March 7, 2021

We are creating some awesome events for you. Kindly bear with us.

Malaysia set to implement facial recognition system to combat crime

According to a recent report, the Malaysian government is are getting increasingly confident about facial recognition technology. Most recently, Malaysia installed a new facial recognition system to help fight crime in the state of Penang.

The Chief Minister of Penang said that the new system uses technology from an American multinational information technology company and is expected to enhance the 767 closed circuit cameras installed by the Penang Island City Council.

He noted that 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.

At the launch, the Chief Minister stated that the monitoring via CCTV is an initiative by the Penang state government to reduce crime, especially street crimes, in an effort to maintain the safety and well-being of the people.

The government spent MYR46.2 million (US$11.15 million) on the cameras thus far and said that the current project involves spending another MYR 12 million (US$2.9 million) on the technology and on the installation of an additional 150 cameras.

Penang Island City Council Mayor believes that the new system can help increase the efficiency of the police force in preventing and resolving criminal cases.

In the case of a snatch theft on the street, for example, the cameras could not only help identify the criminal but also alert the police about his whereabouts — all using facial recognition technology by an American multinational information technology company.

In recent years, several states and provinces in the US, the UK, China, and the UAE have started exploring the technology — and there have been some hiccups.

According to another report, facial recognition software used by the Metropolitan Police force has returned false positives in more than 98 per cent of cases. The system used by the South Wales Police, on the other hand, has returned more than 2,400 false positives in 15 deployments since June 2017.

China, on the other hand, has been delivering success after success with its facial recognition system. In fact, one of the biggest victories was when a suspect was identified among a crowd of 60,000 Jacky Cheung concert goers in Jiaxing, a city in eastern Zhejiang province.

In Malaysia, only time will tell how effective the system is and what the investment actually delivers in terms of results.

In April 2018, OpenGov had reported that Auxiliary Force Sdn Bhd (AFSB), a member of Royal Malaysia Police Cooperative Bhd., became the first security force in the country to integrate body-worn cameras with facial recognition technology.

AFSB’s main responsibility is to administer and manage Polis Bantuan of the Royal Malaysia Police Cooperative Berhad. In addition, the services of AFSB are utilized by private sector entities such as, such as I-City, ERM, MIC, Hatten Group and others.

AFSB is also responsible for enhancing the knowledge, skills and ability of Polis Bantuan personnel and it offers the Polis Bantuan Foundation Course of Excellence. Currently, AFSB monitors and manages the accreditation of private bodyguards in Malaysia.

AFSB is working with YITU Technology (YITU), a pioneer in Artificial Intelligence (AI) research and innovation, for this initiative to transform and augment Malaysia’s public safety and law enforcement efforts.

AFSB is using the facial recognition technology to allow officers to review captured video footage to spositively identify persons of interest post-event. The objective is to enhance the way auxiliary police safeguard the community, infrastructure and assets.

Implemented since February 2018, the body-worn cameras are currently in use by auxiliary police officers of AFSB at various critical infrastructure. Going forward, there are plans to expand the roll-out to more locations across Malaysia in the near future.

Send this to a friend