A not entirely simple question, admittedly. Many factors play a role in answering this question, such as:
- Do the devices communicate via wired connections or wirelessly?
- Do long distances have to be covered or “only” a few meters or even centimeters?
- Are the communication partners “intelligent” devices or rather “only” sensors and actuators?
- Do all participants speak the same language or do we need a translator?
These questions (among other things) play an important role to determine how and if the IoT devices can talk to each other. We would like to shed some more light on this topic in this and the coming posts.
An IoT reference architecture
First, we should take a look at the basic IoT reference architecture and what the most important components of a good IoT architecture are. Here, we will initially limit ourselves to a view from “10,000” meters, so we don’t want to go into too much detail; only as far as it is needed for further understanding.
A rough overview of an IoT architecture – Cruising altitude 10000m
Basically, this architecture can be divided into three areas. At the field level, we have the “Things” (the things, devices, sensors…) that give the Internet of Things its name. This corresponds in a classical sense to the field level, where relevant information is captured, data is generated, possibly aggregated and then sent for further processing. Important insights are then usually generated by data analysis in a cloud environment due to its higher computing power available on demand. These “insights” then allow us to make well-founded (smart) and also early decisions, which is shown in the following image as the “Actions” area.
A closer look at an IoT architecture – Descent to 5000m
Somewhat more technically represented and equipped with the corresponding relevant components, the following picture emerges:
As already discussed, IoT devices are available at field level for the collection, generation and preprocessing of data. In order to generate relevant information (insights) from this data, the data prepared for transmission is sent to a cloud environment. The corresponding endpoint to which the devices connect is called the cloud gateway. This serves as an interface between the Things and the Insights and ensures secure communication with authorized IoT devices. All other unauthorized or unknown devices are rejected and cannot get past the doorman, so to speak, because they lack access authorization.
In addition, the cloud gateway internally routes the data to the internal stakeholders. This usually consists of a streaming analytics process that analyzes the incoming data in near real time and can identify potential initial problems. In addition, the data is usually also forwarded to an appropriate data storage for later and more detailed analysis, where new insights can then be generated through the common and well-known mechanisms of artificial intelligence (machine learning, deep learning,…) but also simpler statistical evaluations such as data correlations. All for the purpose of being able to make smart decisions, which can then be incorporated into corresponding business processes.
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