Harald Maier studied electronics/computer engineering at Aalen University. He started his professional career at TQ as a hardware engineer and gained extensive experience in the areas of embedded modules, system design and project management. Since 2009, his focus has been on product management and business development x86 / IoT. The objective: Optimized solutions for embedded and industrial IoT.

The Industrial Internet of Things is generating more and more data that needs to be managed. This data complexity needs to be mastered. What role does edge computing play in this?

Maier : The intelligent processing of data on site is a crucial success factor in Industrial IoT solutions. The large and complex volumes of data that are generated there often have to be used to make decisions at short notice, which requires local intelligence and, associated with this, edge computing. In addition, intelligent edge devices ensure that huge amounts of data are not simply sent to the cloud, but that meaningful, structured information is initially generated from it, which is then available for IoT cloud services. However, the performance of edge computing can vary greatly depending on the respective application.

Sensor data is pre-selected at the edge, software applications are processed or even AI calculations are carried out. What should users bear in mind with regard to the edge software landscape? Which technologies should/must be taken into account?

Maier : The specifications for the intelligent pre-processing of data, but also for certain edge management functions, can be very variable and are usually defined over time with an ever-increasing range of functions. Edge software solutions must therefore be flexibly expandable and equipped with update and device management functions. Security also plays a key role here, as it must be provided with updates independently of the actual functions. In many cases, container and Docker solutions are the ideal solution to cover a high degree of modularity and flexibility.

As the tasks grow, so do the hardware requirements. What should users look out for when choosing the right edge computing hardware?

Maier: Edge computing can be very diverse and therefore the hardware requirements are also very different. In any case, sufficient reserves should be provided for computing power and memory expansion, as the requirements and desires regarding the range of functions usually increase from the conception stage through the first pilot to the series solution. A modular hardware approach is particularly advantageous for more sophisticated solutions: by using computer-on-modules, edge devices can be equipped with a wide range of performance capabilities and are also upgradeable. This offers a high degree of freedom during the design phase, but also over the entire life cycle. In addition, new generations of devices can always benefit from the latest processor technology and new achievements in efficient data processing. With a modular approach, innovative, future-oriented solutions are created with minimal effort and extremely short development cycles.