Company or Institution
Sustainable Development Goals (SDGs)
SDG 11: Sustainable Cities and Communities
SDG 13: Climate Action
SDG 14: Life Below Water
SDG 15: Life on Land
General description of the AI solution
Earth is experiencing the sixth mass extinction; however, we don’t have enough information to accurately understand the scope of biodiversity loss and prioritize measures to counteract it.
Monitoring biodiversity is critical to our ability to manage the impacts of climate change and provide informed conservation actions.
RFCx’s Arbimon is a free and open platform that harnesses the power of AI to bridge the gap between academia and conservation managers by enabling users to extract ecological insights from acoustic data.
Our AI-based integrated approach is being built to evaluate the impacts of land use and climate change on biodiversity by combining multi-taxon datasets with relevant bioclimatic and environmental features that influence species distributions. By monitoring species richness, behavior, and distribution within vulnerable areas, we’re able to better understand the effects of human and environmental impacts on wildlife to guide more effective preservation of endangered wildlife.
More specifically, our innovative approach relies on harnessing the power of AI to 1) automate species identification in soundscape recordings, 2) integrate rich environmental datasets, 3) predict and map multiple species and taxonomic groups' presence over large time and space scales; 4) summarize and expedite ecosystem and biodiversity indicators to be easily consumed by diverse stakeholders and decision makers. Our solution overcomes existing limitations related to ecological insights over large spatiotemporal scales and taxonomic levels and therefore provides a cost-effective, user-friendly, automated, and scalable biodiversity insights platform.
In addition, to wildlife monitoring, acoustic monitoring also allows us to protect rainforests by detecting illegal logging threats (e.g., poaching and illegal logging) and alerting partners on the ground so they can stop further deforestation, and in doing so, we’re guarding one of the world's largest carbon-capturing heroes – forest.
Github, open data repository, prototype or working demo
Ribeiro, Jr, J.W., Harmon, K., Leite, G.A., de Melo, T.N., LeBien, J. and Campos-Cerqueira, M., 2022. Passive Acoustic Monitoring as a Tool to Investigate the Spatial Distribution of Invasive Alien Species. Remote Sensing, 14(18), p.4565.
Campos-Cerqueira, M., Terando, A.J., Murray, B.A., Collazo, J.A. and Aide, T.M., 2021. Climate change is creating a mismatch between protected areas and suitable habitats for frogs and birds in Puerto Rico. Biodiversity and Conservation, 30(12), pp.3509-3528.
Melo, T.N.D., Cerqueira, M.C., D’HORTA, F.M., Tuomisto, H., Doninck, J.V. and Ribas, C.C., 2021. Impacts of a large hydroelectric dam on the Madeira River (Brazil) on floodplain avifauna. Acta Amazonica, 51, pp.298-310.
LeBien, J., Zhong, M., Campos-Cerqueira, M., Velev, J.P., Dodhia, R., Ferres, J.L. and Aide, T.M., 2020. A pipeline for identification of bird and frog species in tropical soundscape recordings using a convolutional neural network. Ecological Informatics, 59, p.101113.
Campos‐Cerqueira, M., Mena, J.L., Tejeda‐Gómez, V., Aguilar‐Amuchastegui, N., Gutierrez, N. and Aide, T.M., 2020. How does FSC forest certification affect the acoustically active fauna in Madre de Dios, Peru?. Remote Sensing in Ecology and Conservation, 6(3), pp.274-285.
HPC resources and/or Cloud Computing Services