The partnership of IIoT and edge computing

The people behind the name: Sikho Ndzeku
April 1, 2021
Embracing New Business Models Through IIoT
September 29, 2021

Edge computing, while not a direct factor of the Industrial Internet of Things (IIoT), can optimise IIoT implementation to great lengths, especially in times where remote access has become vital to the success of industrial business models.

Data storage has, however, become a challenge for many businesses, especially as IIoT solutions gather more and more data from capturing points. As IIoT devices increase in number, so too the resultant data increases, in turn demanding new technologies and techniques to accommodate the network of data flow. The answer to this challenge may lie in edge computing.

Edge computing allows for expedited data processing and increased network efficiency since it negates the need for data centralisation. As a result, mobile operations will be able to be incorporated in a whole new way into your service offering.

But implementing edge computing into an IIoT system where mobile operators are involved does come with its own challenges. Edge computing is still in its fledgeling phase, and new avenues of implementation are still being sought out and perfected. Its implementations are thus evolving continuously.

Benefitting from the Edge

The greatest benefits of edge computing lie in more efficient response times and increased communication capabilities. Edge computing allows you to retain the high levels of automation that come from IIoT implementation throughout the data processing and integration procedure. Information that is sent through the cloud is effectively minimised thanks to edge computing solutions.

While edge computing will become an integral part of IIoT solutions in the years to come, edge computing already holds various advantages for IIoT:

  • Low latency communication and processing can be realised due to the IIoT device’s proximity to the edge.
  • IIoT device battery life is increased through reduced communication channel activation.
  • Increased data management efficiency is achieved through faster processing and filtering.
  • Increased processing power and data storage let you connect to analytics and Artificial Intelligence.
  • Heightened communication safety owing to dedicated communication paths.
  • Decentralised processing leads to less strain on the greater network.
  • Richer data is captured before analysis.

Data Aggregation

Data aggregation is integral to any plant and involves the collection and presentation of data gathered from numerous sources. What is crucial in data aggregation, is the collection of accurate and high-quality data needed to ensure accurate decision-making.

The primary benefit of edge computing in an IIoT system is the ability to enhance data aggregation efficiency through multiple data capturing points. But while edge computing removes the need for data to be processed through a central hub, where the likelihood of network overload increases and opens up processes to the possibility of delayed communications and information loss, it doesn’t truly assist the data aggregation process. In fact, it may open up the network to overwhelming volumes of incoming data.

A good example of when data aggregation could possibly overwhelm the network is during and after power outages, when meters and sensors send out alerts simultaneously. Yet, what makes data aggregation so much quicker when utilising edge computing is the fact that when multiple messages are received by edge nodes within a short period of time, they are not sent on individually, but rather as a summarised dataset that has been generated on the edge. Furthermore, through sampling, data aggregation through edge computing can streamline network traffic until the status of the disruption changes by analysing only selected devices when numerous devices have been affected.

Cloud Enablement

With greater use of the edge, and novel IIoT possibilities, cloud providers are also finding more opportunities to improve data storage and processing abilities. Working on the edge requires an active relationship between mobile operators and cloud providers, and encourages these providers to continue offering infrastructures that will simplify the use of IIoT solutions and edge computing in order to build an even more beneficial relationship between the two.

But there are already numerous benefits in linking the edge to cloud platforms in an IIoT system, including:

  • The appropriate allocation of resources.
  • Gaining a more accurate and holistic view of data.
  • Improved oversight of security across the network.
  • New business models.
  • Increased scalability.

Taking the First Steps

The implementation of IIoT solutions and edge computing doesn’t happen overnight, though. It requires finding a balance between utilising the benefits of edge computing and managing the set-up and processes of IIoT implementation. It’s not a process you will have to go through alone, however.

We help you find the best edge models for your IIoT solutions and help you maximise plant functionality. As part of an ongoing journey, we also ensure that operators understand how to utilise the cloud on the edge and how each operator should become integrated into the value chain to gain the most benefit from the implemented models.

Cyntech is not simply a product supplier, we are your partner in Industry 4.0: helping your business and plant utilise the benefits of IIoT on the edge and adapt to the changes and possibilities that are still to come.

This is a general information sheet and should not be used or relied on as legal or other professional advice. No liability can be accepted for any errors or omissions nor for any loss or damage arising from reliance upon any information herein. Always contact your legal adviser for specific and detailed advice. Errors and omissions excepted. (E&OE)

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