Uses for edge computing usually originate from the IoT environment and, like the concept of a decentralized cloud architecture, still exist only in future projects. An important growth driver for edge computing technology is the increasing demand for real-time capable communication systems. Decentralized data processing is classified as a key technology for the following projects:
- Car-to-Car communication
- Smart Grid
- Smart Factory
In the future, a Connected Car – networked car – will become more than just a vehicle with an Internet connection. The future of mobility promises cloud-based early warning systems based on car-to-car communication and even completely autonomous means of transport. This requires an infrastructure that makes it possible to exchange data in real time between the vehicles and communication points on the track.
The electricity grid of the future will also be adaptive, and, thanks to decentralized energy management systems, will adapt to fluctuations in output. Smart grids are becoming a key technology in the context of the energy revolution. Switching to renewable energies poses new challenges for electricity grids. Instead of a few large central generators, numerous smaller and decentralized power generators have to be connected to storage facilities and end consumers. Thanks to solar panels, some of the latter even become electricity generators themselves. Intelligent networks therefore not only transport electricity, but they also supply data for its generation, storage and consumption. This enables everyone involved to react to changes in real time. The aim is to keep power grids stable despite increasing complexity and to make them more efficient through intelligent load control. New cloud concepts like Edge and Fog computing are needed to capture, store and process the resulting data masses in the shortest possible time.
A smart factory is a self-organizing production facility and logistics system that ideally no longer requires human intervention. An intelligent factory is practically a system of networked devices, machines and sensors that communicate with each other through the Internet of Things to carry out manufacturing processes. The smart factory communication system even includes the finished product and can therefore automatically react to supply and demand. AI systems and machine learning can be used to automate maintenance processes and production optimization. This requires an IT infrastructure that can evaluate large amounts of data and react to unforeseen events without delay. Traditional cloud systems failed because of the latency problem. Fog and edge computing architectures solve this problem through distributed data processing.