Challenge background
In Sudan, there exists a growing demand for digital data , with an increasing percentage of the population gaining both basic internet access and mobile connectivity. However, amid the surge of information accessibility & adoption in the region, accurate knowledge about local flora and fauna remains limited. The dissemination of credible information is integral, especially considering the ecological richness and biodiversity of Sudan’s wildlife & its major role in the global ecosystem. Misinformation & the lack of data-driven insight often act as hindrances to the public understanding and appropriation of the Sudanese Ecological System.
The problem
There is a significant absence of a comprehensive digital catalog for Sudan’s diverse Biological life forms. This gap has resulted in limited accessibility to reliable information about local species. Inaccuracies or the lack of information can lead to misconceptions, missed conservation opportunities, and inadequate educational resources. Furthermore, there is little to no actionable applications of ecological data, despite the recent modernization & computational breakthroughs.
Goal of the project
- The goal of ZoiDex is to harness Computer Vision, Knowledge Representation,as well as Augmentation & Retrieval (RAR) techniques to create a robust cataloging system for Sudan's flora and fauna, eventually serving as a possible prototype for a global system in the near future.
- Employing advanced AI algorithms & Machine Learning Techniques aimed at detecting, categorizing, and providing accessible and accurate information about Sudan’s various diverse lifeforms.
This system will function akin to an expert guide, offering instant access to comprehensive details about various species through a user-friendly interface.
Project timeline
- 1
Week 1
Data Collection: Initiate gathering image and text data related to Sudanese life forms.
- 2
Week 2
Data Pre-Processing: Clean and organize collected data for analysis.
- 3
Week 3
Exploratory Data Analysis: Analyze data patterns and characteristics.
- 4
Week 4
Modelling: Develop AI models for Computer Vision and RAR.
- 5
Week 5
Model Testing: Evaluate the accuracy and efficiency of developed models.
- 6
Week 6
API Development: Build an accessible API for data retrieval.
- 7
Week 7
Front-end Development: Design an intuitive platform interface.
- 8
Week 8
Deployment: Host and launch the BioDex platform for public access.
What you'll learn
Data Collection and Curation, Advanced Technologies, Machine Learning and AI, User Interface Design, Collaboration and Teamwork, Ecological Understanding, Education and Outreach, Problem-Solving and Critical Thinking, Project Management, Ethical Considerations