Beijing Subway to use facial recognition technology to enhance security

The Beijing Subway, which handles about 12.3 million passengers every day, will use facial recognition technology to classify passengers and help security officials to enhance the safety measures, an official said here on Tuesday.

The decision comes amidst huge pressure on security checks of passengers and items. "While Beijing subway faces large passenger flow in the rail transit network every day, it has placed huge pressure on security checks of passengers and items," Zhan Minghui, director of Beijing Rail Traffic Control Centre, told a meeting on urban rail transit operation and development.

The Beijing Subway is the rapid transit system of Beijing Municipality that has 23 subway lines in operation, with a total length of 678 kms and 394 stations. The rail network transports 12.3 million passengers on average each workday, with 10,560 trains running up to 1.95 million kms on the network every day, according to the state-run China Daily.

Still, 370 kms of the railroad are under construction and will be put into use within three years. By then, Beijing will have more than 1,000 kms of subway railroad, which can transport 17 million passengers a day, the report said. China has begun making extensive use of facial recognition technology as a major tool to enforce security all over the country.

Recently, the Hong Kong government banned the use of facial masks largely being used by pro-democracy protesters as the concealed faces hindered security officials from making use of the facial recognition technology to determine the identity of the agitators. Zhan said that to improve efficiency, the Beijing Subway needs to promote the use of multi-channel security check machines and facial recognition technology.

"The facial recognition system will judge and classify passengers first into groups and inform guards to use relative measures," Zhan was quoted as saying.

(This story has not been edited by Devdiscourse staff and is auto-generated from a syndicated feed.)