Diet selling cabinet commodity management and control system and management and control method thereof

Abstract

The invention relates to a food selling cabinet commodity management and control system and a management and control method thereof, and the system achieves the recognition and timely processing of abnormal commodities in a food selling cabinet through the synergistic effect of a recognition device, a detection device, a management control device and a waste processing device. And it is ensured that the target commodity always meets the commodity storage condition in the diet selling cabinet. Therefore, a set of management and control mechanism for food selling cabinet commodities is formed, quality and safety of target commodities are guaranteed, food waste is reduced, and user experience is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of intelligent meal vending cabinets, and in particular to a meal vending cabinet commodity management and control system and a management and control method thereof. Background Art

[0002] With the rapid development of the prepared food market, meal counters, as a new retail model, are favored by consumers for their convenience and intelligence. Such counters are usually located in crowded places, such as office buildings, shopping malls or schools, providing consumers with convenient and fast meal options. However, with the expansion of the scale of meal counters and the increase in the variety of meals, the management problems of existing meal counters have become increasingly prominent, including the challenge of handling expired products. Traditional management mechanisms are often unable to efficiently identify and handle expired food, which may not only pose a potential risk to consumers' health, but also lead to a waste of resources. In addition, the treatment of unsorted waste also affects environmental sustainability, as a large amount of untreated waste may increase the load of landfills or cause environmental pollution through incineration.

[0003] Therefore, achieving control over the merchandise in meal vending counters and recycling of abnormal merchandise has become an urgent issue to be addressed. Summary of the invention

[0004] The present invention provides a meal vending cabinet commodity management and control system and a management and control method thereof, which are used to realize the identification and processing of abnormal commodities in the meal vending cabinet and form a meal vending cabinet commodity management and control mechanism.

[0005] In a first aspect, the present disclosure provides a meal vending cabinet commodity management and control system, comprising:

[0006] An identification device, used to identify a target commodity in a meal vending cabinet and obtain commodity information of the target commodity;

[0007] A monitoring device, used to monitor environmental data in a meal vending cabinet, wherein the environmental data includes temperature and humidity data;

[0008] A management control device, configured to receive the commodity information fed back by the identification device and the environmental data fed back by the monitoring device, and to generate an environmental adjustment instruction when the environmental data does not meet the storage conditions of the target commodity; and to determine whether the target commodity is an abnormal commodity based on the shelf life information in the commodity information, and to generate a waste disposal instruction when an abnormal commodity exists; the abnormal commodity includes a spoiled commodity or an expired commodity;

[0009] The waste treatment device, in response to the waste treatment instruction issued by the management control device, classifies and stores the abnormal commodities.

[0010] In some embodiments, a remote communication device and a cloud device are also included;

[0011] The management and control device is communicatively connected to the cloud device via the remote communication device, and is used to upload relevant data to the cloud device, wherein the relevant data includes environmental data, commodity sales data, and abnormal commodity data, and to send a recycling service request to the cloud device to notify the service provider to recycle the abnormal commodities in the waste treatment device.

[0012] In some embodiments, an information display device is electrically connected to the management control device.

[0013] In a second aspect, the present disclosure provides a method for controlling goods in a meal vending cabinet, which is applied to the meal vending cabinet commodity control system as described in the first aspect, and the method comprises:

[0014] Obtaining historical environmental data of a meal vending cabinet, as well as inventory, historical sales data, and historical waste data of a target product in the meal vending cabinet;

[0015] Determine commodity status analysis results of all the target commodities under current environmental data based on the historical environmental data and the historical waste data;

[0016] When the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory quantity is adjusted; the abnormal commodities include spoiled commodities or expired commodities;

[0017] Based on the historical sales data, obtain sales trend analysis results of all the target commodities;

[0018] The inventory level is adjusted according to the sales trend analysis result.

[0019] In some embodiments, based on the historical environmental data and the historical waste data, determining the commodity status analysis results of all the target commodities under the current environmental data includes:

[0020] Dividing the historical environmental data into a plurality of temperature and humidity change sequences of the same duration;

[0021] Using the temperature and humidity change sequence as training samples and the historical waste data as labels, the constructed commodity state prediction model is trained to obtain a target commodity state prediction model;

[0022] The current environment data is input into the target commodity state prediction model to obtain the commodity state analysis result.

