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Designing Production-Grade and Large-Scale IoT Solutions.

You're reading from  Designing Production-Grade and Large-Scale IoT Solutions.

Product type Book
Published in May 2022
Publisher Packt
ISBN-13 9781838829254
Pages 412 pages
Edition 1st Edition
Languages
Author (1):
Mohamed Abdelaziz Mohamed Abdelaziz
Profile icon Mohamed Abdelaziz

Table of Contents (15) Chapters

Preface 1. Section 1: Anatomy of IoT
2. Chapter 1: Introduction to the IoT – The Big Picture 3. Chapter 2: The "I" in IoT – IoT Connectivity 4. Chapter 3: The "T" in IoT – Devices and Edge 5. Section 2: The IoT Backend (aka the IoT Cloud)
6. Chapter 4: Diving Deep into the IoT Backend (the IoT Cloud) 7. Chapter 5: Exploring IoT Platforms 8. Chapter 6: Understanding IoT Device Management 9. Chapter 7: In the End, It Is All about Data, Isn't it? 10. Section 3: IoT Application Architecture Paradigms and IoT Operational Excellence
11. Chapter 8: IoT Application Architecture Paradigms 12. Chapter 9: Operational Excellence Pillars for Production-Grade IoT Solutions 13. Chapter 10: Wrapping Up and Final Thoughts 14. Other Books You May Enjoy

IoT definition – the what

James Phillips, corporate vice president of Microsoft's Business Applications group, said the following;

It all starts with data; data is coming out of everything. If you can harness that data, make intelligence out of it, and use it to improve your business processes, you're in a position to transform your company and industry.

Have you heard about the Observe, Orient, Decide, Act (OODA) cycle that has been developed by a military strategist and United States Air Force Colonel, John Boyd? As the name suggests, it is a decision-making process based on a loop or series of steps or tasks. It all starts by observing or monitoring the target by collecting data from multiple sources, and then doing orientation by filtering, analyzing, and enriching the collected raw data. Next comes deciding, based on the insights collected and what actions need to be taken, and then finally executing such actions and assessing whether the decision taken was right or wrong. Such a loop continues endlessly.

Enterprises get insights from customer interactions, sales, and connected products to improve the quality of their products, find untouched revenue streams, increase customer satisfaction and retention, and improve the whole business process and operations.

As we can see, there is a strong relationship between IoT and data, so let's dive further into that relationship to understand IoT better.

The relationship between IoT and data

Imagine converting any physical thing around you into a smart connected thing and getting insights from that physical thing remotely. This would be awesome, wouldn't it?

How can I convert a physical thing into a smart thing, you may ask? The answer is by using IoT technologies and different IoT ecosystems, such as sensors/actuators, microcontrollers, connectivity, and IoT platforms.

Still not clear? Let's take an example. Suppose you run a waste disposal company. The trucks of the company currently travel once a week to different residential areas in the city. After a while, and based on some insights and data analytics, you realize that on some days, the trucks return almost empty as there is not much waste to be collected on those days. That is a business problem as you could save money on the fuel used and employee wages for those days, you could help to save the environment by reducing air pollution and toxic emissions, and so on.

To solve that problem, you need the waste bin to somehow talk to you or notify you whether it is full, halfway there, or empty. Interesting. So how can we do that? We could install in each waste bin a small low-power, constrained IoT device (or a microcontroller in short) equipped with an ultrasonic sensor (such as ultrasonic thru-beam sensors) to detect the level of waste inside the waste bin. You could have another sensor to detect how many times the bin lid has been opened. The microcontroller could have a radio communication module for short-range connectivity options such as Wi-Fi Bluetooth Low Energy or Zigbee, or long-range connectivity options such as cellular (mobile) network connectivity to provide internet or network connectivity to the microcontroller to send the sensor insights or data to the IoT Cloud backend.

Once you have the data in the IoT Cloud, then it becomes just another software or data analytics solution to get insights and act accordingly. Similarly, you could simply convert anything into a smart thing.

The concept of converting any physical thing into an internet-connected thing is really disruptive and has a big impact on the current internet infrastructure. Currently, there are billions of devices already connected to the internet, including laptops, mobiles, tablets, PCs, and other smart connected products, but with such a concept, we have to deal with massive growth in the number of devices connected to the internet network. In a single smart home, for example, you could have 100 devices or more connected to the internet.

The options in terms of dealing with such a massive number of internet-connected devices are either to extend the existing internet infrastructure or to have a dedicated IoT.

Definition of IoT as per Gartner

The IoT is a network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.

Now that we have an idea of what the IoT is, let's move on to its impact on different industries.

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Designing Production-Grade and Large-Scale IoT Solutions.
Published in: May 2022 Publisher: Packt ISBN-13: 9781838829254
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