CN117436958A - Rear-end payment processing method and device applied to unmanned retail device - Google Patents

Rear-end payment processing method and device applied to unmanned retail device Download PDF

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CN117436958A
CN117436958A CN202311434276.6A CN202311434276A CN117436958A CN 117436958 A CN117436958 A CN 117436958A CN 202311434276 A CN202311434276 A CN 202311434276A CN 117436958 A CN117436958 A CN 117436958A
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unmanned retail
inventory
retail device
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payment processing
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陈晶
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Neolix Technologies Co Ltd
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Neolix Technologies Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0283—Price estimation or determination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]

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Abstract

A back-end payment processing method and device applied to an unmanned retail device are disclosed. The method comprises the following steps: collecting a plurality of parameter values corresponding to a plurality of preset parameters; determining the checking times according to the plurality of parameter values; performing inventory operations corresponding to the inventory times on the unmanned retail device, and obtaining the number of commodities currently stored in the unmanned retail device according to the inventory operations, and recording the number as a first number; obtaining the number of goods in stock before the unmanned retail device, and recording the number as a second number; the payment amount is calculated based on the difference between the second amount and the first amount. The method effectively reduces the waiting time of the user and optimizes the purchasing efficiency through dynamic settlement.

Description

Rear-end payment processing method and device applied to unmanned retail device
Technical Field
The present disclosure relates to the field of unmanned retail devices, and more particularly, to a method and apparatus for processing back-end payment for an unmanned retail device.
Background
With advances in artificial intelligence technology and development of autopilot, unmanned retail vehicles have been in front of commercial use overnight. An unmanned retail vehicle refers to an unmanned vehicle specifically designed for a retail environment. Such retail vehicles collect environmental data via sensors (e.g., cameras, lidar, infrared radar, etc.) and walk in conjunction with unmanned technology in an artificial intelligence mode to sell the product. By way of example, the unmanned retail vehicle is an unmanned retail vehicle that sells ice cream.
Typically, unmanned retail vehicles employ front-end payment, i.e., customers pay first and then pick up products. However, the front-end payment settlement mode is efficient and supports simultaneous purchase of multiple people, but is very humanized, so that the situation that the user pays more than one person is very easy to cause, on one hand, merchant goods loss is caused, on the other hand, the situation that the door is opened without goods due to the fact that inventory cannot be checked accurately is damaged, the use experience of subsequent users is damaged, and in addition, the user can change the types and the quantity of goods selected in advance after opening a container. It is therefore necessary to provide a back-end payment processing scheme for unmanned retail vehicles.
Disclosure of Invention
In view of this, the embodiments of the present application provide a back-end payment processing method and device applied to an unmanned retail device.
According to a first aspect of the present application, there is provided a back-end payment processing method applied to an unmanned retail device, the back-end payment processing method being performed after a user turns on and off the unmanned retail device, and comprising the steps of:
collecting a plurality of parameter values corresponding to a plurality of preset parameters;
determining the checking times according to the parameter values;
performing inventory operations corresponding to the inventory times on the unmanned retail device, and obtaining the number of commodities currently stored in the unmanned retail device according to the inventory operations, and recording the number as a first number;
obtaining the number of items previously stocked by the unmanned retail device, and recording the number as a second number;
and calculating a payment amount according to the difference value between the second quantity and the first quantity.
In some embodiments, the determining the number of inventory counts from the plurality of parameter values includes:
calculating a weighted score from the plurality of parameter values;
and comparing the weighting with a pre-established corresponding relation between the weighting score and the counting times to determine the counting times.
In some embodiments, the plurality of parameters is N parameters including detecting whether a door of the unmanned retail device is closed and calculating the weighted score using arithmetic equation (1):
weighting component= (parameter value of parameter 1 + parameter value of parameter 2 + parameter value of parameter 3 + parameter value of parameter … … + parameter N-1) R/N, R equals 0 if the cabinet door is open, R equals 1 if the cabinet door is closed, the parameter value of each parameter is selected from 0 and 1, N is a positive integer greater than 2.
