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5G + AI: better together (Part Two)

In part two of this series, we explore how the partnership between AI and 5G is already reshaping data collection, transportation and healthcare.

|Dec 1|magazine13 min read

To read the first part of this series exploring the evolving relationship between artificial intelligence (AI) and 5G communications, click here. In the second part of this series, we look at the ways in which AI and 5G are already working in concert to revolutionise the data collection, transportation and healthcare sectors. 

AI, 5G and transportation

Data filtered by AI and sent in real-time via 5G could reshape transportation within smart cities by enhancing data-driven services, suggests a recent report by BAI Communications. The study, which collected information from 2,400 respondents in London, New York, Hong Kong, Sydney and Toronto, revealed that 91% of rail users were willing to support government investments in better wireless services, while 85% said they were interested in 5G technology. 

Justin Berger, chief strategy officer at BAI Communications, explains, “Local governments and transit authorities know it’s important to build and maintain wireless infrastructure of the latest generation, given that users’ demand for the network increases exponentially over time.”

By using these two technologies, governments, businesses and transit organisations would be able to analyse data that could predict new business opportunities, better security and safety as well as industry innovations. 

Berger says, “As we build IoT applications and data-driven services that support modern use cases, that can ingest and analyse vast amounts of data in real time, we will need the infrastructure to support it – and that infrastructure is 5G.”

But the technology doesn't have to be contained to public transport services. AI and 5G can be leveraged in the field of autonomous vehicles, creating better surroundings awareness to improve public safety. In-vehicle sensors and roadside infrastructure could be used to predict potential problems. 

Senior analyst at Moor Insights and Strategy, Anshel Sag, says, “Leveraging 5G and AI to improve a driver or vehicle’s awareness beyond the vehicle’s internal sensors and utilising roadside infrastructure can extend these capabilities to anticipate potential problems. C-V2X keeps vehicles abreast, in real time, of other vehicles and the traffic conditions, improving road and public safety and enabling faster and more efficient travel to (hopefully) avoid traffic jams and improve fuel efficiency and reduce emissions.”

AI, 5G and healthcare

According to the report by Ericsson entitled ‘Employing AI techniques to enhance returns on 5G network investments’, 5G and AI have great potential when it comes to healthcare diagnostics and patient and health provider connectivity. The results suggest low latency, security, availability, better device battery life and reliability of the service coverage will make 5G combined with AI, a far more efficient healthcare toolset than the current 4G technology.

The report states, “When it comes to battery life, 42% of cross-industry decision makers expect 5G to enable devices to consume less power which is key in remote monitoring situations. Current consumer-grade wearables are widely used for preventative measures but are not considered sufficiently accurate or reliable for diagnosis.”

It continues, “In addition, for liability reasons, patients’ smartphones cannot be relied upon for connectivity. For their part, wearables require high-frequency updates from a central repository but at low-data rates. 5G connectivity is not limited to wearables; it also enables patients to carry a medical-grade 5G router that then connects to various wearables using Bluetooth.”

Remote procedures are also a possibility – as well as remote training via XR technology – to train medics in life-saving procedures without using real patients for practice. Robotic surgery is already available in some operating theatres, although surgeons stand with the robot as it carries out the procedure, rather than surgery taking place remotely. 

The idea of robotic surgery has been well received by the public, as Ericsson revealed that almost half of the respondents they surveyed (48%) were open to the idea of an AI surgeon carrying out their operation. 

AI, 5G and the IoT

These three aspects are already so interlinked that it would be impossible to untangle them, as the IoT increases in size with new AI devices connecting all the time, and as 5G begins to stream the generated data to billions of delivery points globally. 

But by using AI in conjunction with 5G in the vast network of device-created information, the amount of data collected via the IoT can be limited, with AI screening out useless information and only sending valuable data back to the cloud. As this has the potential to reduce the amount of data gravity pooling, companies are keen to adopt the technology. 

Ericsson’s research shows that the collection of unnecessary data could be the prime reason for companies to show good uptake on the new technologies. It states that 65% of respondents globally and 89% of respondents in North America cited data quality as an issue in terms of generating useful insights. Data from too many sources, degraded data, and a lack of single ownership were also major concerns. 

“At the heart of these concerns is the fact that traditional approaches to data analytics have been based upon centralised and generic analysis tools. These are unsuitable for addressing the increasing complexity and vast volumes of data in 5G networks. The barriers highlighted in our research (data quality, multiplicity of sources and systems) are indicative of the limitations of the traditional approach to data analytics,” the report says, explaining that AI-enabled networks that employ data analytics made systems smart, adaptive, self-aware and prescriptive. 

It adds, “These can play a key role in reducing associated operating costs and in addressing many of the barriers that service providers have indicated are preventing insights from data being acted upon.”

Explore the first installment of this two-part deep dive.
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