AI Science & Discovery
AI Speeds Wildlife Tracking from Months to Days
WSU and Google researchers unveil SpeciesNet, an AI model that analyzes camera trap data with 99% greater efficiency.
A computer screen showing a grid of wildlife photos from camera traps with digital boxes identifying the animals using AI technology.
Photo: Kronos News
Researchers from Washington State University and Google have developed an artificial intelligence model that accelerates wildlife tracking by 99% [1][3]. The system, named SpeciesNet, reduces the time needed to analyze camera trap images from several months to just a few days [2]. This breakthrough study was published on May 7, 2026, in the Journal of Applied Ecology [1].
SpeciesNet identifies animals in thousands of photos with high precision, matching the accuracy of human experts for most species [1][2]. By automating this labor-intensive process, conservationists can monitor biodiversity and animal populations in near real-time [3]. This tool provides a significant advantage for ecological research and rapid environmental response [1][3].
Editorial notes
Transparency note
AI assisted drafting. Human edited and reviewed.
- AI assisted
- Yes
- Human review
- Yes
- Last updated
Risk assessment
Reviewed for sourcing quality and editorial consistency.
Sources
Related stories
View all
Topics
About the author
Kronos News Desk covers ai science & discovery and editorial analysis for Kronos News.