Edge Computing, a booming technology in the industrial sector

Four out of ten Spanish companies will double their investments in Edge Computing by 2022. Next we will analyze: Why is this technology making such a strong impact, what advantages does it have for organizations, what is its degree of maturity in Spain and how to scale its deployment in an efficient and simple way?


The first question we need to answer is: What is edge computing and what benefits does it bring to the industrial sector? Edge computing is a new model that moves data processing from the cloud to its place of origin, reducing latency and energy consumption, which is especially relevant in recent times with the rise in energy prices that is putting so many thousands of companies in dire straits.

In other words, we are talking about a new computing paradigm in which data is processed at or as close as possible to the source that generates it.

Advantages of Edge Computing

Its main advantages include the following:

  1. Scalability: by distributing the storage and processing of data across many locations, the growth of investment in infrastructure and capabilities for higher traffic volume or better algorithms is much more controlled.
  2. Security: by controlling data from its source location and therefore deciding what and when to send to the cloud, the cybersecurity risks of theft or improper access to information are reduced.
  3. Efficiency: analysis frequencies from the edge make it possible to work with thousands of data almost instantaneously, and analysis and response times are in the order of milliseconds. This allows for almost real-time use cases, unthinkable in cloud environments more oriented towards offline analysis of batches of information.

Until now, in most cases, large cloud computing platforms did the work of analysing the data collected by sensors and IoT devices. Now, thanks to Edge Computing, the data does not have to be centralised in its entirety, but part of it can be processed on distributed computers, called Edge Nodes, in the same place where the data is generated.

In this case, only the result or aggregate of such computation can be centralised. This avoids overloading the infrastructure, eliminating unnecessary latency and mitigating the security and data sovereignty risks that are so important to businesses and citizens today.

Recommended reading: IoT Edge Computing, Edge Nodes and Industrial use cases

Electricity and telecoms sectors lead the way

Of all the sectors of activity, the electricity and telecommunications sectors are the ones that have made the greatest commitment to this technology, investing between 100,000 and one million euros.

In fact, more than half of the projects worth more than one million euros that were undertaken last year in the field of edge computing were in the electricity distribution and transmission sector (Smart Grids).

More than $250 billion in Egde Computing

Global spending on edge computing could scale to over $250 billion. And according to some projections, by 2025, 80% of enterprise IoT projects will incorporate data processed by Artificial Intelligence systems. Of which, 75% will be processed through the edge.

Beyond future predictions, Edge Computing is already a reality, at the heart of the technological revolution . Having overcome the debate about when to go digital and knowing that it is now or never, it is time to talk about how.

Having digitised processes is no longer enough on its own, it is now required that these processes are not only digitised, but also as efficient as possible.

Strengthening the industrial sector

The dependence of the growth and health of an economy on the industrial sector is well known. The state of a country's industrial sector is directly related to the creation of more competitive and productive enterprises, which leads to more stable and better paid jobs.

One of the biggest challenges facing the industrial sector is to successfully complete its digital transformation. And in this context, it is worth asking whether edge computing is part of this transformation, knowing the degree of impact and importance it has on it: is edge computing sufficiently implemented in Spanish industry?

The field study carried out on the Barbara's Industrial Edge Computing BarometerThe field study conducted in Spain suggests that an increasing volume of data will be processed with this technology, also in Spain, which suggests that companies are implementing Edge Computing projects.

In its latest analysis of technology trends, the IT research and consulting firm Gartner predicts that this year half of all large companies will integrate edge computing projects. And it points out that the companies that can benefit most from the benefits of this technology are those that work with a high volume of devices that are in distributed geographic situations and generate data with high frequencies.

The new model of distributed Artificial Intelligence vs. the Cloud

The main drawbacks of the Edge compared to the Cloud are: lower computing power and heterogeneity of devices and technologies. Some detractors point out that although Edge computing is good, it still lacks the computing power available in a cloud system.

It is true that the power of the cloud today is not comparable to the Edge, so it will continue to be responsible for creating and serving the most computationally intensive models. While the lighter models are delegated to the Edge, which is also responsible for handling smaller transfer learning tasks in a distributed manner. Nevertheless, Edge technology is enabling more computing power every day , so it will be able to handle more and more complex applications.

You may be interested to read: AI at the Edge: cornerstone of the new industrial revolution

The IoT has revolutionised the Edge computing model by introducing new usage scenarios with the following conditions in common:

  • Real-time: Industries where millisecond decision making is required.
  • Connectivity: Today's mobile networks are often patchy and cannot always guarantee connection to the cloud. Some services need to be always connected.
  • Data volume: The amount of data generated by sensors can be enormous, which could clog wide-area communication channels.
  • Context: a business context that follows the trend of decentralisation, allowing IoT data to be interpreted for decision-making.

The disruption of the cloud model does not mean the disappearance of the cloud, but rather its extension to the periphery. The cloud will continue to exist. In fact, certain functions are better performed in the cloud, such as the training of predictive algorithms, as usually only the cloud has all the necessary history.

AI at the Edge is thus a new model of fully distributed computingThe AI on the Edge thus represents a new model of fully distributed computing, which supports a wide range of communications and interactions. This enables such powerful functionalities as:

  • Autonomous and local decision making based on incoming IoT data and cached enterprise information.
  • Peer-to-peer networks: devices that communicate with each other about an object within their range.
  • Distributed queries across data that is stored on devices, in the cloud and anywhere.
  • Distributed data management, e.g. data ageing: what data to store, where and for how long.
  • Self-learning algorithms that learn and run on the Edge, or in the cloud.
  • Isolation, with devices that are switched off for long periods of time, operating with minimal power consumption to maximise their lifespan.

Barbara, with this distributed computing model, it is possible to go beyond data analytics and not only connect industrial assets, but also coordinate them to analyse situations and make decisions in real time.

The AI implementation at the Edge thus revolutionises the industry as we know it, enabling the creation of value and new opportunities for the actors involved.

If you are interested in this article, please contact us to learn more about Barbara IoT Technology and request a personalised demo.