New AI-powered mosquito trap could help curb dengue outbreaks

by Joey Garcia, University of South Florida

edited by Sadie Harley, reviewed by Robert Egan

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Add to Preferred Sources The mosquito trap uses built-in cameras and artificial intelligence to identify mosquito species and support real-time surveillance efforts. Credit: University of South Florida As Florida continues to face one of its worst dengue outbreaks in nearly a century, a mosquito trap created by USF startup Digitomy is helping curb the spread of the virus and other mosquito-borne diseases. The smart trap contains patented AI technology and has achieved more than 98% accuracy in identifying mosquito species during laboratory testing.

Research behind Digitomy has been underway at USF since 2018. The technology, created by Associate Professor Ryan Carney and Professor Sriram Chellappan, uses artificial intelligence to identify mosquito species, gender and whether they have fed on blood. Paired with cloud computing and a mapping dashboard, the system aims to help public health officials track disease-carrying mosquitoes for more timely, targeted control.

"The mosquito is the deadliest animal on the planet. While there are 3,500 mosquito species, it's primarily only one, Aedes aegypti, that is spreading dengue in Florida. We can use the data from our smart traps to construct a habitat model, as well as to monitor the species' presence and abundance in real time, to strategically mitigate its spread," said Carney.

Digitomy's trap works when hung on a low tree branch or placed on the ground. Either a light or bait at the top can be used to attract mosquitoes, while a fan draws them inside. Once captured on a sticky pad, two built-in cameras photograph the insects, allowing the AI technology to identify their species using a vast database of mosquito images.

"Traditional mosquito surveillance requires a long manual approach by specialists, which can take two to three days under a microscope," Chellappan said. "The AI in our trap speeds up the process and can lead to more targeted disease interventions, while still being human-led."

While smartphones can be used to help identify a mosquito by its physical characteristics, laboratory testing calculations suggest the Digitomy trap is highly efficient, requiring less energy to identify an entire sticky pad of mosquitoes than sharing a single Instagram post.

Testing at USF and the research team's partnership with St. Johns County's Anastasia Mosquito Control District, which includes St. Augustine, has helped advance the technology.

"Collaborating with Digitomy and USF will benefit our programs by helping us explore and adopt new artificial intelligence technology. We will then be able to greatly monitor vector mosquito populations and promote future public participation in mosquito surveillance," said Rui-De Xue, Anastasia Mosquito Control District executive director.

Beyond identifying mosquitoes, Digitomy could help public health officials pinpoint where disease-carrying species are concentrated and direct control efforts more effectively. The technology could also complement Carney's earlier DYCAST early warning system for dengue and West Nile virus outbreaks.

The team has also integrated trap data into a private layer of its Global Mosquito Observations Dashboard, combining trap information with more than half a million citizen science reports. The system could eventually help mosquito control districts monitor populations across different locations and respond more quickly during outbreaks.

Digitomy is also developing a cloud-based education platform for mosquito control professionals and the public. Users can examine mosquito images, identify species and receive AI-generated feedback to improve their identification skills without attending in-person training sessions.

"Education is our secondary line of defense," Carney said. "While our smart traps provide the macro-level data, the public should practice the three D's: Drain standing water, Dress to cover skin and wear DEET. Pairing automated AI data with mosquito control and engaged communities can help us conquer these outbreaks."

The researchers hope to work with mosquito control districts, including Anastasia and Hillsborough, to incorporate the platform into professional training and public education programs.

As Digitomy moves closer to consumer sales, the researchers are preparing for field validation with Hillsborough County while working to bring the technology to market.

Carney and Chellappan are now working with the USF Technology Transfer office to license Digitomy to established mosquito trap manufacturers who can combine their existing equipment with USF's AI identification system.

"Mosquito-control programs wait days to learn what is in their traps," said Diana Shapiro, chief operations officer of Digitomy and operator for several USF ventures in USF Technology Transfer's Launch Program. "Our technology is built to tell them the same day, and to reach the places with the least to spend and the most at stake."

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