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Certis Debuts AI Technology To Identify Aedes Mosquitoes

Wong Pei Ting, Today

Artificial intelligence (AI) is being used to recognise mosquito species fast and help fight dengue fever in Singapore.

SINGAPORE — Artificial intelligence (AI) is being used to recognise mosquito species fast and help fight dengue fever in Singapore, where the number of cases of the mosquito-borne disease has hit a four-year high.

From June 1, security firm Certis, owned by state investment firm Temasek Holdings, will begin testing an AI-enabled system that may someday predict dengue hot spots before they emerge.

The technology’s key advantage is that it can identify mosquito species in 40 milliseconds and also the gender very quickly. Only the female Aedes aegypti mosquito bites and spreads dengue.

Field officers may soon snap a photograph of a mosquito they find in an area and be able to tell on the spot if they are indeed dengue-spreading mosquitoes. 

This will speed up the time taken to eradicate mosquito breeding spots.

Currently, mosquitoes are collected and taken back to the laboratory, where trained lab technicians each take 15 to 25 seconds to scrutinise one sample.

Announcing the news at a virtual press conference on Wednesday (May 27), Mr Fuji Foo, Certis’ chief digital officer, said that its system can read 1,000 samples in 40 seconds, and decipher each of the species with 98 per cent accuracy.

It can tell the mosquitoes’ gender apart with 97-per-cent accuracy.

In the past eight months that the system was being developed, more than 68,000 photograph samples of mosquitoes were used to build the AI to tell the mosquitoes apart.

Future data samples collected through the system may still contribute to helping the authorities nail down the geographical distribution of the mosquitoes.

Certis is already engaged by the National Environment Agency (NEA) to support its efforts to reduce the Aedes mosquito population by trapping and collecting mosquitoes.

Last month, NEA warned that the number of dengue cases in 2020 is projected to surpass 2019’s figure, as almost 5,800 dengue cases were reported as of mid-April — more than double that over the same period in 2019.

Nearly 16,000 dengue cases were reported last year, dwarfing the 2,773 cases in 2017 and 3,283 in 2018.

In the next phase, the system will be fed more data of reported dengue cases, weather conditions, population density, water levels and vegetation cover before it can find correlations among these variables to identify up-and-coming hot spots.

The AI-powered system would need six to eight months in this phase before a critical amount of data is available for the system to find these correlations, Mr Foo said.

Read the full story on Today

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