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\begin{document}

\title{Examining the Effectiveness of Commercial RFID Tags as Soil Moisture
Sensors}



\author[1]{Brett Stoddard}%
\author[2]{Dr. John Selker}%
\author[2]{Dr. Chet Udell}%
\affil[1]{Openly Published Environmental Sensing Lab}%
\affil[2]{College of Engineering/College of Ag. Science, Department of Ecological \& Biological Engineering}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\begin{abstract}
Currently available soil volumetric water content (VWC) sensors have
several drawbacks that pose certain challenges for implementation on
large scale for farms. Such issues include cost, scalability,
maintenance, wires running through fields, and single-spot resolution.
The development of a passive soil moisture sensing system utilizing
Radio Frequency Identification (RFID) would allay many of these issues.
The type of passive RFID tags discussed in this paper currently cost
between 8 to 15 cents retail per tag when purchased in bulk. An
incredibly cheap, scalable, low-maintenance, wireless, high-resolution
system for sensing soil moisture would be possible if such tags were
introduced into the agricultural world. This paper discusses both the
use cases as well as examines one implementation of the tags. In 2015,
RFID tag manufacturer SmarTrac started selling RFID moisture sensing
tags for use in the automotive industry to detect leaks during quality
assurance. We place those tags in soil at a depth of 4 inches and
compared the moisture levels sensed by the RFID tags with the relative
permittivity (\selectlanguage{greek}ε\selectlanguage{english}r) of the soil as measured by an industry-standard probe.
Using an equation derived by Topp et al, we converted to VWC. We tested
this over a wide range of moisture conditions and found a statistically
significant, correlational relationship between the sensor values from
the RFID tags and the probe's measurement of \selectlanguage{greek}ε\selectlanguage{english}r. We also identified a
possible function for mapping vales from the RFID tag to the probe
bounded by a reasonable margin of error.%
\end{abstract}%



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