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Exploring the role of technology in tackling illegal wildlife trade: the case of identifying (song)birds in trade

The following repository is part of an open development process of a wildlife marketplace technology run by Sicily Fiennes, a PhD student in the Extinction Studies Doctoral Training Program at the University of Leeds, England.

My project title is: 'Opportunities for co-design of technology to address the Southeast Asian illegal bird trade', and I will focus on a use case of mobile artificial intelligence species identification technology to address the Southeast Asian illegal bird trade. My doctoral research focuses on legal and illegal songbird trade in Asia and building machine learning tools to optimize species identification in markets. The main project is a machine learning-driven image recognition tool for species for use in bird markets in East Asia, targeted at law enforcement. I also seek to understand factors that influence the adoption and implementation of wildlife marketplace technologies amongst law enforcement and how this interacts with the risk of extinction of songbirds. I am also interested in opportunities for the co-creation of technology and decolonizing design methods.

This repository acts as a live record of my progress on this project, including the use of Microsoft Azure computing credits, via a grant from Microsoft’s AI For Earth. This grant is being used to process data, run models, and design user interfaces.

Further, if you have any images of birds from marketplaces across Southeast Asia? Submit them here 👉 https://bird-trade.azurewebsites.net

Berikut ini adalah bagian dari proses pengembangan terbuka sebuah teknologi pasar satwa liar yang dijalankan oleh Sicily Fiennes, seorang mahasiswa S3 dalam Program Doktor Studi Ke Punahan di Universitas Leeds, Inggris.

Judul proyek saya adalah: "Kesempatan untuk mendesain bersama teknologi untuk menangani perdagangan burung kicau liar di Asia Tenggara yang ilegal", dan saya akan memfokuskan diri pada kasus penggunaan teknologi identifikasi spesies kecerdasan buatan mobile untuk menangani perdagangan burung kicau liar ilegal di Asia Tenggara. Penelitian doktoral saya berfokus pada perdagangan burung kicau legal dan ilegal di Asia dan membangun alat pembelajaran mesin untuk mengoptimalkan identifikasi spesies di pasar. Proyek utama adalah alat pengenalan gambar berbasis pembelajaran mesin untuk spesies yang digunakan di pasar burung di Indonesia, ditujukan untuk penegak hukum. Saya juga ingin memahami faktor-faktor yang mempengaruhi adopsi dan implementasi teknologi pasar satwa liar di kalangan penegak hukum dan bagaimana hal ini berinteraksi dengan risiko punahnya burung bernyanyi. Saya juga tertarik dengan kesempatan untuk mendesain bersama teknologi dan metode desain dekolonisasi.

Repositori ini bertindak sebagai catatan langsung dari progres saya pada proyek ini, termasuk penggunaan kredit komputasi Microsoft Azure, melalui grant dari AI For Earth Microsoft. Grant ini digunakan untuk memproses data, menjalankan model, dan merancang antarmuka pengguna.

Selanjutnya, jika Anda memiliki gambar burung dari pasar di seluruh Asia Tenggara? Kirimkan di sini 👉 https://bird-trade.azurewebsites.net

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