Intelligent cabinet recharge reminding device, method, computer equipment and storage medium

Abstract

This invention discloses a smart locker recharge reminder device, method, computer equipment, and storage medium. The method involves: acquiring the action detection results corresponding to the first smart locker during its use; ensuring the IoT card installed in the first smart locker cannot monitor data usage; when the action detection results include data consumption actions, acquiring the data usage reference value corresponding to the data consumption action, and determining the data usage value of the IoT card based on the data usage reference value; acquiring the total data usage value of the IoT card, and determining the remaining data usage value of the IoT card based on the total data usage value and the data usage value; acquiring a preset data usage warning threshold for the IoT card, and sending a data usage recharge reminder to the client associated with the first smart locker when the remaining data usage value is less than the preset data usage warning threshold. This invention improves the efficiency and accuracy of providing data usage recharge reminders for IoT cards in smart lockers that cannot monitor data usage.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent cabinet detection, and particularly relates to an intelligent cabinet recharge reminding device and method, computer equipment and a storage medium. BACKGROUND

[0002] With the development of science and technology, more and more different types of intelligent cabinets have emerged. For example, commercial intelligent cabinets or household intelligent cabinets. Household intelligent cabinets generally need users to purchase and install Internet of Things cards before they can be used online. However, when the traffic of the Internet of Things card is used up, the household intelligent cabinet cannot continue to be used until the Internet of Things card is recharged.

[0003] In the prior art, the cabinet machine operation platform cannot monitor the traffic and usage state of the Internet of Things card of the household intelligent cabinet. Often, the user only discovers that the household intelligent cabinet cannot be used after the household intelligent cabinet is recharged. This leads to low recharge efficiency of the household intelligent cabinet and poor user experience. SUMMARY

[0004] The embodiments of the present application provide an intelligent cabinet recharge reminding device and method, computer equipment and a storage medium to solve the problem of low recharge efficiency and poor user experience of the household intelligent cabinet in the prior art.

[0005] An intelligent cabinet recharge reminding method comprises the following steps:

[0006] In the use of a first intelligent cabinet, an action detection result corresponding to the first intelligent cabinet is obtained; an Internet of Things card arranged in the first intelligent cabinet cannot be monitored for traffic;

[0007] When the action detection result contains a traffic consumption action, a traffic reference value corresponding to the traffic consumption action is obtained, and a traffic consumption value of the Internet of Things card is determined according to the traffic reference value;

[0008] A total traffic value of the Internet of Things card is obtained, and a remaining traffic value of the Internet of Things card is determined according to the total traffic value and the traffic consumption value;

[0009] A preset traffic warning threshold of the Internet of Things card is obtained, and a traffic recharge reminder is sent to a client associated with the first intelligent cabinet when the remaining traffic value is less than the preset traffic warning threshold.

[0010] An intelligent cabinet recharge reminding device comprises the following steps:

[0011] An action detection module is configured to obtain an action detection result corresponding to a first intelligent cabinet in the use of the first intelligent cabinet; an Internet of Things card arranged in the first intelligent cabinet cannot be monitored for traffic;

[0012] The flow consumption calculation module is configured to, when the flow consumption action is included in the action detection result, acquire a flow reference value corresponding to the flow consumption action, and determine a flow consumption value of the Internet of Things card according to the flow reference value.

[0013] The residual flow calculation module is configured to acquire a total flow value of the Internet of Things card, and determine a residual flow value of the Internet of Things card according to the total flow value and the flow consumption value.

[0014] The recharge reminding module is configured to acquire a preset flow warning threshold of the Internet of Things card, and send a flow recharge reminding to a client associated with the first intelligent cabinet when the residual flow value is less than the preset flow warning threshold.

[0015] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the intelligent cabinet recharge reminding method when executing the computer program.

[0016] A computer readable storage medium stores a computer program, and the computer program is executable by a processor to implement the intelligent cabinet recharge reminding method.

[0017] The intelligent cabinet recharge reminding device, method, computer device, and storage medium improve the accuracy of predicting the flow consumption of the Internet of Things card. After determining the residual flow value according to the flow consumption value and the total flow value, the user is sent a flow recharge reminding in a case where the Internet of Things card cannot send and receive messages according to the preset flow warning threshold and the residual flow value. In this way, the above-mentioned method can relatively accurately make a flow recharge reminding of the Internet of Things card without calling the actual consumption flow of the card, improves the efficiency and accuracy of the flow recharge reminding of the Internet of Things card of the intelligent cabinet that cannot perform flow monitoring (such as the first intelligent cabinet), and further improves the convenience of service and user experience. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor under the premise of the drawings.

[0019] Figure 1 is an application environment schematic diagram of the intelligent cabinet recharge reminding method in an embodiment of the present application;

[0020] Figure 2 is a flowchart of the intelligent cabinet recharge reminding method in an embodiment of the present application;

[0021] Figure 3 is a principle block diagram of the intelligent cabinet recharge reminding device in an embodiment of the present application;

[0022] Figure 4 is a schematic diagram of the computer device in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0024] The intelligent cabinet recharge reminding method provided by the embodiments of the present application can be applied in the application environment as shown in Figure 1 . Specifically, the intelligent cabinet recharge reminding method is applied in an intelligent cabinet recharge reminding system, which includes a client, a server and a first intelligent cabinet as shown in Figure 1 . The client and the server communicate through a network, and the server and the first intelligent cabinet are connected for service, to solve the problems of low recharge efficiency and poor user experience of the existing household intelligent cabinet. The client, also known as the user end, is a program that provides local services for customers corresponding to the server. The client can be installed on, but not limited to, various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of multiple servers. The server can be an independent server or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content distribution networks (CDN), and big data and artificial intelligence platforms, etc. basic cloud computing services.

