Mitigating the taxonomic impediment problem of plants using ML and citizen science-Lebanon

PROJECT IMPACT

$3810

IEEE Funding

20

Estimated Impact

15

Students

3

Volunteers

Location: Lebanon
PROJECT LAUNCHED: March 2024
PROJECT LEADS:

Dr. Dany Abou Jaoude

Lebanon is a hot spot for vascular plant species, home to more than 2,600 vascular plant species. With such diverse flora, it can be difficult to properly identify species, and their respective needs. Because of this knowledge gap, these species have undergone a decline over the past few years. Plant databases in Lebanon are limited to specific nature reserves and only list the names of the species found in these reserves. To ensure better conservation, a bigger, more detailed database is needed. 

A team of students from American University Beirut took note of this issue, and with the Shouf Biosphere Reserve (SBR), are creating a real-time planet identification tool via a smartphone application. This tool is meant for use by nature reserve managers and hopes to create a holistic database of species, areas, and seasons for Lebanese plants. 

The team started by developing a plant identification model, using as much data as they could find online and in the literature. Their goal was to make this tool accessible, and to do so, used a smartphone application that works with the camera already on the phone. This app would specifically be geared towards the flora of Lebanon, making it more effective for use in that biome than other apps already available. The app will even identify endangered species specifically, encouraging conservation. They will also draw attention to areas in Lebanon that need protecting to ensure that the natural flora can thrive. 

The team conducted pilot studies and workshops to educate and improve their project. Their workshops involved speakers, team members, students, volunteers, and other interested participants. They learned taxonomy and database creation, primer to machine learning and computer vision, fieldwork, data collection, and labeling.

This project was made possible by $3,810.00 in funding from APS an EPICS in IEEE partner.

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