Unlocking the Value of Connected Cars

Elliot Garbus, VP-IoT Solutions Group & GM-Automotive Solutions Division, Intel

Elliot Garbus, VP-IoT Solutions Group & GM-Automotive Solutions Division, Intel

Our world is growing more and more digital, and consumers want to be connected all the time. Increasingly, they expect the digital experiences in their car to align with the ones they enjoy outside the car. This is quickly turning the car from a mechanical device into a mobile device, with estimates that there will be 152 million connected cars on the roads by 2020, generating 11 petabytes of data annually. Accelerating this shift are technological forces ranging from the growth in portable devices to the Internet of Things (IoT). These developments have helped make the car an integral part of today’s interdependent web of information flow. The car is now able to both receive data and feed it to the cloud, the traffic infrastructure and other vehicles. Our ability to make the most of the intelligent connected car is directly linked to our ability to turn this data into insight.

The IT Opportunity

The car already generates a great deal of data. This only promises to grow as new capabilities and resources are added, making the car one of today’s most data-rich opportunities. IT managers can now consider how they pull pertinent data off of the car. Drivers, meanwhile, should be able to adjust privacy settings, dialing them up or down depending on preferences. Drivers want to choose how much data is shared based on the perceived value of sharing. This includes diagnostic data that enables car manufacturers to understand how their vehicle is being used, and what is happening inside it. This same intelligence is also allowing marketing, engineering, and IT organizations to work together to improve the car ownership experience. By calling on CRM data as well as a growing understanding of driver’s behavior and preferences, car companies can better anticipate needs, delivering the right experience at the right time. This could mean alerting the driver about an impending vehicle malfunction, and then proactively helping to solve it. By analyzing the data, automakers can capture operational details, observe trends, and understand issues, perhaps even addressing them before they happen. The rewards include cost avoidance and the development of better cars based on more detailed knowledge.

"Almost 50 percent of Americans aspire to live in a driverless city, with more than one-third believing it will happen this decade" 

The Call for Big Data Analytics

Potentially powerful new services such as crash and weather analysis will only be possible if the appropriate data is analyzed. That analysis must be conducted where and when it is needed. Multi-tiered analytics delivers that intelligence, addressing data from the vehicle’s sensors to the cloud, determining in real-time what you need to know now. For drivers, this means their car must analyze data locally and consult with the cloud. Automakers will need to address the entire data cycle, including car to cloud and back, car to transportation infrastructure and back, and eventually car to car. The data value must be extracted at every step—from sensor controllers to gateways, cloud to the client, and car to infrastructure. The results of the analysis can then be shared with other cars and the transportation infrastructure, or used by the driver to respond to issues before they occur. Automakers would also gain insight into their vehicle fleet and be able to provide notifications to car owners. For example, your car could identify trends and ask the automaker whether similar trends have led to expensive repairs or safety risks. Your service appointment could also be scheduled and parts pre-ordered to minimize disruption and avoid expensive courtesy cars. To support advances like autonomous driving and advanced driver assistance systems (ADAS), vehicles require significant compute horsepower, as well as an effective, high-speed connection to a secure, rigorous datacenter backbone for crowd-based analytics in the cloud. Self-driving/autonomous cars will have to use analysis to perform certain actions automatically.

Ensuring Security and Privacy

As connections grow among vehicles and the transportation infrastructure, automakers and consumers alike require that the car and what the car is talking to are secure. Security and safety are being interwoven with vehicles as malicious threats can lead to an actual technical failure. The ability of automakers to respond will help determine how quickly industry advancements (e.g., media and graphics, interactivity, storage) can be rolled out. It is also critical that the growing volumes of data transmitted to, from, and within the vehicle are safe. Vehicles will need to rely on data and the source of that data to make quick, accurate decisions. Only by adopting a multi-tiered analytic model can the vehicle perform the analytics locally, making full use of the car’s data. This helps ensure that before uploading to the cloud, the results are properly anonymized to protect user privacy. And as cars risk being stolen, the connected car will require car-specific anti-theft features to ensure its systems and data are protected and recoverable.

The Future of Driving

Almost 50 percent of Americans aspire to live in a driverless city, with more than one-third believing it will happen this decade. As the idea of the autonomous car gains momentum, automakers must rethink the vehicle again, treating it as a platform with multiple systems that can communicate, collaborate, and deliver the intelligence to know when and where action is needed. Intel is partnering with the automotive industry to channel its technology and expertise on innovations that enable new in-vehicle experiences today, and down the road.

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