Understanding tech buzzwords like edge computing

31 Oct 2023

In today’s world, everything happens at warp speed.

Calls, emails and WhatsApps are sent back and forth, documents are shared, images are shared, information is shared. Data is shared. All at eye-watering rates.

We are all so connected, whether in our personal lives or our professional ones. Sometimes we can’t even see where the personal starts and the professional ends. Everything is so intertwined.

We have a multitude of technological solutions aimed at making our lives easier, more efficient, and more profitable. We are literally operating at the pinnacle of cutting-edge technology on a daily basis – because we have to – in order to keep up with the wants, desires, and expectations of the clients that we serve.

And all this technology, all this connectivity, all this digitisation, all this sharing of information comes down to one thing – data. Not just data, but big data.

This big data needs to be securely stored – in a place that makes sense for the company – but what else?

The limitation of any latency that can sometimes be experienced with cloud computing… that could certainly be another ace up the sleeve.

And with that we enter the world of edge computing…

What is edge computing?

According to IBM, edge computing is –

“a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. This proximity to data at its source can deliver strong business benefits, including faster insights, improved response times and better bandwidth availability”.

Wait a second! What is IoT? According to Tech Target –

“The internet of things, or IoT, is a network of interrelated devices that connect and exchange data with other IoT devices and the cloud. IoT devices are typically embedded with technology such as sensors and software and can include mechanical and digital machines and consumer objects”.

Edge computing isn’t anything new. It’s been around since branch offices have been around – where it’s been more reliable and efficient to place computing resources at the desired location rather than rely on a single central location (Tech Target).

According to Accenture, edge computing is all about processing data closer to where it’s being generated, enabling processing at greater speeds and volumes, leading to greater action-led results in real time.

Simply put – it’s all about the location of your data – getting it as close to the data centre as possible.

But this sounds a little bit like the cloud. Doesn’t it?

IPWatchDog describes the differences as follows –

“To distinguish edge computing from cloud computing, think of edge computing as computing power required to instantly analyse data generated by specific users and devices. In contrast, big data generated by masses of users and devices is analysed in the cloud. Indeed, the two technologies work in tandem to form a network infrastructure or architecture”.

Don’t be confused. It’s as simple as this – cloud computing is used for big data and is analysed in the cloud and edge computing is for specific users and their data, which is analysed instantly i.e. no lag between the cloud and the user.

To further illustrate this, Accenture sets out as follows –

“Cloud and the edge work hand in hand to enable new experiences. Data is generated or collected in many locations and then moved to the cloud, where computing is centralised, making it easier and cheaper to process data together in one place and at scale. Edge computing uses locally generated data to enable real-time responsiveness to create new experiences, while at the same time controlling sensitive data and reducing costs of data transmission to the cloud. Edge reduces latency, meaning it lowers response time by doing the work close to the source instead of sending it to the more distant cloud and then waiting for a response”.

Why is edge computing such a hyped-about topic?

Well, there are a number of reasons edge computing is so important. First and foremost is the potential it has to transform industries.

In fact, Accenture sets out as follows –

“Much of today’s computing already happens at the edge in places like hospitals, factories, and retail locations, processing the most sensitive data and powering critical systems that must function reliably and safely. These places require solutions with low latency that do not need a network connection. What makes edge so exciting is the potential it has for transforming business across every industry and function, from customer engagement and marketing to production and back-office operations. In all cases, edge helps make business functions proactive and adaptive – often in real-time – leading to new, optimised experiences for people.

Edge allows businesses to bring the digital world into the physical. Bringing online data and algorithms into brick-and-mortar stores to improve retail experiences. Creating systems that workers can train and situations where workers can learn from machines. Designing smart environments that look out for our safety and comfort. What these examples all have in common is edge computing, which is enabling companies to run applications with the most critical reliability, real-time and data requirements directly on-site. Ultimately, this allows companies to innovate faster, stand up new products and services more quickly and opens up possibilities for the creation of new revenue streams”.

Where is edge computing used?

Edge computing is generally used to collect, filter, process and analyse data “in-place” and in real-time at or as close to the data centre as possible. It’s a way to use, process and analyse data that doesn’t have to be shared to a centralised location – like the cloud – first.  The key differential with edge computing is the fact that data is analysed in real time.

The different industries edge computing may be used include –

1. Manufacturing – monitor manufacturing, enabling real-time analytics and machine learning – instantaneously – to find production errors and improve product manufacturing quality. A manufacturer can make faster and more accurate business decisions regarding the factory facility and manufacturing operations.
2. Farming – using sensors enables a farmer to track water use, nutrient density and determine optimal harvest. Data is collected and analysed to find the effects of environmental factors and continually improve the crop-growing algorithms and ensure that crops are harvested in peak condition.
3. Network optimisation – edge computing can help optimise network performance by measuring performance for users across the internet and then employing analytics to determine the most reliable, low-latency network path for each user’s traffic. In effect, edge computing is used to “steer” traffic across the network for optimal time-sensitive traffic performance.
4. Workplace safety – edge computing can combine and analyse data from on-site cameras, employee safety devices and various other sensors to help businesses oversee workplace conditions or ensure that employees follow established safety protocols – especially when the workplace is remote or unusually dangerous, such as construction sites or oil rigs.
5. Improved healthcare – healthcare facilities collect a vast amount of patient information (or data) from devices, sensors, and other medical equipment. That enormous data volume requires edge computing to apply automation and machine learning to access the data, ignore “normal” data and identify problem data so that clinicians can take immediate action to help patients avoid health incidents in real time.
6. Transportation – autonomous vehicles require and produce anywhere from 5 TB to 20 TB per day, gathering information about location, speed, vehicle condition, road conditions, traffic conditions and other vehicles. And the data must be aggregated and analysed in real time, while the vehicle is in motion. This requires significant onboard computing – each autonomous vehicle becomes an “edge.”
7. Retail – the large amounts of data generated by retail stores from surveillance cameras to stock tracking and sales data can be analysed to identify business opportunities, such as an effective endcap or campaign, predict sales and optimise vendor ordering (Tech Target).

With edge computing one must also keep in mind that backing up data is crucial. Businesses and law firms that implement edge computing may need to rethink their backup process and recovery strategies to ensure that data stays in the right place, protected and secure.

To read some pointers on the disadvantages of edge computing, read the article drafted by ENS titled  Navigating the legal frontier: Exploring the risks of edge computing.

When shopping around for your latest legal tech investment, don’t get hoodwinked by the overuse of technical buzzwords or empty promises of providing you the world – “Sure, we can help you with a healthy edge computing” – because once you understand what the word means, you will know whether they are a smart investment or not.

(Sources used and to whom we owe thanks: IBM; Tech Target; Accenture and IPWatchDog).

If you have any queries relating to legal tech and how you can incorporate it into your practice, get-in-touch and let’s see how we can take your software solution from good to phenomenal.

If you don’t have any software supporting your legal practice yet, it’s not a problem. We are here to help you from scratch too.

AJS – as always – has your back!

See also:

• Derick and the delicate dance of data protection
• Understanding tech buzzwords like a Distributed Cloud
• The future of tech law in South Africa
• The implications of open finance on data protection

(This article is provided for informational purposes only and not for the purpose of providing legal advice. For more information on the topic, please contact the author/s or the relevant provider.)