I/O rates and timing
Future Features and Capabilities
Faster processors with integrated high-speed buses will enable faster
streaming to disk rates.
Flash storage will continue to increase in density and lower in cost.
Vendors will offer seamless integration between data-logging systems
and the cloud.
With more RAM and higher clock cycles on processors, data-logging
systems will integrate more advanced signal processing and become
less dependent on PCs for post-processing.
Logging systems will incorporate faster I/O rates.
More custom timing options will be available by leveraging heterogeneous computing technologies and programmable logic.
Software tools will run and be customizable directly on mobile devices
Integration with mobile devices will be the norm.
Buttons and knobs will disappear and every screen within a data-logging system will be multitouch enabled.
With more networking capabilities and processing power embedded
in processors, more connectivity and synchronization options will be
integrated into logging systems.
Low-power processing technologies will enable high-performance loggers to be smaller with wider operating temperature ranges.
which eliminates the need to transfer or store
large amounts of data.
With data-logging systems featuring more
intelligence and processing, the software they are
running is a primary way for vendors to differentiate themselves. Traditional data-logging software consists of turnkey tools that engineers use
to configure the system and get to the measurements quickly. The downside of turnkey tools is
that they tend to be less flexible. At the other end
of the spectrum, engineers and scientists can take
advantage of a text-based programming tool or
a graphical programming approach to program
the processors within these systems. Programming tools offer the most customization for these
data-logging systems, including a wider range of
signal processing and the ability to embed any
type of intelligence. But they have a steeper learning curve compared to turnkey tools.
bytes of data that need to be analyzed and sifted
through offline. With more intelligence, systems
can instead monitor a machine or structure
continuously and quickly adapt when certain
conditions are met. With more processing power,
signal processing functionality can be embedded
in the data-logging system itself on multicore
processors or programmable logic. These more
advanced systems can analyze the data inline and,
in turn, deliver more meaningful results faster,
Senior Group Manager for Data Acquisition
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