How Edge Computing & AI are Changing Mobile Technology
The telecommunications industry is in a prime position to capitalise on the latest advancements in mobile technology, with generative AI (Gen AI) alone predicted to generate up to US$100bn in impact. Edge computing also plays a crucial role in the telecommunications transformation by providing the infrastructure for deploying AI algorithms right where the data is generated.
Here, two telecommunications and mobile experts explore.
Telecoms, AI and edge computing
Manish Singh, CTO for Telecom Systems Business at Dell Technologies, sees that the telecommunications industry is positioned to capitalise on the advancements in AI.
AI can constantly analyse network traffic using machine learning and vast amounts of real-time data. By identifying and addressing bottlenecks, reducing latency and optimising resource allocations, Manish sees that AI can ensure that networks are able to seamlessly support the data-hungry applications we rely on daily.
“Network operators can also achieve their sustainability goals by applying AI to make their networks more energy efficient,” he continues. “Additionally, AI’s predictive capabilities are also revolutionising network maintenance. Through analysing historical data and identifying patterns, AI algorithms can predict equipment failures before they occur. This allows telecom operators to shift from reactive to proactive maintenance strategies, enhancing service reliability and lowering costly downtime.”
Studies indicate that AI-driven predictive maintenance can reduce critical incidents by as much as 35%, resulting in significant cost savings and a vastly improved customer experience – crucial factors in today’s always-connected world.
Manish knows that there are specific benefits that telecom providers can unlock by integrating AI into their edge infrastructure.
“Bringing data processing closer to its source means AI algorithms deployed at the edge can prioritise time-sensitive operations and generate actionable business insights closer to business operations,” he says.
They can also help to improve network optimisation by:
Efficiently examining network traffic patterns
Predicting congestion points
Dynamically rerouting traffic.
This not only enhances network performance, but also ensures optimal utilisation of resources, resulting in improved reliability and seamless connectivity for users.
“AI-integrated telecom networks leverage algorithms to safeguard their security infrastructure by speedily identifying anomalies and neutralising potential threats at the source,” Manish continues. “By embracing enhanced zero-trust principles and processing data locally at the edge, telecom providers significantly bolster data privacy and security, which, in turn, offers robust protection for users.”
Telecom operators have also been prioritising sustainability and reduced energy costs (well, what sector hasn’t?). Fortunately, AI plays a vital role in network energy efficiency – particularly at the edge in usually unstaffed locations.
“Using AI to gain insights into equipment usage patterns, operators can automate energy management processes and improve energy consumption at edge locations,” he shares.
Finally, telecom operators can leverage AI-ready infrastructure at the edge to launch cutting-edge services tailored to individual customer needs and preferences.
“By offering inferencing services at the edge, operators can provide customers with fast, personalised and context-aware solutions,” he says. “This approach not only elevates user experiences but also unlocks new revenue streams, fostering growth and competitiveness within the telecommunications market.”
“However, the speed of data creation has started to outpace the speed of data processing, which is becoming a big problem for businesses in our new age of AI,” shares Manish. “Edge computing enables bringing AI to the data, closer to where the data is generated.”
Previously, generating and retaining as much valuable data as possible was seen as a priority. Now, the focus for businesses has shifted to creating an infrastructure that can process this data in real time.
“Traditionally, all data is sent to a central location for processing, which isn't fit for purpose for a business bursting at the seams with data because it puts too much pressure on the network. This is why edge has fast become one of the key pillars of modern infrastructure for the AI era.”
Edge computing cuts out the middleman of having to send data to a central data centre to process. Instead, edge data is processed close to the source of the data in real-time, which significantly reduces latency, increases the speed of output and puts less pressure on a business’ central networks. This is critical for applications where ultra-low latency is essential.
“This is essential for any AI deployments that businesses want to roll out in the field, for example, in industries such as manufacturing. The greater availability of 5G networks also makes this the perfect time to invest in edge-powered AI, as its high bandwidth enables lower latency,” Manish adds.
So what is behind the rise of edge computing influencing the adoption and application of AI across businesses?
“The ability to deploy AI at the edge presents businesses with greater scope for innovation, especially in industries where businesses manage many different locations with different needs.”
