Unveiling AMBER: A Glimpse into Biodiversity Monitoring in Singapore using AI
A UKCEH-NParks-NTU Sharing Session While recent studies suggest a sharp decline in insect populations around the world, limited...
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The Amber Project
Abot AMBER
While recent studies suggest a sharp decline in insect populations around the world, limited monitoring data, especially in highly biodiverse areas threatened by intensive land use or climate change, hinders a comprehensive understanding. With the need for additional research, novel technologies offer promising, standardized, and less invasive monitoring solutions.
In a unique collaboration between the Alan Turing Institute, UK Centre for Ecology & Hydrology (UKCEH), and abrdn Charitable Foundation, the AMBER (AI-assisted Monitoring of Biodiversity using Edge-processing and Remote Sensors) project made its debut in Singapore on November 24, 2023.
To kick off this initiative, the project partnered with the Tropical Ecology & Entomology Lab (TEE Lab) at the Asian School of Environment (ASE) in Nanyang Technological University (NTU) and received local support from National Parks Board (NParks).
what is amber?
AMBER stands for AI-assisted Monitoring of Biodiversity using Edge-processing and Remote sensors.The AMBER project is testing the use of automated camera and audio systems, combined with AI to deliver more standardised monitoring of insects, bats and birds.
The Automated Monitoring of Insects (AMI) system provides practical and cost-effective solutions for standardised monitoring that are non-biased, non-invasive and can monitor at wide spatial and temporal scales. The AMI-trap combines computer vision and an autonomous imaging system to capture images of moths in the field, locate them in the image, and classify them to species.Developments in data science are required to realise the potential of new data streams generated through automated sensors. For example, machine learning models to locate insect in an image, and classify them to species.
Over the next two years, the project aims to deploy a network of 40 biodiversity monitoring units (AMI-systems), together with AI data processing in biodiverse locations across the world – including 10 systems in Singapore.
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