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DOE OSTI · 2500796

An AI-Based 3D Bat Movement Tracking System at Wind Energy Facilities Using Multi-Thermal Video Cameras

Ryu, Sora (ORCID:0009000006913212)·Yarbrough, John·Hein, Cris (ORCID:0000000330407998)·Rooney, Samantha·Clerc, Jeffery·Quon, Eliot (ORCID:0000000284455840)·Sinner, Michael (ORCID:0000000187660711)·Bortolotti, Pietro (ORCID:0000000285159488)·Schipper, Jessica·Cryan, Paul·Straw, Bethany
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Abstract

The poster at the 15th Wind Wildlife Research Meeting discusses how to leverage the potential of real-time thermal-imaging methodologies in quantifying nocturnal bat activities at wind turbines, using 3D computer vision techniques within a deep learning framework. This innovation enables the automatic detection and classification of bats, birds, and insects in thermal-imaging videos captured at wind turbine sites, facilitating efficient and accurate data analysis for enhanced understanding and mitigation of bat-wind turbine interactions.

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AImachine learningMATHEMATICS AND COMPUTING,WIND ENERGYobject detectionobject trackingstereo visionwind-wildlife interactions

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Ryu, Sora (ORCID:0009000006913212), Yarbrough, John, Hein, Cris (ORCID:0000000330407998), Rooney, Samantha, Clerc, Jeffery, Quon, Eliot (ORCID:0000000284455840), Sinner, Michael (ORCID:0000000187660711), Bortolotti, Pietro (ORCID:0000000285159488), Schipper, Jessica, Cryan, Paul, Straw, Bethany. 2025-01-09. An AI-Based 3D Bat Movement Tracking System at Wind Energy Facilities Using Multi-Thermal Video Cameras. https://doi.org/10.2172/2500796

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