This Malaysian state is using facial recognition to catch criminals

The state has 767 CCTV cameras on Penang Island alone and now, many of them have been equipped with facial and Artificial Intelligence technology developed by IBM.

While some might think that this is a breach of privacy, the Penang City Council has assured citizens that it is only used to detect faces of and to reduce street crime.

 

“This technology, which is capable of detecting the faces of criminals or people wanted by the police, will be operated from the CCTV control room of the MBPP and the Penang police headquarters.

“The monitoring via CCTV is an initiative by the Penang state government to reduce crime, especially street crimes, to maintain the safety and well-being of the people,” said Chief Minister of Penang Chow Kon Yeow in a statement to Tech News.

Chow added, “We hope to increase the number of CCTVs installed with this face recognition technology to 3,000 units in stages, for better crime prevention, and to expand it to areas under the Seberang Perai Municipal Council (MPSP).”
 

IMAGE: Chow kon Yeow’s Facebook pageState police chief A. Thaiveegan said that the local police would be able to upload an image of a criminal or a wanted person. The system will then inform the relevant authorities immediately if it manages to track the subject.

Facial recognition technology in China. IMAGE: Austin County NewsPenang is taking hints from China who has installed CCTV cameras with facial recognition since 2005.

Although facial recognition is not 100% reliable, like detecting a jaywalker which turned out to be a bus, the Chinese authorities have managed to identify 2,000 suspects, arrest more than 800 people, and solve 200 cases since its deployment.

China is heavily invested in facial recognition. In 2018, they installed facial recognition toilet paper dispensers which dispenses 90cm of toilet paper after scanning your face.

The aim was to cut down on toilet paper use and deter citizens from stealing toilet paper from public restrooms.

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