SAFR from RealNetworks has been deployed in one of the biggest hotel groups in South Australia, where Ecash worked in partnership with RealNetworks to deploy the solution in 7 hotels via 18 cameras located in the hotel group’s gaming areas.
SAFR added superior situational awareness across the group hotels, daily detecting thousands of faces, comparing them to a watchlist of barred people, and alerting surveillance staff about potential barred people by email and SMS. The deployment complies with the new state regulation, which requires an authorized facial recognition solution to be installed in all venues with 30 or more gaming machines, if one or more of which uses note acceptors, because of its ability to quickly identify barred patrons and automatically notify matches to surveillance staff.
The SAFR and Ecash partnership offers server and cameras monitoring 24 hours a day. SAFR health check application runs on each local server, performing a large range of checks such as applications status, camera stream status, system usage with the collection of CPU, GPU, RAM and hard drive statists, ports checks, and CBS connectivity status. Real-time alarm notifications are generated by the central management server when any failures are detected in the system. The SAFR health check solution is self-healing, not only reporting issues, but also taking automatic actions to solve them when any failures are detected.
The social impact of problem gambling is undeniable as governments all over the world have been implementing significant gambling reforms to minimize gambling harm on communities. A great example being, self-exclusion and third-party barring options measures offered by the South Australian Government, where individuals can ask to be barred or families can request to bar a family member from many forms of gambling such as gaming venues and casinos.
Despite the great initiative and strong society’s adherence, gaming venues and governments have been struggling to identify barred people in a real environment as manually monitoring for each person of interest was an arduous and inefficient task — which is very difficult without the right video surveillance technology. SAFR from RealNetworks, was recently approved by the Government of South Australia as an official facial recognition solution for enforcing gambling bans in gaming venues across the state.
An approved system must offer technical expertise in a large range of capabilities and applications. SAFR has been integrated with the barring database held by the state’s CBS (Consumer and Business Services) agency to import and keep barred person data up to date and then use this data to compare with the images of persons entering a gaming area. Furthermore, SAFR action module is used to send SMS and E-mail notifications to the gambling provider when a suspected barred person is identified. Finally, SAFR has been customized to send daily statistics reports regarding the number of persons detected and the number of barred patrons recognized from each gaming venue to SA Government.
The hotel group’s operations managers have been working worked to choose a reliable facial recognition software that is internationally recognized and approved by the SA Government, with an accuracy rate above 99.8 per cent for all races. SAFR was tested and selected by one of the biggest hotel groups in SA because it complies with these criteria and due to its advantages compared to other FR systems evaluated such as superior performance on live video, previous deployments in gaming in the US, the lower total cost of ownership, and local support with solid FR knowledge.
The new surveillance technology offers the possibility to increase the barred people recognition rate by automatic detections, showing the benefits of face recognition technology to social change, and helping problem gambling.
“The impact to our day-to-day operations has been minimal, the system just works as we were told it would— emails and SMS alerts have been received in less than 60 seconds,” said a hotel spokesperson.
#sen.news
