CASE
STUDY
❝
WE HAVE BEEN DEVELOPING
DUAL CAMERAS THAT ALLOW
USERS TO SWITCH BETWEEN
VISION AND THERMAL DATA
STREAMS FOR SOME TIME.
NOW WE HAVE PUT THESE
DATA STREAMS INTO THE
NVIDIA CHIP AND IT MEANS
USERS CAN DO SOME VERY
SMART THINGS WITH IT
S
MEs are central to the UK and Europe
commercial drone industry which
has enjoyed phenomenal growth in
recent years with one report suggesting
world sales will top $12bn in 2021, up from
$8bn last year.
This innovative technological unmanned
aerial vehicle market includes a long list
of commercial clients in construction,
energy, telecoms and land management
with many more business opportunities
expected to come online soon.
One company at the forefront of this
expansion is Aerialtronics, a Dutch-based
enterprise which has just announced it
is producing the first commercial drones
featuring cognitive computing capabilities
32
SME
from the IBM Watson Internet of Things
(IOT) Platform on IBM Cloud.
It’s another significant breakthrough
for the SME which employs less than 50
people but has recently won deals to deliver
unmanned aerial vehicles to the USA,
Indonesia, Peru and a number of countries
in Europe. The technology can provide
high-quality inspection services for global
organisations across multiple industries,
from monitoring city traffic patterns to
inspecting wind turbines, oil rigs and cell
tower optimisation across the UK and the
rest of the world.
Now, rather than climbing towers to
inspect key areas, teams can do the work
with unmanned drones from the safety
of the ground and, using high definition
cameras, immediately gain a 360-degree,
high resolution overview of what is
happening. Drones can capture these images
in minutes and send them to be analysed in
near real-time.
By putting Watson IoT capabilities into
flight, Aerialtronics can help companies
gain insight into places not otherwise
easily accessible. Possible scenarios
include:
Crowd safety: City police can gain
a full aerial view of crowds at major
events, tracking the flow of individuals
and identifying any anomalies that
might be a cause for concern. For
example, if an unusually large group
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