In some embodiments, the plurality of parameters further includes one or more of the following: the cabinet door opening quantity, commodity price, residual inventory, idle busy hours, site environment, user behavior credibility, historical order and commodity taking time.
In some embodiments, the determining the number of inventory counts from the plurality of parameter values includes:
calculating a weighted score from the plurality of parameter values;
comparing the weighting with a pre-established corresponding relation between the weighting score and the inventory time to determine corresponding settlement time;
and comparing the corresponding settlement time with the preset average counting time to obtain the counting times.
In some embodiments, the unmanned retail device performs inventory periodically before the user turns on the unmanned retail device and records the number of items in inventory by the unmanned retail device.
In some embodiments, the unmanned retail device records the number of items in inventory by the unmanned retail device to a cloud server.
According to a second aspect of the present application there is provided a back-end payment processing apparatus for use in an unmanned retail device, comprising:
the counting frequency determining module is used for collecting a plurality of parameter values corresponding to a plurality of preset parameters and determining the counting frequency according to the plurality of parameter values;
the taking-out quantity calculating module is used for executing counting operation corresponding to the counting times on the unmanned retail device, obtaining the quantity of the commodities currently stored in the unmanned retail device according to the counting operation result, marking the quantity as a first quantity, obtaining the quantity of the commodities previously stored in the unmanned retail device, marking the quantity as a second quantity, and subtracting the first quantity from the second quantity to obtain the quantity of the taken-out commodities;
and the payment amount calculation module is used for calculating the payment amount according to the quantity of the fetched commodities.
According to a third aspect of the present application, there is provided a computing device comprising a memory and a processor, the memory further storing computer instructions executable by the processor, the computer instructions, when executed, implementing the back-end payment processing method of any of the above.
According to a fourth aspect of the present application, there is provided a computer readable medium storing computer instructions executable by an electronic device, the computer instructions, when executed, implementing a back-end payment processing method of any of the above.
The back-end payment processing method and device applied to the unmanned retail device (including the unmanned retail vehicle) have the following advantages: firstly, for a user, only the code scanning and door opening are needed, the objects are selected, the door closing and automatic settlement are realized, the worry that the goods are not obtained after payment is avoided, the service of sharing before payment is experienced, and for a merchant, the commodity inventory condition can be mastered in real time, the theft loss is prevented, and the error and the workload of manual inventory are reduced; secondly, because the purchase behaviors of the users are greatly different, the purchase efficiency can be optimized through dynamic settlement, and the overall shopping experience of the users is improved.
Drawings
The above and other objects, features and advantages of the present application will become more apparent by describing embodiments thereof with reference to the following drawings in which:
FIG. 1 is a schematic illustration of an unmanned retail vehicle provided in an embodiment of the present application;
FIG. 2 is an interactive schematic diagram of an unmanned retail vehicle system provided in accordance with an embodiment of the present application;
FIG. 3 is a flow chart of a back-end payment processing method for use with an unmanned retail device according to an embodiment of the present application;
FIGS. 4A-4B are flowcharts of two particular embodiments of the step of FIG. 3 of determining the number of inventory counts based on a plurality of parameter values;
fig. 5 is a functional block diagram of a back-end payment processing apparatus for use in an unmanned retail device according to an embodiment of the present application.
Detailed Description
The present application will be described in more detail below with reference to the accompanying drawings. Like elements are denoted by like reference numerals throughout the various figures. For clarity, the various features of the drawings are not drawn to scale. Furthermore, some well-known portions may not be shown.
Related terms and special words.
Radio frequency identification (Radio Frequency Identification, RFID) is one of automatic identification technologies, and is used for non-contact bidirectional data communication in a radio frequency mode, and a recording medium (an electronic tag or a radio frequency card) is read and written in a radio frequency mode, so that the purposes of identification target and data exchange are achieved.
