Challenge

Without action, 38 percent of all species could be extinct by 2100. Many animal species are especially vulnerable due to poaching, habitat loss, and climate change. Fighting extinction requires a tremendous amount of data, including population size, location, and migration patterns. Gathering this data manually is time-consuming and expensive, making citizen engagement critical to data collection efforts.

Solutions

Wild Me used computer vision and deep learning algorithms to create a platform called Wildbook, which scans millions of crowdsourced wildlife images at scale. Wildbook can identify the species as well as the individual animal, and the public can follow the movements of their favorite animals. The aggregated data is used by scientists to help inform conservation decisions. Microsoft is supporting their efforts by hosting Wildbook on Azure and making Wild Me’s open source algorithms available as APIs.

How Wild Me uses Azure

Wild Me uses the following Azure services:

  • Translator Text API to translate multi-lingual YouTube videos into English, and to create Wildbooks for global audiences.
  • Computer Vision API for optical character recognition, to extract text from YouTube videos, and use it for date/location prediction with machine learning.
  • Virtual machines to power Wildbook; Wild Me runs all Wildbooks on high-performing Linux VMs
  • Data Science Virtual Machines to create natural language processing (NLP) predictors for our YouTube reviewing intelligent agent.
  • Application Insights to monitor Wild Me servers and services for outages.
  • Container Registry to store Wildbook containers.
  • Azure Backup to back up virtual machines and protect critical wildlife data.
  • DevOps for operation monitoring during development.

These components are also available as an architecture diagram.

Wild Me on GitHub

All of Wildbook’s code is open-source and available on GitHub.

Two adults and one baby giraffe stand in a field.

Using AI to fight extinction

A zebra stands in a field.