Projects / AI Innovation Challenge

Developing an AI System to Identify Ecosystem Services and Automate Data Collection for Endangered Species



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In this 8-week challenge, a global team of 50 collaborators built solutions to identify relevant ecosystem services for individual species and built a dataset that can be used to model and value the economic contribution of species to a region or country.

The Problem

This is a sequel to Omdena’s completed challenge with Endangered Wildlife OÜ. The previous challenge succeeded in determining the species to be included in a food web, interactions between different species within the food web, and extracting population data trends. 

Part of the process of valuing biodiversity is to identify ecosystem services, i.e. the ways in which species of biodiversity contribute to human economic activities.

The Project Goals

Building on the previous challenge, the project will develop an AI system that is able to identify relevant economic activities for individual species and to extract time-series data from online data resources to build a dataset that can be used to model and value the economic contribution of the species to a region or country.

This can be broken into two steps.

Step 1. Determine the economic activities supported by a species. EW selects one “target” species population, which it researches to understand the economic activities that are supported by the species. EW then categorizes the activities into up to 28 pre-set sectors. This information can be sourced from websites and species’ studies.

The deliverable of this step is the list of economic activities attributable to a specific Species.

Step 2. Build a dataset containing time series data of the economic activities listed in Step 1 of the target species in a specific location, ending with the latest possible time point. 

The deliverable of this step is a time-series dataset containing the activity, year, and relevant fields.

There are up to 28 potential economic sectors. For example, most species have a tourism value which includes data such as:

  1. Number of tourists to the selected region;
  2. Average price per night for a hotel in the region; and
  3. Average meal price in the region.

For the purpose of this project, the scope will be restricted to 3 or 4 species in 1 location each.

Why join? The uniqueness of Omdena AI Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities



Your benefits

Address a significant real-world problem with your skills

Get hired at top companies by building your Omdena project portfolio (via certificates, references, etc.)

Access paid projects, speaking gigs, and writing opportunities



Requirements

Good English

A very good grasp in computer science and/or mathematics

Student, (aspiring) data scientist, (senior) ML engineer, data engineer, or domain expert (no need for AI expertise)

Programming experience with Python

Understanding of Data Analytics, Machine Learning and Data Engineering.



This challenge is hosted with our friends at


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