The Amazing Ways Volvo Uses Big Data, Machine Learning and Predictive Analytics

Cars are increasingly generating more and more data as they become ever more connected and empowered by smart, Internet of Things technology. The need to capitalize on this data is forcing auto manufacturers to rethink their data strategies.

Thanks to modern telemetry, vehicles have been gathering and transmitting data on how they are used for several decades. But the real explosion in data volume is down to customer data available from the applications and services available to today’s motorists.

The generally accepted definition of a “connected car” is a vehicle which can access online information and use it to assist in the maintenance and operation of the vehicle, as well as enhance the comfort and convenience of drivers and passengers.

Research suggests that by 2020, 75% of new cars shipped will fit this definition. The glut of data that will come with connected cars presents unprecedented opportunities for insight, but also significant challenges.

Swedish auto manufacturer Volvo has a reputation for safety, and so made upholding this one of the priorities of its data strategy. Additionally, it focuses on minimizing the impact of mechanical or systems failures, and detecting what features and functionality its customers want from their connected car.

Their director of business intelligence, Jan Wassen, tells me “We are trying to coordinate both creating and enabling tools for analytics, as well as making sure it is being triggered within areas where we should be active.

“There are clearly different areas where we have seen the need for this, and seen different opportunities. Then there are some areas where we haven’t seen so much.”

Identifying areas where analytics could provide the most benefit is part of Wassen’s job. Since Volvo launched its first car with internet connectivity in 1998, it has worked to evolve its data strategy, initially working on combining warranty claim data with telemetry to predict when parts would fail or when vehicles would need servicing.

The growing complexity of this dataset, along with the richness of the insights, prompted the business to vastly upscale its analytics technology, and today, it works with Teradata to carry out predictive, machine-learning driven analytics across petabyte scale datasets.

Their Early Warning System analyses over one million events every week to discern their relevance to breakdown and failure rates.

As well as predicting failure and breakdown rates, the company has put data to use in order to uphold its reputation as a maker of safe vehicles. One pilot project launched last year and scheduled to run until 2017 involves 1,000 cars fitted with sensors to detect driving conditions. The focus here is on monitoring the vehicles’ performance in hazardous situations such as when roads are icy. Data is uploaded to the Volvo Cloud and also shared with the Swedish highway authorities.

The third focus of Volvo’s analytic strategy is improving driver and passenger convenience. Efforts here involve monitoring the use of applications and comfort features to see what their customers are finding useful, and what is being underused or ignored. This includes entertainment features like built-in connectivity with streaming media services, as well as practical tools such as GPS, traffic incident reporting, parking space location and weather information.

“We are looking into what types of applications are being used and we continuously measure this in order for us to understand what it is that the customers want us to develop in the future,” Wassen tells me.

Of course, the next hot topic in the car world is autonomous vehicles, and Volvo, unsurprisingly, see safety as the main beneficiary here. A National Highway Safety Administration report found last year that 90% of US road accidents can be blamed on driver error. This helped firm up Volvo’s belief that removing the driver from the equation will lead to the largest ever reduction in accidents.

“We believe that one of the major contributors to road safety will be autonomous vehicles,” Wassen says. “We have very ambitious plans here, that are very much dependent on connectivity and IOT.”

One hundred autonomously driven Volvos will take to the streets of Gothenburg next year, with trials also planned for London and Shanghai in the near future.

In line with other auto manufacturers moving into self-driving and autonomously driven vehicles, Volvo is developing its own AI algorithms in house. Wassen says “I believe that this is really an important step for us. The next step with autonomously driven vehicles is to work out what the transportation service will look like. Will everyone have their own vehicle which is parked 95% of the time? Or will there be fleets of vehicles which you join? Clearly this is something which is already starting and we want to be on top of it, and Big Data and analytics is how we make sure we reap the benefit of this development.”

Of course once autonomous vehicles hit the roads in real numbers, another barrier is going to be broken in terms of the amount and quality of data which will routinely be gathered by everyday devices. In order to operate safely, its essential that the cars will have enough sensors and collect enough data to give an accurate picture of their surroundings at any time. This will have privacy implications – Volvo, or indeed any maker of autonomous vehicles, will essentially have access to a mobile network of highly sophisticated data gathering devices, constantly traversing every highway and road.

This quality and scale of data has previously only been available to governments and law enforcement agencies, via technology such as automatic number plate recognition (ANPR). Putting it in the hands of a large and diverse number of vehicle manufacturing companies, along with their tech partners, will be a security challenge that will require careful consideration.

In the short term, though, autonomous vehicles and the benefits, as well as challenges, which they will bring, are an inevitability. In my opinion the reduction in road deaths and serious injuries alone will be justification enough. But for the population at large reassurances are likely to be needed – that both the vehicles, and the data they collect, will be safe.

As always, I’d be interested in hearing your thoughts in the comments below.

Thank you for reading my post. Here at LinkedIn and at Forbes I regularly write about management, technology and Big Data. If you would like to read my future posts then please click ‘Follow‘ and feel free to also connect via TwitterFacebookSlideshare, and The Advanced Performance Institute.

You might also be interested in my new and free ebook on Big Data in Practice, which includes 3 Amazing use cases from NASA, Dominos Pizza and the NFL. You can download the ebook from here: Big Data in Practice eBook.

0

Start typing and press Enter to search