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Implementing Cellular IoT Solutions for Digital Transformation

Implementing Cellular IoT Solutions for Digital Transformation

By : Dennis McCain
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Implementing Cellular IoT Solutions for Digital Transformation

Implementing Cellular IoT Solutions for Digital Transformation

5 (3)
By: Dennis McCain

Overview of this book

Even if you’re an IoT technology manager with a sound understanding of wireless local area network technologies like Wi-Fi and Bluetooth, you may face many unique challenges when implementing a wireless wide area network (WWAN) IoT solution with cellular technologies with respect to choosing the optimal IoT device, cellular connectivity, and architecture. To help you overcome such roadblocks, this digital transformation book guides you in implementing a robust, end-to-end cellular IoT solution using best practices for all aspects of managing the IoT solution. Starting with an introduction to the top IoT markets and solutions in the context of an enterprise’s digital transformation, this book will show you how this leads to cost savings and new business models. You’ll grasp all you need to know about the IoT system components, life cycle, and best practices for implementing an IoT solution. While the book explains all the leading IoT wireless technologies, the focus is on LTE and 5G cellular technologies. With a review of real-world cellular IoT solution case studies and future IoT trends, you'll be ready to work with wireless IoT technologies, devices, and architectures. By the end of this book, you'll be able to identify the best wireless technologies for your IoT use cases and successfully implement cellular IoT solutions addressing key issues in the solution life cycle.
Table of Contents (16 chapters)
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1
Part 1: Entering the World of the Internet of Things
5
Part 2: Deep Dive into Cellular IoT Solutions
11
Part 3: Cellular IoT Solution Life Cycle and Future Trends

Edge computing

In the context of an enterprise IoT solution, edge computing is where the IoT data collected by the device is analyzed/processed either directly by the device or at computing nodes physically closer to the device. As shown in Figure 6.4, any IoT network can be visualized as the IoT end device being the edge, with the network/computing nodes between the device and the cloud servers being the fog compute nodes where IoT data processing can reduce latency and network load in the overall IoT solution. Compared to the traditional IoT solution architecture, where the IoT device sends all data directly to a centralized cloud server for processing, edge and fog computing can enable more efficient data processing with lower latency for more real-time IoT applications.

Figure 6.4 – IoT edge, fog, and cloud architecture

Figure 6.4 – IoT edge, fog, and cloud architecture

Edge computing also enables more robust and scalable enterprise IoT solutions by distributing the IoT processing load to edge...

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