2025 | Early stage | Education | Ethiopia | SDG11 | SDG13 | SDG2 | SDG3
AksumAI: Multilingual Crisis Response Platform for East Africa

Organisation Name

Addis Ababa Science and Technology University

Industry

Education

Organisation Website

https://www.aastu.edu.et

Country

Ethiopia

Sustainable Development Goals (SDGs)

SDG 2: Zero Hunger

SDG 3: Good Health and Well-being

SDG 11: Sustainable Cities and Communities

SDG 13: Climate Action

General Description of the AI tool

AksumAI is an inclusive AI platform that delivers real-time disaster alerts and health advisories to vulnerable communities in Ethiopia and East Africa via low-bandwidth voice interfaces. Using fine-tuned NLP models for Amharic, Oromo, and Tigrinya, it translates satellite flood/drought predictions and epidemic warnings into actionable voice/SMS messages—accessible even to illiterate users. By fusing local language processing with climate/health data, we reduce disaster response time by 70%, empower smallholder farmers with crop-saving insights, and enable NGOs to coordinate aid efficiently.

Github, open data repository

https://zenodo.org/records/5504175

Relevant Research and Publications

0. Girma Neshir Alemneh, Andreas Rauber, Solomon Atnafu (2020). BERT Fine-Tuning for Amharic Sentiment Classification. Workshop co-located with the Eighth Swedish Language Technology Conference (SLTC).
1. Girma Neshir Alemneh, Andreas Rauber, Solomon Atnafu (2021). Meta-Learner for Amharic Sentiment Classification. Applied Sciences, 11(18), 8489. doi: 10.3390/app11188489.
2. Girma Neshir Alemneh, Andreas Rauber, Solomon Atnafu (2021). Topic Modeling for Amharic User Generated Texts. Information, 12(10), 401. doi: 10.3390/info12100401.
3. Girma Neshir Alemneh, Andreas Rauber, Solomon Atnafu (2019). Dictionary-Based Amharic Sentiment Lexicon Generation. In Information and Communication Technology for Development for Africa (pp. 311-326). Springer International Publishing.
4. Girma Neshir Alemneh, Andreas Rauber, Solomon Atnafu (2020). Negation Handling for Amharic Sentiment Classification. Workshop co-located with AAAI 2020. Available at: http://kdd.cs.ksu.edu/
5. Girma Neshir Alemneh, Andreas Rauber, Solomon Atnafu (2019). Corpus-Based Amharic Sentiment Lexicon Generation. CEUR Proceedings, Forum Artificial Intelligence Research (FAIR). Available at: http://ceurws.org/Vol-2540/, and workshop co-located with AAAI. Available at: http://kdd.cs.ksu.edu/

Needs

Personnel

CONTACT

International Research Centre
on Artificial Intelligence (IRCAI)
under the auspices of UNESCO 

Jožef Stefan Institute
Jamova cesta 39
SI-1000 Ljubljana

info@ircai.org
ircai.org

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