CN111160793A

CN111160793A - Method, device and equipment for configuring number of self-service equipment of service network point

Info

Publication number: CN111160793A
Application number: CN201911412752.8A
Authority: CN
Inventors: 朱江波; 赵赛; 师鹏超; 杨宏; 董宝璐; 张盛素; 高鹏; 马雪莹; 郭彦伟; 张自鹏; 刘颖超; 刘真真
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2019-12-31
Filing date: 2019-12-31
Publication date: 2020-05-15

Abstract

The specification provides a method, a device and equipment for configuring the number of self-service equipment of a service network point, wherein the method comprises the following steps: the method comprises the steps of determining the vacancy rate and the longest waiting time of each self-service device based on device use data of the self-service devices in the service network to be processed, and further determining the number interval of the self-service devices in the service network to be processed based on the vacancy rate and the longest waiting time of the self-service devices, so that the number of the self-service devices required to be set by the service network to be processed is determined. The method has the advantages that the use vacancy rate and the longest waiting time of the self-service equipment based on the service network can accurately evaluate the flow of people of the service network and the use condition of the self-service equipment by the user, the number of the determined self-service equipment can not only ensure the use requirement of the user of the service network, but also avoid the waste of resources, and meanwhile, the service handling efficiency of the service network can be improved.

Description

Method, device and equipment for configuring number of self-service equipment of service network point

Technical Field

The present disclosure relates to computer technologies, and in particular, to a method, an apparatus, and a device for configuring the number of self-service devices in a service network.

Background

For some service sites such as: banks, telecom business offices, related government departments and the like increasingly use self-service equipment, and users handle services at the self-service equipment by themselves. For example: when people go to a service network to handle business, the business can be handled through manual service of a counter or through self-service equipment equipped in the service network. Along with the development of science and technology, banking businesses which can be handled by self-service equipment are more and more, the efficiency of handling banking businesses through self-service equipment is higher, and meanwhile, the pressure of counter businesses can be reduced.

The configuration of the number of self-service equipment in the service network is usually determined manually, and the setting of the number of equipment is generally random. If too many self-service devices are placed, some self-service devices may not be used by more or less people, which causes waste of resources, and if too few self-service devices are placed, customers can get behind for a long time, and customer experience is poor.

Disclosure of Invention

An object of the embodiments of the present specification is to provide a method, an apparatus, and a device for configuring the number of self-service devices in a service node, so as to implement accurate configuration of the self-service devices in the service node and avoid waste of resources.

In one aspect, an embodiment of the present specification provides a method for configuring the number of self-service devices at a service node, including:

acquiring equipment use data of self-service equipment in a service network to be processed within a specified time range;

determining the sum of the vacancy rates of the self-service equipment of the service network to be processed and the sum of the longest waiting time according to the equipment use data and the monitoring data of the service network;

determining a self-service equipment quantity interval of the service network point to be processed according to the sum of the vacancy rates, the sum of the longest waiting time, a preset vacancy rate threshold and a preset longest waiting time threshold;

and selecting an integer numerical value from the self-service equipment quantity interval as the quantity of the self-service equipment of the service network to be processed.

Further, the determining the self-service device number interval of the service network to be processed according to the sum of the vacancy rates, the sum of the longest waiting time, and a preset vacancy rate threshold and a longest waiting time threshold includes:

determining the number interval of the self-service equipment of the service network to be processed by adopting the following formula:

wherein M represents the self-service device number interval, d represents the sum of the longest waiting time, k represents the sum of the vacancy rates, n represents the total number of self-service devices of the to-be-processed service site, f1 represents the vacancy rate threshold, and f2 represents the longest waiting time threshold.

Further, the method further comprises:

a plurality of service network points under the service center to be processed are used as the service network points to be processed;

after the self-service equipment quantity interval of the service network point to be processed is determined, selecting a numerical value from the self-service equipment quantity interval as the total quantity of the self-service equipment of a plurality of service network points which belong to the service center to be processed;

and respectively determining the number of self-service equipment of a plurality of service network points under the service center to be processed according to the vacancy rate and the longest waiting time of the self-service equipment of the service network points under the service center to be processed.

Further, the method further comprises:

dividing the service network points to be processed into a first network point set and a second network point set according to the sum of the vacancy rates of all self-service equipment in the service network points to be processed and a preset vacancy rate, or the sum of the longest waiting time and the preset longest waiting time;

respectively determining the number intervals of self-service equipment corresponding to the first network point set and the second network point set;

respectively selecting a numerical value from the self-service equipment quantity intervals respectively corresponding to the first network point set and the second network point set, wherein the numerical value is respectively used as the total quantity of the self-service equipment of each service network point to be processed in the first network point set and the total quantity of the self-service equipment of each service network point to be processed in the second network point set;

and determining the number of the self-service equipment of each service network point to be processed in the first network point set and the second network point set according to the total number of the self-service equipment of each service network point to be processed in the first network point set and the second network point set, the vacancy rate of each service network point to be processed in the first network point set and the second network point set and the longest waiting time.

