IoT

Internet of Things – what it is and what it’s not

The Internet of Things (IoT) or would it be better to say: “The Internet for Things”? After all, it’s all about depicting the real world in the digital world.

The term “IoT” encompasses everything to do with communication with “things”. After all, in the digital world, we have possibilities that we daren’t even dream of in the physical world:

• We can access information without being on-site.
• We can make custom transactions without being on-site.
• Machines can be optimized by monitoring processes.
• The production quality rises due to the improved exchange of information.
• Components with faults are noticed before they can cause damage. Predictive maintenance is a key term here, and you’ve surely been aware of it for years.
• Software updates allow your customers to benefit from the latest developments even for products that have already been delivered.

And why is this? In the digital world, many things that are really difficult (inefficient) or simply not possible in the physical world are much easier:

• Fast and efficient communication between small parts (sensors & actuators)
• Computing, networks, and data stores that are becoming more cost-effective and more energy-efficient
• Increasing degree of networking in society and industry

If, with this knowledge, we’re asked for a definition of the IoT, we’ll probably come up with an answer similar to that of the Federal Ministry for Economic Affairs and Energy: “With the Internet of Things, objects […] become intelligent due to programmability, storage capacities, sensors, and communication functions. For example, […] machine tools are controlled using software and […] networked […].”.

A bit vague? Not at all! Because each company must find out for itself what the IoT means. And that’s some job. The IoT is an enabler, and the way in which you use it sets you apart from your competitors. The main question here is this: What added value can my customers gain through the IoT? When answering this, it’s vital to consider the following:

• Customers are digital and networked.
• The context consists of today’s possibilities at all levels (sensors, network, computing, artificial intelligence, and more).

Before getting specific, let’s take a look at why it’s now exactly the right time for the IoT.

Why the IoT is growing

Regardless of which curve you look at: The costs for the infrastructure of digitalization – processors, storage devices, bandwidth – are halved on a regular basis. Or: If you take a look at the pure technical data, you’re always going to get more for your investment. This also applies to:

• Prices of sensors and actuators
• Sensor dimensions
• Energy consumption of sensors and other digital components
• Costs for energy storage systems

Source: The Atlas, charts, average cost of IoT sensors

The consequences of these developments are diverse:

• Applications that were previously too bulky can now be realized elegantly. The best known example is the mobile computer (smartphone).
• Increasingly efficient sensors (and batteries with a higher capacity) enable cost-effective usage where this was not previously possible.

What seems impossible today will be reality tomorrow. Small conveniences gradually make life, production, work, and placing orders easier:

• Changing the route for collecting dumpsters on the basis of how full they are? In some cases, this is already reality.
• Quality checks on the basis of intelligent cameras are becoming standard.
• Digital price displays in supermarkets – once too expensive and not economically viable. Today, they enable completely new pricing strategies. Read for yourself how it will soon be possible to save up to 50% on food waste thanks to dynamic price labels.

This exponential development forces us to rethink strategies constantly. But why now exactly? Because we need to make up some ground – and because together we can better integrate our customers into production, the supply chain, and the value creation process.

The significance of Industry 4.0

The definition of Industry 4.0 has been advanced by government-supported projects and work groups. Accordingly, descriptions and examples can be found on the Web pages of the Federal Ministry for Economic Affairs and Energy.

Source: © Plattform Industrie 4.0, Principles graphic

Particularly in Germany, the term Industry 4.0 (see Plattform Industrie 4.0) has attained a great significance. It’s about the networking of industry, networking at the factory – primarily automations in production.

In our country, small and medium-sized businesses have a special importance: Tailored production that’s been optimized to the smallest detail, perfect logistics, and seamless communication. We’re perfectly honed – and our products are perfect. We’re both innovative and cost-effective.

We could talk for much longer about how Germany’s small and medium-sized businesses have made it so successful. And we really must not forget why. But… what is the connection to the New World like? Let’s take a look at Amazon, Facebook, Google, Microsoft, Uber, Lyft, Spotify and More. Once thing’s clear: Business models are used there that we do not yet benefit from. Why not? How about having a kind of Amazon for our products and services? What if end-users could inspect and configure our machines via Facebook? Can I display location-specific information on my tablet in a production hall? Can I take this information into account when searching for spare parts?

There are many examples of Industry 4.0 applications. What’s important is that instead of being swamped by the digital world, we learn to swim as quickly as possible:

• Learning what Industry 4.0 means for us, today and tomorrow.
• Learning what our business partners expect from us, today and tomorrow.
• Implementing, adjusting, driving things forward.

