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How will AIoT bring 5G into the mainstream?

(Image credit: O2)

5G will usher in a new era of connectivity, kickstarting the beginning of a technology revolution during which high-speed connectivity will become the new norm. It will transform the way we work, play and innovate.

That being said, 5G will also introduce newfound complexities for network and service operators. With 5G comes 8K video streaming, machine communications and vast quantities of new programmes and applications – while this promises high-quality audio and video, it also brings in challenges for network and service providers. Operators will be inundated with data which will all need to be analysed, interpreted and acted upon.

What’s more, telco operators are under pressure to meet rising consumer demand for convenience and flexibility. In response, automation provides a welcome solution. For example, AI and machine learning solutions enable operators to remain competitive by providing efficient and stable services while optimising 5G networks. 

The data dilemma

The anticipation surrounding 5G is enormous. By connecting everyone to everything, and across every sector, the technology is widely expected to kick off a new industrial and technological revolution.

Yet the advent of 5G invites a massive capacity and operational challenge. As more customers and organisations migrate, 5G networks are expected to grow to cover 65 per cent of the world’s population and carry 35 per cent of all its mobile data by 2024. For telecommunications operators, this data will be generated in unprecedented volumes. Telecommunications operators will need to constantly invest in their infrastructure to support the capacity increases needed.

With the number of devices connected and communicating within the Internet of Things (IoT), and the high-speed, high-bandwidth possibilities of 5G, traditional data collection and analysis is no longer sufficient. For the sake of planning, running and optimising customer experiences, operators will have a limitless need for more intelligent decision-making. Decisions also need to be taken across domains and silos in a split second to meet customer expectations and honour service agreements.

Delivering on this promise would be impossible if we could only depend on human staff and operators to generate insight and make decisions. Fortunately, AI and machine learning have a vital role to play here. When you merge AI and IoT, you get the Artificial Intelligence of Things, or AIoT – a revolutionary combination that can transform industries, elevate customer experiences and accelerate business performance exponentially.

By 2022, Gartner predicts that more than 80 per cent of enterprise IoT projects will include an AI component, up from a mere 10 per cent today.

Preparation is key

Telcos should seek to automate processes continuously during 5G rollout, with each step iterating on the last. By doing this, operators can sidestep major investments and overhauls by performing focused adjustments and expansions that both improve network performance and enhance the user experience.

However, before you maintain or enhance a 5G network, you first need to build it. Even at the planning stage there is enormous potential to make use of AIoT.

In today’s fast-moving, digital world, telcos are under tremendous pressure to deliver speed and scalability. To compete, they must be able to move resources, deliver connectivity and construct new capacity rapidly. However, it isn’t easy to respond with agility when, to supply connectivity to a new site of location, often requires the building of a new radio tower or data centre and significant civil engineering.

Network planning is often time and resource-intensive because the work is so data-heavy. Before a decision can be made, operators need to carefully review and analyse an assortment of population tables and network traffic. The objective is to have the cell site built and ready before customer demands start flooding in, but it’s challenging when the planning process is so complex and time-consuming.        

AIoT solutions are invaluable here because they can do much of the heavy-lifting for you. AIoT and analytics can process and produce insights from an immense amount and variety of data faster than any human can. With this information, operators can truly predict - rather than simply respond - to demand, ensuring they can build a cell site in the most lucrative location before the competition moves in.  

The customer comes first

AIoT really comes into its own, however, in network operations. 5G networks are micro in nature, made up of thousands of disparate and often siloed cell sites and data centres, each carrying and processing immense quantities of data. Keeping track and monitoring all of these sites, ensuring they are working properly and running efficiently, won’t be feasible without some form of automation.

You also need to consider the huge amount of data that needs to be analysed. It’s no longer feasible to move all of that data to a data centre or the cloud before you are able to detect network anomalies. This means that you need the ability to deploy AI out to the edges of the network, analysing the data in-stream, as it’s created. Actions can then be taken to fix problems before they disrupt the network, by detecting patterns of behaviour that provide an early warning of likely issues.

AIoT can predict network faults based on historical data and real-time, continuous analysis. It uses many different prediction models to work out the probability that a set threshold will be breached, alerting operators to the threat before it can snowball into a crisis.

The process is even more rigorous when machine learning is deployed for anomaly detection. Once a capacity issue is discovered, AIoT can search for the root cause and find the answer fast. From a business perspective, this enables automated monitoring and helps deliver on customer priorities like KPIs and SLAs.

‘Closed loop automation, whereby the AIoT automatically fixes network issues and delivers resources to operators, is still some time off. However, that’s not to say the technological foundations haven’t been laid. The challenge centres around how workers can collect the information needed to inform decisions in order to automate the entire decision-making process.

That being said, AI is helping to improve efficiencies when implemented in conjunction with human workers. By sifting through vast quantities of analytical data, they provide operators with actionable insights on which they can overcome complex problems. The benefits this presents are two-fold; not only are the risks of human error limited, but experts can also concentrate on the more value-adding tasks.

5G will transform the telco landscape, bringing in both opportunities and challenges. Technology stands to ease the disruption caused by its introduction – AI should be seen as an opportunity for businesses to exceed their goals, while delivering the services demanded by customers.

Jennifer Major, Head of IoT, SAS UK & Ireland