Afretec awards almost $1.7 million

Emily Liu

Jun 18, 2024

Afretec logo

The African Engineering and Technology Network (Afretec), a pan-African collaboration consisting of technology-centric universities across Africa, has awarded five $250,000 grants and eight $50,000 grants to build research capacity and accelerate inclusive digital growth throughout the African continent. Each multi-institutional research team will build on existing science, engineering, and technology in disciplines such as artificial intelligence (AI), machine learning, robotics, information technology, and cybersecurity.

The selected projects are particularly focused on improving the state of health, environment and sustainability, and energy in Africa. Several projects will also address the United Nations Sustainable Development Goals (UN SDGs), which were created with the goal of improving every aspect of human and environmental well-being.

Awarded full grants

Revolutionizing oxygen supply in healthcare: a sustainable approach through water-based oxygen harvesting

Principal investigator: Davies Segera

Partner institutions: University of Nairobi, American University in Cairo, University of Lagos

This project aims to harvest oxygen and hydrogen directly from water using advanced electrolysis. By integrating sensor technology and data analytics to enhance efficiency and assess environmental impact, the novel approach could potentially reduce the carbon footprint of the production of oxygen and hydrogen by up to 60%.

Enhanced CVD discovery in medically underserved communities via AI-assisted stethoscopy

Principal investigators: Khalil Elkhodary, Vijayakumar Bhagavatula, Carine Pierrette Mukamakuza

Partner institutions: American University in Cairo, Carnegie Mellon University, Carnegie Mellon University Africa, University of Porto

Quantitative diagnoses of cardiovascular diseases are expensive and can be difficult to access. This project aims to transform electronic stethoscopes, which are much less expensive, into reliable testing tools that accurately quantify the severity of disease, paving the road for the improvement of healthcare in medically underserved regions.

Wakanda AI: engineering smart solutions for mother tongues by advancing language technologies in the African context

Principal investigators: Bhiksha Raj, Abraham Nyete, Moise Busogi, Moustapha Diaby

Partner institutions: Carnegie Mellon University, University of Nairobi, Carnegie Mellon University Africa, Ecole Supérieure Africaine des Technologies de l’Information et de la Communication

By establishing a curated data repository of speech and text data, identifying use cases tailored to the African market, and analyzing existing speech and language models, this project will endeavor to reduce language barriers and improve access to information in Africa.

Birds’ detector and repellent system for large-scale smart farming

Principal investigator: Emmanuel Ndashimye

Partner institutions: Carnegie Mellon University Africa, University of Rwanda, University of Nairobi

Bird damage to crops poses a serious threat to numerous communities, especially those that depend heavily on agriculture. This project proposes an AI-based system that, upon detecting the presence of a bird, emits a non-harmful high-frequency sound that repels birds while remaining imperceptible to humans.

Deep learning-driven multiplexed prospectivity modeling of rare earths in radiothermic carbonatites

Principal investigators: Angeyo Hudson Kalambuka, Kaniu Ian Muchai, Digne E. Rwabuhungu, Iyobo Usman

Partner institutions: University of Nairobi, University of Rwanda, University of the Witwatersrand

Rare-earth metals are valued for their applications in advanced technologies and carbon-free fuels, but it can be difficult to locate these metals in geothermal, high background radiation areas. This project aims to develop deep learning-driven, multiplexed spectral and imaging models for the rapid prospecting of rare earths in the alkaline radiothermic carbonatite complexes of Eastern Africa.

Awarded seed grants

Real-time noise level web mapping through crowdsourcing: toward creating sustainable urban environments

Principal investigator: David Siriba

Partner institutions: University of Nairobi, University of Rwanda, Israel Institute of Technology

Noise pollution can have negative impacts on the well-being, health, and quality of life of urban residents. However, implementing and enforcing noise regulations requires consistent, continued availability of live data. This project proposes Volunteered Geographic Information (VGI), a tool that could help with effective noise reduction by crowdsourcing noise level data and creating a real-time noise level database and map.

