Mobile application for forest species recognition

• Guilherme Yudi Shibuya UTFPR http://orcid.org/0009-0008-5121-7740
• Jandrei Sartori Spancerski UTFPR https://orcid.org/0000-0002-4077-281X
• Ricardo Sobjak UTFPR http://orcid.org/0000-0001-5652-5840
• Deborah Leite UTFPR https://orcid.org/0000-0001-7032-7373
• Pedro Luiz de Paula Filho UTFPR https://orcid.org/0000-0002-6291-9237

DOI: https://doi.org/10.5753/latinoware.2024.245667

Abstract

Environmental issues such as forest preservation and biodiversity protection are becoming increasingly relevant in light of the challenges posed by deforestation and unsustainable exploitation of natural resources. The ability to quickly identify endangered and protected forest species, is crucial for enforcement and monitoring efforts in remote areas. The goal of this work was to develop a fully offline mobile application for forest species recognition. Implemented in Java and supported on Android devices, the application integrates a deep learning model capable of identifying 44 species of wood. The software is open-source and available to everyone in a GitHub repository.

Keywords: forest species recognition, open source, android application

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