Intelligent Edge

Network technologies are now part and parcel of almost all aspects of our private and professional lives. They offer many advantages and make countless working processes simpler. At the same time, the data traffic arising from them leads to hefty tasks, ties up resources, and requires time. One solution for this is intelligent edge which reduces the distance between devices and the cloud, letting you gather and analyze data close to its point of collection. The result is noticeably quicker and more secure data processing that is a boon for companies and working processes.

With typical data processing, the data leaves its point of origin (i.e. the system or device on which it is collected) and is stored on a cloud or in an external data center, where it is inspected, analyzed and then played back. Obviously, this happens super quickly, but the constantly growing number of devices that are part of the Internet of Things also means that it is constantly getting more complex and that processes are getting longer. This is where intelligent edge comes in. Intelligent edge is located as close as possible to the point of collection of the data or at the location of the user. There, powerful edge computers capture the data, read it, play it back and only then do they forward it in a streamlined form on to the cloud.

Intelligent edge has two major advantages. The first is that it makes processes much quicker. As the data is evaluated, sorted, and played back closer to its point of collection, processes can also be optimized much more quickly. The devices that send the data get more direct input and can react to it immediately. On-site evaluation also means that potentially sensitive data is kept even more secure. As the data remains near its point of origin until it has been fully analyzed, there is a smaller risk of it being intercepted or damaged en route to an external data center or the cloud.

To use intelligent edge, powerful processors are needed, and they also need to have enough memory space. It is only with good enough performance that results can be achieved that actually bring value to users. The tasks that should be automated by AI down the line must first be trained. Once the AI has finished internalizing the various processes, precise ranges of tasks can be defined and carried out on a routine basis. Careful monitoring is therefore required right from the start. Data is transferred over the Internet or via an internal, decentralized network.

Intelligent edge is first and foremost suitable for companies that handle large amounts of data on a daily basis and therefore need as quick an analysis as possible. In time-sensitive processes, such as automated production, a few fractions of a second can be decisive when determining an optimal procedure.

If the data stays near its point of collection, adjustments can be made much more quickly. This also means that network problems are no longer an issue. Intelligent edge is also an attractive solution for companies that work with personal (customer) data. Such data can be protected in this way and any applicable regulations can be more easily complied with.

Given the ever-increasing quantities of data and the increasingly demanding requirements for its processing, the need for intelligent solutions will itself also increase. One application of this is the intelligent cloud which takes on board the ideas of intelligent edge and pushes them further. To do this, an AI creates a computer environment directly next to your own data processing environment. Latency is significantly reduced and working processes are automatically adjusted and optimized on site.

The intelligent cloud is much more than just a simple storage location – it carries a range of functions with it to analyze and sort data in real time and to send it back to its starting point.