Industrial Intelligence: AI’s Implications on Security, Seamlessness and Services for the IIoT
having enough time to complete all of my
assigned tasks.
I NTRODUCTION
Shifting from cleverness to intelligence
requires a degree of technical magic.
Fortunately, the building blocks are in place
and IoT and AI practitioners are jumping at
the chance to build a Digital David Blaine.
The Internet of Things is a confluence of
technologies that have matured earlier than
anticipated. This precociousness is not a bad
thing – it makes for clever devices that
simplify our lives by turning lights on and off
using timers or mobile applications. Other
clever systems can check the traffic each
morning and set my alarm to wake me
optimally based on a utility function
balancing my love of sleeping and in-car
public radio with my distaste of sitting in
gridlock. These applications make the world
a little more fun, a little happier, a little more
efficient. But…
A RTIFICIAL I NTELLIGENCE : A G RAND ,
O LD V ISION , C OMING OF A GE
Artificial Intelligence is a suite of
technologies capable of affording machines
perception and cognition. Perception allows
digital systems to observe themselves and
the surrounding world through sensors and
other data streams. Cognition allows
machines to learn rules and to solve
problems based on examples and models.
These elements combine such that machines
may develop an almost human-like intuition,
with an awareness of their own place,
purpose, and processes.
As researchers watching IoT evolve from
technological seedling into a powerful and
scalable innovation platform, we can’t help
but feel a little like parents watching a child
grow up. IoT is exciting, clever and lovable –
but it’s destined for greatness if it can
cultivate its talents. Having watched other
technologies grow, we know that being
precocious and clever is not sufficient – we
need IoT to be intelligent.
We are in the midst of an AI revolution – in
the sense that we’ve seen evolutions before.
AI has been used successfully in research
since the 1950’s. 1 However, Artificial
Intelligence struggled with adoption due to
the cost and complexity of its
implementation. Limited input data and
slow processing additionally challenged the
technology’s growth.
An intelligent IoT would read my emotion
from wearable devices and change the color
and brightness of my lights as I walk through
the house to evoke a pleasant response. An
intelligent alarm clock would consult my
medical records, work e-mails and calendar
events to ensure that I woke up at the right
time able to perform my best, while still
Today, things are a bit different from AI’s
nascent days. Computers are less expensive
and more power efficient, while popular,
1
Frank Rosenblatt is credited with creating the first perceptron in 1957 at the Cornell Aeronautical Laboratory. This is considered
by many to be the forerunner to modern artificial intelligence.
IIC Journal of Innovation
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