Edge Computing: journey to the edgeof industrial networks

The amount of IoT devices and data produced has increased and it is increasingly difficult to manage them through the data centre infrastructures used until now. One of the solutions identified is to move data and resources to the place where they are generated: if it is not possible to bring the data closer to the data centre, we bring the data centre close to the data. These are, in a nutshell, the foundations of Edge Computing, whose industrial networks produce tangible benefits such as a reduction in latency and a significant improvement in performance.

Let’s find out more about the world of Edge Computing: a journey to the edge of industrial networks to understand how this new technology can positively influence performance within automation contexts.

Definitions and benefits

Edge Computing is a distributed data processing method that takes place near the data collection and analysis point, therefore without the use of centralized servers and/or Clouds. Sensors are used to collect the information and Edge servers for secure and real-time processing.

This technology is able to increase the company’s operational efficiency, while improving performance and ensuring the security of the data processed. It can also be enhanced by technologies such as 5G, Digital Twin and Cloud-native platforms.

In fact, Edge Computing allows to manage a large amount of data directly on devices or in proximity servers, with undoubted advantages:

  • reduction of the time dedicated to data processing;
  • reduction of the bandwidth necessary for the transfer of information;
  • increased safety and operational efficiency.

It is therefore possible to distinguish between the concepts of Edge devices, capable of generating data located at the edge of the network, and Edge gateways, the nodes in charge of the transition between the IoT and the central network.

Enabling technologies

There are technologies that are considered enabling for Edge Computing and whose effect is tangible in many respects.


It is possible to solve the latency problem using the speed of 5G technology combined with the significant processing power of Edge Computing.

AI/ML (Artificial Intelligence/Machine Learning)

The increase in network performance and the consequent reduction in latency are necessary elements to guarantee the essential response time for the correct functioning of AI/ML-based solutions.

Digital twin

It is a key technology to enable the transition from physical to digital and from Cloud to Edge.

IT-OT convergence

IIoT, Edge and AI allow the convergence between IT (Information Technology) and OT (Operational Technology), with the development of parameters such as innovation and digitization.


Technology dedicated to safeguarding data privacy is enhanced when Edge processing is used.

Applications and data

Edge Computing is an ideal technology for managing data which, very often due to their high volume, cannot be transferred to a centralized location. But decentralization is a process that requires high levels of control and monitoring, which are guaranteed by Edge solutions.

The benefits of an Edge network architecture can be significant, as any outages are limited to a single point on the network, as well as significantly reducing traffic to data centres.

On the other hand, it should be remembered that, since IoT devices are still very vulnerable in terms of security, it is necessary to make the Edge network as protected and immune to attacks as possible.

We also talk about Edge Analytics regarding all aspects of the collection, analysis and action on data collected close to the source.

And here are some of the uses and applications that can be managed in practice by Edge Computing.

Industrial production

Artificial Intelligence and Machine Learning can be used in combination with an Edge structure, overcoming, as already mentioned, the problem of latency also in the context of Machine-To-Machine communication.

Predictive maintenance

Edge Processing can guarantee important results in areas such as predictive maintenance, identification of any anomalies, safety monitoring in critical or dangerous contexts and much more.

Industry 5.0

Combining IoT, Cloud and Edge it is possible to express a significant potential and overcome the limits within the Industry 5.0, in which the role and contribution of the industry within society are enhanced.

Job security

By cross-referencing and analysing the information arriving from different devices, it is possible to support companies in monitoring workplace conditions and compliance with safety protocols.

Edge Computing: the journey to the edge of industrial networks has allowed us to understand its enormous potential which in the coming years will contribute to making the contexts in which it will be used increasingly efficient.


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