The battle to elbow rivals away and get to the front of the bar is a proud weekend tradition stretching back generations — but it causes headaches for bar staff trying to work out who has been waiting the longest.
Now, British developers behind a new “AI bar” are promising to consign shouts of “who’s next” to history, with the help of facial recognition.
The new system will use a webcam to film arrivals at the bar, feeding back the order of a virtual line to bartenders via a display screen behind the counter.
It means that, in theory, customers may never have to stare down a line-jumper who gets their order as soon as they’ve muscled their way to the front. It also means bar staff won’t have to navigate a frustrated crowd.
The technology was tested in June at a bar in central London, and will be trialed at more establishments starting in September.
It will alert customers to their place in the line, and will also scan their faces to analyze their age, with the aim of reducing the time it takes to ask for identification.
DataSparQ, the company behind the system, says it carried out research that revealed British people spend about two months of their life waiting at bars.
“Queuing is a part of British life that we all have to endure — but we wanted to do something to improve the experience,” John Wyllie, managing director at DataSparQ, said in a statement.
“It’s the uncertainty of waiting times alongside queue jumpers that’s adversely affecting consumer behaviours in bars and pubs,” he added.
The company is in talks with pubs around the United Kingdom with a view to rolling out the software. The software will cost pub landlords £199 ($240) per month.
The company also hopes the technology can serve a wider purpose — slowing down the punishing decline of pubs across Britain. Fourteen pubs close each week in the country, according to the Campaign for Real Ale.
DataSparQ said its technology will provide landlords with data about when a pub is getting more orders, allowing them to adjust staffing and other costs accordingly.