Further, the determining the number of the self-service devices of each service network point to be processed in the first network point set and the second network point set includes:

if the first network point set and the second network point set are divided based on the vacancy rate, determining the number of self-service equipment of each service network point to be processed in the first network point set and the second network point set by adopting the following formula:

wherein V1 represents the number of self-service devices of a first target to-be-processed service node in the first node set, N1 represents the total number of self-service devices of each to-be-processed service node in the first node set, k1 represents the vacancy rate of the first target to-be-processed service node, kA represents the sum of the vacancy rates of the self-service devices of each to-be-processed service node in the first node set, V2 represents the number of self-service devices of a second target to-be-processed service node in the second node set, N2 represents the total number of the self-service devices of each to-be-processed service node in the second node set, k2 represents the vacancy rate of the second target to-be-processed service node, and kB represents the sum of the vacancy rates of the self-service devices of each to-be-processed service node in the second node set.

if the first network point set and the second network point set are divided based on the longest waiting time, determining the number of self-service equipment of each service network point to be processed in the first network point set and the second network point set by adopting the following formula:

wherein P1 represents the number of self-service devices of a first target to-be-processed service mesh point in the first mesh point set, N1 represents the total number of self-service devices of each to-be-processed service mesh point in the first mesh point set, d1 represents the longest waiting time of the first target to-be-processed service mesh point, dA represents the sum of the longest waiting times of the self-service devices of each to-be-processed service mesh point in the first mesh point set, P2 represents the number of self-service devices of a second target to-be-processed service mesh point in the second mesh point set, N2 represents the total number of the self-service devices of each to-be-processed service mesh point in the second mesh point set, d2 represents the longest waiting time of the second target to-be-processed service mesh point, and dB represents the sum of the longest waiting times of the self-service devices of each to-be-processed service mesh point in the second mesh point set.

Further, the determining a sum of the vacancy rates of the self-service devices in the service network to be processed and a sum of the longest waiting time includes:

acquiring the vacancy rate and the longest waiting time of each self-service device in the service network to be processed in each day within the specified time range according to the device use data and the monitoring data of the service network;

calculating the average value of the vacancy rate and the average value of the longest waiting time of each self-service device in the service network points to be processed in the appointed time range according to the vacancy rate and the longest waiting time of each self-service device in the service network points to be processed in each day in the appointed time range;

and adding the average values of the vacancy rates of the self-service devices to obtain a sum of the vacancy rates of the self-service devices of the service network to be processed, and adding the average values of the longest waiting time of the self-service devices to obtain a sum of the longest waiting time of the self-service devices of the service network to be processed.

In another aspect, the present specification provides a device for configuring the number of self-service devices at a service site, including:

the equipment data acquisition module is used for acquiring the equipment use data of the self-service equipment in the service network to be processed within a specified time range;

the parameter calculation module is used for determining the sum of the vacancy rates of the self-service equipment of the service network to be processed and the sum of the longest waiting time according to the equipment use data and the monitoring data of the service network;

a quantity interval determination module, configured to determine a self-service device quantity interval of the service network point to be processed according to the sum of the vacancy rates, the sum of the longest waiting time, and a preset vacancy rate threshold and a longest waiting time threshold;

and the equipment quantity determining module is used for selecting an integer numerical value from the self-service equipment quantity interval as the self-service equipment quantity of the service network point to be processed.

In another aspect, the present specification provides a device for configuring the number of self-service devices of a service site, including: the system comprises at least one processor and a memory for storing processor executable instructions, wherein the processor executes the instructions to realize the configuration method of the number of self-service equipment of the service network.

In yet another aspect, the present specification provides a computer-readable storage medium, on which computer instructions are stored, and when executed, the instructions implement the above configuration method for the number of self-service devices of a service network.

The configuration method, the configuration device, the processing device, and the storage medium for the number of self-service devices in a service network provided by the present specification determine an idle rate and a longest waiting time of each self-service device based on device usage data of the self-service devices in a service network to be processed, and further determine a self-service device number interval of the service network to be processed based on the idle rate and the longest waiting time of the self-service devices, thereby determining the number of self-service devices to be set by the service network of the device to be processed. The method has the advantages that the use vacancy rate and the longest waiting time of the self-service equipment based on the service network can accurately evaluate the flow of people of the service network and the use condition of the self-service equipment by the user, the number of the determined self-service equipment can not only ensure the use requirement of the user of the service network, but also avoid the waste of resources, and meanwhile, the service handling efficiency of the service network can be improved.

Drawings

In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.

