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In the last decades, we have witnessed a tremendous increase in dengue fever cases. Four decades ago, only nine countries had reported severe dengue epidemics. Currently, dengue is endemic in more than 100 countries. In this project, we discuss why we are losing the war against dengue and propose a completely different vector control approach. We propose to further develop our recent research on intelligent sensors to field conditions. Our idea is to propose an inexpensive device that will empower the population with the knowledge of Aedes aegypti densities. This will motivate local mosquito control activities and put the community, governmental and aid organizations far ahead of disease outbreaks.
Funding Agency
Google - Google Research Awards for Latin America
USAID - United States Agency for International Development
IVCC - Innovative Vector Control Consortium
Achievements
Achievements
Data gathering
Data gathering
Data collected
Data collected
We collected more than one million instances for 20 different insect species including mosquitoes, houseflies, bees, and wasps. For 10 out of 20 insect species, it was possible to collect the data for each individual sex, totaling 30 class labels
Machine learning classifier
Machine learning classifier
A simple experiment with a classifier embedded into the cylindrical chambers. The left chamber contains Aedes aegypti females, the right one Anopheles quadrimaculatus females, and the center chamber females from both species were put in.
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