[0025] In an embodiment, as shown in Figure 2 , an intelligent cabinet recharge reminding method is provided. Taking the server in Figure 1 as an example, the method includes the following steps:

[0026] S10: In the use process of the first smart cabinet, the action detection result corresponding to the first smart cabinet is obtained; the Internet of Things card arranged in the first smart cabinet cannot be monitored for traffic.

[0027] Understandably, the first smart cabinet is a household smart cabinet. When the user purchases the first smart cabinet, the first smart cabinet does not carry the originally provided Internet of Things card. Instead, the user purchases the Internet of Things card (which only supports online function and does not support functions such as making a phone call or sending a message) and installs the purchased Internet of Things card on the first smart cabinet, and activates and uses the first smart cabinet by himself. Therefore, the server cannot monitor the actual traffic change of the Internet of Things card of the first smart cabinet. Further, in this embodiment, the action detection result corresponding to the first smart cabinet is detected, and the traffic consumption value corresponding to the Internet of Things card is predicted according to the action detection result. The action detection result represents the operation performed by the first smart cabinet in the use process. For example, the opening action of the first smart cabinet (i.e., the compartment on the first smart cabinet is opened), the closing action of the first smart cabinet (i.e., the compartment on the first smart cabinet is closed), the two-dimensional code updating action (i.e., the dynamic two-dimensional code displayed on the first smart cabinet is updated), and the service connection action (i.e., the first smart cabinet and the server are connected in communication).

[0028] Further, after the user scans the dynamic two-dimensional code displayed on the first smart cabinet and inputs the corresponding verification information (the verification information can be the last number of the user's mobile phone or other verification code), the server will determine whether the verification information is valid. When the server determines that the verification information is valid, the corresponding compartment information (the compartment information is the compartment number on the first smart cabinet) and the storage information (the storage information can be package data) are returned. After the user receives the compartment information and the storage information, the user can click the pick-up button or the opening button on the client. The server sends the compartment opening instruction carrying the compartment information to the first smart cabinet in response to the operation of the pick-up button or the opening button. The first smart cabinet receives the compartment opening instruction and opens the corresponding compartment according to the compartment information. At this time, it is detected that the first smart cabinet has performed the opening action. Further, when the user takes out the object in the compartment, the user closes the compartment. At this time, it is detected that the first smart cabinet has performed the closing action.

[0029] Further, the dynamic two-dimensional code displayed on the first smart cabinet has a validity period. When the display time of the dynamic two-dimensional code exceeds the validity period, or the dynamic two-dimensional code is scanned by the user within the validity period, the dynamic two-dimensional code is in an invalid state and needs to be updated. Therefore, the server sends a new dynamic two-dimensional code to the first smart cabinet. After receiving the new dynamic two-dimensional code, the first smart cabinet updates the new dynamic two-dimensional code on its display screen (the display screen can be an ink screen, etc.). At this time, it is detected that the first smart cabinet has performed the two-dimensional code updating action.

[0030] Further, the first smart cabinet and the server are in communication connection. However, the first smart cabinet can be in a network abnormal state (e.g., the signal of the first smart cabinet is shielded), and the communication connection between the first smart cabinet in the network abnormal state and the server is disconnected. After the first smart cabinet returns to a network normal state, a service connection request is sent to the server. When the server receives the service connection request and re-establishes the communication connection with the first smart cabinet, it is detected that the first smart cabinet performs the service connection action at this time.

[0031] S20: When the action detection result contains the traffic consumption action, a traffic reference value corresponding to the traffic consumption action is obtained, and a traffic consumption value of the Internet of Things card is determined according to the traffic reference value.

[0032] It can be understood that in the above description, it is pointed out that the embodiment is to predict the traffic consumption value of the Internet of Things card according to the action detection result. However, only the action performed by the first smart cabinet is detected in step S10. Therefore, a traffic reference value corresponding to the traffic consumption action needs to be set. Further, when the first smart cabinet performs the traffic consumption action, the traffic consumption value of the Internet of Things card of the first smart cabinet is determined according to the traffic reference value corresponding to the executed traffic consumption action. Further, the traffic consumption value is the predicted value, not the actual traffic consumption value of the first smart cabinet. The traffic consumption action can include but is not limited to the door opening action, the door closing action, the two-dimensional code updating action, and the service connection action.

[0033] Further, the traffic reference value is generated according to the quality inspection traffic data of the first smart cabinet before leaving the factory and the self-put traffic data of the second smart cabinet. The quality inspection traffic data is the traffic value consumed by the first smart cabinet when performing the traffic consumption action before leaving the factory. The self-put traffic data is the actual traffic consumption value of the second smart cabinet. The second smart cabinet is a commercial smart cabinet (e.g., a smart cabinet sold to a real estate or property company), which carries an originally provided Internet of Things card. Therefore, the server can monitor the actual traffic change of the Internet of Things card of the second smart cabinet, which is the self-put traffic data. It should be noted that the difference between the first smart cabinet and the second smart cabinet is only whether the originally provided Internet of Things card is carried. That is, the first smart cabinet and the second smart cabinet can be the same type of smart cabinet (e.g., the same size, the same number of compartments, and the same parts on the smart cabinet).