Fig. 1 is a schematic diagram of an unmanned retail vehicle provided in an embodiment of the present application. As shown in the figure, the unmanned retail vehicle 100 includes a container 101, a radio frequency module 102, an antenna 103, and an in-vehicle terminal 104.
The storage space of the container 101 is divided into one or more containers 1011. Each pod 1011 has independently opening and closing doors and each pod 1011 typically stores only one type of commodity or each pod 1011 stores the same price of commodity. Each of the outer packages of the articles is attached with a radio frequency tag that can be identified by RFID technology, the labeled articles being represented by article 105 and tag 11.
The antennas 103 are disposed inside the container 101 and one antenna can be disposed inside each container 1011, i.e., the antennas are disposed one-to-one with the container, such as the antennas 103 disposed on the interior side walls or top wall of the container 1011.
The radio frequency module 102 is coupled to the vehicle terminal 104, and is configured to send inventory instructions to each antenna 103, and receive information recorded by radio frequency tags of respective goods in a container where the antenna is located from each antenna 103. In some embodiments, the antenna 103 calculates the number of goods in the container where the antenna is located according to the information recorded by the radio frequency tag of the received goods, in other embodiments, the antenna 103 feeds back the information recorded by the radio frequency tag of the received goods to the radio frequency module 102, and the radio frequency module 102 calculates the number of goods in the container where each antenna is located.
The in-vehicle terminal 104 includes a processor and a memory, the memory stores a vehicle-end application 1041 existing in a software program, and the vehicle-end application 1041 implements the following operations when executed by the processor: receiving a user instruction, and transmitting the instruction to corresponding parts of the unmanned vehicle to realize opening of a cabinet door of the container 1011 when the user instruction instructs to drive the container 1011 to open, so that a user can take out goods from the container 1011 and close the container 1011, wherein the user instruction can instruct to simultaneously open a plurality of containers 1011, so that the cabinet door of the containers 1011 is simultaneously opened, and the user can respectively take out goods from the containers 1011; and then the vehicle end application obtains inventory results of the commodity quantity in the container 1011 before the cabinet door of the container 1011 is opened and after the cabinet door of the container 1011 is closed through the radio frequency module, obtains the taken-out quantity of the commodity according to the inventory results, reports the taken-out quantity to the cloud program, generates payment amount and a payment bill through the cloud program, and provides the payment amount and the payment bill to a user so that the user can pay the bill according to the payment bill. In some cases, before reporting the number of removed items to the cloud program, it is determined whether the number of removed items is 0, and if so, the number of removed items does not need to be reported to the cloud program.
Fig. 2 is an interaction diagram of an unmanned retail vehicle system according to an embodiment of the present application, the interaction diagram involving a user and the radio frequency module 102, the vehicle end application 1041, the unmanned retail vehicle 100, and the cloud program 106 in fig. 1.
As shown in the figure, the user performs an operation on the graphical interface provided by the vehicle-side application 1041 (i.e., S11). The end-of-vehicle application 1041 generates instructions in this regard to other components of the unmanned retail vehicle 100 to actuate the opening of the doors of the corresponding cargo box of the unmanned retail vehicle 100 (i.e., S12). The doors of the corresponding cargo box of the unmanned retail vehicle 100 are then opened, at which point the end-of-vehicle application 1041 records the status of the corresponding cargo box as the doors open. Then, after the user takes out the goods from the opened cabinet door (i.e. S14), the cabinet door of the container is closed (i.e. S15), and at this time, the vehicle end application 1041 records the state of the corresponding container as the cabinet door is closed. The vehicle-side application 1041 then issues a point-of-disk instruction (i.e. S16). After the radio frequency module 102 receives the counting instruction, the radio frequency module 102, the antenna 103 and the antenna 11 interact with each other through the RFID signals, so as to complete the counting and obtain the counting result (i.e. S17). The vehicle end application 1041 obtains the number of goods after the user takes out the goods in the opened container according to the checking result, then obtains the number of goods before the user takes out the goods in the container, compares and calculates (S18) according to the two numbers of goods, obtains the number of goods taken out by the user in the container, and reports the number of goods taken out to the cloud program 106 (S19), meanwhile, the vehicle end application 1041 can restore the purchasing capability of the container, in other words, after the container is opened, the system can lock the container, the container is selected from the interface at this time, and after the container is closed, the system restores the container to normal, and the user can purchase the goods therein. The cloud program 106 generates a bill for payment according to the amount of the commodity taken out (S21), and provides the bill for the user, and the user completes the payment operation (S22).