[0023] In some embodiments, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0024] Performing seasonal separation on the historical sales data to obtain seasonally adjusted historical sales data;

[0025] Using the seasonally adjusted historical sales data to train the initially constructed first sales trend analysis and prediction model to obtain a first target sales trend analysis and prediction model;

[0026] The sales trend analysis result at the current time point is obtained through the first target sales trend analysis and prediction model.

[0027] In some embodiments, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0028] Extracting frequent item sets from the historical sales data and generating association rules for the frequent item sets;

[0029] Calculating the confidence of the association rule, and combining the confidence threshold to filter out the target association rule;

[0030] Based on the target rule, the sales trend analysis result of the target commodity is determined.

[0031] In some embodiments, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0032] Using a clustering algorithm, the historical sales data is classified to obtain clustering results of multiple consumer groups;

[0033] The clustering result and the target product are associated, and the sales trend analysis result of the target product is determined according to the consumer preference change information in the clustering result.

[0034] In a third aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the above aspects when executed by a processor.

[0035] In a fourth aspect, the present disclosure provides a computer program product, including a computer program / instructions, which implements the steps of the method described in the above aspects when the computer program is executed by a processor.

[0036] The present disclosure provides a meal vending cabinet commodity management and control system and a management and control method thereof, the system comprising: an identification device for identifying a target commodity in a meal vending cabinet and obtaining commodity information of the target commodity; a monitoring device for monitoring environmental data in the meal vending cabinet, the environmental data including temperature and humidity data; a management and control device for receiving commodity information fed back by the identification device and environmental data fed back by the monitoring device, and generating an environmental adjustment instruction when the environmental data does not meet the storage conditions of the target commodity; and, based on the shelf life information in the commodity information, determining whether the target commodity is an abnormal commodity, and generating a waste treatment instruction when an abnormal commodity exists; the abnormal commodity includes a spoiled commodity or an expired commodity; a waste treatment device for classifying and storing the abnormal commodity in response to the waste treatment instruction issued by the management and control device. Through the synergistic effect of the identification device, the detection device, the management and control device, and the waste treatment device, the abnormal commodity in the meal vending cabinet is identified and promptly treated, and it is ensured that the target commodity always meets the commodity storage conditions in the meal vending cabinet. Thus, a set of meal vending cabinet commodity management and control mechanism is formed to ensure the quality and safety of the target commodity, reduce food waste, and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0038] Figure 1 A schematic diagram of the composition of a meal vending cabinet commodity management and control system provided in the first embodiment of the present disclosure;

[0039] Figure 2 A flowchart of a method for controlling merchandise in a meal vending cabinet provided in the second embodiment of the present disclosure;

[0040] Figure 3 This is a flowchart of the steps of a method for controlling merchandise in a meal vending cabinet provided in Embodiment 3 of the present disclosure. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0042] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0043] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0044] Embodiment 1

[0045] Figure 1 The schematic diagram of the composition of a meal vending cabinet commodity management and control system provided by the first embodiment of the present disclosure is shown as an example. Figure 1 As shown, in this example, the system includes: an identification device 101, a monitoring device 102, a management and control device 103 and a waste treatment device 104;

[0046] The identification device 101 is used to identify the target commodity in the meal vending cabinet and obtain commodity information of the target commodity;

[0047] A monitoring device 102, for monitoring environmental data in a meal vending cabinet, wherein the environmental data includes temperature and humidity data;

[0048] The management control device 103 is used to receive the commodity information fed back by the identification device and the environmental data fed back by the monitoring device, and generate an environmental adjustment instruction when the environmental data does not meet the storage conditions of the target commodity; and determine whether the target commodity is an abnormal commodity based on the shelf life information in the commodity information, and generate a waste disposal instruction when an abnormal commodity exists; the abnormal commodity includes a spoiled commodity or an expired commodity;

[0049] The waste treatment device 104, in response to the waste treatment instruction issued by the management control device, classifies and stores the abnormal commodities.

[0050] In the embodiment of the present invention, the identification device 101 is used to obtain the commodity information by scanning the commodity RFID and / or commodity barcode of the target commodity; the monitoring device 102 is used to monitor the current environmental data in real time. The commodity information includes: shelf life, commodity attribute information and commodity price.

[0051] It should be noted that commodity RFID refers to the label or chip on the commodity that uses radio frequency identification technology. RFID technology embeds microchips and antennas into commodity labels or packaging, and uses wireless radio frequency signals to transmit and identify information, thereby realizing rapid identification, tracking and management of commodities.

