its low tag costs, passive RFID offers users a way to keep
better track of those basic assets.
“Asset management is one of the key applications,” said
Wheeler. “Users want to control their assets, keep track of
where they are, and reduce shrink of assets and the inven-
tory they’re associated with.”
In contrast, active RFID is a better match for a facility
that’s looking to track moving assets both inside the facility
and out in the yard. “This is great for classic warehouse
applications where real-time location is a step up from the
level of visibility you have with warehouse management
systems (WMS), which only know the last location you
scanned,” Wheeler said. “When we really know the location
of lift trucks and people, it can lead to improved safety, pro-
ductivity, and workflow.”
SENSORS MAKE TAGS SMARTER
In response to the growing interest in RFID-enabled asset
tracking, some vendors are shifting their focus from ways of
making tags cheaper to ways of making tags smarter. That
is, they’re manufacturing tags that are capable of determining much more about each asset than just its location. As
part of that effort, RFID suppliers have begun outfitting
their tags with sensors, software, microprocessors, and
batteries.
Loaded with extras, such an RFID tag could be the size
of a TV remote and cost anywhere from $250 to more than
$1,000, said I.D. Systems’ Ehrman. But the tag’s enhanced
capabilities would more than offset the extra cost, he
argues. “If a Wal-Mart truck is sitting there with a loaded
trailer and the door is opened, we will notice,” Ehrman said.
“Or if it’s been sitting at the DC for more than two hours,
we could send a message to the manager that it is outside its
operating parameters.”
Typically deployed on large assets like lift trucks, inter-
modal containers, trailers, chassis, and rental cars, these
tags can bypass handheld readers, beaming data directly
back to a central network via Wi-Fi, cellular network, or
satellite signal. In line with the growing popularity of the
Internet of Things, this method tracks asset data through a
tag-to-system model instead of the standard tag-to-reader
approach.
Among other data, these long-range tags can collect
information on odometer mileage, fleet usage, dwell time,
and transit time for moving assets such as forklifts and
chassis. By graphing the results and comparing the statistics
with industry benchmarks, users can analyze the data with
an eye toward eliminating extraneous vehicles, scheduling
needed maintenance, and identifying savings opportunities.
“The bottom line is, these [trucks and other assets] are
carrying the inventory,” Ehrman said. “And ultimately, the
cost of tracking these assets will continue to go down, so we
will go from tracking the highest of the high-value assets to
lower- and lower-value assets.”