[0034] Specifically, after obtaining the action detection result corresponding to the first smart cabinet, if the action detection result includes a traffic consumption action, it indicates that the Internet of Things card of the first smart cabinet will change in traffic. Then, a traffic reference value corresponding to the traffic consumption action can be obtained, and the traffic consumption value of the Internet of Things card of the first smart cabinet can be determined according to the traffic reference value. Further, the calculation of the traffic consumption value for different traffic consumption actions can be calculated separately, or the same type of traffic consumption action can be integrated and calculated. For example, the door opening action is often related to the door closing action. Therefore, in addition to being able to separately record the traffic reference value of the door opening action or the door closing action as the traffic consumption value, the sum of the traffic reference values of the door opening action or the door closing action can also be recorded as a traffic consumption value. In this way, the computing pressure of the server can be reduced.

[0035] S30: Obtain a total traffic value of the Internet of Things card, and determine a remaining traffic value of the Internet of Things card according to the total traffic value and the traffic consumption value.

[0036] It can be understood that the total traffic value is the traffic value currently contained by the Internet of Things card, and the total traffic value will decrease after the first smart cabinet performs a traffic consumption action, and will increase after the user recharges the Internet of Things card. Specifically, after determining the traffic consumption value of the Internet of Things card according to the traffic reference value, the total traffic value of the Internet of Things card is obtained. The difference between the total traffic value and the traffic consumption value is determined as the remaining traffic value of the Internet of Things card.

[0037] S40: Obtain a preset traffic warning threshold value of the Internet of Things card, and send a traffic recharge reminder to a client associated with the first smart cabinet when the remaining traffic value is less than the preset traffic warning threshold value.

[0038] Specifically, after determining the remaining traffic value of the Internet of Things card according to the total traffic value and the traffic consumption value, a preset traffic warning threshold value of the Internet of Things card is obtained. The remaining traffic value and the preset traffic warning threshold value are compared. If the remaining traffic value is greater than or equal to the preset traffic warning threshold value, it indicates that the Internet of Things card of the first smart cabinet still has a large amount of traffic value. If the remaining traffic value is less than the preset traffic warning threshold value, it indicates that the current remaining traffic value of the Internet of Things card of the first smart cabinet is small. Then, a traffic recharge reminder is sent to a client (such as a smart phone or a personal computer, etc.) associated with the first smart cabinet. The preset traffic warning threshold value can be set according to the recharge package of the Internet of Things card. For example, assuming that the recharge package of the Internet of Things card is 500 traffic values, the corresponding preset traffic warning threshold value can be set to 10% of the recharge package, that is, 50 traffic values.

[0039] Further, it is pointed out in the above description that the Internet of Things card in the embodiment is a pure Internet of Things card, that is, the Internet of Things card does not have the functions of making phone calls and sending short messages. Therefore, when sending a traffic recharge reminder to the client associated with the first intelligent cabinet in the embodiment, the traffic recharge reminder is sent to the application program of the client associated with the first intelligent cabinet through a network. The application program can be a chat software (such as WeChat) or a small program with communication function. In addition, although the Internet of Things card of the first intelligent cabinet does not have the functions of making phone calls and sending short messages, a secondary card with the functions of making phone calls and sending short messages can be set for the Internet of Things card, or a mobile phone number can be bound to the Internet of Things card. In this way, the traffic recharge reminder can be sent to the client associated with the first intelligent cabinet through short messages.

[0040] In the embodiment, whether the first intelligent cabinet performs a traffic consumption action is determined by detecting the action of the first intelligent cabinet. After the first intelligent cabinet performs the traffic consumption action, the traffic consumption value of the Internet of Things card of the first intelligent cabinet is predicted according to the pre-set traffic reference value corresponding to the traffic consumption action, and the traffic consumption value is obtained. The accuracy of predicting the traffic consumption of the Internet of Things card is improved. After the remaining traffic value is determined according to the traffic consumption value and the total traffic value, the traffic recharge reminder is sent to the user in time according to the pre-set preset traffic warning threshold and the remaining traffic value, and the Internet of Things card cannot send and receive short messages. In this way, the above-mentioned method does not need to retrieve the actual consumed traffic of the card of the operator, and can relatively accurately make the traffic recharge reminder of the Internet of Things card, improve the efficiency and accuracy of the traffic recharge reminder of the Internet of Things card of the intelligent cabinet that cannot perform traffic monitoring (such as the first intelligent cabinet described above), and further improve the convenience of the service and the user experience.

[0041] In an embodiment, the traffic consumption action includes an opening door action and a closing door action; and the obtaining of the action detection result corresponding to the first intelligent cabinet comprises:

[0042] (1) Real-time monitoring of the change state of the cabinet door of the compartment of the first intelligent cabinet.

