Accelerating Performance with the Artificial Intelligence of Things
Think real-time analytics. Use event
stream processing to analyze diverse
data in motion and identify what’s
most relevant.
Deploy intelligence where the
application needs it, whether in the
cloud, at the network edge or at the
device itself.
Combine AI technologies. AI
capabilities
such
as
object
identification or processing natural
language by themselves are valuable;
used in synergy, they are
indomitable.
Unify the complete analytics life
cycle, from streaming the data,
filtering it, scoring the data using the
model and storing relevant results to
continuously improve the system.
Think real-time analytics
Analyze high-velocity big data while it’s still
in motion – before it is stored – so you can
take immediate action on what’s relevant
and ignore what isn’t. Seize opportunities
and spot red flags hidden in torrents of fast-
moving data flowing through the business.
Event stream processing plays a vital role in
handling IoT data, and will be even more
vital with advances like 5G, to:
Detect events of interest and trigger
appropriate action. Event stream
processing
pinpoints
complex
patterns in real time, such as an
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action on a person’s mobile device or
unusual activity detected during a
banking transaction. Event stream
processing offers quick detection of
threats or opportunities.
Monitor aggregated information.
Event
stream
processing
continuously monitors sensor data
from equipment and devices, looking
for trends, correlations or anomalies
that could indicate a problem. Smart
devices can take remedial action,
such as notifying an operator,
moving loads or shutting down a
motor.
Cleanse and validate sensor data.
When sensor data is delayed,
incomplete or inconsistent, several
factors could be at play. Is dirty data
caused by an impending sensor
failure or a network disruption error?
A variety of techniques embedded
into data streams can detect
patterns and troubleshoot data
issues.
Predict and optimize operations in
real time. Advanced algorithms can
continuously score streaming data to
make decisions in the moment. For
example, information on a train’s
arrival could be analyzed in context
to delay a train’s departure from
another station, so commuters won’t
miss their connections.
June 2019