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Development of Web Application Front-end to Monitor Deforestation in Mangrove Forests

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This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

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The problem

The mangrove forests in the Rufiji Delta of Tanzania face the pressing issue of deforestation, leading to significant environmental and ecological consequences. The lack of an efficient monitoring mechanism hinders the timely detection and response to deforestation activities. This results in the loss of valuable carbon-rich ecosystems, threatening biodiversity, exacerbating climate change, and undermining sustainable development efforts in the region.

The unchecked deforestation in mangrove forests has severe repercussions on both the environment and the local communities. It contributes to the loss of habitat for numerous species, disrupts the delicate balance of the ecosystem, and reduces the natural defense against coastal erosion and storm surges. Additionally, the depletion of carbon-rich mangroves exacerbates climate change by releasing stored carbon dioxide into the atmosphere. The communities relying on these forests for their livelihoods face socioeconomic challenges and potential displacement.

The proposed solution aims to address the problem of deforestation in mangrove forests by developing a web application front-end to monitor and analyze changes in the Rufiji Delta. By leveraging AI technologies and remote sensing data, the system will provide a reliable and efficient means of monitoring deforestation activities in near real-time. The front-end web application will serve as an accessible platform for the Government of Tanzania, local conservation groups, and communities to track and respond to deforestation incidents promptly.

The project goals

The ultimate project goal is to develop a web application front-end for monitoring deforestation in mangrove forests that will contribute to the preservation of valuable ecosystems, biodiversity conservation, climate change mitigation, and sustainable development in the Rufiji Delta of Tanzania.

Project Scope:

  • Develop the Front-end Web Application: Build a user-friendly and intuitive web application front-end that allows stakeholders to interact with the AI-based monitoring system effectively. The interface should provide easy access to relevant information, visualizations, and alerts regarding deforestation activities in the mangrove forests of the Rufiji Delta.
  • Implement AI-based Deforestation Analysis: Integrate AI algorithms into the system to analyze remote sensing data and detect deforestation incidents. The AI models will process satellite imagery and other relevant data sources to identify changes in forest cover, enabling accurate and timely detection of deforestation activities.
  • Pilot the Monitoring System: Conduct a pilot implementation of the AI-based monitoring system in a specific area of the Rufiji Delta. Evaluate the system’s effectiveness in monitoring and analyzing deforestation activities, considering factors such as accuracy, timeliness, and usability.
  • Enhance Conservation Efforts: Facilitate informed decision-making and proactive conservation measures by providing actionable insights and alerts through the web application front-end. Enable the Government of Tanzania, local conservation groups, and communities to take prompt action to mitigate deforestation and protect the mangrove forests.

**More details will be shared once the project is joined.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works

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Eligibility to join an Omdena Top Talent project

Finished at least one AI Innovation Challenge

Received a recommendation from the Omdena Core Team Member/ Project Owner (PO) is a plus

Skill requirements

Good English

Machine Learning Engineer

Experience working with Web Application is a plus.

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