Big Data in the Automobile Industry

Google recently revealed that their self-driving cars gather/create about 750 MB of data per second.  Cars can discard much of this data immediately, but a great deal of it will be batch-uploaded to the cloud, where it can be leveraged for a variety of purposes. User Experience customization, settings storage, preferences, maintenance, telematics, car monitoring are obvious solutions, but my using the latest technologies in Big Data analysis.

Once Big Data is truly unleashed (meaning that there are capture systems, storage systems, analytics, and business intelligence systems) there will be many applications across various industry verticals and the transportation industry is an excellent example.   The average American spends roughly 600 hours in their car in a year.  There is a lot of data that can be collected about habits, location, inferred driving, preferences, and more.  This data can be used for a variety of purposes including marketing, safety, road planning, etc.

Obtaining data from vehicles is a good example of one of the data capture types: machine learning.  Big Data will drive a variety of related areas including Machine-to-Machine (M2M), cloud storage, and more.

For more information about Big Data in various industry verticals, see:

http://www.mindcommerce.com/Publications/BigDataIndustryVerticals.php

About Mind Commerce

Analysis of telecom and ICT infrastructure, technologies, and applications.
This entry was posted in Big Data, Google, M2M. Bookmark the permalink.

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