AI & Environment Resource HubBiotfy · Publication date unknown
[Environmental Monitoring] Using AI to improve environmental monitoring and biodiversity conservation.
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Biotfy. Date unknown. Víctor Galvín Coronil. https://www.linkedin.com/in/victor-galvin/ (AI & Environment Resource Hub; record atlas-660bafd8ace4; collection snapshot 2026-10-04).
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Source sheet: People of Interest · Row 11 · Original ID: Not supplied.
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Shared topics: Biodiversity and ecosystems
Improved machine learning techniques enhance bird call detection in passive acoustic monitoring, boosting precision and biodiversity tracking in climate research.
Shared topics: Biodiversity and ecosystems
This study proposes a low-cost IoT-based TinyML model that intelligently activates mosquito repellent only when an Anopheles mosquito is detected, using a 1D-CNN for efficient classification of mosquito wingbeat sounds, reducing energy waste and potential health risks.
Shared topics: Biodiversity and ecosystems
A hybrid machine learning model improves soil respiration predictions, enhancing carbon cycle modeling and greenhouse gas management strategies.
Shared topics: Biodiversity and ecosystems
A deep learning-based bioacoustic AI tool enables citizen scientists and law enforcement to accurately identify traded songbird species in Asian markets, achieving 91.6% accuracy and supporting conservation efforts against overexploitation and illegal wildlife trade.