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Proceedings Paper

Drone-Based technologies used to assess modern farming practices in undergraduate research
Author(s): S. A. Wilkerson; S. A. Gadsden; J. Cerreta; M. Al-Shabi
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Paper Abstract

The modern farm is a technological marvel, from smart tractors to genetically modified organisms (GMOs), along with chemical pesticides and fertilizer. Farms today have continuously increased production by utilizing these various techniques. Many farms on the east coast of North America are growing dent or field corn while also rotating crops between soybeans of various types and winter wheat. These crops have become symbiotic in nature due to the need for specific soil nutrients of the crops and the practice of no till farming. More recently, schools with farm programs have started researching the use of drone technologies and multispectral analysis as a means to reduce chemical usage thereby saving farmers annual chemical costs. This paper investigates the use of drones in capstone projects for undergraduate engineering and computer science programs. Undergraduate capstone projects usually require a design and build element to satisfy ABET accreditation requirements. Therefore, the students needed to design and build an airframe capable of surveying farms with a multispectral camera. In the course of the aircraft design process it was discovered that the students needed to have a broader understanding of federal regulations, experimentation, and a robust understanding of how the drones and data would be used to benefit a typical farm. In addition, we look at the results obtained and discuss the problems associated with making the data and analysis accessible to the farmers who participated in our study. In the process we also discovered other potential uses for the images we created.

Paper Details

Date Published: 14 May 2019
PDF: 11 pages
Proc. SPIE 11008, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV, 110080K (14 May 2019); doi: 10.1117/12.2519801
Show Author Affiliations
S. A. Wilkerson, York College of Pennsylvania (United States)
S. A. Gadsden, Univ. of Guelph (Canada)
J. Cerreta, Embry-Riddle Aeronautical Univ. (United States)
M. Al-Shabi, Univ. of Sharjah (United Arab Emirates)


Published in SPIE Proceedings Vol. 11008:
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV
J. Alex Thomasson; Mac McKee; Robert J. Moorhead, Editor(s)

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