In some embodiments, the radio frequency module 102 periodically sends an inventory command to an antenna in the container when the door of the container is closed, so as to obtain inventory results of the number of goods in each container, and the vehicle-mounted terminal 1041 periodically sends the inventory results to the cloud program, the cloud program stores the inventory results, when the vehicle-mounted terminal 1041 performs the comparison calculation in step S18, the vehicle-mounted terminal draws the latest inventory results of the number of goods before the user takes the goods out of the corresponding container from the cloud program to perform the comparison calculation, in other embodiments, the radio frequency module 102 obtains the inventory results of the number of goods in each container, although the vehicle-mounted terminal 1041 periodically sends the inventory results to the cloud program, the vehicle-mounted terminal 1041 also caches a part of the latest inventory results, compares the cached inventory results with the inventory results drawn from the cloud program, so as to determine whether the abnormality exists, and if the abnormality exists, performs the comparison calculation. In order to reduce errors, after each user completes purchase, the cloud program 106 performs a real-time inventory verification, the radio frequency module 102 performs real-time inventory and reports inventory results, then compares the real-time inventory results with the historical inventory results of the cloud, if there is an abnormality in data, records the last order as an abnormal order, and gives the abnormal order to an operator for processing, and at this time, the inventory results stored in the cloud can be corrected to inventory results reported in real time through the radio frequency module.
In some embodiments, multiple inventory is performed first, then multiple inventory results are integrated according to a preset strategy to obtain a final inventory result, and only the final inventory result is recorded. For example. Under the condition that the cabinet door of the container A is closed, the radio frequency module 102 performs three counting on the container A to obtain counting results of the commodity numbers 101,102 and 103 respectively, and records the counting result as the commodity number 103 according to a strategy of selecting the counting result with the largest numerical value as the final counting result. For another example, when the container B is checked three times to obtain the check results of the commodity numbers 101,102 and 102, respectively, the check result similar to the adjacent check result is used as the final check result, and the check result in the previous example is recorded as the commodity number 102.
In some embodiments, the information recorded by the radio frequency tag is set according to the following rules: the number N is a total number, the first M numbers represent the number of the goods, the last (N-M) numbers represent the serial numbers, the serial numbers increase from an initial value, the initial value is 1, and the information recorded by each tag is unique. Examples: 100000000000000000000001, the first digit is the container identifier and the next 23 digits are the commodity number. And when the cloud program is reported to the disk point result, the disk point result is carried out in a format of time stamp, vehicle identification, container identification and commodity number. The cloud program can store the inventory results of all unmanned retail vehicles for a plurality of continuous days and generate statistical data so that operators can conduct fault investigation by using the statistical data.
With the gradual investment of unmanned retail vehicles into commercial operations, the unmanned retail vehicles based on back-end payment have the following problems: when settling accounts in the current retail activities, multiple counting is often required to obtain accurate counting results in order to ensure accuracy, however, the time for performing multiple counting clearly increases the waiting time of users, but if only one counting is performed, the probability of errors is relatively high.
Therefore, the application provides a back-end payment processing method applied to an unmanned retail device (including an unmanned retail vehicle), wherein the method adopts a flexible settlement mode for back-end payment according to the current actual situation, more specifically, the checking times are determined firstly according to the current actual situation, then the commodity quantity of the current inventory of the unmanned retail device is determined according to the checking result of the checking operation corresponding to the checking times, and the payment amount is calculated according to the commodity quantity.
