Researchers at the University of Wollongong in Australia have developed an intelligent monitoring device to quickly and accurately identify mosquito species at risk of causing disease by capturing and analyzing the sound of mosquitoes waving their wings. The device was developed by Dr. Kieran Trivedi and was exhibited at the UN Global Summit on Artificial Intelligence for Good. The equipment relies on artificial intelligence technology to identify the 3 most harmful mosquito species in the world, such as Aedes, Anopheles, and Culex. There is a slight difference in the frequency of the wings of different mosquito species, forming a unique “sound pattern”. The device can quickly distinguish between different mosquito species within a few seconds by accurately analyzing the frequency of winged wings. The equipment is equipped with miniature machine learning technology and is suitable for promotion and use in rural and remote areas. The core of this device is a miniature circuit board based on the Arduino platform, equipped with a microphone and display. The R&D team used open source audio data of mosquito wings to train the AI model. Currently, the device's mosquito species identification accuracy rate has reached 88%.

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