RFID and Drones: The Next Generation of Plant Inventory

Collection of plant inventory (i.e., count, grade, plant size, yield) data is time-consuming, costly, and can be inaccurate. In response to increasing labor costs and shortages, there is an increased need for the adoption of more automated technologies by the nursery industry. Growers, small and lar...

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Published in:AgriEngineering Vol. 3; no. 2; pp. 168 - 181
Main Authors: Quino, Jannette, Maja, Joe Mari, Robbins, James, Fernandez, R. Thomas, Owen, James S., Chappell, Matthew
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-06-2021
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Abstract Collection of plant inventory (i.e., count, grade, plant size, yield) data is time-consuming, costly, and can be inaccurate. In response to increasing labor costs and shortages, there is an increased need for the adoption of more automated technologies by the nursery industry. Growers, small and large, are beginning to adopt technologies (e.g., plant spacing robots) that automate or augment certain operations, but greater strides must be taken to integrate next-generation technologies into these challenging unstructured agricultural environments. The main objective of this work is to demonstrate merging specific ground and aerial-based technologies (Radio Frequency Identification (RFID), and small Unmanned Aircraft System (sUAS)) into a holistic systems approach to address the specific need of moving toward automated on-demand plant inventory. This preliminary work focuses on evaluating different RFID tags with respect to their distance and orientation to the RFID reader. Fourteen different RFID tags, five distances (1.5 m, 3.0 m, 4.5 m, 6.0 m, and 7.6 m), and four tag orientations (the front of the tag (UP), back of the tag (DN), tag at sideways left (SL), and tag at sideways right (SR)) were assessed. Results showed that the tag upward orientation resulted in the highest scanning total for both the laboratory and field experiments. Two orientations (UP and SR) had significant effect on the scan total of tags. The distance between the reader and the tags at 1.5 m and 6.0 m did not significantly affect the scanning efficiency of the RFID system in horizontally fixed (p-value > 0.05) position regardless of tags. Different tag designs also produced different scan totals. Overall, since most of the tags were scanned at least once (except for Tag 6F), it is a very promising technology for use in nursery inventory data acquisition. This work will create a unique inventory system for agriculture where locations of plants or animals will not present a barrier as the system can easily be mounted on a drone. Although these experiments are focused on inventory in plant nurseries, results for this work has potential for inventory management in other agricultural sectors.
AbstractList Collection of plant inventory (i.e., count, grade, plant size, yield) data is time-consuming, costly, and can be inaccurate. In response to increasing labor costs and shortages, there is an increased need for the adoption of more automated technologies by the nursery industry. Growers, small and large, are beginning to adopt technologies (e.g., plant spacing robots) that automate or augment certain operations, but greater strides must be taken to integrate next-generation technologies into these challenging unstructured agricultural environments. The main objective of this work is to demonstrate merging specific ground and aerial-based technologies (Radio Frequency Identification (RFID), and small Unmanned Aircraft System (sUAS)) into a holistic systems approach to address the specific need of moving toward automated on-demand plant inventory. This preliminary work focuses on evaluating different RFID tags with respect to their distance and orientation to the RFID reader. Fourteen different RFID tags, five distances (1.5 m, 3.0 m, 4.5 m, 6.0 m, and 7.6 m), and four tag orientations (the front of the tag (UP), back of the tag (DN), tag at sideways left (SL), and tag at sideways right (SR)) were assessed. Results showed that the tag upward orientation resulted in the highest scanning total for both the laboratory and field experiments. Two orientations (UP and SR) had significant effect on the scan total of tags. The distance between the reader and the tags at 1.5 m and 6.0 m did not significantly affect the scanning efficiency of the RFID system in horizontally fixed (p-value > 0.05) position regardless of tags. Different tag designs also produced different scan totals. Overall, since most of the tags were scanned at least once (except for Tag 6F), it is a very promising technology for use in nursery inventory data acquisition. This work will create a unique inventory system for agriculture where locations of plants or animals will not present a barrier as the system can easily be mounted on a drone. Although these experiments are focused on inventory in plant nurseries, results for this work has potential for inventory management in other agricultural sectors.
