In order to build on the statement that edge analytics is like the personal computer revolution, but for IoT devices, let's take a technological step back and look at the way application computing used to be done. We'll start by taking a customary look at early computers.

Operators of early digital computers accessed the computer through paper punch cards, paper tape readout, blinking lights, and teletype machines adapted for computer use. By the mid-1960s, CRT (known as cathode ray tube) displays were used as displays in place of paper, allowing for better flexibility. CRT displays were the technology of television sets at the time. By the mid-1970s, dumb terminals using CRT...

What are the advantages of using an edge analytics architecture over a standard IoT architecture? Why go with a more expensive and complicated edge analytics solution over a basic IoT one? To answer these questions, let's outline a potential business model and apply both architectures to it.

Let's suppose you are an entrepreneur and you introduce the world to an exciting new soft drink, Edge Cola. Business is growing swiftly and you roll out your new soft drink with high-tech vending machines. You've heard of IoT and wonder how it could work with your vending machines.

Would a standard IoT architecture work for your business, or should you look into edge analytics?

As we have seen in the previous section, implementing edge analytics into our IoT design has advantages that outweigh the costs and complexity. However, before we can build an edge analytics system, we need to know what the key benefits are.

The following is a list of those benefits (note that these are the same key benefits as described in the Edge computing section):

• Privacy
• Latency
• Reliability

Let's take a look at an example. In the following diagram, we have designed an advanced security application using an edge analytics architecture. As you can see, we have a Raspberry Pi connected to a webcam, automated door, and a light sensor:

Our advanced security application uses the webcam and Raspberry Pi to recognize a visitor trying to gain access to the building. Based on the match of our visitor with a repository of known visitors, our advanced...

As with any application we design, when the time comes to design an edge analytics application, it is good to explore the options available. We will start off this section looking at a basic edge analytics architecture—one that does not involve using a vendor-specific solution. We will then turn our attention to the Microsoft Azure IoT platform and Microsoft Azure IoT Edge.

By basic edge analytics architecture, I am referring to an environment where the platform is made up of just the core physical components—a system where a standard operating system with custom code is used in place of a platform such as Microsoft Azure IoT. Let's face it&...

As with any technology, it is easy to get excited by its possibilities. However, before dedicating time to learning a new technology, the real-world usages of it may be called into question. Is anyone or any organization using this technology today?

For the American company Mars Drinks, keeping their vending machines fully stocked is very important for retaining customers. Mars Drinks rolled out a Microsoft Azure IoT Edge solution for just that purpose.

Route optimization directs service experts in their day-to-day operations restocking the machines. Using data analyzed from the vending machines, a service route may be planned or modified based on individual machine inventory. This makes the day-to-day task of the service experts in charge of refilling the machines more efficient.

Historical weather information collected by the Azure platform...

In this chapter, we began by touching briefly on the various computing platforms. We described how the mainframe computer with accompanying dumb terminals was superseded in part by the rise of connected personal computers, and how this was similar to the difference between an IoT application and an edge analytics one. We discussed how edge analytics is really just an edge computing paradigm.

We then looked at the advantages of using edge analytics over a traditional IoT application. We described a scenario where a vending machine uses a standard IoT solution, and the challenges this type of approach has.

We also started looking at the Microsoft Azure IoT offering. We discussed Microsoft Azure IoT Edge and how this relates to Azure IoT.

We concluded the chapter with a cursory look at a real-world example of the Microsoft Azure IoT Edge platform. In the next chapter, we...

Having learned the lessons in this chapter, try answering the following questions on your own:

1. True/False. Edge analytics is about processing data at the sensory level.
2. True/False. The first IoT device was a vending machine built by graduate students at CMU.
3. How many computers did Thomas Watson say the world would ever need?
4. What are the three key benefits of edge analytics to be understood?
5. True/False. The automated door used in our security application may be controlled anywhere in the world.
6. What are the advantages of using edge computing?
7. True/False. Azure IoT Edge and edge computing share the same advantages.
8. What were some of the uses of early P2P networks?
9. True/False. Microsoft Azure IoT is a collection of Azure services used to build IoT applications.
10. True/False. Route optimization was one of the benefits to Mars Drinks of using Azure IoT.