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Ansine, Janice; Dodd, Michael; Valentine, Chris; Rüger, Stefan; Siddharthan, Advaith and Dadswell, Damian
(2023).
URL: https://youtu.be/PMfevw5pYME
Abstract
This presentation shares best practice on the use, integration and testing of two artificial intelligence (AI) Cos4Cloud services in iSpot (www.iSpotnature.org). Cos4Cloud is a European Horizon 2020 project boosting citizen science technological services to help increase and improve the quantity and quality of observations. It includes the participation of nine established citizen observatories, including iSpot, that have contributed to the development of these technological services. iSpot: your place to share nature is a citizen science platform (citizen observatory) for biodiversity developed and operated by The Open University (OU), a Cos4Cloud partner. It is aimed at helping anyone share wildlife observations, identify, explore and learn about nature.
With an interest in experimenting with automatic image identification to help the community identify observations and support learning, plans were put in place to introduce two AI systems on iSpot: Pl@ntNet-API (for plants) and FASTCAT-Cloud (initially for mammals then birds and invertebrates). Considerations for implementation also included whether adding an option that could more immediately give a response with a range of possibilities could be helpful as a learning tool for iSpot users.
Integration involved collaborating with the community to trial and test the services and user feedback was collated, to contribute to the development process. However, balancing user suggestions, demands, requirements and expectations could be challenging and this presentation will share incite from efforts to engage the iSpot community and user experience.
FASTCAT-Cloud is a service developed by DynAIkon that uploads and analyses nature videos and pictures, filtering out empty images automatically, helping to select more relevant images and recordings of wildlife activity from camera traps. The Pl@ntNet-API is an AI plant identification Application Programming Interface (API), developed by Inria, that uses Pl@ntNet's image recognition to make identifications of plant species, which can be used to improve the user experience in citizen observatories.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)