Author Maja, Joe Mari
Quino, Jannette
Fernandez, R. Thomas
Chappell, Matthew
Robbins, James
Owen, James S.
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Cites_doi 10.1109/MPRV.2006.2
10.3389/fevo.2019.00257
10.1016/j.rse.2015.09.011
10.3390/ani11030829
10.1016/j.compag.2011.08.010
10.3390/rs11222645
10.1016/j.compag.2005.09.003
10.1117/12.2228929
10.3390/electronics6010009
10.19080/ARTOAJ.2018.14.555924
10.3390/rs10020285
10.1117/12.2304739
10.3390/s21051875
ContentType Journal Article
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Copyright_xml – notice: 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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References Ehsani (ref_2) 2015; 171
Robbins (ref_6) 2017; 45
Bridge (ref_16) 2019; 7
Lunadei (ref_10) 2011; 79
ref_14
ref_13
Want (ref_9) 2006; 5
ref_12
Fernandez (ref_8) 2014; 9
ref_1
Wang (ref_11) 2006; 50
ref_3
ref_18
ref_17
ref_15
ref_5
ref_4
ref_7
References_xml – volume: 5
  start-page: 25
  year: 2006
  ident: ref_9
  article-title: An Introduction to RFID Technology
  publication-title: IEEE Pervasive Comput.
  doi: 10.1109/MPRV.2006.2
  contributor:
    fullname: Want
– volume: 7
  start-page: 257
  year: 2019
  ident: ref_16
  article-title: An Arduino-Based RFID Platform for Animal Research
  publication-title: Front. Ecol. Evol.
  doi: 10.3389/fevo.2019.00257
  contributor:
    fullname: Bridge
– volume: 171
  start-page: 33
  year: 2015
  ident: ref_2
  article-title: Optimum spectral and geometric parameters for early detection of laurel wilt disease in avocado
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2015.09.011
  contributor:
    fullname: Ehsani
– ident: ref_17
  doi: 10.3390/ani11030829
– ident: ref_12
– volume: 79
  start-page: 42
  year: 2011
  ident: ref_10
  article-title: The role of RFID in agriculture: Applications, limitations and challenges
  publication-title: Comput. Electron. Agric.
  doi: 10.1016/j.compag.2011.08.010
  contributor:
    fullname: Lunadei
– ident: ref_7
  doi: 10.3390/rs11222645
– volume: 50
  start-page: 1
  year: 2006
  ident: ref_11
  article-title: Wireless sensors in agriculture and food industry—Recent development and future perspective
  publication-title: Comput. Electron. Agric.
  doi: 10.1016/j.compag.2005.09.003
  contributor:
    fullname: Wang
– ident: ref_4
  doi: 10.1117/12.2228929
– volume: 45
  start-page: 33
  year: 2017
  ident: ref_6
  article-title: Small Unmanned Aircraft Systems (sUAS): An Emerging Technology for Horticulture
  publication-title: Hortic. Rev.
  contributor:
    fullname: Robbins
– ident: ref_15
  doi: 10.3390/electronics6010009
– ident: ref_1
  doi: 10.19080/ARTOAJ.2018.14.555924
– ident: ref_3
  doi: 10.3390/rs10020285
– ident: ref_13
– ident: ref_14
– volume: 9
  start-page: 6
  year: 2014
  ident: ref_8
  article-title: RFID: How It Works and What It Can Do For The Green Industry
  publication-title: Am. Newsl.
  contributor:
    fullname: Fernandez
– ident: ref_5
  doi: 10.1117/12.2304739
– ident: ref_18
  doi: 10.3390/s21051875
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Snippet Collection of plant inventory (i.e., count, grade, plant size, yield) data is time-consuming, costly, and can be inaccurate. In response to increasing labor...
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SubjectTerms Agricultural industry
Agriculture
Animals
Antennas
Data acquisition
Design
drone
Drone aircraft
Drones
Field tests
Inventory
Inventory control
Inventory management
microcontroller
Moisture content
ornamental
precision agriculture
Radio frequency identification
Receivers & amplifiers
RFID
Scanning
Tags
Unmanned aircraft
Title RFID and Drones: The Next Generation of Plant Inventory
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