FIG. 1 is a flow chart illustrating a method for configuring the number of kiosks at a service site in one embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a method for configuring a self-service device of a service site in another embodiment of the present disclosure;

FIG. 3 is a block diagram of an embodiment of a configuration apparatus for number of self-service devices at a service site provided in the present specification;

FIG. 4 is a block diagram of a hardware configuration of a configuration server for serving network site kiosk quantities in one embodiment of the present disclosure.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.

For some service network points providing convenience for people, more and more self-service equipment is used for self-service, and users can handle related services by self through the self-service equipment. For example: the network business network can provide self-service network business handling equipment, the fast food hall can provide self-service checkout equipment, and shopping places such as supermarkets and the like can also provide self-service checkout equipment. The self-service equipment replaces partial manual service handling, improves the efficiency of service handling, saves human resources, and can reduce the error rate of service handling.

The configuration method for the number of the self-service devices of the service network points in the embodiment of the description can be applied to a client or a server, and the client can be an electronic device such as a smart phone, a tablet computer, a smart wearable device (smart watch and the like), a smart vehicle-mounted device and the like.

Fig. 1 is a schematic flow chart of a method for configuring the number of self-service devices at a service site in an embodiment of the present description, and as shown in fig. 1, the method for configuring the number of self-service devices at a service site provided in an embodiment of the present description may include:

and 102, acquiring the equipment use data of the self-service equipment in the service network to be processed within a specified time range.

In some embodiments of this specification, a self-service device may be understood as a device that is set at a service network and can be operated by a user to perform business transaction, such as: ATM cash dispenser/deposit machine of bank, self-service ordering machine of restaurant, self-service checkout equipment, business self-service processing machine of telecom business hall, etc. The to-be-processed service network can represent a service network needing to determine self-service equipment, such as: the system can be a bank outlet, a restaurant, a telecommunication business hall, a supermarket, a government department and the like, and the embodiment of the specification is not particularly limited. In a specific implementation process, when the number of self-service devices of the to-be-processed service network point needs to be determined, device usage data of each self-service device in the to-be-processed service network point within a specified time range may be obtained first. Wherein the device usage data may include a start-stop time of use of the self-service device, such as: the start time of each user starting to use the self-service equipment and the end time of the business transaction of the user during the business hours of the service network can be counted.

For example: if the service network to be processed is a bank network 1, the current self-service devices of the bank network 1 are 3, and the service device data of the 3 self-service devices of the bank network 1 in 30 days can be acquired. Such as: the start time of use of 3 self-service devices for each day within 30 days is obtained.

And step 104, determining the sum of the vacancy rates of the self-service equipment of the service network to be processed and the sum of the longest waiting time according to the equipment use data and the monitoring data of the service network.

In a particular implementation, the vacancy rate may represent the proportion of time that the self-service device is not serving a customer during business hours to total business hours of a day, per unit of time, e.g., 1 day. For example: the business time of the bank outlet 1 every day is 10 hours, and according to the obtained device use data of one self-service device a in the bank outlet 1, it is found that the time when the self-service device a does not serve a customer in a certain day, that is, the time when the self-service device a does not use a user is 5 hours, and the vacancy rate of the self-service device a in the day is 5/10-0.5.

The maximum waiting time can be understood as the maximum waiting time of a customer when a self-service device is in a peak service. The method comprises the steps of obtaining monitoring data of the service network point according to monitoring equipment of the service network point, and obtaining time when each user using the self-service equipment enters the service network point to be processed or time when the user using the self-service equipment starts queuing in the user using the self-service equipment and time when the user starts using the self-service equipment based on the monitoring data. According to the acquired time when the user enters the service network to be processed or the time when the user starts to queue and the time when the user starts to use the self-service equipment, the waiting time when all the users use the self-service equipment can be determined, and the maximum value of the waiting time is taken as the longest waiting time of the self-service equipment.

After the vacancy rates and the longest waiting time of the self-service devices in the service network to be processed are sequentially obtained by the method, the vacancy rates and the longest waiting time of the self-service devices can be respectively added to obtain the sum of the vacancy rates and the sum of the longest waiting time of the self-service devices in the service network to be processed.

In some embodiments of the present specification, the sum of the vacancy rates of the self-service devices in the service network to be processed and the sum of the longest waiting time may be determined by the following methods:

In a specific implementation process, the usage data of each self-service device in the to-be-processed service network and the monitoring data of the to-be-processed service network may be, for example: and monitoring data through a video, calculating the vacancy rate and the longest waiting time of each self-service device in the service network to be processed every day, respectively carrying out average value calculation on the vacancy rate and the longest waiting time of each self-service device in 30 days, and determining the average value of the vacancy rate and the average value of the longest waiting time of each self-service device in 30 days. Adding the average values of the vacancy rates of the self-service devices in the service network points to be processed to obtain a sum of the vacancy rates, and adding the longest waiting time of the self-service devices to obtain a sum of the longest waiting time.

