Project Premonition

Project Premonition

Established: March 2, 2015

“Project Premonition aims to detect pathogens before they cause outbreaks”

Emerging infectious diseases such as Zika, Ebola, Chikungunya and MERS are dangerous and unpredictable. Public health organizations need data as early as possible to predict disease spread and plan responses. But, early data is very difficult to obtain, because it requires sampling and testing potential disease sources directly from the environment. Project Premonition aims to detect pathogens before they cause outbreaks, using mosquitoes to sample pathogens in the environment. (Researchers estimate between 60 and 75% of emerging infectious diseases evolve in animals.) Turning a mosquito into a device requires new technologies to autonomously locate, robotically collect, and computationally analyze mosquitoes.

Project Premonition technologies



“Robotic mosquito traps that identify and capture interesting mosquitoes in milliseconds”

Project Premonition requires lots of interesting mosquitoes, but this is easier said than done. Existing mosquito traps can’t distinguish mosquitoes from other insects, requiring entomologists to process the insects collected from every trap. Project Premonition redesigned the mosquito trap to be robotic and smart. It is comprised of 64 smart cells, each of which monitors the insects flying into it. If the wing movements of an insect match that of an interesting mosquito, then a cell can close a door, capturing that insect and tagging with key environmental data including time, temperature and light levels. The trap can learn from its mistakes to become more efficient, and it is designed to run for more than 20 hours in hot and humid environments. It is currently being deployed in Houston and is capturing an unprecedented 100’s of gigabytes of data per week about mosquito behavior.

“Drones that locate mosquito hotspots…and eventually place traps”

Finding mosquito hotspots is also harder than it sounds. Mosquito populations change daily with weather. One urban block might have thousands of mosquitoes, and the next block almost none. Drones offer an efficient means to scan a large area for likely mosquito habitat. In order for this to work, we are programming drones to safely and securely navigate complex areas with advanced software engineering methods. We also are applying machine learning and cloud computing to recognize visual features indicative of mosquito hotspots. Eventually, we would like drones to actually place and retrieve traps on their own.

“Algorithms that detect known and unknown pathogens”

Some emerging infectious diseases are caused by pathogens that were known to exist, but were not regularly tested for in labs, e.g. Zika and Ebola. Others are caused by pathogens that were previously unknown to science, e.g. SARS and MERS. These properties make emerging diseases very difficult to detect early using traditional techniques. We are developing algorithms to detect these threats by analyzing the genetic material obtained from mosquitoes. Gene sequencing converts mosquitoes into hundreds of gigabytes of genetic data without focusing on a specific set of pathogens. This data can tell us about the species of mosquitoes collected, the animals they have bitten, and the pathogens they may have encountered. New algorithms must be developed to quickly search for viruses and microbes, which are needles in this haystack of data.

Project Premonition detection overview

More Articles and News

Research Team

Grenada Feasibility Study: Catching mosquitoes and training drones

Watch the video