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Before it Drives Cars, Big Data Will Drive the Car Industry

April 7, 2014 No Comments

Featured article by Yves de Montcheuil, Vice President of Marketing, Talend

Self-driving cars are still at the prototyping stage. But it’s unquestionable that these cars are driven by big data – thousands of data points per minute streaming from sensors and external data sources into the car’s computers to ensure a smooth and safe experience. However, well before we see these cars on our roads, another revolution is happening in the automotive industry – a revolution driven by big data.

Let’s follow a new car buyer (we’ll call him William) and see how much big data plays a role in his experience…

William just decided to get a new car. He begins his search on the Web, chatting with friends on social networks, reading comparisons and reviews published online by the trade press, and clicking on targeted banner ads. Before long, his Inbox begins to fill with messages inviting him to test out the latest models of different manufacturers. As William pulls into the chosen dealership, he gets a text message offering a promotional discount on the model that caught his attention the day before. He has barely set a foot outside his car when a salesman comes to greet him: not only does he already know that William is coming in today, he knows what model he is interested in and has several offers lined up for him.

William doesn’t need very long to make his decision. Along the way, let’s note that this model was designed based on user feedback, data collected by the sensors of previous generation vehicles, as well as feedback from dealers (what is popular or attractive and unappealing? What is needed and expected?). Changing patterns of use were also taken into account and the findings were refined based on the analysis of several different types of data, including performance data from Grand Prix races and test benches published by trade journals.

William is particularly interested by the latest generation navigation system included in the car, which not only tracks the travel time of other motorists to avoid traffic jams, but also to avoid particularly accident-prone areas and optimize fuel consumption and therefore carbon emissions. William’s decision is further helped by the custom financing terms, including insurance, offered by the dealer.

Once the vehicle is delivered, William’s first impulse is to program his driver preferences: adjustment and programming of the mirrors, height of the seat and steering wheel, temperature and favorite radio stations. This data is transmitted to the cloud instantly and can be used in other vehicles (loaner or rental). He also configures his mailbox (to check messages in voice mode) and his favorite routes on the navigation system. This also enables him to locate the cheapest gas station on his route based on his destination and actual fuel efficiency.

William decides to take a road-trip, but at times it is a bit long and monotonous. He did not sleep much the night before. His eyes begin to close intermittently and as time goes on he becomes careless in maintaining safe distances with the vehicles ahead. An alarm sounds and a friendly voice advises him to take a break. His driving behavior is analyzed in real time and compared with the average normal behavior of motorists. Eyes that close, a body that is slouching in the seat and swaying or rocking movements of the head are all warning signs of drowsiness. William decides to stop for a coffee. If he had not, the car could replace him in the event of imminent danger, or simply stop at the next parking lot or rest stop.

Leafing through the preventive maintenance manual of his vehicle, William learns that maintenance, previously based on the distance traveled, is now personalized based on the information collected by multiple sensors (brakes wear and tear, engine speed, fluids pressure, etc.). A detailed analysis of this data (compared to that from other drivers and the description of the breakdowns or repairs handled by dealers that the Data Scientists of the manufacturer examined) establishes the best timing for maintenance. As the car is connected, all this data is sent to the cloud to feed statistical models and send alerts to the driver if a potential anomaly is detected. In addition, data links now allow vehicles to communicate with each other to detect any potential problems in advance (safe distance, car broken down around a bend, traffic jam, etc.).

Does William’s experience sound futuristic? Some of it might be. But it’s closer than you think. And certainly closer than mainstream self-driving cars.

 

YvesM casual2 lores Before it Drives Cars, Big Data Will Drive the Car Industry

Yves de Montcheuil is the Vice President of Marketing at Talend, the recognized leader in open source integration. Yves holds a master’s degree in electrical engineering and computer science and has 20 years of experience in software product management, product marketing and corporate marketing. He is also a presenter, author, blogger, social media enthusiast, and can be followed on Twitter: @ydemontcheuil.

APPLICATION INTEGRATION, DATA and ANALYTICS , Fresh Ink, OPEN SOURCE

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