[0043] It can be understood that the compartment is a containing space for storing articles (such as express delivery) in the first intelligent cabinet. However, taking out or storing articles from the compartment of the first intelligent cabinet can occur at any time, so it is necessary to real-time monitor the change state of the cabinet door of the compartment of the first intelligent cabinet. For example, the change state of the cabinet door can be that the cabinet door of the compartment changes from a closed state to an open state, or that the cabinet door of the compartment changes from an open state to a closed state.

[0044] (2) When the change state of the cabinet door indicates that the compartment changes from a closed state to an open state, it is determined that the action detection result contains an opening door action.

[0045] (3) When the door state change of the cabinet indicates that the door of the compartment is switched from the open state to the closed state, it is determined that the action detection result includes the closing action.

[0046] It can be understood that, in the above description, it is indicated that, after the server issues the compartment opening instruction to the first intelligent cabinet, the first intelligent cabinet will open the cabinet door of the compartment indicated in the compartment opening instruction. At this time, the door state change of the compartment of the first intelligent cabinet is switched from the closed state to the open state. That is, the first intelligent cabinet corresponds to the opening action in the action detection result. Further, after the user takes out the object in the compartment, the compartment is closed. At this time, the door state change of the compartment of the first intelligent cabinet is switched from the open state to the closed state, that is, the closing action of the first intelligent cabinet is detected.

[0047] In an embodiment, the flow consumption action includes a two-dimensional code updating action; and the obtaining of the action detection result corresponding to the first intelligent cabinet includes:

[0048] (1) After sending the updated two-dimensional code to the first intelligent cabinet in a timely manner, the two-dimensional code updating state of the first intelligent cabinet is monitored.

[0049] It can be understood that, since the dynamic two-dimensional code displayed on the first intelligent cabinet has a valid period, when the display time of the dynamic two-dimensional code exceeds the valid period or the dynamic two-dimensional code is scanned by the user within the valid period, the dynamic two-dimensional code is in an invalid state and needs to be updated. Therefore, the server issues a new dynamic two-dimensional code, that is, an updated two-dimensional code, to the first intelligent cabinet, and detects the two-dimensional code updating state of the first intelligent cabinet. The two-dimensional code updating state indicates whether the first intelligent cabinet replaces the invalid dynamic two-dimensional code with the updated two-dimensional code.

[0050] (2) When the two-dimensional code updating state indicates that the updated two-dimensional code is displayed on the first intelligent cabinet, it is determined that the action detection result includes the two-dimensional code updating action.

[0051] Specifically, after sending the updated two-dimensional code to the first intelligent cabinet in a timely manner, the two-dimensional code updating state of the first intelligent cabinet is monitored. If the two-dimensional code updating state indicates that the updated two-dimensional code is displayed on the first intelligent cabinet, that is, the first intelligent cabinet performs the two-dimensional code updating action. If the two-dimensional code updating state indicates that the updated two-dimensional code is not displayed on the first intelligent cabinet, it indicates that the first intelligent cabinet has not updated the invalid dynamic two-dimensional code. Then, the first intelligent cabinet can be sent a two-dimensional code updating reminder instruction to replace the invalid dynamic two-dimensional code with the updated two-dimensional code on the display screen immediately after receiving the two-dimensional code updating reminder instruction.

[0052] In an embodiment, the traffic consumption action comprises a service connection action; and the obtaining the action detection result corresponding to the Internet of Things card of the first intelligent cabinet further comprises:

[0053] (1) receiving a service connection request sent by the first intelligent cabinet at a regular time, and establishing a service connection with the first intelligent cabinet based on the service connection request.

[0054] Understandably, when the first intelligent cabinet is in a network abnormal state, the communication connection between the first intelligent cabinet in the network abnormal state and the server is disconnected. After the first intelligent cabinet recovers to a network normal state, a service connection request is sent to the server. Alternatively, the first intelligent cabinet sends a service connection request to the server at a regular time in order to maintain a stable service connection with the server. In this way, the service connection between the server and the first intelligent cabinet can be maintained. Therefore, after the server receives the service connection request, a service connection is established with the first intelligent cabinet based on the service connection request. In this embodiment, the service connection mode between the first intelligent cabinet and the server is not limited.

[0055] (2) when the service connection with the first intelligent cabinet is successfully established, determining that the action detection result comprises the service connection action.

[0056] Specifically, after the service connection with the first intelligent cabinet is established based on the service connection request, if the service connection between the server and the first intelligent cabinet is successfully established, it is determined that the first intelligent cabinet has performed the service connection action. If the service connection between the server and the first intelligent cabinet fails, the service connection with the first intelligent cabinet is continued. If the service connection with the first intelligent cabinet still cannot be established, the network state of the first intelligent cabinet is detected. If the first intelligent cabinet is in a network abnormal state, the service connection with the first intelligent cabinet is established after the first intelligent cabinet recovers to a network normal state.

[0057] In an embodiment, before step S20, that is, before the obtaining of the traffic reference value corresponding to the traffic consumption action, further comprises:

[0058] (1) obtaining a cabinet machine quality inspection data table corresponding to the first intelligent cabinet; the cabinet machine quality inspection data table comprises at least one quality inspection traffic data; one quality inspection traffic data is associated with one traffic consumption action.

