AI & Environment Resource HubBiotfy · Publication date unknown
[Environmental Monitoring] Using AI to improve environmental monitoring and biodiversity conservation.
Biotfy. Date unknown. Víctor Galvín Coronil. https://www.linkedin.com/in/victor-galvin/ (AI & Environment Resource Hub; record atlas-660bafd8ace4; collection snapshot 2026-09-15).
Included in the original People of Interest collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
Source sheet: People of Interest · Row 11 · Original ID: Not supplied.
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Shared topics: Cross-cutting sustainability; Biodiversity and ecosystems
Learn about how AI can be used to protect biodiversity, fight climate change, and just better understand our planet through 5-minute explainers covering academic papers on AI for the Planet. AI is not just chatbots! Grace Lindsay is a professor of Data Science & Psychology. She teaches a course on Machine Learning for Climate Change.
Shared topics: Cross-cutting sustainability; Biodiversity and ecosystems
Trust is a cornerstone and enabler of human civilization, determining the very nature of how people interact with each other. The swift integration of artificial intelligence (AI) into daily life poses grand societal challenges and necessitates a reevaluation of trust. Our bibliometric literature review calls for scientists and stakeholders to cross traditional academic boundaries to address emerging and evolving societal challenges arising from AI. We propose a transdisciplinary research framework to understand and bolster trust in AI and address grand challenges in domains as diverse and urgent as misinformation, discrimination, and warfare.
Shared topics: Cross-cutting sustainability; Biodiversity and ecosystems
The abstract argues that policy debates about “sustainable AI” are stuck in an overly simplistic binary, AI as both an environmental threat and a tool for ecological transition, which leads to shallow regulatory approaches focused mostly on energy reporting. Drawing on law-and-technology scholarship, the authors show how technological determinism, exceptionalism, and regulatory solutionism distort the debate, and they propose reframing regulation around the socio-economic drivers and power dynamics of AI development rather than the technology itself.
Shared topics: Cross-cutting sustainability; 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.