Two student researchers from the Rapid VBP KNUST, Nutifafa Agbenor-Efunam and Lakyiere Alice Bagyiereyele, are currently interning at the University of Bremen where they each delivered oral and poster presentations after their first month of research.
Nutifafa Agbenor-Efunam is developing an energy-efficient mosquito monitoring system that adapts based on environmental cues like rainfall, temperature, and humidity. The system intelligently manages power consumption by activating components such as fans and machine learning models only when needed, helping to extend operational time in the field without compromising surveillance.
Lakyiere Alice Bagyiereyele’s research focuses on mosquito detection and classification using image-based deep learning. Her system identifies multiple mosquitoes in a single image and classifies them by genus (Aedes, Anopheles, or Culex), advancing efforts in scalable, automated vector identification.
These projects are part of AI4PEP Ghana’s broader goal to leverage AI for malaria elimination, contributing innovative, scalable tools for vector surveillance. The impact extends beyond research, supporting global public health systems in tackling mosquito-borne diseases with data-driven precision.
