions of things connected and communicating with each other and the cloud is well and good, the value lies in what is within the data, what is not in the data, and what the patterns of data tell us. These are the data science and data analytics portions of IoT, and probably the most valuable areas for the customer.

Analytics for the IoT segment deals with:

  • Structured data (for example, SQL storage): A predictable format of data
  • Unstructured data (for example, raw video data or signals): A high degree of randomness and variance
  • Semi-structured (for example, Twitter feeds): Some degree of variance and randomness in form

Data also may need to be interpreted and analyzed...