[0059] Understandably, the quality inspection flow data refers to the flow value consumed by the first smart cabinet during flow consumption actions tested before it leaves the factory. For example, the above description indicates that flow consumption actions include, but are not limited to, door opening, door closing, QR code updating, scheduled querying, and service connection actions. Therefore, before the first smart cabinet leaves the factory, the flow value consumed by the first smart cabinet during door opening, door closing, QR code updating, and service connection actions can be tested. Thus, the average of the sum of the flow values ​​corresponding to each identical flow consumption action after multiple tests can be used to determine the quality inspection flow data corresponding to that flow consumption action. A cabinet quality inspection data table is then generated based on all flow consumption actions and their corresponding quality inspection flow data.

[0060] (2) Obtain the cabinet self-discharge data table corresponding to the second smart cabinet; the cabinet self-discharge data table includes at least one self-discharge flow data; each self-discharge flow data is associated with a flow consumption action; the IoT card set in the second smart cabinet can perform flow monitoring.

[0061] Understandably, the self-dispensing traffic data refers to the actual traffic consumption value detected by the second smart cabinet. The second smart cabinet is a commercial smart cabinet (such as one sold to real estate or property management companies), which carries the originally provided IoT card. Therefore, the server can monitor the actual traffic changes of the IoT card in the second smart cabinet. This allows the detection of the traffic consumption value corresponding to each traffic consumption action, i.e., the self-dispensing traffic data. Thus, the average of the sums of the traffic values ​​corresponding to each identical traffic consumption action across multiple different second smart cabinets can be used to determine the self-dispensing traffic data for that action. A cabinet self-dispensing data table is then generated based on all traffic consumption actions and their corresponding self-dispensing traffic data.

[0062] (3) Obtain the quality inspection weight value corresponding to the quality inspection flow data and the self-investment weight value corresponding to the self-investment flow data.

[0063] Understandably, the quality inspection weight value and the self-dispensing weight value can be set by the user, or adjusted according to different application scenarios of the first intelligent cabinet. The sum of the quality inspection weight value and the self-dispensing weight value is 1. For example, both the quality inspection weight value and the self-dispensing weight value can be set to 0.5. Alternatively, the quality inspection weight value can be set to 0.3, and the self-dispensing weight value can be set to 0.7, etc. Preferably, the quality inspection weight value is any value between 0.3 and 1.

[0064] (4) Determine the reference value of the flow corresponding to the flow consumption action based on the quality inspection weight value, the self-injection weight value, the quality inspection flow data and the self-injection flow data corresponding to the same flow consumption action.

[0065] Specifically, after obtaining the quality inspection weight value corresponding to the quality inspection flow data and the self-investment weight value corresponding to the self-investment flow data, the quality inspection weight value and the quality inspection flow data can be determined as the quality inspection flow value, and the self-investment weight value and the self-investment flow data can be determined as the self-investment flow value. Then, the sum of the quality inspection flow value and the self-investment flow value corresponding to the same flow consumption action is determined as the flow reference value corresponding to that flow consumption action.

[0066] In one embodiment, after sending the data recharge reminder to the client associated with the first smart cabinet, the method further includes:

[0067] (1) Detect the number of times the first smart cabinet recharges traffic within a preset time range.

[0068] Understandably, the preset time range can be set according to needs. For example, the preset time range can be set to one month or six months, etc. The number of data top-ups refers to the number of times the client tops up the data on the IoT card of the first smart locker within the preset time range. Generally, within one month, the user will top up the data on the IoT card of the first smart locker once. However, in special application scenarios (such as the application scenario of an online shopping platform), the user will top up the data on the IoT card of the first smart locker multiple times.

[0069] (2) Obtain the preset number of times to recharge corresponding to the preset time range, and compare the number of times to recharge with the preset number of times to recharge.

[0070] Understandably, the preset recharge count refers to the number of times a user will recharge the IoT card of the first smart locker within a preset time range. This preset recharge count can be determined based on the historical recharge counts of the IoT cards of the second smart lockers within the preset time range. For example, assuming there are five second smart lockers, the recharge counts of the IoT cards from these five smart lockers within the preset time range can be obtained, and the average of the sum of these recharge counts can be determined as the preset recharge count. Then, the data recharge counts are compared with the preset recharge count.

[0071] (3) If the number of times the traffic is recharged is greater than the preset number of times, the quality inspection weight value and the self-investment weight value are adjusted to obtain the quality inspection update value corresponding to the quality inspection weight value and the self-investment update value corresponding to the self-investment weight value.

[0072] Specifically, after comparing the number of data recharges with the preset number of recharges, if the number of recharges exceeds the preset number, it indicates that the application scenario of the first smart cabinet requires a large amount of data consumption, meaning that the application scenario of the first smart cabinet may involve a large number of data-consuming actions (such as online shopping platforms, which may require a large number of door opening and closing actions). Therefore, the quality inspection weight value and the self-dispensing weight value can be adjusted to obtain the quality inspection update value corresponding to the quality inspection weight value, and the self-dispensing weight value corresponding to the self-dispensing weight value. For example, if the initial values ​​of both the quality inspection weight value and the self-dispensing weight value are 0.5, then in the online shopping platform application scenario, the quality inspection weight value can be decreased, and the self-dispensing weight value can be increased. For example, the quality inspection weight value can be decreased to 0.3, and the self-dispensing weight value increased to 0.7. This ensures that the actual data flow data obtained from the IoT card monitoring of the second smart cabinet accounts for a larger proportion, thereby improving the accuracy of the data flow reference value and making the adjusted data flow reference value more consistent with the actual data flow consumption scenario.