Leveraging IoT and Edge-AI for detecting and managing schistosomiasis

Principal investigators: Moustafa Youssef, Benyl Muyoma Ondeto

Partner institutions: American University in Cairo, University of Nairobi, Université Cheikh Anta Diop

Schistosomiasis is a parasitic disease diagnosed by detecting microscopic worm eggs in stool, urine, or organ biopsies. The drug praziquantel is effective against schistosomiasis, but the disease continues to impact impoverished communities, especially in Africa. The goal of this project is to develop a prototype of a sensing device and an AI-based decision support system to help with the detection and management of schistosomiasis.

Application of AI techniques for extracting carbon from landfill waste for renewable energy

Principal investigator: Abdul Ganiyu Adelopo

Partner institutions: University of Lagos, University of Nairobi, Carnegie Mellon University Africa

African cities face a critical challenge in waste management due to rising urban populations and overloaded landfills. This project aims to use AI to assess the potential of resource reuse from landfills in African cities, focusing on renewable energy storage. The project will endeavor to create new datasets for predictive landfill machine-learning models and promote a cost-effective shift to renewable energy in African cities.

An investigation of a monitoring and predicting algorithm model for climate change-related diseases in African urban cities

Principal investigator: Immaculata Nwokoro

Partner institutions: University of Nairobi, University of Lagos

This project proposes an AI-driven predictive management system to tackle climate change-related diseases in African urban cities, addressing the acute challenges of limited health facilities and workforce shortages. The study aims to develop a robust data gathering system using Interactive Voice Response (IVR) connected to the Internet of Things (IoT), ensuring data inclusivity and confidentiality.

Evaluating digital transformation and maturity in youth-led micro, small, and medium enterprises across Sub-Saharan Africa: a comparative study in the health, energy, environment and sustainability sectors in Nigeria, Kenya, and South Africa

Principal investigator: Duncan Elly

Partner institutions: University of Nairobi, University of the Witwatersrand, University of Lagos

This project will investigate the role of micro, small, and medium enterprises (MSMEs) in Sub-Saharan Africa, specifically in the health, energy, environment and sustainability sectors across Nigeria, Kenya, and South Africa. The project seeks to help create a more supportive environment for youth-led MSMEs in the face of contemporary challenges.

Empowering African communities: culturally relevant cybersecurity education through comic books and AI models for children's online protection

Principal investigator: Jema David Ndibwile

Partner institutions: Carnegie Mellon University Africa, University of Rwanda

In the digital age, African children are increasingly at risk of being exposed to violent content, cyberbullying, or online sexual exploitation. This project aims to develop culturally relevant cybersecurity education materials and digital solutions tailored to the unique needs of African children and marginalized communities. The project seeks to empower African children to navigate the digital world safely.

An AI-driven environmental monitoring platform for low-resource setting

Principal investigator: Edwin Mugume

Partner institutions: Carnegie Mellon University Africa, Makerere University, University of Rwanda, University of Twente

Sub-Saharan Africa lacks sufficient environmental and weather monitoring nodes, mainly due to their high cost. This hinders efforts to accurately track the effects of climate change in the region. The project will design, develop, and test low-cost sensors for measuring temperature, humidity, wind speed and direction, precipitation, and particulate matter parameters.

Optimizing a mobile application for enhancing parents’ reporting and prediction of adverse effects following maternal and child immunization in Rwanda

Principal investigator: Aimable Musafiri

Partner institutions: University of Rwanda, Carnegie Mellon University Africa, Rwanda Food and Drugs Authority

Although over 90% of children and pregnant women in Rwanda receive vaccinations, there’s still a significant gap in the reporting of adverse effects following immunization (AEFI). This project proposes the VigiMobile application, which parents can use to directly report AEFI and bridge the gap between report and response. The project will also use machine learning algorithms to identify factors influencing AEFI in the Rwandan population.