An intelligent queuing system for face-to-face signing

Abstract

The invention discloses an intelligent queuing system for face-to-face signing. The invention relates to the technical field of intelligent queuing for face-to-face signing. It solves the technical problem of low work efficiency caused by the inability to reasonably dispatch business personnel in the prior art, and analyzes the customer queue through a personnel dispatching unit. Information, and reasonably transfer business personnel to obtain customer queue information; obtain the transfer coefficient DD of business employees through the formula, if the transfer coefficient DD of business employees ≥ the threshold of the transfer coefficient, generate an employee supplementary signal, and send the staff supplementary signal to The mobile phone terminal of the mobile employee adds the management channel of the mobile employee at the same time; if the transfer coefficient DD of the business employee < the transfer coefficient threshold value, an employee removal signal is generated, and the employee removal signal is sent to the mobile phone terminal of the mobile employee, and the management of the mobile employee is canceled at the same time Channel; real-time monitoring of customer queues, reasonable mobilization of employees, improved service quality, and reduced congestion time.

Description

technical field [0001] The invention relates to the technical field of intelligent queuing for face-to-face signing, in particular to an intelligent queuing system for face-to-face signing. Background technique [0002] Counter service industries are all faced with the pressure of customer queuing, such as bank counter service industry, queuing phenomenon is relatively common, so that the counter service personnel are under overload work pressure, and the service quality of the counter will also decline accordingly, and customers complain strongly. Therefore, to solve the queuing problem in counter services such as banks, it is necessary to find a balance of resources as much as possible, so that the number of customers and the number of windows can reach the best balance. However, due to the lack of scientific models and algorithms, the existing queuing management systems and methods can only qualitatively and subjectively judge whether the number of windows is large or sma...

AI Technical Summary

Problems solved by technology

However, due to the lack of scientific models and algorithms, the existing queuing management systems and methods can only qualitatively and subjectively judge whether the number of windows is large or small. This method of rough estimation is difficult to find the balance point of resources, because in practice In daily life, different outlets, different working days, and even different time periods of the same working day will have different queuing phenomena, so it is necessary to provide a real-time dynamic window optimization method

[0003] In the existing technology, when customers queue up to handle business, the queue cannot be analyzed in real time, so that business personnel cannot be reasonably dispatched, resulting in low work efficiency, delaying customer time, and even being unable to handle business

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