58 | AutoPartsAsia | FEBRUARY 2018the long-term, I am sure induction
charging will come into highways
with some stretches of the lane
having this equipment. You don’t
have to halt and park, the vehicle
will get charged while you drive,” he
said.
In India, about the automotive
industry, Bala shared this view,
“Using our IoT and Blockchain
platform, one can help reduce or
prevent occurrences of odometer
fraud. Odometers could be adjusted
downward to hide the fact that a
given vehicle travelled off-course
prior to reaching its intended
destination; in some scenarios
where one’s compensation is
predicated by the miles drive,
unscrupulous drivers could
also adjust the miles driven
shown on the odometer upwards,
in order to receive a higher
compensation.”
In the odometer fraud scenario, an
edge-device has to be placed in the
vehicle as a tracking mechanism.
Bala said, “In the automotive
space we leverage OBD2 (On
board diagnostics) port in vehicles
and include firmware to push the
relevant data upstream. About 80
percent of our focus will be on the
platform, the back-end. When no
edge-device exists, we develop the
necessary hardware and firmware
and have done so in several
domains.”Data Sharing In
Automotive Sector
Using Blockchain
As the world quickly progressestoward autonomous cars, a key
area of concern is the sharing of
data among automakers. Bala
commented, “Data sharing among
automotive players in the eco
system is very important as it
involves safety and security issues.
One of the consortiums NetObjex
belongs to is ITIC - International
Transportation Innovation Centre,
run by Professor Joachim Taiber,
a former professor of innovation at
Clemson University. He works
with different car companies
on test beds to experiment with
different theories and concepts.
One of the biggest areas he is
focusing on is data sharing.
ITIC is trying to get everyone to
share data.”“Sharing data can be accomplished
in various ways. One of the ways
is to collect it from all auto sources
like OEMs, distributors, service
groups, third party sources, etc and
put it in a decentralised network.
Crypto-currency and distributor
ledger technology has really
taken off in countries that have a
socialist mindset; many countries
in Europe don’t mind sharing data
as they don’t believe in hoarding
it. We must ensure that it becomes
more broad-based to include more
countries. You can share and still
compete; companies need to think
about that. You compete based not
on the data but the algorithms, how
you are able to synthesise such
data to develop knowledge.
Data should be shared universally,”
he said.Edge Computing, Cloud
Computing And AI
In contrasting how decision making
can either be performed locally (or
at the edge) or done in the cloud,
Bala illustrated with the following
scenario. “For instance, in a
transportation ecosystem,one can
measure traffic patterns on the road
through sensors. If there is vehicle
congestion on the road, then the
localised sensors may be able to
provide feedback from a given
traffic junction and make localised
decisions, but each node wouldn’t
know what is happening across
the network. In order to ease the
congestion, the cloud will aggregate
data from all the nodes and make
a decision to change the traffic
pattern,by adjusting the length
of each traffic light, so as to ease
congestion. Aggregate decision-
making would be made at the cloud
level,” he said.
Bala also commented on how
AI links in the decision making
process. “Artificial Intelligence
(AI) has three main branches:
machine learning, natural language
processing and robotics. In the
above traffic example, Machine
Learning can be leveraged to figure
out what can be done to improve
traffic flow, which is very dynamic
and changes with time (e.g. during
school holidays the pattern will
change significantly).Another example may be the peak
periods at airports. One can easily
draw a correlation between airline
arrivals and departures to the traffic
flow in the areas surrounding theFOCUS