A Horizontal Taxonomy for the Industrial IoT
This has huge architectural impact. Collection systems can often benefit from a hub-and-spoke
“concentrator” or gateway. Widely-distributed systems can use a cloud-based server design, thus
moving the concentrator to the cloud.
Figure 10: IIoT Collection and Monitoring Applications
Collecting and analyzing field-produced data is perhaps the first “killer app” of the IIoT. The IIC’s “track and
trace” testbed, for instance, tracks tools on a factory floor so the system can automatically log use.Other
applications include monitoring gas turbines for efficient operation, testing aircraft landing gear for potentially
risky situations, and optimizing gas pipeline flow control. Since there is little inter-device flow, “hub and spoke”
system architectures that ease collection work well for these systems.
4.
DIMENSIONAL DECOMPOSITION AND MAP TO IMPLEMENTATION
The analogy with a biological taxonomy only goes so far. Industrial systems do not stem from
common ancestors and thus do not fall into crisply-defined categories. As implied above, most
systems exhibit some degree of each of the characteristics. This is actually a source of much of
the confusion, and the reason for our attempt to choose hard metrics at the risk of declaring
arbitrary boundaries. In the end, however, the goal is to use the characteristics to help select a
single system architecture. Designs and technologies satisfy the above goals to various extents.
With no system science to frame the search, the selection of a single architecture based on any
one requirement becomes confusing.
Perhaps a better analysis is to consider each of the k ey characteristics as an axis in an Ndimensional space. The taxonomical classification process then places each application on a point
in this N-dimensional space.
This is not a precise map. Applications may be complex and thus placement is not exact. The
metrics above delineate architecturally-significant boundaries that are not in reality crisp. So, the
lines that we have named are somewhat fuzzy. However, an exact position is often not important.
Our classification challenge is really only to decide on which side of each boundary our application
falls.
IIC Journal of Innovation
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