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Cheyenne Simmons thesis (FINAL).pdf (3.74 MB)

GRAIN HARVESTING LOGISTICAL TRACKING – UTILIZING GPS DATA TO BETTER UNDERSTAND GRAIN HARVESTING EFFICIENCY

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thesis
posted on 2024-04-29, 18:53 authored by Cheyenne Eunice/ Cox SimmonsCheyenne Eunice/ Cox Simmons

Precision agriculture has been around for many, many years but as technology has rapidly grown with the population, farmers are looking for more ways to improve their operation with the help of these tools. These tools help farmers manage, understand, and decide when, how and what should be done regarding the tough decisions in the field based on their machinery statues. The tools that utilize GPS location and provide farm managers with useful information and feedback on large scales of value in the Harvesting and planting operation. With previous works done focusing on identify state machine activity utilizing GPS location data with the use of loggers and algorithms this study carries on from one field to the next identifying the truth data set for each and the accuracy of the algorithm. The goal is to add a more realistic view to the states identifying turning and transporting throughout the harvesting operation in truth data and from algorithm results. Also diving into truck activity with lower standard GPS tracking to see how accurately they can be predicted to complete the harvesting cycle from vehicle to vehicle. Overall, the combine and grain cart held at 88% accuracy for labeling all state activity during the harvesting operation for multiple fields, while for the model algorithm with the grain trucks having an overall accuracy of 94%.

History

Degree Type

  • Master of Science

Department

  • Agricultural and Biological Engineering

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Dr. John T. Evans IV

Additional Committee Member 2

Ankita Raturi

Additional Committee Member 3

James Krogsmeier