The difference between IoT and Industry 4.0

Let it melt in your mouth: According to the Internet of Things 2019 study, quality assurance is one of the main application areas to date. German engineering – known top quality. Capitalizing on an existing advantage – it’s definitely possible with the latest technology. And if production costs can be reduced at the same time, by precisely predicting when each machine must be maintained, then we’ve done everything right.

A few words about the difference between the IoT and Industry 4.0: To sum up, the IoT generally relates to the general networking of “things”, with most of these developments affecting us all: Smartphones, the concept of a smart home, package tracking etc. Industry 4.0 uses the same technologies but in an industrial context, usually in production halls. As you can imagine, industrial requirements are generally more stringent than those for end-users in the field of smart homes. 

Now, the customer enjoys double the benefit:

• The digitalization and usage of the IoT brings customers closer to production or creates new services entirely (for example, the purchasing of services instead of machines).
• More efficient production processes increase quality and reduce costs.

Industrial IoT (IIoT)

The different terms for similar things might already have made you realize that this is a complex topic. In addition to the IoT and Industry 4.0, there’s the term “Industrial IoT”, “IIoT” for short:

The IoT, IIoT, and Industry 4.0 build upon a broad shared basis. Generally, we speak of networking, sensors and actuators, data, and central security concepts. However, the different elements give us different perspectives on IoT technologies:

Once you and your company get to grips with the IoT, you’ll realize this: The different viewpoints cannot be clearly separated. Because with advancing digitalization, you’re going to have to take in all views at once:

• The end-customer view that requires you to dive into the IoT or Industrial IoT.
• The internal view that – if you’re a producer – makes the Industry 4.0 perspective necessary at all times.

Convinced? Then stick with us, and be inspired by real solution scenarios!

The added value of use cases

Do you know the IoT use cases used in your sector? They’re easy enough to find out. There’s plenty of reading material. However, “easy to find out” is not something that’s going to set you apart from the competition. You have the information and understand the contexts that make you unique. And that’s why you’re successful. But how can you use your knowledge for Industry 4.0 technologies and the IoT? And that’s success factor no. 1: Using your knowledge and experience in conjunction with new technologies and concepts.

The design thinking method

We use tried-and-trusted and new methods here. Design thinking is a method that’s grown particularly close to our hearts. However, it always comes down to the challenge, to you and the problem you face. In workshops, we’ll find out together which customer benefits you can extract from the IoT. We’ll find out how you can pick up modern, digitalized customers – in the real (physical) world and in their digital world, too. You’ll be amazed at the possibilities.

Even if you cannot set yourself apart from the competition with use cases, that’s no reason not to be aware of them. On the contrary: It’s your duty to get to know the usual use cases (application scenarios) and to know how they can be used and what this requires. Below, we list some of the best known, most often used usage cases in German small and medium-sized companies at present:

IoT use case

But what’s awaiting you when you implement a project driven by the IoT and/or Industry 4.0? The next paragraph will answer that for you.

The benefits of reference architectures

Reference architectures make sense for the following reasons:

• They create standards for your IT applications. This makes troubleshooting, general maintenance, and the introduction of enhancements easier. Overall, you save on costs and retain flexibility.
• You gain comparability – and can easily check whether a change (such as switching to another cloud provider) would be a good move. Because your IT is structured and transparent.
• As your IT becomes more ordered, the speed at which you can get a grip on your IT applications and interdependencies increases. New employees can be trained up quickly – special knowledge, which is often restricted to employees with a history, is kept to a minimum.
  

It doesn’t matter whether your company pursues a known reference architecture or introduces a specific reference architecture for you alone. But before you get started on the task of defining your reference architecture, you should take a look at some suggestions and assess whether they would work for you. Note that reference architectures generally cover specific functions, tasks, and dimensions. They’re rarely complete, and often you only require a part of them. Knowing this allows you to protect yourself from unnecessary complexity, especially when introducing a new topic. In addition, you will need to extend your existing reference architecture in line with your needs.

Reference Architectural Model Industrie 4.0 (RAMI 4.0)

The Reference Architectural Model Industrie 4.0 (RAMI 4.0) was created by Zentralverband Elektrotechnik- und Elektronikindustrie e.V. (ZVEI) and Plattform Industrie 4.0. It allows a solution or scenario to be positioned on the basis of its most important coordinates. A 3D image with the following axes is used for this:

• The “Hierarchy Levels” axis depicts the various functions in a factory.
  
• The “Life Cycle Value Stream” axis describes the life cycle of plants and products.
  
