An image classification and analytics application that uses the power of AI to dramatically increase the efficiency of conservation organizations.
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The Problem

50,000

Number of images the Lincoln Park Zoo’s urban wildlife initiative captures every month.

Conservation researchers rely on automated camera traps to provide them with the raw data they need for their work. The images captured help us know when species are in decline or recovery, if they’re being forced to migrate by climate change or predators, and when humans begin interfering in remote parts of the globe.

The data these images provide is vital to understanding and protecting our world. However, obtaining this data is a big challenge. Not only are there hardware challenges facing the use of camera traps – once the images are collected, they’re manually tagged and categorized. This can result in months-long delays in gaining vital insights.

How we help

Autofocus

Autofocus uses AI and data science modeling to vastly speed up the labeling process by automatically classifying the images camera traps take.

The application can reduce the amount of work it takes to label photos by 97%, freeing up valuable time and resources for researchers to analyze, evaluate and take action on the results.

Our goal is to help researchers save time and money that they can add back into their conservation efforts.


Advantages of Autofocus
1

Easy to Use

It works with popular conservation industry technology to create a scalable solution for conservationists and researchers. The interface is simple and easy to use, enabling organizations to quickly get started and gain insights from their data.

2

Increases Efficiency Through Automation

It performs auto-classifications of images to detect species and alert researchers and activists.

3

Maps and Analyzes Species

Our analytics dashboard enables researchers to clearly map the locations of species and determine actionable next steps based on data visualizations of image classifications.

Impact

The power of AI

2018 Goals

  • Open source the image classification and API tool for researchers to use and contribute to.
  • Further develop our image classification to produce increasingly nuanced insights.
  • Launch a cloud-based application with partners.
  • Convene conservationists and researchers to establish best practices in the field.