[0052] Product barcode is a coding symbol system widely used in product identification and management. It is usually composed of a set of vertical black stripes and blank spaces, representing different numerical or letter information.

[0053] In the embodiment of the present invention, the waste treatment device 104 is further configured to compress and pack the abnormal commodities when the abnormal commodities are fully loaded.

[0054] Meanwhile, the system also includes: a remote communication device and a cloud device 105;

[0055] The management and control device is connected to the cloud device 105 through the remote communication device, and is used to upload relevant data to the cloud device 105, wherein the relevant data includes environmental data, commodity sales data, and abnormal commodity data, and send a recycling service request to the cloud device 105 to notify the service provider to recycle the abnormal commodities in the waste treatment device 104.

[0056] In an embodiment of the present invention, the operation client can check the sales trend analysis results, product status analysis results, recycling instruction execution status and inventory level of the target product through the cloud device 105, and send the formulated promotion plan through the cloud device 105 after checking. At the same time, the operator can also notify the waste recycling service provider to provide recycling services according to actual conditions.

[0057] In addition, the system further includes: an information display device 106 electrically connected to the management control device 103 .

[0058] In an embodiment of the present invention, the information display device 106 can display the commodity attribute information, commodity price, shelf life information, and promotion plans formulated internally or received from the operation client of the target commodity in the meal vending cabinet, so as to facilitate consumers to understand the target commodity.

[0059] In the embodiment of the present invention, the commodity information of the target commodity on sale is obtained by the identification device 101, and the environmental data of the meal vending cabinet is monitored in real time by the monitoring device 102. Then, the environmental data and the commodity storage conditions in the commodity information are compared by the management and control device 103. When the environmental data does not meet the commodity storage conditions, an environmental adjustment instruction is generated, and the temperature and humidity are adjusted by the control system of the meal vending cabinet until the environmental data meets the commodity storage conditions. In addition, the management and control device 103 is used to determine whether there are abnormal commodities including spoiled commodities or expired commodities in the meal vending cabinet, and when there are abnormal commodities, a waste disposal instruction is generated. After receiving the waste disposal instruction, the waste disposal device 104 will classify and recycle the abnormal commodities.

[0060] In the above-mentioned first embodiment, through the synergistic effect of the identification device 101, the monitoring device 102, the management and control device 103 and the waste treatment device 104, the abnormal commodities in the meal vending cabinet are identified and promptly processed, and the target commodities are ensured to always meet the commodity storage conditions in the meal vending cabinet. Thus, a set of management and control mechanism for meal vending cabinet commodities is formed to ensure the quality and safety of the target commodities, reduce food waste, and improve user experience.

[0061] Embodiment 2

[0062] Figure 2 The following is a flowchart showing a method for controlling a meal vending cabinet commodity provided in the second embodiment of the present disclosure. Figure 2 As shown, in this example, the method is applied to the meal vending cabinet commodity management and control system as in the above-mentioned embodiment 1, and the method steps include:

[0063] S201, obtaining historical environmental data of a meal vending cabinet, and inventory, historical sales data, and historical waste data of a target commodity in the meal vending cabinet;

[0064] The embodiment of the present invention identifies the inventory of the target commodity through the identification device in the meal vending cabinet commodity management and control system, obtains the current environmental data information of the target meal vending cabinet through the monitoring device, and obtains the historical environmental data and historical waste data through the cloud device.

[0065] S202, determining commodity status analysis results of all the target commodities under current environmental data based on the historical environmental data and the historical waste data;

[0066] In the embodiment of the present invention, when the target commodity is known, the commodity status analysis result of the target commodity under different storage conditions is determined through the existing historical environmental data and historical waste data.

[0067] S203, when the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory is adjusted; the abnormal commodities include spoiled commodities or expired commodities;

[0068] In the embodiment of the present invention, when the commodity status analysis result shows that there are abnormal commodities, the spoiled commodities are classified and recycled through the waste treatment device.

[0069] S204, obtaining sales trend analysis results of all the target commodities based on the historical sales data;

[0070] In the embodiment of the present invention, the saved historical sales data can be used to obtain the sales trend of the target product over time and the impact of different combinations of target products on sales, thereby obtaining the sales trend analysis results of the target product.

[0071] S205: Adjust the inventory level according to the sales trend analysis result.

