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alternative approaches due to the productivity
gains of NI approach to system design, par-
ticularly with NI Linux Real-Time and the
LabVIEW FPGA Module. With the software
already provided by the NI SOM, Airbus can
focus more on system key features, such as
image processing on FPGAs.
Another key Industrial IoT application is in
renewable energy, where demand has rap-
idly increased as fossil fuel plants become
decommissioned. Grid operators are finding
that traditional measurement systems do not
offer adequate coverage to handle these new
challenges or manage the new risks they face.
National Grid U.K., the transmission system
operator for nearly 20 million people in the
United Kingdom, is deploying an advanced,
upgradable grid measurement system to pro-
vide better operational data for the condition
of the U.K. grid. Like many energy providers,
National Grid U.K. faces the challenges that
come with a rapidly changing grid; thus, the
company is focused on developing a flexible
solution that can be upgraded with new soft-
ware as the measurement needs of the grid
and amount of data available evolve.
Gathering reliable, real-time data from all
grid areas is critical to identifying problems
early and preventing power disruptions. To
keep the grid running consistently, operators
must be able to gather data from a wide range
of measurements and quickly gain insight
from that data to monitor the overall health of
the grid. Software-designed systems provide
customized measurement solutions that can
be upgraded in the future as new grid mod-
ernization challenges arise.
To address these challenges, National Grid U.K.
adopted a platform built on the Zynq-SoC-
based CompactRIO system that can provide
more measurements and adapt with the evolv-
ing grid for generations to come. This intercon-
nected network includes 136 systems, with 110
permanently installed in substations through-
out England and Wales, and 26 portable units
that provide on-the-go spot coverage as needed.
An identical software application runs on both
versions, minimizing the impact on system
integration, training and support. With an
open, flexible, software-designed instrument,
National Grid U.K. engineers can customize
the information available for grid operation
and easily make upgrades as needs change.
This approach improves grid monitoring
and reliability while reducing the amount of
equipment needed. Additionally, with the
advanced processing power of CompactRIO,
National Grid U.K. can easily maintain its net-
work of connected systems and push intelli-
gence down the grid to turn massive amounts
of raw data into useful information, keeping
the lights on for millions of businesses and
homes throughout the United Kingdom. The
idea of a smarter world that involves systems
with sensors and local processing connected
to share information is taking hold in every
industry. These Industrial IoT systems will
connect with users and with one another
on a global scale to help users make more
informed decisions.
Developing and deploying these systems will
involve a massive investment for decades
to come. The only way to meet the needs of
today and tomorrow is by deploying a net-
work of systems flexible enough to evolve and
adapt through a platform-based approach. A
single flexible hardware architecture such as
the Xilinx Zynq-SoC, deployed across many
applications, removes substantial hardware
complexity and makes each new problem pri-
marily a software challenge.
The same principle must be applied to soft-
ware tools to form a powerful hardware-soft-
ware platform that creates a unified solution.
An effective platform-based approach does
not focus on hardware or software but instead
on the innovation within the application itself.
The ongoing design of the IIoT represents a
massive business and technology opportunity
for everyone. Organizations worldwide are
working hard to define the IIoT and actively
gather use cases to better understand how best
to foster more innovation.
Engineers and scientists are already imple-
menting systems on the leading edge of the IIoT,
but they face many unknowns and much work
ahead. Engineers and scientists must start con-
centrating on a platform-based approach and
become part of the IIoT generation by getting
involved with these bodies to define the future
and ensure that businesses focus on innovation
and not simply integration.
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