Plant identification app with automated image recognition and e-commerce / Carl Jayson S. Angeles, Joseph Eleazar B. Arias, John Richard D. Dado, Justine B. Vergara.

By:

Angeles, Carl Jayson S

Contributor(s):

Arias, Joseph Eleazar B

Material type: Text

TextManila : Technological University of the Philippines, 2022Description: x, 110 pages : illustrations ; 28 cm. + 1 CD-ROM (4 3/4 in.)Subject(s):

LOC classification:

BTH T 58.5 A54 2022

Dissertation note: College of Science -- Bachelor of Science in Information Technology, Technological University of the Phillippines, 2022. Abstract: The study developed the "Plant Identification App with Automated Image Recognition and E-commerce." The objective of the study is to create an Android application that can identify a plant using image recognition, provide more information about the plant, and act as a marketplace where users can buy or sell plants. The system was developed using Java, PI@ntNet API, Android Studio, and Firebase. The application was developed using the agile method approach, which is one of the most commonly used methodologies in software development. It was tested for its functionality and accuracy, meeting all the expected results for the functionalities, and obtaining an accuracy percentage of 100% for whole plants, 95% for fresh leaves, 0% for dry leaves, 12% for damaged leaves, 11% when zoomed out, and 45% when zoomed in. The application was evaluated by 30 respondents, and it was determined to be highly acceptable with a grand mean of 3.60 using the criteria Functional Suitability, Performance Efficiency, Usability, Reliability, Security, Maintainability, and Portability from ISO 25010. --Author's Abstract.

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Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Bachelor's Thesis COS	TUP Manila Library	Thesis Section-2nd floor	BTH T 58.5 A54 2022 (Browse shelf(Opens below))	c.1	Not for loan		BTH0003444

Thesis (Undergraduate)

College of Science -- Bachelor of Science in Information Technology, Technological University of the Phillippines, 2022.

The study developed the "Plant Identification App with Automated Image Recognition and E-commerce." The objective of the study is to create an Android application that can identify a plant using image recognition, provide more information about the plant, and act as a marketplace where users can buy or sell plants. The system was developed using Java, PI@ntNet API, Android Studio, and Firebase. The application was developed using the agile method approach, which is one of the most commonly used methodologies in software development. It was tested for its functionality and accuracy, meeting all the expected results for the functionalities, and obtaining an accuracy percentage of 100% for whole plants, 95% for fresh leaves, 0% for dry leaves, 12% for damaged leaves, 11% when zoomed out, and 45% when zoomed in. The application was evaluated by 30 respondents, and it was determined to be highly acceptable with a grand mean of 3.60 using the criteria Functional Suitability, Performance Efficiency, Usability, Reliability, Security, Maintainability, and Portability from ISO 25010. --Author's Abstract.

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