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WHDL - 00020707

Android fruit harvest helper apple detection app development with React Native

Brandon Thomas Duncan

Resource Types

Academic (Thesis, Dissertation, Etc.)

Resource Languages

English

Institutional Repository

Northwest Nazarene University

Description / Abstract

Submitted to the Department of Mathematics and Computer Science in partial fulfillment of the requirements for the degree of Bachelor of Science.

The Android Fruit Harvest Helper is an innovative application developed using React Native, aimed at assisting farmers in estimating fruit yields, particularly in apple orchards. This project bridges the gap between iOS and Android platforms by recreating an existing iOS app for blossom detection in a cross-platform environment. The app's intuitive user interface (UI), designed with farmers in mind, simplifies the process of estimating fruit yields by providing a frictionless experience for image selection and processing. The Fruit Harvest Helper’s UI features two boxes for the selected and processed image, along with a button enabling users to select or take a photo. For the backend, the app employs a color-based feature extraction machine learning algorithm, implemented in OpenCV C++, to detect apples in images of apple trees. Results show a Mean Absolute Percentage Error (MAPE) of 8.52% in apple detection when evaluating pictures from both sides of an apple tree. A correlation coefficient of 0.6 between detected and actual apples was found as well. While the app has promising functionality, opportunities for improvement exist, including the development of an object-based machine learning apple detection algorithm and methods to detect various types of fruits. Fruit Harvest Helper represents a significant step towards precision agriculture, nearing real-world utility for farmers in yield monitoring and farm management.

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Copyright Notes

This material is used by permission of the rightsholder in accordance with the terms of the relevant content release. As a user, you have permission to use this content and download a copy for non-commercial use only. Downloading multiple quantities of this resource is expressly forbidden.

KeywordsAndroid app, React Native, Apple detection, Fruit yield estimation

Degree AwardedBachelor of Science

Awarding InstitutionNorthwest Nazarene University

Committee MembersDuke Bulanon

Supervisor or ChairDale Hamilton

Peer Reviewed?No

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