Fig. 3 is a flow chart of a back-end payment processing method for use with an unmanned retail device provided herein.
In step S311, a plurality of parameter values corresponding to a plurality of preset parameters are acquired.
In step S312, the number of inventory times is determined based on the plurality of parameter values.
In step S313, an inventory operation corresponding to the number of inventory is performed on the unmanned retail device, and the number of commodities currently stocked by the unmanned retail device is obtained according to the result of the inventory operation and recorded as the first number.
In step S314, the number of items previously stocked by the unmanned retail device is obtained and noted as a second number.
In step S315, a payment amount is calculated based on the difference between the second amount and the first amount.
Typically, the purchasing behavior of the user includes at least the following actions: the unmanned retail device is turned on first, then the required goods are taken out (the user can also not take out any goods), and finally the unmanned retail device is turned off. Based on this, the back-end payment processing method proposed in the present embodiment is performed after the user turns on and off the unmanned retail device. The method comprises the steps of firstly obtaining a plurality of parameter values corresponding to a plurality of preset parameters, wherein the preset parameters can be preset variables used for representing the self condition of the unmanned retail device, can be preset variables used for representing the purchasing behavior and the portrait of a current user, can also be preset variables used for representing the peripheral condition of the unmanned retail device, obtaining the real-time parameter values of the plurality of parameters, obtaining the counting times to be executed according to the real-time parameter values, driving the unmanned retail device to execute counting operations corresponding to the counting times, obtaining the commodity quantity of the current stock of the unmanned retail device according to the counting operation result, obtaining the commodity quantity of the previous stock of the unmanned retail device, and finally calculating the payment amount based on the subtracted difference value of the two.
The back-end payment processing method is applied to the unmanned retail vehicle, the commodity quantity in the container before the user opens the cabinet door of the unmanned retail vehicle is obtained firstly, then the commodity quantity in the container after the user closes the cabinet door of the unmanned retail vehicle is obtained, the commodity quantity taken out by the user is obtained through comparison calculation, and then the payment amount and the payment bill are calculated according to the commodity quantity taken out by the user, so that the user can pay according to the payment bill. And the cabinet door of the container is closed by a user to flexibly execute counting for different times, and the counting times of each time are calculated according to the field condition and the user condition, so that balance is achieved between reducing the waiting time of the user and avoiding counting errors as much as possible.
Fig. 4A is a flowchart of a specific embodiment of the step of determining the number of inventory according to a plurality of parameter values in fig. 3, specifically including the following steps.
In step S411, a weighting score is calculated from a plurality of parameter values.
In step S412, the correspondence between the weighting and the pre-established weighting score and the count is used to determine the count.
The present embodiment is described below by way of example. Table 1 shows exemplary preset parameters and parameter values. In table 1, a plurality of preset parameters are divided into a first stage and a second stage. Embodiments of the present application are not limited to whether to rank or not.
Table 1
The corresponding weighted score calculation formula (1) is: weighting component= (parameter value of parameter 1 + parameter value of parameter 2 + parameter value of parameter 3 + parameter value of parameter … … + parameter N-1) R/N, R equals 0 if the cabinet door is open, R equals 1 if the cabinet door is closed, the parameter value of each parameter is selected from 0 and 1, N is a positive integer greater than 2.
Table 2 then gives exemplary weighted score-count correspondence.
Table 2
Then, based on the present embodiment, the parameter value corresponding to each parameter in the unmanned retail device and in table 1 is obtained in sequence, then a weighted value is obtained based on formula (1), and then the weighted value is compared with table 2 to obtain the count.
Fig. 4B is a flowchart of another specific embodiment of the step of determining the number of inventory according to a plurality of parameter values in fig. 3, specifically including the following steps.
In step S421, a weighting score is calculated from a plurality of parameter values.
In step S422, the corresponding relationship between the weighting and the pre-established weighting score and the inventory time is used for comparison to determine the corresponding settlement time.
