Academic journal article Technology and Engineering Teacher

Reducing Water Waste through Data-Driven Irrigation Practices

Academic journal article Technology and Engineering Teacher

Reducing Water Waste through Data-Driven Irrigation Practices

Article excerpt


Technological advances, artificial intelligence innovations, and widespread computing have all combined to necessitate a new generation of knowledge workers where data becomes a ubiquitous part of decision making (Sutton, 2006). Teaching today's students through the application of this "new" knowledge to long-established fields represents a key opportunity for innovation, improvement, and progress (Vasisht, et al., 2017). Students, living in a world of "big data," can become powerful innovators as they learn to collect, synthesize, and utilize data for data-driven decision making, innovating, and creating. However, despite widespread agreement on the necessity of these skills, the best way to interest, engage, and instruct students in interacting with and utilizing data for data-driven decision making is not clearly understood, Further, assisting students in comprehending and engaging with abstract data sets, visualizations, and tables has proven difficult (Beihler, 1997; delMas, Garfield, & Ooms, 2005; Edwards, Ozgun-Koca, & Barr, 2017), and efforts to help students appropriately visualize data have not always proven successful--even in firmly established fields of study.

The authors present here their experience, and the accompanying materials developed, while working with high school students in a setting that intentionally combined "new" knowledge--derived from high-tech sensors and aerial imagery captured by a drone-with the longstanding Bartholomew, practices and traditions of irrigation in agriculture. In this lesson, we teamed up with a local teacher and Daphne several students attending a rural Fauber, Jon high school to develop materials Charles Worth related to aerial imagery collected from an agricultural drone and an and John associated design challenge aimed socially relevant contexts at reducing water waste in irrigation practices. To introduce students to data and help them understand the imagery provided by drones in agricultural applications, the authors introduced them to the sensors involved, the image acquisition process, the data processing performed, and visualization techniques prior to them flying the drone. Although, like many of the existing drone software packages, the software utilized by the students in this scenario (FieldAgent) performed many data-processing and visualization steps automatically, we felt it was important to help students understand both the technology involved and the imaging pipeline prior to interpreting the data and utilizing their findings to inform their design decision making while attempting to devise solutions to reduce water waste in irrigation. We believe this emphasis on both data acquisition and application is important for influencing the students' designing and introduction to data-driven decision making.

Drones in Agriculture

The use of elaborate, autonomous technologies in agriculture is in the process of revolutionizing the field (pun intended) as people know it. Inventions such as GPS-controlled autonomous tractors, capable of plowing, fertilizing, and harvesting a field without human control, have recently entered the farming scene; these advancements can reduce the time associated with tedious work done by farmers, resulting in more efficient and significantly more precise processes. However, as is the case for many of the newest technological advancements, these autonomous tractors have largely only been implementable by large-scale farming operations due to their hefty price tag. Of the most recent technological advancements, unmanned aerial vehicles (UAVs) are one example of a more accessible technology revolutionizing agriculture for farming operations of all sizes due to their low cost and perceived ease of use (King, 2017).

Although RC planes and helicopters have been used by hobbyists for years, the movement into UAVs has emphasized their use as a truly valuable tool when coupled with a camera and/or other sensor(s) that can collect a variety of data upon which to base crop assessments or make other previously difficult data-based decisions. …

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