Design and performance evaluation of soil nitrogen tester / by JC Joseph R. Ortiz and Kazelle Anne P. Salleque.

By:

Ortiz, JC Joseph R [author]

Contributor(s):

Material type: Text

TextLanguage: English Publication details: Indang, Cavite : Cavite State University- Main Campus, 2019.Description: xxvi, 168 pages : illustrations ; 28 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

Subject(s):

DDC classification:

620.2 Or8 2019

Online resources:

Click here to view abstract and table of contents

Production credits:

College of Engineering and Information Technology (CEIT), Department of Computer and Electronics Engineering

Abstract: ORTIZ, JC JOSEPH R. and SALLEGUE, KAZELLE ANNE A. Design and performance evaluation of Soil Nitrogen Tester. Undergraduate Design Project. Bachelor of Science in Electronics and Communications Engineering. Cavite State University, Indang, Cavite. June 2019. Adviser: Engr. Nemilyn A. Fadchar The general objective of the study was to design and evaluate the performance of a soil nitrogen tester. Specifically, it aimed to design and assemble a portable soil nitrogen tester. It also targeted to test and evaluate the precision and sensitivity of the system. Moreover, it intended to conduct a cost analysis of the device. The design project was composed of Arduino Uno R3 which served as the microcontroller unit. Its ports were used to interface input and output devices such as the photodiode, infrared proximity sensor, infrared light emitting diodes (IR LEDs), LED indicators, stepper motor, motor driver, and piezo buzzer. The application software was programmed and developed using the matrix laboratory (MATLAB) App Designer. Artificial neural network and support vector machine were the learning algorithms used to determine which model was appropriate for soil nitrogen level prediction. The project was tested by the researchers at Bancod, Indang, Cavite. The evaluation was conducted at the Engineering Science Building, Cavite State University, Indang, Cavite and at the Department of Agricultural and Food Engineering, Cavite State University, Indang, Cavite. The performance of the soil nitrogen tester was evaluated by scanning distinct soil samples with low, medium, and high levels of nitrogen. Throughout the three phases of evaluation, the artificial neural network model had precision percentages of 33.33 percent, 66.67 percent, and 77.78 percent. On the other hand, the support vector machine had performance percentages of 55.56 percent, 100 percent, and 100 percent. Hence, support vector machine had the better prediction and was implemented as the final predictive model for the application software. Based on the results of the evaluation, the design project met the given objectives. The system was able to operate in accordance to its intended function. The overall performance of the system is satisfactory. The total cost of the system amounted to P20,216.39 and the break-even point was calculated to be 213 samples.

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Holdings
Item type	Current library	Collection	Call number	Materials specified	URL	Status	Notes	Date due	Barcode
Theses / Manuscripts	Ladislao N. Diwa Memorial Library Theses Section	Non-fiction	620.2 Or8 2019 (Browse shelf(Opens below))		Link to resource	Room use only	DP-681		00079505

Design Project (Bachelor of Science in Electronics and Communication Engineering) Cavite State University.

Includes bibliographical references.

College of Engineering and Information Technology (CEIT), Department of Computer and Electronics Engineering

ORTIZ, JC JOSEPH R. and SALLEGUE, KAZELLE ANNE A. Design and performance evaluation of Soil Nitrogen Tester. Undergraduate Design Project. Bachelor of Science in Electronics and Communications Engineering. Cavite State University, Indang, Cavite. June 2019. Adviser: Engr. Nemilyn A. Fadchar
The general objective of the study was to design and evaluate the performance of a soil nitrogen tester. Specifically, it aimed to design and assemble a portable soil nitrogen tester. It also targeted to test and evaluate the precision and sensitivity of the system. Moreover, it intended to conduct a cost analysis of the device. The design project was composed of Arduino Uno R3 which served as the microcontroller unit. Its ports were used to interface input and output devices such as the photodiode, infrared proximity sensor, infrared light emitting diodes (IR LEDs), LED indicators, stepper motor, motor driver, and piezo buzzer. The application software was programmed and developed using the matrix laboratory (MATLAB) App Designer. Artificial neural network and support vector machine were the learning algorithms used to determine which model was appropriate for soil nitrogen level prediction. The project was tested by the researchers at Bancod, Indang, Cavite. The evaluation was conducted at the Engineering Science Building, Cavite State University, Indang, Cavite and at the Department of Agricultural and Food Engineering, Cavite State University, Indang, Cavite. The performance of the soil nitrogen tester was evaluated by scanning distinct soil samples with low, medium, and high levels of nitrogen. Throughout the three phases of evaluation, the artificial neural network model had precision percentages of 33.33 percent, 66.67 percent, and 77.78 percent. On the other hand, the support vector machine had performance percentages of 55.56 percent, 100 percent, and 100 percent. Hence, support vector machine had the better prediction and was implemented as the final predictive model for the application software. Based on the results of the evaluation, the design project met the given objectives. The system was able to operate in accordance to its intended function. The overall performance of the system is satisfactory. The total cost of the system amounted to P20,216.39 and the break-even point was calculated to be 213 samples.

Submitted to the University Library 07/23/2019 DP-681

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