Projects / AI Innovation Challenge

Tackling Deforestation in Tanzania with AI: A Pilot Project Focused on Mangroves.

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Demonstrate the potential of AI-based systems to monitor and analyze deforestation in Tanzania’s carbon-rich mangroves and to provide a scalable model for monitoring deforestation across the whole country. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.

The problem

Tanzania has Africa’s third largest forest cover yet the fifth highest rate of deforestation in the world, contributing to over 70% of the country’s GHG emissions. Deforestation is the process of clearing or removing trees and forests from an area, typically resulting in the conversion of the land for agricultural or industrial purposes. This problem is significant because forests play a critical role in regulating the Earth’s climate, by absorbing carbon dioxide from the atmosphere and storing it in their biomass. Deforestation, therefore, contributes to the release of greenhouse gases (GHG) into the atmosphere, exacerbating global climate change and the associated negative impacts on the environment and human society.

Tanzania’s high rate of deforestation is particularly alarming, as it contributes significantly to the country’s GHG emissions. This means that Tanzania’s deforestation problem has far-reaching consequences, not only for the country itself but also for the global environment. The loss of forest cover can also have significant local impacts on the ecosystem, such as soil erosion, loss of biodiversity, and disruption of water cycles, which can lead to negative social and economic consequences, such as reduced agricultural productivity and food security.

Tanzania’s extensive forest resources have attracted the interest of forest carbon offset project developers, providing a significant opening for local communities to benefit from the rapidly growing carbon markets. To maximize the benefits of carbon finance for both the environment and communities, Tanzania needs to enhance its technical skills in advanced AI deforestation analysis. This requires strengthening academic research and technical expertise to foster effective collaboration with developers on equal footing.

The project goals

The pilot project’s primary objective is to demonstrate the potential of an AI-based system to monitor and analyze deforestation in Tanzania’s carbon-rich mangroves and provide a framework for scaling up the system to cover the entire country. The project also aims to build capacity within Tanzania to manage and utilize the data generated by the system in developing and implementing the AI-based solution.

The main goals of this project are:

  • Develop an AI-based system to analyze deforestation in Tanzania’s carbon-rich mangroves in a specific area.
  • Provide up-to-date data and analysis on deforestation in the pilot area.
  • Develop a user-friendly front-end for the AI-based system that is accessible to the public.
  • Pilot the AI-based system to test its effectiveness in analyzing and monitoring deforestation in a specific area.
  • Refine and improve the AI-based system and front-end for broader implementation.
  • Provide recommendations for scaling up the system to cover the whole country, including data management.

Why join? The uniqueness of Omdena AI Innovation 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.

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Your Benefits

Address a significant real-world problem with your skills

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Access paid projects, speaking gigs, and writing opportunities


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 Machine Learning and/or Data Science

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