The device use data of the service network point to be processed is analyzed and processed, and based on a large amount of historical data, after the average value of the vacancy rates and the average value of the longest waiting time of the self-service devices in the execution time range are calculated, the sum value of the vacancy rates of the self-service devices of the service network point to be processed and the sum value of the longest waiting time are determined. The vacancy rate and the longest waiting time determined based on the historical data of the equipment can accurately reflect the service condition of the self-service equipment of the service network to be processed, and an accurate data basis is provided for the quantity configuration of the subsequent self-service equipment.

And 106, determining a self-service equipment quantity interval of the service network to be processed according to the sum of the vacancy rates, the sum of the longest waiting time, a preset vacancy rate threshold and a preset longest waiting time threshold.

In a specific implementation process, a person in charge of the service network to be processed may preset an vacancy rate threshold and a maximum waiting time threshold according to data such as revenue, cost, customer satisfaction of the self-service device, and the specific values of the vacancy rate threshold and the maximum waiting time threshold are not specifically limited in this embodiment of the present specification. After the sum of the vacancy rates of the self-service devices of the service network points to be processed and the sum of the longest waiting time are obtained, the number interval of the self-service devices of the service network points to be processed can be determined according to the preset threshold of the vacancy rates, the preset threshold of the longest waiting time, and the sum of the obtained vacancy rates of the self-service devices and the sum of the longest waiting time. The self-service equipment number interval can represent the value range of the number of the self-service equipment of the service network to be processed. Such as: the setting rules of the self-service equipment quantity intervals can be preset, and the setting rules can include that when the numerical relationship between the vacancy rate threshold value and the sum of the vacancy rates of the self-service equipment and the numerical relationship between the longest waiting time threshold value and the sum of the longest waiting times of the self-service equipment meet different conditions, different self-service equipment quantity intervals are correspondingly arranged. Alternatively, a machine learning model may be constructed by training historical sample data, and then the constructed machine learning model is utilized to determine the self-service equipment quantity interval of the service network point to be processed, which is not specifically limited in the embodiments of the present specification.

In some embodiments of the present description, the following formula may be used to determine the self-service device number interval of the service network to be processed:

The minimum value a and the maximum value b of the self-service equipment number interval can be calculated by using the formula (1), and the self-service equipment number interval [ a, b ] of the service network point to be processed is further determined.

And 108, selecting an integer numerical value from the self-service equipment quantity interval as the quantity of the self-service equipment of the service network to be processed.

In a specific implementation process, after the self-service equipment interval of the service network point to be processed is determined, an integer numerical value can be arbitrarily selected from the interval to serve as the number of the self-service equipment of the service network point to be processed. For example: if it is determined based on the method of the above embodiment that the self-service device interval of the to-be-processed service network is [8,10], any one of the values 8, 9, and 10 may be used as the number of the self-service devices of the to-be-processed service network. The self-service equipment of the service network point to be processed can be adjusted according to the determined number of the self-service equipment, and certainly, when the self-service equipment is actually used, if the number of the self-service equipment existing in the service network point to be processed is located in the determined self-service equipment interval, the self-service equipment arriving at the service network point to be processed can not be adjusted. If the number of the self-service devices in the service network to be processed is not in the determined self-service device interval, the number of the self-service devices in the service network to be processed can be increased or decreased according to the number of the existing self-service devices and the self-service device number interval.

In the actual use process, when a new service network needs to set self-service equipment, the number of the self-service equipment of the new service network can be determined according to the equipment use data of the self-service equipment of the service network with similar distance or environment, surrounding user number and the like.

The method for configuring the number of self-service devices in a service network provided in the embodiment of the present specification determines an idle rate and a longest waiting time of each self-service device based on device usage data of the self-service devices in a service network to be processed, and further determines a self-service device number interval of the service network to be processed based on the idle rate and the longest waiting time of the self-service devices, thereby determining the number of self-service devices to be set by the service network to be processed. The method has the advantages that the use vacancy rate and the longest waiting time of the self-service equipment based on the service network can accurately evaluate the flow of people of the service network and the use condition of the self-service equipment by the user, the number of the determined self-service equipment can not only ensure the use requirement of the user of the service network, but also avoid the waste of resources, and meanwhile, the service handling efficiency of the service network can be improved.