[0073] In one embodiment, after step S40, that is, after sending the data recharge reminder to the client associated with the first smart cabinet, the method further includes:

[0074] (1) After detecting that the client has successfully recharged the IoT card, obtain the client's recharge record information.

[0075] Specifically, after sending a data top-up reminder to the client associated with the first smart locker, the system continuously monitors whether the IoT card has been successfully topped up. Once the client's top-up of the IoT card is detected, the client's top-up record information can be obtained. This record information indicates the data plan purchased by the client for topping up the IoT card. The data allowance can then be determined based on the top-up data plan.

[0076] (2) Determine the recharge traffic value corresponding to the IoT card based on the recharge record information, and determine the update traffic value corresponding to the IoT card based on the recharge traffic value and the remaining traffic value.

[0077] Specifically, after obtaining the client's recharge record information, the recharge record information is parsed to determine the data plan that the client recharged for the IoT card. By querying the preset data plan list (which records the data recharge values ​​corresponding to different data plans), the data recharge value corresponding to that data plan is determined. Then, the sum of the recharged data value and the remaining data value is determined as the update data value corresponding to the IoT card.

[0078] In one embodiment, before sending the data recharge reminder to the client associated with the first smart cabinet, the method further includes:

[0079] (1) Obtain the actual consumption value corresponding to the IoT card set in the first smart cabinet from the third-party operation platform.

[0080] Understandably, the third-party operating platform can be a platform developed by the operator corresponding to the IoT card. It should be noted that, in step S10, the statement that the IoT card installed in the first smart cabinet cannot be monitored for traffic means that its traffic cannot be monitored by the server referred to in this invention (i.e., the server associated with the user who sold the first smart cabinet). However, the third-party operating platform can obtain the actual value of the IoT card's traffic consumption during the use of the smart cabinet, i.e., the actual consumption value. Furthermore, this actual consumption value can be determined by the sum of the actual traffic values ​​corresponding to each traffic consumption action performed by the smart cabinet.

[0081] (2) The difference between the flow consumption value and the actual consumption value is determined as the flow prediction difference, and the flow prediction difference is compared with a preset difference range.

[0082] Understandably, the preset difference range is used to assess the accuracy of the traffic consumption prediction for the IoT card of the first smart cabinet. That is, when the traffic prediction difference is within the preset difference range, it indicates that the traffic reference value corresponding to each set traffic consumption action matches the actual traffic consumption value relatively well. When the traffic prediction difference is not within the preset difference range, it indicates that the traffic reference value corresponding to each set traffic consumption action differs significantly from the actual traffic consumption value, thus requiring adjustment of the traffic reference value. The preset difference range can be set according to requirements.

[0083] (3) When the traffic prediction difference is not within the preset difference range, the traffic reference value is adjusted to obtain the adjusted reference value.

[0084] Specifically, after determining the difference between the traffic consumption value and the actual consumption value as the traffic prediction difference, and comparing the traffic prediction difference with a preset difference range, if the traffic prediction difference is within the preset difference range (i.e., the traffic prediction difference is greater than or equal to the minimum value of the preset difference range and less than or equal to the maximum value of the preset difference range), then it is determined that the traffic reference value corresponding to each currently set traffic consumption action matches the actual traffic consumption value corresponding to each traffic consumption action, and no adjustment to the traffic reference value is required.

[0085] Furthermore, if the traffic prediction difference is not within the preset difference range, that is, the traffic prediction difference is less than the minimum value of the preset difference range or greater than the maximum value of the preset difference range, it is determined that there is a significant difference between the traffic reference value corresponding to each traffic consumption action and the actual traffic consumption value corresponding to each traffic consumption action, and the traffic reference value needs to be adjusted. The adjustment method can be as follows: determine the actual traffic consumption value of each traffic consumption action based on the actual consumption value, and then compare the actual traffic consumption value of the same traffic consumption action with the traffic reference value. Adjust the traffic reference value with the largest difference between the actual traffic consumption value and the traffic reference value. For example, an action traffic difference can be set and compared with the difference between the actual traffic consumption value and the traffic reference value. The traffic reference value corresponding to the action traffic difference is determined as the traffic reference value with the largest difference. If the traffic prediction difference is less than the minimum value of the preset difference range, it indicates that the traffic reference value is set too small, and the traffic reference value can be increased. If the traffic prediction difference is greater than the maximum value of the preset difference range, it indicates that the traffic reference value is set too large, and the traffic reference value can be decreased.

[0086] Furthermore, the above example of adjusting the traffic reference value with the largest difference is merely one example. Adjustments can also be made to all traffic reference values ​​with the second largest difference or those exceeding the action traffic difference. In addition, the first and second weight values ​​mentioned in the above embodiments can also be adjusted to achieve the effect of adjusting the traffic reference value.

[0087] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0088] In one embodiment, a smart locker recharge reminder device is provided, which corresponds one-to-one with the smart locker recharge reminder method described in the above embodiments. For example... Figure 3 As shown, the smart locker recharge reminder device includes an action detection module 10, a data consumption calculation module 20, a remaining data calculation module 30, and a recharge reminder module 40. Detailed descriptions of each functional module are as follows:

[0089] The motion detection module 10 is used to obtain the motion detection results corresponding to the first smart cabinet during its use; the IoT card installed in the first smart cabinet cannot perform traffic monitoring.

