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To cope with the peak of summer visitor flow, the Forbidden City introduced AI algorithm model to identify "scalpers"

2024-08-21

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As the 2024 summer vacation draws to a close, the number of summer tourists has surged, and scalpers have been scrambling to grab tickets online, squeezing out ticket resources and disrupting normal visit order. In order to ensure the safety of the Forbidden City's heritage, cultural relics and visitors, and to provide tourists with a comfortable and good visiting environment, the Palace Museum has implemented a daily reservation limit of 40,000 people in recent years, which is also the carrying capacity of the Forbidden City World Heritage. Since the beginning of the summer vacation, the Palace Museum has actively responded to the peak of tourist traffic to Beijing, and has taken dozens of measures in ticket management, safety management, and open reception.

Forbidden City Ticket Booking Platform

How to effectively identify scalpers?

In order to prevent scalpers from snatching tickets and ticket machines from swiping tickets, the Palace Museum continues to optimize its ticketing system, continuously increase technical prevention efforts, and improve security protection levels. At the same time, a dedicated person is on duty every night, and the ticket quota is slowly released manually after the ticket release starts at 20:00. On the one hand, it can improve the audience's ticket purchasing experience and ticket purchase success rate, and relieve the audience's anxiety; on the other hand, extending the ticket release time can effectively guarantee the time for inbound tour groups and overseas audiences to purchase tickets on multilingual websites, and improve the efficiency of inbound tour groups and individual tourists to purchase tickets.

In the three stages before, during and after ticket purchase, the Forbidden City uses in-depth defense technology to identify "scalpers" in real time, identifies risks of users who have made reservations at the "millisecond level", and gives judgment results. It mainly relies on trusted device identification technology, intelligent risk control engines, and AI algorithm models to establish a risk control system that integrates traffic, accounts, and equipment.