| | MARCH 20149CIOReviewunderstanding 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. The Call for Big Data AnalyticsPotentially 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 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 PrivacyAs 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 DrivingAlmost 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. Almost 50 percent of Americans aspire to live in a driverless city, with more than one-third believing it will happen this decade
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