[0090] The traffic consumption calculation module 20 is used to obtain a traffic reference value corresponding to the traffic consumption action when the action detection result includes a traffic consumption action, and determine the traffic consumption value of the IoT card based on the traffic reference value.

[0091] The remaining data usage calculation module 30 is used to obtain the total data usage value of the IoT card and determine the remaining data usage value of the IoT card based on the total data usage value and the data usage consumption value.

[0092] The recharge reminder module 40 is used to obtain the preset traffic warning threshold of the IoT card, and send a traffic recharge reminder to the client associated with the first smart cabinet when the remaining traffic value is less than the preset traffic warning threshold.

[0093] Preferably, the motion detection module 10 includes:

[0094] The compartment detection unit is used to monitor the changes in the cabinet door status of the compartments of the first smart cabinet in real time.

[0095] The door opening detection unit is used to determine that the action detection result includes a door opening action when the cabinet door change state characterizes the compartment changing from a closed state to an open state;

[0096] A door closing detection unit is used to determine that the action detection result includes a door closing action when the cabinet door change state characterizes the compartment changing from an open state to a closed state.

[0097] Preferably, the motion detection module 10 includes:

[0098] The QR code sending unit is used to periodically send an updated QR code to the first smart cabinet and then monitor the QR code update status of the first smart cabinet.

[0099] A QR code detection unit is used to determine that the action detection result includes the QR code update action when the QR code update status indicates that the updated QR code is displayed on the first smart cabinet.

[0100] Preferably, the motion detection module 10 includes:

[0101] The request receiving unit is used to receive service connection requests sent periodically by the first smart cabinet, and to establish a service connection with the first smart cabinet based on the service connection requests.

[0102] The connection detection unit is used to determine that the action detection result includes the service connection action when a service connection is successfully established with the first smart cabinet.

[0103] Preferably, the smart locker recharge reminder device further includes:

[0104] The quality inspection data acquisition module is used to acquire the cabinet quality inspection data table corresponding to the first smart cabinet; the cabinet quality inspection data table includes at least one quality inspection flow data; each quality inspection flow data is associated with a flow consumption action;

[0105] The self-discharge data acquisition module is used to acquire the self-discharge data table of the cabinet corresponding to the second smart cabinet; the self-discharge data table includes at least one self-discharge flow data; each self-discharge flow data is associated with a flow consumption action; the IoT card installed in the second smart cabinet can perform flow monitoring.

[0106] The weight value acquisition module is used to acquire the quality inspection weight value corresponding to the quality inspection flow data and the self-investment weight value corresponding to the self-investment flow data;

[0107] The traffic reference value calculation module is used to determine the traffic reference value corresponding to the traffic consumption action based on the quality inspection weight value, the self-injection weight value, the quality inspection traffic data and the self-injection traffic data corresponding to the same traffic consumption action.

[0108] Preferably, the smart locker recharge reminder device further includes:

[0109] The recharge count detection module is used to detect the number of times the first smart cabinet recharges within a preset time range;

[0110] The recharge count comparison module is used to obtain the preset recharge count corresponding to the preset time range, and compare the data recharge count with the preset recharge count;

[0111] The weight adjustment module is used to adjust the quality inspection weight value and the self-investment weight value if the number of traffic recharges is greater than the preset number of recharges, so as to obtain the quality inspection update value corresponding to the quality inspection weight value and the self-investment update value corresponding to the self-investment weight value.

[0112] Preferably, the smart locker recharge reminder device further includes:

[0113] The recharge information acquisition module is used to acquire the client's recharge record information after detecting that the client has successfully recharged the IoT card;

[0114] The data flow update module is used to determine the recharge data flow value corresponding to the IoT card based on the recharge record information, and to determine the update data flow value corresponding to the IoT card based on the recharge data flow value and the remaining data flow value.

[0115] Preferably, the smart locker recharge reminder device further includes:

[0116] The actual consumption value acquisition module is used to obtain the actual consumption value corresponding to the IoT card set in the first smart cabinet from a third-party operation platform;

[0117] The difference comparison module is used to determine the difference between the traffic consumption value and the actual consumption value as the traffic prediction difference, and compare the traffic prediction difference with a preset difference range;

[0118] The reference value adjustment module is used to adjust the traffic reference value when the traffic prediction difference is not within the preset difference range, so as to obtain an adjusted reference value.

[0119] Specific limitations regarding the smart locker recharge reminder device can be found in the limitations of the smart locker recharge reminder method described above, and will not be repeated here. Each module in the aforementioned smart locker recharge reminder device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0120] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data used in the smart locker recharge reminder method described in the above embodiment. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a smart locker recharge reminder method.

[0121] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the smart cabinet recharge reminder method described in the above embodiment.

[0122] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the smart cabinet recharge reminder method described in the above embodiment.

[0123] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0124] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0125] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A smart locker recharge reminder device, characterized in that, include: The motion detection module is used to obtain the motion detection results corresponding to the first smart cabinet during its use; the IoT card installed in the first smart cabinet cannot perform traffic monitoring. The traffic consumption calculation module is used to obtain a traffic reference value corresponding to the traffic consumption action when the action detection result includes a traffic consumption action, and determine the traffic consumption value of the IoT card based on the traffic reference value. The remaining data usage calculation module is used to obtain the total data usage value of the IoT card, and determine the remaining data usage value of the IoT card based on the total data usage value and the data usage consumption value; The recharge reminder module is used to obtain the preset traffic warning threshold of the IoT card, and send a traffic recharge reminder to the client associated with the first smart cabinet when the remaining traffic value is less than the preset traffic warning threshold.

