Sustainability & AI
Bioacoustic monitoring
Using microphones and AI to detect and identify species from environmental sound, tracking biodiversity at scale.
Definition
Using environmental sound recordings and AI analysis to detect and identify species — and human disturbances — across landscapes continuously.
Quick reference
At a glance
- Subject
- Sustainability & AI
- Editorial status
- Editorial draft
- Definition status
- Established
- Last updated
- 21 August 2026
- Also known as
- passive acoustic monitoring with AI · acoustic biodiversity monitoring
References
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Overview
What it means
Passive acoustic sensors record soundscapes for months at negligible cost; machine-learning classifiers such as BirdNET (Kahl et al. 2021) then identify calls, turning audio into species occurrence data. The approach covers birds, bats, amphibians and insects, and can flag chainsaws or gunshots in protected areas.
How it is used
Researchers and conservation bodies deploy sensor networks for population trends, restoration monitoring and anti-poaching response. Data volumes are enormous, making automated classification — with human validation of uncertain calls — the only viable workflow.
Why it matters
Sound reveals what cameras miss: nocturnal, canopy and underwater life. Bioacoustics plus AI gives conservation a persistent, scalable sensory system — one whose classifications, like any model output, require calibration against expert ground truth.
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