Secure Edge Computing for IoT-Systems

Reliable Edge Computing systems

Digital processes generate a large amount of data. Often, communication via the cloud is not fast enough and effective enough. Reliable Edge Computing systems are needed to enable system integration and upgrading to Industry 4.0 capability to manage a large number of different interfaces, network different isolated solutions, integrate new application programs and take IT security in systems into account.

For many applications it becomes clear that data collection in the cloud is not the optimal solution. There are currently two competing approaches to data storage and processing: Cloud and Edge Computing. Digital applications, in particular, generate large amounts of data that are usually not actually needed to this extent. In addition, some processes require real-time information so that they can respond quickly to various events. When applications need data on an economical scale immediately and above all securely, it is questionable whether data storage in the cloud is the most suitable solution.

What is Edge Computing?

Edge Computing is a process in which data, services and application information are shifted directly to the logical «edge» of a network. The costly route to and from the cloud, which is often the bottleneck for fast and effective communication, is eliminated.

How does Edge Computing work?

Edge Computing only transfers data that is actually needed in the cloud to optimize processes. This architecture makes it easier to meet security requirements and the desire for data economy. The availability of systems, low latency times as well as data backup and encryption are easier to implement.

A gateway collects all incoming data and stores it internally. It then selects the data and sends the relevant information according to individual specifications for storage on local servers or, if necessary, in the cloud. Services with analysis functionality prepare this data for further processing.

Challenges of Edge Computing

System integration and upgrading to Industry 4.0 capability with Edge Computing components always leads to the same questions:

  • How do I manage the multitude of different interfaces?
  • How do I link the different island solutions with each other?
  • How do I integrate new application programs?
  • How do I take IT security into account in my system?


Challenge when using an AI (e.g. for predictive maintenance)


Accurate data is needed so that subsequent processes can be executed correctly. Incorrect or inaccurate data leads to wrong decisions. Companies therefore ask themselves the question when using cognitive intelligence: How do I get the right data?


What data is actually required?


In many applications, the machine control data is often not sufficient to assess the quality of a produced product. With additional information, scrap can be reduced and the life of equipment can be extended.


A suitable information architecture is often required in real time


An optimized data management which brings together different sources, stores the data centrally and can process structured and unstructured data, is required in the IoT. Metadata management, which provides proof of data origin, storage location and system status, is also necessary.

Functionality of Edge Computing


Data Management

Only on the basis of data can states of systems be analysed, visualised and controlled in a suitable way. Our know-how puts us in a position to extract relevant data from any systems on site, to link them with each other and on this basis to implement novel services, among other things.


Edge Analytics

As soon as relevant data is available on site via data management, it can be analyzed with Edge Analytics algorithms. With these analyses and evaluations, processes can be checked and optimized.


Edge Framework

Linking platforms should be designed for various communication technologies and should also provide a runtime environment for local apps as well as be able to run on various edge controllers. Individual programs manage all upcoming tasks on site.

Our service portfolio

The complete chain from one source:

  • Data acquisition and management with Edge Computing
    Our know-how enables us to extract relevant data from any systems on site, to link them with each other as required and, on this basis, to implement innovative services.
  • Edge Analytics
    We draw the right conclusions on site from the relevant data.
  • Data security
    We know how to secure systems, defend against attacks, and protect data ownership.
  • System integration
    We are able to integrate new technologies into our customers' existing systems and make them fit for the Industrial Internet of Things (IIoT).

Typical Edge Computing applications

  • Retrofitting of existing plants for Industry 4.0 suitability
  • Data Analytics
  • Predictive maintenance
  • Anomaly detection and energy management for life cycle management and production optimization