In step S423, the corresponding settlement time is compared with the preset average counting time to obtain the counting times, and the counting times are obtained.
The difference between this embodiment and the previous embodiment is that the settlement time is obtained according to the parameter values of a plurality of preset parameters, the settlement time is the maximum settlement time allowed by the purchasing behavior, and then the count number is obtained by dividing the settlement time by the preset average count time. For example.
Table 3 shows exemplary correspondence of weighted scores and settlement times. In table 2, when the parameter of "whether the cabinet door is opened" is equal to 0, the checking is not waited, and the settlement is immediately carried out; when the primary coefficient is 1 and 1 secondary coefficient is satisfied, the weighting is divided into 0.125, and the corresponding settlement time is 5s; etc.
TABLE 3
Therefore, according to this embodiment, the parameter value corresponding to each parameter in table 1 in the unmanned retail device is obtained sequentially, then a weighted value is obtained based on formula (1), the weighted value is compared with table 3 to obtain the settlement time, and then the count number is obtained by dividing the settlement time by the preset average count time. For example, if the settlement time obtained is 20s while the experimental result of the history data indicates that the time taken for one inventory is 5s, 3 inventory may be performed in 20 s.
In addition, the present application provides some improved embodiments, for example, the flexible counting times may further include setting a counting interrupt condition, and when the counting interrupt condition is satisfied, counting may be ended. For example, the setting of the inventory breaking condition is to determine whether the results of two adjacent inventory are the same, if the results are the same, the inventory is ended, more specifically, if the calculation results require 3 inventory steps to be performed, but when the second inventory step is performed, it is found that the inventory of the two inventory steps is 100 items, the inventory can be ended at this time according to the inventory breaking condition, and the following steps are performed.
Fig. 5 is a functional block diagram of a back-end payment processing apparatus for use in an unmanned retail device according to an embodiment of the present application. The apparatus 500 includes the following modules.
The inventory count determining module 501 is configured to collect a plurality of parameter values corresponding to a plurality of preset parameters, and determine inventory count according to the plurality of parameter values.
The commodity fetching amount calculating module 502 is configured to perform an inventory operation corresponding to the inventory number for the unmanned retail device, obtain the number of commodities currently stored in the unmanned retail device according to the inventory operation result, record the number as a first number, obtain the number of commodities previously stored in the unmanned retail device, record the number as a second number, and subtract the first number from the second number to obtain the number of fetched commodities;
the payment amount calculation module 503 is configured to calculate a payment amount according to the number of the fetched commodities.
It should be understood that the apparatus of this embodiment corresponds to the back-end payment processing method provided above, and the relevant content will be understood by reference, and will not be described in detail here.
In summary, the method and the device for processing the back-end payment applied to the unmanned retail device (including the unmanned retail vehicle) provided by the embodiment of the application have the following advantages: firstly, for a user, only the code scanning and door opening are needed, the objects are selected, the door closing and automatic settlement are realized, the worry that the goods are not obtained after payment is avoided, the service of sharing before payment is experienced, and for a merchant, the commodity inventory condition can be mastered in real time, the theft loss is prevented, and the error and the workload of manual inventory are reduced; secondly, because the purchase behaviors of the users are greatly different, the purchase efficiency can be optimized through dynamic settlement, and the overall shopping experience of the users is improved.
Further, the present embodiment provides a computer-readable storage medium storing computer instructions that, when executed, implement the steps of the back-end payment processing method of the example above applied to the unmanned device.
The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium is, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer readable storage medium include the following: in particular, the electrical connection of one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical memory, a magnetic memory, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with a processing unit, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a notch. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any other suitable combination. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., and any suitable combination of the foregoing.
Computer program code for carrying out embodiments of the present application may be written in one or more programming languages or combinations. The programming languages include object oriented programming languages such as JAVA, c++, and may also include conventional procedural programming languages such as C. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
It should be noted that in this document relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The embodiments according to the present application, as described above, are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention and various modifications as are suited to the particular use contemplated. This application is to be limited only by the claims and the full scope and equivalents thereof.

