Title

GrowME

Lead Author Major

Computer Science

Lead Author Status

Senior

Second Author Major

Computer Science

Second Author Status

Senior

Third Author Major

Computer Science

Third Author Status

Senior

Fourth Author Major

Computer Science

Fourth Author Status

Senior

Format

SOECS Senior Project Demonstration

Faculty Mentor Name

Shon Vick

Faculty Mentor Email

svick@pacific.edu

Faculty Mentor Department

Computer Science

Additional Faculty Mentor Name

Osvaldo Jimenez

Additional Faculty Mentor Email

ojimenez@pacific.edu

Additional Faculty Mentor Department

Computer Science

Abstract/Artist Statement

In 2015, exports of agricultural products were worth an estimated 133 billion-U.S. dollars, while imports were worth around 113.5 billion-U.S. dollars. Within the United States alone, there are approximately 2.08 million farms. [5]. Today’s farmers and growers utilize advanced technology to minimize production costs. Technological advancements, such as robots, weather patterns and temperature, and aerial images, are making a significant impact within the agricultural industry. Our team was inspired by this emerging AGTech field. We recognized the usefulness of a predictive analytics application within the industry, which is how the idea of GrowME (Maturation Evaluator) came about. Another motivation for our proposed system, GrowME, is that the world population is still ever growing and putting more pressure on the need for increased food production which will lead to adverse side-effects on the environment [2]. Focusing our collective energy on creating innovating farming technology can optimize crop yields while simultaneously addressing the issues of environmental impact. GrowME, the proposed solution, is a user-friendly tool that collects data through sensors; utilizes its large knowledge base to conduct comparative analyses for the gathered information, and presents detailed and high leveled reports. Users, may it be your everyday home gardener or corporate farmers, can utilize the application to access useful data that would otherwise go unknown. In our project, we found the average reading level of dry soil and drenched soil. Depending on the soil type associated with the plant, a recommended level of soil moisture is prescribed so the specific plant. Plants that prefer moist soil may experience optimal growth in levels of lower readings whereas desert type plants may experience optimal growth in higher readings.

Location

School of Engineering & Computer Science

Start Date

4-5-2018 2:30 PM

End Date

4-5-2018 4:00 PM

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May 4th, 2:30 PM May 4th, 4:00 PM

GrowME

School of Engineering & Computer Science

In 2015, exports of agricultural products were worth an estimated 133 billion-U.S. dollars, while imports were worth around 113.5 billion-U.S. dollars. Within the United States alone, there are approximately 2.08 million farms. [5]. Today’s farmers and growers utilize advanced technology to minimize production costs. Technological advancements, such as robots, weather patterns and temperature, and aerial images, are making a significant impact within the agricultural industry. Our team was inspired by this emerging AGTech field. We recognized the usefulness of a predictive analytics application within the industry, which is how the idea of GrowME (Maturation Evaluator) came about. Another motivation for our proposed system, GrowME, is that the world population is still ever growing and putting more pressure on the need for increased food production which will lead to adverse side-effects on the environment [2]. Focusing our collective energy on creating innovating farming technology can optimize crop yields while simultaneously addressing the issues of environmental impact. GrowME, the proposed solution, is a user-friendly tool that collects data through sensors; utilizes its large knowledge base to conduct comparative analyses for the gathered information, and presents detailed and high leveled reports. Users, may it be your everyday home gardener or corporate farmers, can utilize the application to access useful data that would otherwise go unknown. In our project, we found the average reading level of dry soil and drenched soil. Depending on the soil type associated with the plant, a recommended level of soil moisture is prescribed so the specific plant. Plants that prefer moist soil may experience optimal growth in levels of lower readings whereas desert type plants may experience optimal growth in higher readings.