Categorization and criteria of classification for IoT systems and smart systems comparison

In this article, I’ll try to create categories and criteria for IoT and smart systems comparison.

If you don’t want to read the whole story — click here to go up to the point.

I’ve read a few articles about smart systems. Some systems were created by big brands like Amazon, Google or Philips. Some were small DIY systems…
Do you know what the problem is?
When I read these articles I didn’t know which one would be the best for me! Which should I use?

There’s no one simple way to compare smart systems. Every article I’ve read describes one system or scratches only the surface of the problem and compares only a few similar systems.

My conclusion was — we need one, systematized naming and categorization criteria.

Where to start?

I’ve compared 13 systems which could be (and are) called “smart”:

I’ve tried to collect a set of very different systems. Some of them are focused on one feature — like Philips Hue (light) or Sonos (sound/music). Some are much wider.

The mess

When you are trying to compare systems mentioned above your first thought is — THE HARDWARE!

You do so when you are looking for a new PC or phone, right? HW specification tells you how fast it is (performance), how good the camera is, how fast graphic is etc. You can easily (if you know what all letters and numbers mean) compare such devices this way. The reason why we do so is that most of PCs and phones have the same “features”. PCs can run Windows/Linux and phones mainly run Android or iOS. Everything beyond that are (reductive, but essentially) OS’ features and applications.

But look at this table:

This table shows central-points HW comparison. As you can see, it tells us nothing.

The most important for users in case of smart systems are features. So let’s compare them this way.


To notice differences and make a first approach to the topic let’s create a simple table:

  • green tick — the system offers this feature (directly),
  • read cross — the system does not offer such feature,
  • yellow arrows — the system offers the feature indirectly. It means other systems that offer the feature directly can be integrated with it.

I’ve assumed in the juxtaposition above that if the manufacturer does not mention such feature in official sources — the system does not offer it.

As you can see, there are many differences between systems.

The point — categorization and criteria

After analyzing the table above, we can conclude that some systems offer many features, while others are focused on one or two. In the light of these conclusions, we can propose “activity range” criterion and two groups:

  • complex,
  • non-complex.

We can call the system “complex” when it offers at least 3 of features from the list below:

  • multimedia management,
  • garage automation, opening doors or windows,
  • doors or windows opening sensors,
  • lights management,
  • temperature management,
  • devices’ power management,
  • cleaning devices management,
  • fire protection devices integration,
  • anti-intrusion systems,
  • video-monitoring management,
  • transport management.

I assumed that offering features from 1 or 2 groups mentioned above is not enough to call the system “complex”.

Groups unify the understanding of complexity. Without them, we could say that platform which offers smart lightbulbs, smart LED-strips, and smart desk lamps management is complex. In our case, this system offers the feature of only one group — lights management, so it is non-complex.

Using this approach you can easily compare systems — one can be more complex than another when 1st offers three and 2nd six features.

Further analysis shows us, that there are systems that propose many functionalities directly, and systems that offer them indirectly. In this case, we can group systems based on their role:

  • independent
  • independent with extension possibility
  • grouping
  • grouping expanded.

We will call systems which do not offer any external connections or any integration with external systems as “independent”.

“Independent with extension possibility” would be such systems, that offer more direct than indirect features.

“Groupingsystems would offer more features in an indirect way.

“Grouping expanded” are in addition to “grouping” also complex (as defined above).

It may seem to be complicated at first, but it’s intuitive. About system, which cannot manage any other, we can say it’s independent. If platform itself offers only a few options and its strength is managing other systems — we can say it’s “grouping”. When such platform gives us many features directly, and we can easily extend it, we can say it’s “grouping, expanded”.

Moving forward — some systems offer interesting solutions in autonomy area and they are able to make decisions without human intervention. We can identify such categories:

  • non-autonomous,
  • minor matter decision autonomy,
  • fully autonomous.

“Non-autonomous” platform cannot make any decision. Every operation is preceded by human action (for example entering settings — including default settings)

“Minor matter decision autonomy” means that platform can decide about things that do not threaten human life and health. For example, the system learns what is our favorite temperature in the morning and sets it for us (without entering default “morning temperature” value).

Fully autonomous — decisions can affect human’s health damage or death. Definitely, autonomous cars fit perfectly to this group.

The last group is based on the geographical spread. This category applies only to “smart space” systems. Grouping proposal:

  • local,
  • large,
  • metropolitan,
  • wide-area

Local systems apply to one flat or home.

Large platforms cover the area of many buildings inside one organization or settlement. Systems are limited to the 1km2 area.

Metropolitan platforms cover whole towns and cities areas (more than 1km2).

Wide-area systems apply to many cities, provinces, states or countries.

We see the similarity to LAN, MAN and WAN categorization. The additional “large” category is added to distinguish the one-house systems (most of the currently available platforms) from wider, settlement or whole company systems (much rarer).


As you can see we can categorize smart systems (also IoT systems) in many ways (not always completely separable). Every categorization group can give us some useful information about the platform.

We can distinguish categorization groups, based on:

activity range:

  • complex,
  • non-complex,

system’s role:

  • independent
  • independent with extension possibility
  • grouping
  • grouping expanded,


  • non-autonomous,
  • minor matter decision autonomy,
  • fully autonomous,

geographical spread:

  • local,
  • large,
  • metropolitan,
  • wide-area

Full system’s description should assign it to one from every criterion, for example complex, grouping expanded, non-autonomous and large.