AI Case Study

The Zoological Society of London is preventing poaching with machine vision and machine learning

The Zoological Society of London (ZSL) is leveraging machine learning and vision technology from Google to tackle poaching. The technology analyses footage captured in the wild to track wild animals using automated image-tagging. The ZSL has managed to decrease the otherwise 9 months time required to process the data and identify threats in wildlife to an instant.

Industry

Public And Social Sector

Ngo

Project Overview

"The Zoological Society of London (ZSL) has turned to Google's new Cloud AutoML platform to track wildlife by automatically analysing millions of images captured by cameras in the wild.

These cameras help ZSL to conserve different species of wildlife by identifying their movements and potential poachers.

The motion-triggered camera traps use heat sensors to identify when wildlife or humans move past, and produce vast amounts of data that quickly needs to be tagged.

Reporting on that data typically takes up to nine months, by which time the animal movements and ZSL strategies may well have changed.

Google's Cloud AutoML uses artificial intelligence and machine learning algorithms to cut those nine months down to an instant. The platform helps organisations with limited machine learning expertise, such as ZSL, to build their own high-quality custom models using advanced machine learning techniques and tools.

ZSL uses these cameras to capture the motion of animals and humans and identify poaching threats. The images need to be tagged in order to analyse the data, which ZSL conservationists previously had to do manually.

ZSL provided Google with around 1.5 million tagged images to help advance the Cloud AutoML platform, which was announced in January. The charity is now training a custom model by feeding it data on conservation details such as region, environment and species that will create a complete auto-tagging tool."

Reported Results

"Nine months cut down to an instant."

Technology

"Google's Cloud AutoML uses artificial intelligence and machine learning algorithms to cut those nine months down to an instant. The platform helps organisations with limited machine learning expertise, such as ZSL, to build their own high-quality custom models using advanced machine learning techniques and tools."

Function

Risk

Audit

Background

"Reporting on data about potential poachers typically takes up to nine months, by which time the animal movements and ZSL strategies may well have changed." 'You need that information much quicker in the fight to conserve wildlife or stop poaching,' Sophie Maxwell, the conservation technology lead at ZSL tells Computerworld UK.

Benefits

Data

1.5 million tagged images