RFID at the Edge: Real-Time Asset Visibility on Handheld Devices in High-Interference Airport Environments

Abstract

Airports are among the most electromagnetically congested environments in which enterprise asset tracking systems are deployed, combining dense metal structures, high powered radar and communications emitters, overlapping wireless local area networks, and constantly moving ground vehicles, all of which degrade the read reliability of radio frequency identification systems relative to controlled warehouse or retail settings. This research article examines how edge computing architectures, in which signal filtering and decision logic execute directly on handheld RFID readers rather than in a centralized back end system, can materially improve real time asset visibility for baggage, ground support equipment, unit load devices, and maintenance tools operating within these high interference conditions.

The article surveys RFID fundamentals relevant to edge deployment, catalogs the specific sources of radio frequency interference present in ramp, hangar, and terminal environments, and reviews edge filtering techniques, including dense reader mode operation, frequency hopping, and machine learning based signal classification, that can be executed within the constrained compute and battery envelope of a handheld device. It further presents a comparative review of RFID against Bluetooth Low Energy, ultra wideband, and Wi-Fi based real time locating systems, an illustrative zone by zone simulation of read rate performance, and a discussion of the architectural, security, and governance considerations relevant to fleet scale handheld deployment across a large airport campus.

●      Ultra high frequency passive RFID tags typically cost between 0.05 and 0.15 United States dollars per unit at high volume, making tag level tracking economically viable across baggage and small asset populations numbering in the millions annually.

●      Read range for handheld ultra high frequency readers in open, low interference conditions typically spans 3 to 8 meters, but has been observed to degrade by 40 to 70 percent in dense metal ramp and hangar environments absent mitigation.

●      Global commercial airports handled well over 4 billion passenger bags annually in the years immediately preceding this study, with an increasing share tagged for automated tracking under industry baggage tracking resolutions adopted in 2018.

●      Edge based filtering approaches discussed in this article have demonstrated false read reduction in the range of 60 to 85 percent relative to unfiltered raw tag reads in comparable dense reader environments.