On the basis of the foregoing embodiments, in some embodiments of the present specification, the method may further include:

In a specific implementation process, some service nodes have a centralized management center, such as: in a banking system, a branch may have a plurality of banking outlets, in which case, a plurality of service outlets subordinate to a service center to be processed may be referred to as a service outlet to be processed as a whole, for example: a plurality of banking outlets under one branch may be referred to as a pending service outlet as a whole. And determining a total self-service equipment quantity interval for a plurality of service network points in the service center to be processed according to the equipment use data of the plurality of service network points, namely all self-service equipment in the service network points to be processed, which belong to the service center to be processed. Such as: a service center to be processed belongs to 3 service network points, can obtain the equipment use data of the self-service equipment of the 3 service network points, and the monitoring equipment monitoring data of the 3 service network points, determines the sum of the vacancy rates of the self-service equipment of the 3 service network points and the sum of the longest waiting time, and determines the self-service equipment quantity interval corresponding to the 3 service network points by adopting the formula (1).

After the self-service equipment number interval of the plurality of service network points belonging to the service center to be processed is determined, a numerical value can be selected from the interval to serve as the total number of the self-service equipment of the plurality of service network points. And distributing the determined total number of the self-service equipment based on the vacancy rate, the longest waiting time and the like of the self-service equipment of each service network node subordinate to the service center to be processed, and determining the number of the self-service equipment of a plurality of service network nodes subordinate to the service center to be processed. For example: a certain branch of a banking system is subordinate to 3 banking outlets, the 3 banking outlets are used as a whole to determine that the number interval of self-service equipment corresponding to the 3 banking outlets is [8, 11], and 10 self-service equipment is selected from the interval to serve as the total number of the self-service equipment of the 3 banking outlets. And then distributing 10 self-service devices to the 3 banking outlets according to the vacancy rates and/or the longest waiting time of the self-service devices of the 3 banking outlets. Such as: through statistical analysis of the device use data of the self-service devices of the 3 banking outlets, the sum of the vacancy rates of the self-service devices of the 2 banking outlets a and b and the sum of the longest waiting time are found to be close, and the sum of the vacancy rates of the other banking outlet c is smaller than the sum of the vacancy rates of the 2 banking outlets, so that 3 self-service devices can be distributed to the banking outlets a and b, and 4 self-service devices can be distributed to the banking outlet c.

The total number of the self-service devices belonging to the plurality of service network points under the service center to be processed is determined, when the total number of the self-service devices is distributed, the number of the original self-service devices of each service network point can be considered, and if the difference between the newly distributed number and the original number is not large, the number of the original self-service devices of the service network points can be selected to be kept.

In the embodiment of the specification, a plurality of service network points belonging to one service center are regarded as a whole, so that data sources are increased, the number of the determined self-service equipment is more consistent with the service condition of the self-service equipment in the service network points, and the accuracy of the number configuration of the self-service equipment is improved. Meanwhile, the service types, the service efficiencies and the like of the same service center are possibly similar, the service conditions of the self-service equipment are possibly related, the service conditions are considered as a whole, the total number of the determined self-service equipment is distributed, the service network points do not need to be configured one by one, and the data processing efficiency is improved.

In a specific implementation process, the service nodes may be classified according to the vacancy rate or the longest time of the self-service devices of each service node, for example: a set of service mesh points whose sum of the vacancy rates of the self-service device is greater than a preset vacancy rate may be used as a first mesh point set, and a set of service mesh points whose sum of the vacancy rates of the self-service device is less than or equal to the preset vacancy rate may be used as a second mesh point set. Or a set of service nodes of which the sum of the longest waiting time of the self-service equipment is greater than the preset longest waiting time may be used as a first node set, and a set of service nodes of which the sum of the longest waiting time of the self-service equipment is less than or equal to the preset longest waiting time may be used as a second node set. The specific values of the preset vacancy rate and the preset maximum waiting time may be set according to actual use conditions, and embodiments of the present specification are not specifically limited.

The service network points in the two sets are processed separately, each service network point in the first network point set is regarded as a whole, the equipment data of each self-service equipment in each service network point in the first network point set is obtained respectively, the sum of the vacancy rates of the self-service equipment of each service network point in the first network point set and the sum of the longest waiting time are further determined, and then the self-service equipment number interval of each service network point in the first network point set is determined. The description of the above embodiments may be referred to for a specific determination method of the number interval of the self-service devices in the first network point set, and details are not repeated here. And randomly selecting a numerical value from the self-service equipment quantity interval of the first network point set as the total quantity of the self-service equipment of each service network point in the first network point set, and distributing the determined total quantity of the self-service equipment according to the vacancy rate and the longest waiting time of the self-service equipment of each service network point in the first network point set, wherein the distribution mode can refer to the distribution mode of the self-service equipment of a plurality of service network points belonging to the service center to be processed. And determining the number interval of the self-service equipment of the second network point set and distributing the self-service equipment of each service network point in the second network point set in the same way, which is not described herein again.

