Semester 2 2023 App Development
Ocell.ai
Description
In the realm of biosecurity, insect images serve a pivotal role in taxonomically identifying pest insects. The integration of machine learning technologies further amplifies their importance in effectively managing biosecurity threats. Despite this potential, these advanced tools remain out of reach for frontline biosecurity staff and entomologists directly dealing with pest insects. Enter Ocell.ai, our solution to bridge this gap. We aspire to connect the dedicated professionals safeguarding New Zealand's ecosystems with the cutting-edge tools developed by expert entomologists. Our platform provides an efficient and intuitive interface, allowing these frontline workers to easily identify insect species through simple image uploads. This integration promises to streamline and enhance the effectiveness of biosecurity efforts in preserving ecosystems.
Design and Features
๐ ๐๐จ๐๐ง ๐๐ง๐๐๐ฃ๐๐ก๐ฎ, ๐๐ฃ๐ฉ๐ช๐๐ฉ๐๐ซ๐ ๐ฉ๐ค ๐๐๐ซ๐๐๐๐ฉ๐ No machine learning knowledge needed! Just select the type of insect family you want to query, and upload your images! ๐ง ๐๐ฃ๐๐ค๐ง๐ข๐๐ฉ๐๐ค๐ฃ ๐๐๐๐ ๐๐๐ก๐๐๐๐ก๐ Our results page not only highlights the top insect species predictions for your ease, but also encourages you to verify the validity of the output by providing you references such as the extended set of the machine learning predictions, and the speciesโ information from the Global Biosecurity Information Facilityโs (GBIF) database. ๐ชฒ๐พ๐ง๐๐๐ฉ๐๐ ๐ฌ๐๐ฉ๐ ๐ฉ๐๐ ๐๐๐๐๐จ ๐ค๐ ๐ฝ๐๐ค๐จ๐๐๐ช๐ง๐๐ฉ๐ฎ ๐๐๐ง๐จ๐ค๐ฃ๐ฃ๐๐ก ๐๐ฃ ๐๐๐ฃ๐ For each top prediction, weโve included: โ๏ธ Pest status tags โ๏ธ An interactive map highlighting the distribution of a species โ๏ธ Links to reliable reference images via gbif.org
developed by Software Alchemists
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