Science and Technology Research │ Artificial Intelligence
Wovenware partners with the PRVCU to develop a solution for automating the identification and classification of mosquito species.
The world’s deadliest animal is not a shark or a snake, it is the mosquito. The tiny creatures have killed 32 times as many people as every war in human history combined. The Puerto Rico Science, Technology & Research Trust and its Vector Control Unit (PRVCU) has been working to help prevent and manage diseases spread by mosquitoes, to gain an understanding of why many mosquitoes have become immune to insecticides approved by the FDA.
Researchers have spread out across the island, capturing different mosquito species in traps; monitoring and testing them for viral presence and insecticide resistance; and labelling and classifying them. Manually capturing and classifying thousands of mosquitoes in different locales can take many months before any specific patterns can emerge.
Wovenware partnered with the PRVCU to develop an RPA solution composed of deep learning models and other processes to automate the identification and classification of mosquito species. It significantly reduced manual work, allowing entomologists to spend more time in more advanced research activities.
Wovenware proposed an RPA solution to automate counting the total number of mosquitoes in traps, classifying the species and the gender.
Technologies we take advantage of
In order to create the deep learning solution capable of counting and classifying the mosquitos, the wovenware team had to:
The automated classification process was four times faster than the manual process and it freed up time for the entomologists to focus on analytics and research to understand why many mosquitoes have become immune to insecticides approved by the FDA. The team is experimenting with camera setup to automate the tasks of taking pictures from traps. Future improvements can be made by including time-series analysis, genome analysis, and remote monitoring and classification.