When I started driving, cars were generating very little data. They got you from A to B without the addition of gadgets or gizmos. Connected cars as we know them today were certainly not a thing.
Today many vehicles are computers in their own right, connected to the Internet and data is flooding in. In fact, it’s estimated that a single connected car uploads 25GB of data to the cloud per hour.
With a quarter of a billion smart vehicles set to be on the road by 2020, that’s over 6 billion GBs every 60 minutes.
Such vast amounts of data are only going to continue growing in the years to come, putting the automotive industry in a leading position within the Internet of Things (IoT).
But at the same time a growing number of challenges and pressures are becoming apparent – namely the need to process, analyse and store all this new information.
As a result, datacentres are fast becoming the solution to the automotive sector’s rapid data growth, but how exactly are these data halls driving the connected car revolution forward?
From connected cars to autonomous autos
For the past few years, connected cars have been the hype of the sector.
By ‘connected’, we mean vehicles that have access to the internet in some form; cars that are often spotted with sensors that enable machine to machine (M2M) and machine to human (M2H) communication. As already noted, this level of connectivity generates substantial data sets.
The industry is continuing to innovate rapidly, and before connected cars even become commonplace, conversations are shifting to autonomous (or self-driving) vehicles – the futuristic Hollywood vision realised.
Here we’re talking about vehicles that operate without a human driver. While this could well give rise to many transportation efficiencies (reduced driving costs, improved convenience etc.) it will also undoubtedly bring about a more drastic automotive data revolution.
If one connected car today generates 25 GB of data an hour, one autonomous car in the future is likely to generate ten times that information.
On top of all the data a connected car generates, self-driving vehicles will have to be truly intelligent – learning how to their ‘drivers’ like to drive, sensing the physical environment around them, broadcasting location data and interacting with other vehicles and objects to traverse the roads safely.
By producing data on data in this way, autonomous cars will require even quicker analysis and bring entirely new elements of machine learning to the mix.
Which means beyond M2M/M2H communication we must also consider vehicle to vehicle (V2V), vehicle to everything (V2X), vehicle to infrastructure (V2I) vehicle to person (V2P) and vice versa (P2V).
Driving datacentre demand
The resulting complexity and scale of automotive data sets means more and more automotive giants are recognising the need for complex computing to drive their businesses (and vehicles) forward.
HPC – and the datacentre industry as a whole – sits in the driving seat of the intelligent automotive revolution
In turn, this has resulted in an exponential growth in the number of customers from the automotive industry turning to external data centre providers to meet their Big Data and High Performance Computing (HPC) demands.
The need for scalable, secure HPC datacentre solutions is therefore being felt keenly. For many auto-companies, these kind of data hubs are not necessarily those on their doorstep, and IT decision makers are looking to colocation datacentre providers to support their HPC operations, by supplementing compute capacity and improving operational costs.
In order to support the rapid innovation the automotive industry is showing at present, such campuses must present an ‘HPC-ready’ solution – offering the expertise to support the management of information loads as quickly, efficiently and successfully as the automotive experts that have been handling complex vehicle data for decades.
Innovating in Iceland
More often than not, these are remote facilities with the power infrastructure, resiliency levels and computing resources needed to process HPC loads cost-effectively. Moving automotive HPC workloads to campuses with inherent HPC-ready capability gives automotive manufacturers the medium and high power computing density required at significantly lower energy costs.
Ultimately that enables the ability to gain more insight from more data, and moves us closer to the benefits of autonomous driving.
A number of automotive leaders have recognised these benefits, and are already reaping the rewards. One such manufacturer is Volkswagen, which recently announced the migration of one megawatt of compute-intensive data applications to Verne Global’s Icelandic campus in order to support on-going vehicle and automotive tech developments.
Likewise, BMW is a well-established forward-thinker in this area, having run portions of its HPC operations – those responsible for the iconic i-series (i3/i8) vehicles, and for conducting simulations and computer-aided design (CAD) – from the same campus since 2012.
These automotive leaders consider Iceland an optimal location for their HPC clusters – not only for the energy and cost efficiencies it delivers, but the opportunity it allows them to shift their focus from time-intensive management of the technical compute requirements of their day-to-day work to what’s really important: continued automotive innovation.
Even so, wherever automotive data is stored, analysed and understood one thing is for sure: HPC – and the datacentre industry as a whole – sits in the driving seat of the intelligent automotive revolution.
It will advance our understanding of auto-tech, smarten our driving behaviours and ultimately carve a path to the coveted driverless and connected car technologies that will radically change the way we travel into the future.
Interested in hearing industry leaders discuss subjects like this and sharing their IoT use-cases? Attend the IoT Tech Expo World Series events with upcoming shows in Silicon Valley, London and Amsterdam to learn more.