In the implementation of the description, the service network nodes are classified based on the vacancy rate or the longest waiting time of the self-service devices of the service network nodes, and the number of the self-service devices in the classified service network node set is configured. The configuration of self-service equipment is not required to be carried out on each service network point one by one, and the data processing efficiency is improved. Meanwhile, the service network points with similar service conditions of the self-service equipment are used as a set, the data characteristic quantity of the service network points of the same type is increased, and the quantity configuration accuracy of the self-service equipment can be further improved.

On the basis of the foregoing embodiments, in some embodiments of the present specification, the determining the number of self-service devices of each to-be-processed service network point in the first network point set and the second network point set includes:

When the vacancy rates are used for classifying the service network points, after the total number N1 of the self-service devices of each service network point in the first network point set and the total number N2 of the self-service devices of each service network point in the first network point set are determined, the number of the self-service devices required by each service network point can be calculated by adopting the formula (2) according to the vacancy rates of the self-service devices in the first network point set and the second network point set and the sum of the total vacancy rates of the self-service devices of the service network points in the first network point set and the second network point set.

Similarly, when the longest waiting time is used for classifying each service network point, the following formulas can be used to determine the number of self-service devices of each service network point to be processed in the first network point set and the second network point set:

When the longest waiting time is used for classifying the service network points, after the total number N1 of the self-service devices of each service network point in the first network point set and the total number N2 of the self-service devices of each service network point in the first network point set are determined, the number of the self-service devices required by each service network point can be calculated by adopting the formula (3) according to the longest waiting time of each self-service device in the first network point set and the second network point set and the sum of the total longest waiting times of the self-service devices of each service network point in the first network point set and the second network point set.

It should be noted that, when the formula (2) or the formula (3) is used to calculate the number of the self-service devices of each service network, the calculation result needs to be rounded, that is, the calculated number of the self-service devices is a positive integer.

In the embodiment of the description, the service network points can be classified according to the vacancy rate or the longest waiting time of the self-service equipment, and after classification, the service network points in a network point set are used as a whole day to determine the total number of the self-service equipment of the service network points in the set. Based on the vacancy rate or the longest waiting time, self-service equipment is distributed to each service network point in the set, an accurate distribution mode is provided, and the quantity of the self-service equipment is rapidly configured.

Fig. 2 is a schematic diagram of a configuration method of a self-service device of a service node in another embodiment of the present specification, and the following specifically describes the configuration method of the self-service device of the service node in the embodiment of the present specification by taking the application to a banking node as an example with reference to fig. 2:

1. the vacancy rate of each self-service device can be estimated based on the use data of the self-service device of the bank outlet to be processed by the customer, namely the proportion of the time which does not serve the customer in the business hours of one day to the business hours of one day.

2. The longest customer waiting time at peak service for each self-service device is estimated. I.e., the longest waiting time of the customer at the end of the line, which may be the time that the customer has elapsed from entering the site to the customer beginning to transact business, may be determined based on the monitoring equipment of the banking site.

3. Assuming that the bank outlet has n self-service devices at present, the vacancy rate and the longest waiting time corresponding to the n self-service devices are respectively as follows: k1, … …, kn, d1, … …, dn. Sum of vacancy rates: k — 1+ ·+ kn, the sum of the longest latencies: d1+. + dn.

4. The upper limit value f1 of the vacancy rate (i.e., the threshold value of the vacancy rate described in the above embodiment) and the maximum value f2 of the waiting time (i.e., the threshold value of the maximum waiting time described in the above embodiment) may be set by the bank staff according to the profit, cost, and customer satisfaction of the self-service terminal.

5. The number of self-service devices to be arranged by the bank outlet can be as follows:

5.1, the number of the self-service devices at the bank outlet is any number in the self-service device number interval [ a, b ], wherein a is min (d/f2, (n-k)/(1-f1)), and b is max (d/f2, (n-k)/(1-f 1)).

5.2, regarding a plurality of banking outlets under one branch, the plurality of banking outlets can be regarded as a whole to determine the total number of self-service devices of the whole, and then the number of the self-service devices of each outlet is determined based on the vacancy rate and the longest waiting time of each banking outlet.

5.3, the banking outlets can be divided into two first outlet sets A and a second outlet set B based on any one of the indicators (vacancy rate or maximum waiting time). Based on the indicator, a total number of two aggregate self-service devices is then determined. And then proportionally distributing the number of the self-service terminals to the two arbitrary sets based on the index value of each network point.

Such as: based on the vacancy rate, determining the total number of self-service devices of the first website set A and the second website set B, such as: a was allocated N1, B was allocated N2. Then banking site a1 in the first site set a allocates the number of terminals based on its own vacancy rate k 1: n1 × k1/kA, where kA is the sum of the vacancy rates of all the dots in the first set of dots a.

