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How Vodafone is using scalable data streaming at the edge to boost road safety

Mark Samuels Profile picture for user Mark Samuels October 23, 2023
Telecommunications giant Vodafone is exploring how Confluent technology can play a key role in helping to make roads a safer place for everyone.

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(Image by Peggy und Marco Lachmann-Anke from Pixabay )

Vodafone is investigating how it can use scalable data streaming at the mobile edge to improve road safety for the people who use roads every day.

Marco Dias Silva, 5G and edge computing Expert at Vodafone Group, explained at the London leg of Confluent’s Data in Motion Tour 2023 how his organization is bringing insights on road use together with the help of mobile edge computing (MEC). 

Dias Silva said Vodafone wanted to find a way to use technology to make European roads safer. He quoted research that suggests as many as 3,500 people are killed globally in road traffic incidents every day. While technology is being used to help boost in-care safety, he said there is much to do regarding other users of roads, including those who aren’t driving vehicles:

The reality is that there are still big societal problems in our infrastructure today. Most of the technology has been applied within an automotive scenario or within vehicles. But everyone who uses the road is not just driving vehicles, including people walking on the street and road cyclists. In fact, everybody else comprises more than 50% of the deaths per year.

His team’s challenge was how Vodafone, as a telecommunications company with a huge amount of data, could use technology to help solve this problem. Dias Silva says his team worked with AWS and Confluent to think about how they could combine their services to generate data on road use from a range of mobile and fixed devices:

From the Vodafone side, we provide the connectivity, services, location, relevancy, and then we partner with AWS and their tools, such as cloud provision and a breadth of services, and we put that technology into edge computing.

Building a platform 

The number of edge devices – such as vehicles, IoT sensors and in-car computer systems – is increasing exponentially. Vodafone’s team used MEC, which sits between the packet core and AWS, to reap the benefits of centralized processing and data storage. Using Confluent technology, data that’s streamed from the edge can be processed in the MEC in milliseconds, says Dias Silva:

MEC provides enhanced quality of experience. Using Confluent on the edge means you can get messages at low latency.

Dias Silva says this approach means his team has been able to create a platform that helps them research how to improve European road safety. Known as Safer Transport for Europe Platform (STEP), this system uses the automotive messaging standard vehicle-to-everything (V2X) to exchange messages in real time:

At the heart our platform is the V2X message broker, which is where we apply Confluent to help stream data in real time. And the crucial aspect when you want to develop safety services – especially in automotive scenarios, where everything is happening and moving all the time – is to actually work in real time.

Dias Silva’s team collects data from devices and users across a range of areas, such as speed and position. His team also collects data from other organizations, such as local councils and emergency services, which might be undertaking roadworks or issuing traffic warnings:

You can use that data to expand your level of knowledge of what's happening on the roads. So, that's how we get into building more services for safety purposes.

Dias Silva says the aim is to keep building this network of connected data points:

We would hope that a lot of vehicles, people or bicycles will be digitally connected, but we're not there yet. Hopefully, that will come in the future.

Delivering real-time benefits

With the information that his team is managing to collect, Dias Silva says that Confluent technology is playing a critical role:

We have the broker, we have Kafka, and then you manage all that data over the Confluent piece to actually disseminate information across to all road users. Imagine that this information goes back into the devices and to the people, such as road authorities or emergency services.

Dias Silva says his team exposes its data via APIs and SDKs with the aim of building a broad ecosystem of participants and beneficiaries:

Data is in motion because it's being generated by people who are constantly moving from location to location. We can only make roads safer if we get high participation in our project to build a bigger picture of what's happening, which means we can then create more data-led services.

With the real-time picture that his team is creating, Dias Silva says there is the potential to create all kinds of benefits for organizations and the people who use roads:

Now, with all these messages, you can understand where accidents are happening, where traffic jams are happening, how to reroute traffic, and how roadworks are being set up, and then you can actually operate around them. It’s all about providing real-time information to people and vehicles.

Dias Silva says road operators can issue localized alerts to people who might be affected. The big hope is that the platform can eventually help to increase road safety for non-drivers, such as pedestrians and cyclists. He says that’s a challenge, as many of these individuals aren’t confined to a vehicle and aren’t digitally connected. But there is a potential solution and his team provides an SDK to help people link devices into the platform:

Every one of us has a smartphone in our pocket. Every one of us as a device that is able to use communication and generate messages into the system.

While the big potential benefit of the STEP platform is improved road safety, Dias Silva says it’s important to recognize that the technology can potentially be applied to other use cases across the automotive industry and beyond, such as organizations that need to move vehicles due to an emergency, or a delivery firm that wants to boost its operational efficiencies:

By leveraging the real-time communication of the platform, you can generate out-of-the-box thinking. The project shows what you can do with a combination of edge computing and connectivity and by building on your Confluent and Kafka workloads.

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