Date of Award

5-2026

Document Type

Thesis

Degree Name

Bachelor of Arts (BA)

Department

Natural Sciences

First Advisor

Roy, Tania

Area of Concentration

Computer Science

Abstract

With the surge in popularity of handheld devices over the last few decades, technology-driven citizen science projects have become more accessible than ever before. This application has been created on the basis of supporting biodiversity monitoring through citizen science in Sarasota, FL. The development of the mobile app— Speciespy— utilized React Native [13], Expo [14], and Firebase [15] as a Backend-as-a-Service (BaaS), enabling users to identify organisms, share geotagged observations, and interact with the local community by liking and commenting on others’ posts. Automatic species identifications are made with a dual-API pipeline leveraging Pl@ntNet (pronounced “Plant Net”) [10] and Animal Detect [11] APIs. Images are first sent to Pl@ntNet for plant identification. If no plant is detected, the photo is forwarded to Animal Detect for wildlife classification, eliminating the need for a locally trained model. This thesis document will discuss the visual and systematic design choices, limitations, future improvements, and real-world applications for Speciespy.

Rights

The author has granted New College of Florida the nonexclusive right to archive, make accessible, and distribute for educational purposes this work in whole or in part in all forms of media, now or hereafter known. The copyright of this work remains with the author.

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