The vacancy rate and the maximum wait time obtained in the embodiments of the present specification are estimated values based on a large number of historical sample values. For example, 30 days of data may be taken, each day corresponding to a null rate and a maximum waiting time, and an estimated value may be obtained by using 30 sample values.

The embodiment of the specification can estimate the number of the self-service equipment placed in the service network based on the use data of the self-service equipment of each service network, so that the resources of the network can be effectively configured, the queuing time of customers is reduced, and the waste of resources is avoided.

In the present specification, each embodiment of the method is described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The relevant points can be obtained by referring to the partial description of the method embodiment.

Based on the configuration method for the number of self-service devices of the service network, one or more embodiments of the present specification further provide a configuration device for the number of self-service devices of the service network. The apparatus may include systems (including distributed systems), software (applications), modules, components, servers, clients, etc. that use the methods described in the embodiments of the present specification in conjunction with any necessary apparatus to implement the hardware. Based on the same innovative conception, embodiments of the present specification provide an apparatus as described in the following embodiments. Since the implementation scheme of the apparatus for solving the problem is similar to that of the method, the specific apparatus implementation in the embodiment of the present specification may refer to the implementation of the foregoing method, and repeated details are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Specifically, fig. 3 is a schematic diagram of a module structure of an embodiment of a configuration apparatus for number of self-service devices at a service site provided in this specification, and as shown in fig. 3, the configuration apparatus for number of self-service devices at a service site provided in this specification may include: an equipment data obtaining module 31, a parameter calculating module 32, a number interval determining module 33, and an equipment number determining module 34, wherein:

the device data acquisition module 31 is configured to acquire device usage data of self-service devices in the service network to be processed within a specified time range;

the parameter calculation module 32 is configured to determine a sum of vacancy rates of self-service devices of the service network to be processed and a sum of the longest waiting time according to the device usage data and the monitoring data of the service network;

a quantity interval determination module 33, configured to determine a self-service device quantity interval of the service network point to be processed according to the sum of the vacancy rates, the sum of the longest waiting time, and a preset vacancy rate threshold and a longest waiting time threshold;

and the equipment quantity determining module 34 is configured to select an integer value from the self-service equipment quantity interval as the self-service equipment quantity of the service network point to be processed.

The configuration device for the number of self-service devices in a service network provided in the embodiment of the present specification determines an idle rate and a longest waiting time of each self-service device based on device usage data of the self-service devices in a service network to be processed, and further determines a self-service device number interval of the service network to be processed based on the idle rate and the longest waiting time of the self-service devices, thereby determining the number of self-service devices to be set by the service network to be processed. The method has the advantages that the use vacancy rate and the longest waiting time of the self-service equipment based on the service network can accurately evaluate the flow of people of the service network and the use condition of the self-service equipment by the user, the number of the determined self-service equipment can not only ensure the use requirement of the user of the service network, but also avoid the waste of resources, and meanwhile, the service handling efficiency of the service network can be improved.

It should be noted that the above-described apparatus may also include other embodiments according to the description of the method embodiment. The specific implementation manner may refer to the description of the above corresponding method embodiment, and is not described in detail herein.

An embodiment of the present specification further provides a device for configuring the number of self-service devices at a service node, including: at least one processor and a memory for storing processor-executable instructions, where the processor executes the instructions to implement the configuration method for the number of self-service devices at the service network site in the above embodiments, such as:

It should be noted that the above-mentioned processing device may also include other implementations according to the description of the method embodiment. The specific implementation manner may refer to the description of the above corresponding method embodiment, and is not described in detail herein.

The configuration device or the processing device for the number of the self-service devices of the service network provided by the specification can also be applied to various data analysis and processing systems. The system or the device or the processing equipment may include any one of the configuration devices for the number of self-service equipment of the service network. The system or apparatus or processing device may be a single server, or may include a server cluster, a system (including a distributed system), software (applications), an actual operation device, a logic gate device, a quantum computer, etc. using one or more of the methods or one or more of the embodiments of the present disclosure, and a terminal device incorporating necessary hardware for implementation. The system for checking for discrepancies may comprise at least one processor and a memory storing computer-executable instructions that, when executed by the processor, implement the steps of the method of any one or more of the embodiments described above.

The method embodiments provided by the embodiments of the present specification can be executed in a mobile terminal, a computer terminal, a server or a similar computing device. Taking an example of the configuration server running on a server, fig. 4 is a hardware structure block diagram of a configuration server of the number of self-service devices of a service network point in an embodiment of the present specification, where the server may be a configuration apparatus or system of the number of self-service devices of the service network point in the foregoing embodiment. As shown in fig. 4, the server 10 may include one or more (only one shown) processors 100 (the processors 100 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 200 for storing data, and a transmission module 300 for communication functions. It will be understood by those skilled in the art that the structure shown in fig. 4 is merely an illustration and is not intended to limit the structure of the electronic device. For example, the server 10 may also include more or fewer components than shown in FIG. 4, and may also include other processing hardware, such as a database or multi-level cache, a GPU, or have a different configuration than shown in FIG. 4, for example.

