Most people know that the term ”AI” is short for ”artificial intelligence”

AI is a true buzzword like the terms IoT and Industry 4.0 – and it is a term many tend to get insecure about the actual meaning of. Here we give you an explanation you can understand.


An extension of the human intelligence

Overall, the purpose of artificial intelligence was to serve as an extension of the human intelligence. AI technology has become possible thanks to machine learning and a great variety of algorithms.

These algorithms enable the AI to recognize appearance in smartphones face recognition, point out routes in GPS navigation and predict moving patterns in digital chess games.

Overall, artificial intelligence was created to serve as an extension of the human intelligence. 


Two types of AI

– with examples you can understand

Artificial intelligence is divided into two types:

  • General AI
  • Narrow AI

The general AI’s work is related to data learning – in relation to logic or language. This is the type of AI behind for example GPS navigation and interactive robots used in the production in many manufactories.

On the other hand, the work of the narrow AI is related to data learning – in relation to recognition. This AI-based feature is based on classification and recognizes everything from forms to complex patterns. This AI is for example used to recognize personal appearance in security systems in buildings and face appearance in smartphones. 

To sum it up:

General AI = data learning regarding logic or language

Narrow AI = data learning regarding recognition

AI consists of algorithms

If you are employed in the field of manufacturing, you should give innovative AI a chance. Especially in the field of building operation and production, AI is often worth large amounts of money.

The function of an algorithm is to process a certain amount of data – often called big data – and thereby understand and remember how different data is related. 

An example of an AI-based solution

ReMoni’s solution for energy savings is based on narrow AI. When we help companies save energy, the AI’s algorithms focus on pattern recognition and knowledge about how two data set are related.

Since AI consists of multiple algorithms, it can register if a defect might occur or a pattern should change. This has become possible thanks to the algorithm’s knowledge of how a certain installation is usually operating.

Two related data set

For further understanding, ReMonis temperature sensor HeatMoniSpot could make a concrete example. Placed outside water pipes, with one probe monitoring the temperature inside the water pipes and the other monitoring the room temperature, it collects two related data set.

Two data set are continuously registered and sent from sensor to ReCalc.

Here you can keep an eye of the relation between the two data set – and should you be busy when an error occurs, the AI based system will instantly let you know with an AI-based alarm.


Note: This explanation is based on leakage from water pipes and is just one way to understand the structure beyond AI. In this case the AI is neither located in sensor or gateway but exclusively in the technology behind the cloud-platform ReCalc.


Save money on building management

Use the AI to get insights about temperature, visitor numbers, power consumption or something fourth. AI gives you various ways to save money on building management.

In our society where building management has already been changed by IoT and Industry 4.0, we have to acknowledge that staying openminded for novel technology – and not at least AI – does pay off in the long run.