Page 27 - Big Data Analytics for Connected Vehicles and Smart Cities

8 Big Data Analytics for Connected Vehicles and Smart Cities Introduction 9

This is done in a practical way by defining questions that are valuable and
relevant to transportation today. In some cases, readers may already be aware
of the questions and issues that are defined here; it is hoped, however, that the
descriptions given will reinforce readers’ preexisting knowledge and lend a bet-
ter grasp of the practical application of big data and analytics.
The questions to be addressed can be considered as essential elements
within the bridge between data science and transportation. It can be assumed
that the questions lie firmly on the transportation side of the bridge and that
the solutions lie on the data science side. Through defining the questions, we
begin the construction of the bridge and get our readers ready to walk across it

Chapter 3
This chapter explores the nature of big data with the intention of providing
a solid overview and understanding of this topic. This is not a data scientist’s
definition of big data; rather, it is a transportation view of data science subjects.
Chapter 3 addresses the different dimensions of big data, the importance of
big data, and the relevance of big data to transportation in a smart city. In ad-
dition, Chapter 3 provides examples of big data sources that exist within the
transportation ecosphere and the nature of that big data. The overall objective is
to thoroughly define the nature of big data and its role in forming the enabling
platform for analytics.
Chapter 4
Chapter 4 discusses connected and autonomous vehicles. These are two dif-
ferent subjects that are related using advanced technology for vehicles, some-
times referred to as telematics. Big data and analytics have a significant role to
play in the connected vehicle. The connected vehicle involves the concept of
linking vehicles to roadside infrastructure and vehicles to other vehicles with
wireless technology. Essentially this capability enables data to be obtained from
the vehicle and information to be provided to the driver while the vehicle is in
motion. Chapter 4 is an important element of the book because of the huge
potential data source that connected vehicles represent.
A recent article in Forbes magazine [3] featured the Ford Fusion Energi
plug-in hybrid. This car, which achieves 108 miles per gallon, generates 25 GB
of data every hour. Extrapolating this data rate across the entire U.S. vehicle
fleet, then connected vehicles could generate approximately 2 ZB of data every
year. This is a difficult number to comprehend, even by data scientists, but
consider that in 2013, the entire World Wide Web generated 4 ZB. This offers
some idea of the potential scale of connected vehicle data—50% of the entire
World Wide Web’s volume. Admittedly, this estimate is likely to be on the high
end because not all vehicles will be as smart as this particular Ford vehicle. How-
ever, it does give a sense of the impact that big data from connected vehicles will