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0:04
The example of statistics
in the shipping sector.
0:08
Passenger and
freight ferries sail
between ports and islands, and
form a very important part of
our infrastructure
and trade systems.
They use a lot of fuel.
0:19
The context of this
research is that improving
fuel consumption in
shipping reduces costs,
but also, more importantly,
reduces emissions of
greenhouse gases, and this
is needed for conformance
to new regulations.
Ships produce what
is called Big Data.
Big Data is characterised
by the three V's.
It is data that pours
in at a great Velocity,
in great Volume and in a
wide Variety of formats.
Data scientists use the big data
transmitted by sensors on
the ships' engines with
open source meteorological
data to identify factors
affecting fuel
consumption, and a lot of
research has been
carried out on this.
The research questions
we're interested
in is finding the gap in
the current research and
in addition to
meteorological data,
also looking at the
effect of tide.
Therefore, our
research question is,
does the tide affect
fuel consumption when a ship
passes through a channel?
This is a particular issue in
shipping going
through islands where
the ship is sailing in open
water with heavy tides,
that could affect the
consumption of fuel.
If the tide does affect
the fuel consumption,
is the effect great enough to
justify timetable changes?
Shipping management are
interested to know whether they
should change their practice to
accommodate the effect of tide.
1:39
Here, the research
method is as follows.
We select a sample
of ship journeys.
We collect company data on
the fuel consumption
through the channel.
We gather associated information
including the load of the ship,
the meteorological, that is
the weather, and the tidal data.
We use statistical
methods to investigate
the effects of all these
factors on fuel consumption.