Claims (10)

1. A back-end payment processing method applied to an unmanned retail device, the back-end payment processing method being performed after a user turns on and off the unmanned retail device, and comprising the steps of:
collecting a plurality of parameter values corresponding to a plurality of preset parameters;
determining the checking times according to the parameter values;
performing inventory operations corresponding to the inventory times on the unmanned retail device, and obtaining the number of commodities currently stored in the unmanned retail device according to the inventory operations, and recording the number as a first number;
obtaining the number of items previously stocked by the unmanned retail device, and recording the number as a second number;
and calculating a payment amount according to the difference value between the second quantity and the first quantity.
2. The back-end payment processing method of claim 1, wherein said determining the number of inventory counts from the plurality of parameter values comprises:
calculating a weighted score from the plurality of parameter values;
and comparing the weighting with a pre-established corresponding relation between the weighting score and the counting times to determine the counting times.
3. The back-end payment processing method according to claim 2, wherein the plurality of parameters is N parameters including detecting whether a cabinet door of the unmanned retail device is closed or not, and calculating the weighted score using arithmetic equation (1):
weighting component= (parameter value of parameter 1 + parameter value of parameter 2 + parameter value of parameter 3 + parameter value of parameter … … + parameter N-1) R/N, R equals 0 if the cabinet door is open, R equals 1 if the cabinet door is closed, the parameter value of each parameter is selected from 0 and 1, N is a positive integer greater than 2.
4. A back-end payment processing method as recited in claim 3, wherein the plurality of parameters further comprises one or more of the following: the cabinet door opening quantity, commodity price, residual inventory, idle busy hours, site environment, user behavior credibility, historical order and commodity taking time.
5. The back-end payment processing method of claim 1, wherein said determining the number of inventory counts from the plurality of parameter values comprises:
calculating a weighted score from the plurality of parameter values;
comparing the weighting with a pre-established corresponding relation between the weighting score and the inventory time to determine corresponding settlement time;
and comparing the corresponding settlement time with the preset average counting time to obtain the counting times.
6. The back-end payment processing method of claim 1, wherein the unmanned retail device performs inventory periodically before the user turns on the unmanned retail device and records the number of items in inventory of the unmanned retail device.
7. The back-end payment processing method of claim 6, wherein the unmanned retail device records the number of items in inventory of the unmanned retail device to a cloud server.
8. A back-end payment processing apparatus for use with an unmanned retail device, comprising:
the counting frequency determining module is used for collecting a plurality of parameter values corresponding to a plurality of preset parameters and determining the counting frequency according to the plurality of parameter values;
the commodity taking-out quantity calculating module is used for executing counting operation corresponding to the counting times on the unmanned retail device, obtaining the current inventory commodity quantity of the unmanned retail device according to the counting operation result, marking the current inventory commodity quantity as a first quantity, obtaining the previous inventory commodity quantity of the unmanned retail device as a second quantity, and subtracting the first quantity from the second quantity to obtain the taken-out commodity quantity;
and the payment amount calculation module is used for calculating the payment amount according to the quantity of the fetched commodities.
9. A computing device comprising a memory and a processor, the memory further storing computer instructions executable by the processor, the computer instructions, when executed, implementing the back-end payment processing method of any of claims 1 to 8.
10. A computer readable medium storing computer instructions executable by an electronic device, the computer instructions when executed implementing the back-end payment processing method of any of claims 1 to 8.
CN202311434276.6A 2023-10-31 2023-10-31 Rear-end payment processing method and device applied to unmanned retail device Pending CN117436958A (en)

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CN202311434276.6A CN117436958A (en) 2023-10-31 2023-10-31 Rear-end payment processing method and device applied to unmanned retail device

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CN117436958A true CN117436958A (en) 2024-01-23

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