• The “Layers” axis depicts the software or machine using a layered architecture.
  

Source: © Plattform Industrie 4.0

Several things are of note here:

• The concept of interlinking these three axes and arranging Industrie 4.0 applications accordingly is extremely attractive, and enables the visualization of aspects that were previously hidden from view.
  
• A certain amount of initial training is required in order to understand the complexity of the model and to interpret it. Only then do the benefits become apparent. In our experience, however, it is worth familiarizing yourself with the model and procedure. Even an examination of the thought processes of the creators of the model is extremely helpful.

One last comment here: Basically, RAMI 4.0 is a reference architecture model that aims to describe Industry 4.0 solutions in general. The flexibility that the model requires is, naturally, reflected in its complexity. When looking at it, find the topics that are particularly relevant for you. Set priorities. Alternatively, the Industrial Internet Reference Architecture (IIRA) is worth taking a look at – but the focus is different (Industrial IoT).

The Azure IoT reference architecture, which we describe below, is much more tangible.

Microsoft Azure IoT reference architecture

The Microsoft Azure IoT reference architecture is primarily tailored to the offerings of Microsoft, but can naturally be transferred to other providers of IoT platforms, too (whereby these also describe reference architectures). We recommend that you examine at least one reference architecture in detail.

Source: Microsoft Azure IoT reference architecture

In the first abstraction, the reference architecture is divided as follows:

• Things – The sensors (IoT devices), edge devices, and – in some cases – cloud gateways. The fact that software that needs to be updated from time to time (bulk service provisioning) is installed on sensors and other components should not be underestimated.
• Insights – Components that receive, transform, and save data and analyze this data in the traditional way.
• Action – Lastly, the execution of actions with the IoT (real actions or making decisions, for example).

The main functions of the Azure IoT reference architecture

The functions of the individual components in the Azure IoT reference architecture are  Microsoft Azure IoT reference architecture displayed clearly there. The most important ones are described in brief here in the form of an overview:

• IoT (edge) devices are the sensors, which can optionally already make data analyses (edge analytics). The sensors are assigned to an (Azure) IoT hub individually or by means of the DPS (Device Provisioning Service).
  
• The cloud gateway is responsible for managing the sensors. It provides secure communication between the sensors and the cloud.
• Data processing is divided into several stages. There are different paths here: The “warm” path is intended for the immediate interpretation of the data, so when you need to react to an event on an ad-hoc basis, for example. The “cold” path is used for the downstream interpretation of the data in order to generate new information from the data by means of machine learning, for example. The “stream” path provides traditional methods for the data processing of large datasets.
  
• Lastly, services are offered for the visualization and implementation of business logic (UI reporting, business integration services).
  

In comparison with RAMI 4.0, the Microsoft Azure IoT reference architecture is significantly more tangible with regard to logical components. In addition, the fact that data can be processed ad-hoc (warm) and downstream (cold) is beneficial. The focus is not on Industry 4.0 applications here; instead, the processing of data and the use of the Azure IoT is in the foreground. However, the breaking down of an automated factory into its various layers and the associated product life cycles is not described and must be solved on a case-by-case basis (if required).

Simplified definition and structure of an IoT reference architecture

A simple structure of an IoT reference architecture might appear as follows:

Sensors and actuators – this means sensors that record data and pass it onto the next level: Temperature data, telemetry data, humidity, pressure etc. In addition, actuators can be addressed here.

The Data transport – is the connection of the sensors and actuators with the layer above. Different protocols play a part here, such as MQTT (Message Queuing Telemetry Transport).

Data evaluation is where the gold embedded in the data is mined. The possibilities are manifold, and you’ll hear terms such as data science, data analytics, big data, stream processing, complex event processing, machine learning, artificial intelligence, and more.

At the application/visualization/dashboard level the results of the data evaluation are used: The service technician is told if a machine requires a maintenance run so that it does not fall victim to a failure during the next few weeks. And a single glance at the dashboard is enough to get an overview of the production status.

Security – is important at all levels and in all functions. This can affect the design of the hardware (for example, the use of TPM 2.0 chips) or just the software and configuration.

You can now see that a reference architecture can be extremely simple. However, you’ve probably noticed that we haven’t yet mentioned the fact that this simple reference architecture requires interpretation!

• The individual blocks can be seen as layers, but in fact they depict individual functions.
• The (cloud or IoT) gateways that securely forward the data – but can also evaluate it – should be assigned to data evaluation or data transport.
  
• Data can be saved at all levels.