The memory 200 may be used to store software programs and modules of application software, such as program instructions/modules corresponding to the configuration method of the number of self-service devices of a service node in the embodiment of the present specification, and the processor 100 executes various functional applications and resource data updates by running the software programs and modules stored in the memory 200. Memory 200 may include high speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 200 may further include memory located remotely from processor 100, which may be connected to a computer terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission module 300 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal. In one example, the transmission module 300 includes a Network adapter (NIC) that can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission module 300 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The method or apparatus provided by the present specification and described in the foregoing embodiments may implement service logic through a computer program and record the service logic on a storage medium, where the storage medium may be read and executed by a computer, so as to implement the effect of the solution described in the embodiments of the present specification.

The embodiment of the present application further provides a computer storage medium of a method for configuring a number of self-service devices at a service node, where the computer storage medium stores computer program instructions, and when the computer program instructions are executed, the computer program instructions may implement:

The storage medium may include a physical device for storing information, and typically, the information is digitized and then stored using an electrical, magnetic, or optical media. The storage medium may include: devices that store information using electrical energy, such as various types of memory, e.g., RAM, ROM, etc.; devices that store information using magnetic energy, such as hard disks, floppy disks, tapes, core memories, bubble memories, and usb disks; devices that store information optically, such as CDs or DVDs. Of course, there are other ways of storing media that can be read, such as quantum memory, graphene memory, and so forth.

The configuration method or apparatus for the number of self-service devices at a service node provided in the embodiment of the present specification may be implemented by a processor executing corresponding program instructions in a computer, for example, implemented by using a c + + language of a windows operating system at a PC end, implemented by a linux system, or implemented by using android and iOS system programming languages at an intelligent terminal, implemented by using processing logic based on a quantum computer, and the like.

It should be noted that descriptions of the apparatus, the computer storage medium, and the system described above according to the related method embodiments may also include other embodiments, and specific implementations may refer to descriptions of corresponding method embodiments, which are not described in detail herein.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to only the partial description of the method embodiment.

The embodiments of the present description are not limited to what must be consistent with industry communications standards, standard computer resource data updating and data storage rules, or what is described in one or more embodiments of the present description. Certain industry standards, or implementations modified slightly from those described using custom modes or examples, may also achieve the same, equivalent, or similar, or other, contemplated implementations of the above-described examples. The embodiments using the modified or transformed data acquisition, storage, judgment, processing and the like can still fall within the scope of the alternative embodiments of the embodiments in this specification.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

Although one or more embodiments of the present description provide method operational steps as described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive approaches. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When the device or the end product in practice executes, it can execute sequentially or in parallel according to the method shown in the embodiment or the figures (for example, in the environment of parallel processors or multi-thread processing, even in the environment of distributed resource data update). The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. The terms first, second, etc. are used to denote names, but not any particular order.

For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, when implementing one or more of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, etc. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable resource data updating apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable resource data updating apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable resource data update apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable resource data update apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage, graphene storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

As will be appreciated by one skilled in the art, one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the present specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, and the relevant points can be referred to only part of the description of the method embodiments. In the description of the specification, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

The above description is merely exemplary of one or more embodiments of the present disclosure and is not intended to limit the scope of one or more embodiments of the present disclosure. Various modifications and alterations to one or more embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present specification should be included in the scope of the claims.

Claims

1. A method for configuring the number of self-service devices of a service network point is characterized by comprising the following steps:

2. The method of claim 1, wherein the determining the interval of the number of self-service devices of the service network to be processed according to the sum of the vacancy rates, the sum of the maximum waiting times, and preset vacancy rate thresholds and maximum waiting time thresholds comprises:

3. The method of claim 1, wherein the method further comprises:

4. The method of claim 1, wherein the method further comprises:

5. The method of claim 4, wherein the determining the number of self-service devices of each of the first network point set and the second network point set to be processed comprises:

6. The method of claim 4, wherein the determining the number of self-service devices of each of the first network point set and the second network point set to be processed comprises:

7. The method of any one of claims 1 to 6, wherein the determining a sum of the vacancy rates of the self-service devices and a sum of the maximum wait time in the to-be-processed service network comprises:

8. A device for configuring the number of self-service devices of a service network, the device comprising:

9. A configuration device for the number of self-service devices of a service network point is characterized by comprising: at least one processor and a memory for storing processor-executable instructions, the processor implementing the method of any one of claims 1-7 when executing the instructions.

10. A computer-readable storage medium having stored thereon computer instructions which, when executed, implement the steps of the method of any one of claims 1 to 7.