2. The intelligent cabinet recharge reminder device as described in claim 1, characterized in that, The flow consumption actions include opening and closing the door; the action detection module includes: The compartment detection unit is used to monitor the changes in the cabinet door status of the compartments of the first smart cabinet in real time. The door opening detection unit is used to determine that the action detection result includes a door opening action when the cabinet door change state characterizes the compartment changing from a closed state to an open state; A door closing detection unit is used to determine that the action detection result includes a door closing action when the cabinet door change state characterizes the compartment changing from an open state to a closed state.

3. The intelligent cabinet recharge reminder device as described in claim 1, characterized in that, The traffic consumption action includes the QR code update action; the action detection module further includes: The QR code sending unit is used to periodically send an updated QR code to the first smart cabinet and then monitor the QR code update status of the first smart cabinet. A QR code detection unit is used to determine that the action detection result includes the QR code update action when the QR code update status indicates that the updated QR code is displayed on the first smart cabinet.

4. The intelligent cabinet recharge reminder device as described in claim 1, characterized in that, The traffic consumption actions include service connection actions; the action detection module further includes: The request receiving unit is used to receive service connection requests sent periodically by the first smart cabinet, and to establish a service connection with the first smart cabinet based on the service connection requests. The connection detection unit is used to determine that the action detection result includes the service connection action when a service connection is successfully established with the first smart cabinet.

5. The intelligent cabinet recharge reminder device as described in claim 1, characterized in that, The smart locker recharge reminder device also includes: The quality inspection data acquisition module is used to acquire the cabinet quality inspection data table corresponding to the first smart cabinet; the cabinet quality inspection data table includes at least one quality inspection flow data; each quality inspection flow data is associated with a flow consumption action; The self-discharge data acquisition module is used to acquire the self-discharge data table of the cabinet corresponding to the second smart cabinet; the self-discharge data table includes at least one self-discharge flow data; each self-discharge flow data is associated with a flow consumption action; the IoT card installed in the second smart cabinet can perform flow monitoring. The weight value acquisition module is used to acquire the quality inspection weight value corresponding to the quality inspection flow data and the self-investment weight value corresponding to the self-investment flow data; The traffic reference value calculation module is used to determine the traffic reference value corresponding to the traffic consumption action based on the quality inspection weight value, the self-injection weight value, the quality inspection traffic data and the self-injection traffic data corresponding to the same traffic consumption action.

6. The intelligent cabinet recharge reminder device as described in claim 5, characterized in that, The smart locker recharge reminder device also includes: The recharge count detection module is used to detect the number of times the first smart cabinet recharges within a preset time range; The recharge count comparison module is used to obtain the preset recharge count corresponding to the preset time range, and compare the data recharge count with the preset recharge count; The weight adjustment module is used to adjust the quality inspection weight value and the self-investment weight value if the number of traffic recharges is greater than the preset number of recharges, so as to obtain the quality inspection update value corresponding to the quality inspection weight value and the self-investment update value corresponding to the self-investment weight value.

7. The intelligent cabinet recharge reminder device as described in claim 1, characterized in that, The smart locker recharge reminder device also includes: The recharge information acquisition module is used to acquire the client's recharge record information after detecting that the client has successfully recharged the IoT card; The data flow update module is used to determine the recharge data flow value corresponding to the IoT card based on the recharge record information, and to determine the update data flow value corresponding to the IoT card based on the recharge data flow value and the remaining data flow value.

8. The intelligent cabinet recharge reminder device as described in claim 1, characterized in that, The smart locker recharge reminder device also includes: The actual consumption value acquisition module is used to obtain the actual consumption value corresponding to the IoT card set in the first smart cabinet from a third-party operation platform; The difference comparison module is used to determine the difference between the traffic consumption value and the actual consumption value as the traffic prediction difference, and compare the traffic prediction difference with a preset difference range; The reference value adjustment module is used to adjust the traffic reference value when the traffic prediction difference is not within the preset difference range, so as to obtain an adjusted reference value.

9. A method for reminding users to recharge at a smart locker, characterized in that, include: During the use of the first smart cabinet, the action detection results corresponding to the first smart cabinet are obtained; the IoT card set in the first smart cabinet cannot perform traffic monitoring; The traffic consumption calculation module is used to obtain a traffic reference value corresponding to the traffic consumption action when the action detection result includes a traffic consumption action, and determine the traffic consumption value of the IoT card based on the traffic reference value. The remaining data usage calculation module is used to obtain the total data usage value of the IoT card, and determine the remaining data usage value of the IoT card based on the total data usage value and the data usage consumption value; The recharge reminder module is used to obtain the preset traffic warning threshold of the IoT card, and send a traffic recharge reminder to the client associated with the first smart cabinet when the remaining traffic value is less than the preset traffic warning threshold.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the smart cabinet recharge reminder method as described in claim 9.

11. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the smart cabinet recharge reminder method as described in claim 9.

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