Case Study: Zoological Society of London achieves faster species identification with Looker

Zoological Society of London Taking the pulse of the planet with AutoML

The Zoological Society of London (ZSL) is an international conservation charity that uses camera traps to monitor wildlife, but it was spending months manually tagging huge volumes of images, many of them blank. ZSL needed a faster, more scalable way to identify species and analyze biodiversity data, and it worked with Looker as part of its Google Cloud data and analytics setup, alongside machine learning tools.

Looker supported ZSL’s broader cloud-based solution, which used AutoML, Cloud Storage, Dataflow, BigQuery, and App Engine to automate image labeling and model training. The result was the ability to identify species from thousands of images in days instead of months, reducing manual data entry and helping ZSL focus more on conservation work. The faster turnaround also lays the groundwork for real-time wildlife monitoring in the future.

Zoological Society of London

Robin Freeman

Head of the Indicators and Assessments Unit