Data is a valuable asset – a lot of SMEs have now realized that. However, since their transport to the cloud, where they are processed, often takes too long for many IoT processes and with increasing data volume, edge computing is becoming increasingly interesting.
Everyone wants to mine it – the gold of the 21st century; using sensors, actuators or other IoT technologies. Also the many medium-sized companies that cannot start their journey on the green field. The problem: The data is processed in the cloud. For many IoT applications, however, the transport there takes too long or costs too much due to the large amount of data or poor network connection.
We have known for a long time that it is not possible to process unlimited amounts of data even in the computer cloud. This results in great difficulties for the required IoT data exchange between the automation level and the cloud. All too often, added values are generated from the transmission and processing of real-time data or through the integration of sensors. Some examples of this are gripper modules, valve terminals with feedback, aggregates on machine tools, intelligent valve heads with additional logic or proportional control valves. Metadata that is rarely transmitted provides valuable information, for example why certain components have failed. They are therefore the basis for the development of IoT applications such as predictive maintenance or condition monitoring.
Also Read: Internet of Things (IoT) – Revolution Of IoT In Modern World
Endstation Latency
In these scenarios, latency is not just a disruptive factor, but an exclusion criterion. In addition, it can be assumed that the amount of data will become even larger in the future due to the increasing use of more data-intensive sensors, such as vibration or image sensors. The solution? Local temporary storage as well as aggregation and application of further algorithms to send the data already prepared for information to the cloud.
This is exactly the role of edge computing. Put simply, it moves data processing closer to the source or the production process and only forwards pre-filtered data in the required form. If the Edge Gateway comes from the operator, data sovereignty is also guaranteed at all times and the industrial IoT platforms, which are usually billed according to data rate, are used efficiently. In this way, edge computing not only speeds up the transport and processing of data in the cloud. It also reduces the risk of confidential data being disclosed. Because the local use of computing power also puts companies in a position to better control the distribution of information (such as trade secrets) or to be able to comply with guidelines (such as the GDPR).
Last but not least, companies in rural regions can benefit from these advantages. Many of them still do not have an adequate network connection – cloud computing is simply not possible for many. By moving data processing to a decentralized edge infrastructure – i.e. to the edge of the Internet – you save valuable bandwidth that can be used for just that.
That Speaks For Edge Computing
- Accelerate data transfer and processing in the cloud
- Improved controllability of confidential data
- Minimize load times
- Minimize latency
- Limitation of transmission delays and service failures
- Bypassing bandwidth restrictions
- Enabling real-time monitoring and services
- Reduction of network costs
Decentralized Data Processing
Data collection from existing systems, excessive latency, lack of bandwidth – medium-sized companies, in particular, have to face a number of hurdles on the way to IIoT. Edge computing solves these challenges by having a company share a pool of resources across multiple locations.
Also Read: Top 10 Artificial Intelligence Technologies In 2020