AI and edge computing are being used to improve customer service, productivity and employee experience. The convergence of AI and 5G networks further amplifies these benefits. AI optimises 5G performance by predicting traffic patterns and dynamically managing resources. In turn, 5G's high bandwidth and low latency unlock advanced AI applications at the edge.
“By analysing customer behaviour and preferences, telecom operators can leverage AI to deliver personalised services and targeted promotions, enhancing customer satisfaction and driving revenue generation,” Manish concludes. “Additionally, AI-powered predictive maintenance reduces network downtime and optimises energy consumption, contributing to cost savings and sustainability goals.”
Evolving technologies in the mobile sector and their impact on telecommunications
Daily life is infused with direct and indirect experiences, accessed increasingly via mobile devices and mobile networks. In a state of connectivity, we are now ‘phygital’ beings (that is ‘physical-digital’), living in a mobile-enhanced world.
Our new mobile experiences are now realised through mobile-enabled personal wearables (watches, glasses, jewellery, earbuds, medical monitors and so on) and through home, school, workplace, commercial and public IoT. Our interactions with these mobile devices are changing. Voice interaction is as essential as touch, but the need for security is only increasing.
“As the connected ecosystem of AI home appliances expands, the importance of security is growing exponentially,” said Miyoung Yoo, EVP and Head of the Software Development Team, Digital Appliances Business at Samsung Electronics. “Samsung will continue to develop security solutions and achieve new certifications
Miyoung is at the forefront of AI development across the whole Samsung ecosystem and prioritises user peace of mind in regards to device security.
Michael Becker, Personal Data & Identity Working Group Chair of the Mobile Ecosystem Forum (MEF), echoes the sentiments shared by Miyoung.
“Voice and data are being shaped by Internet technology, which is fundamentally being shaped by the mobilisation of our lives,” he explains. “Privacy, security, data stewardship, processing and transparency are on people’s minds.”
The Mobile Ecosystem Forum (MEF) is a global trade body that was established in 2000 and is headquartered in the UK, with members across the world. As the voice of the mobile ecosystem, it focuses on cross-industry best practices, anti-fraud and monetisation. The Forum offers members the opportunity to network, collaborate and solve industry problems.
Michael observes that internet technologies are evolving quickly, such as:
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Enhanced communication protocols and standards (such as VoLTE, Vo5G, GR NR, Wi-Fi 6, 6G, DIDCom), as well as IoT, including DNA (Device, Network, Application)
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Cloud computing, edge and decentralised computing
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On-device processing and Blockchain
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AI (machine learning, discriminative and generative models, and general vs. personal AI deployments)
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New approaches to deploying and securing application programming interfaces (API)
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New data security and encryption measures
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Age assurance solutions and services (the Internet is becoming age-aware)
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New digital identity management strategies and solutions—biometrics, liveness, governance and trust frameworks and protocols.
The latter two points, says Michael, that the Internet is becoming age and Identity aware, cannot be underestimated.
“This new Internet is witnessing a convergence of traditional and new people-centric approaches to digital identities and data ownership and control,” he shares. “The nature of data is changing. It is growing in volume and becoming mission-critical to our daily interactions. Data – all data – is becoming more and more personal.”
Our identity focus is changing as well. In addition to individual customer identity management, new organisational (aka; entity) identity management solutions and services are taking shape.
“Not only will organisations be able to know your customer (KYC), individual customers will be able to know your entity (KYE),” he continues.
KYE services will manifest themselves as cryptographically verifiable branded calling, branded messaging (like with RCS), authentic content and delegated authority credentials—individuals will be able to verify the authority of an entity's representative, such as employees, call centre representatives, delivery agents and chatbots.
“Organisations will need to manage these new requirements, along with the obligations that are coming from a host of new identity and data-centric regulations,” Michael adds.
As voice and internet technologies converge new models of data exchange, selective disclosure and consent will emerge. Indeed, one day Michael anticipates that terms of services will go both ways.
“Not only will an individual need to agree to a business's terms of service, but businesses may also need to agree to an individual’s terms of access,” he says. “There is very little doubt that most of these interactions will be predominantly mediated via the ‘digital credentials wallet’ on mobile.”
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