[0072] In the embodiment of the present invention, the method of adjusting the inventory quantity includes replenishing, promoting sales, adjusting the order quantity, and scrapping or donating.

[0073] In the above-mentioned second embodiment, by obtaining the historical environmental data of the meal vending cabinet, as well as the inventory, historical sales data and historical waste data of the target commodity in the meal vending cabinet; based on the historical environmental data and the historical waste data, determining the commodity status analysis results of all the target commodities under the current environmental data; when the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory is adjusted; the abnormal commodities include spoiled commodities or expired commodities; based on the historical sales data, the sales trend analysis results of all the target commodities are obtained; according to the sales trend analysis results, the inventory is adjusted. The identification and timely processing of spoiled commodities in the target meal vending cabinet are realized, and a set of management and control mechanism for meal vending cabinet commodities is formed, which ensures the quality and safety of target commodities, reduces food waste and improves user experience while ensuring a reasonable inventory.

[0074] Embodiment 3

[0075] Figure 3The flowchart of the steps of a method for controlling the commodity in a meal vending cabinet provided in the third embodiment of the present disclosure is shown as an example. Figure 3 As shown, in this example, the method is applied to the meal vending cabinet commodity management and control system as in the above-mentioned embodiment 1, and the method steps include:

[0076] S301, obtaining historical environmental data of a meal vending cabinet, as well as inventory, historical sales data, and historical waste data of a target commodity in the meal vending cabinet;

[0077] S302, dividing the historical environmental data into a plurality of temperature and humidity change sequences of the same duration;

[0078] S303, using the temperature and humidity change sequence as a training sample and the historical waste data as a label, training the constructed commodity state prediction model to obtain a target commodity state prediction model;

[0079] S304, inputting the current environment data into the target commodity state prediction model to obtain the commodity state analysis result;

[0080] S305, when the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory is adjusted; the abnormal commodities include spoiled commodities or expired commodities;

[0081] S306, obtaining sales trend analysis results of all the target commodities based on the historical sales data;

[0082] The embodiment of the present invention analyzes historical sales data through preset algorithms including time series analysis algorithm, association rule algorithm, clustering algorithm, classification algorithm and optimization algorithm, so as to obtain sales trend analysis results of target commodities. Among them, the time series analysis algorithm aims to predict the sales volume of target commodities in a certain time period in order to adjust inventory; the association rule algorithm aims to discover the association rules between target commodities, so as to bundle and promote target commodities; the clustering algorithm aims to divide consumers into different groups, so as to carry out targeted marketing activities for consumers in different groups; the classification algorithm aims to classify target commodities according to sales speed, shelf life information and consumer preferences; the optimization algorithm aims to determine and calculate the best commodity order quantity and replenishment time, as well as determine the best waste recycling time and frequency.

[0083] When using the time series analysis algorithm for analysis, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0084] Performing seasonal separation on the historical sales data to obtain seasonally adjusted historical sales data;

[0085] Using the seasonally adjusted historical sales data to train the initially constructed first sales trend analysis and prediction model to obtain a first target sales trend analysis and prediction model;

[0086] The sales trend analysis result at the current time point is obtained through the first target sales trend analysis and prediction model.

[0087] In the specific implementation, after preprocessing the historical sales data including cleaning, processing missing values ​​and outliers, the historical sales data is seasonally decomposed through the STL algorithm to obtain seasonally adjusted historical sales data. The data includes three parts: seasonal changes, trends and residuals. The seasonal change part reflects the cyclical fluctuations within a specific time period, the trend part represents the changes in the long-term trend, and the residual part contains random fluctuations that are not explained by the trend and seasonal models.

[0088] The seasonally adjusted historical sales data is used to train the constructed time series model, namely the first sales trend analysis and prediction model. During the iterative training process, the model parameters are continuously adjusted to obtain the target first sales trend analysis and prediction model. Finally, the sales trend at the current time point is predicted through the first target sales trend analysis and prediction model to obtain the sales trend analysis results.

[0089] It should be noted that during the training process, the model fitting effect needs to be continuously evaluated, such as using residual analysis and other techniques to check whether the model residuals meet the model assumptions. Through such seasonal adjustment and model selection and fitting process, the seasonality, trend and random components in sales data can be better understood and predicted.

[0090] When using the association rule algorithm for analysis, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0091] Extracting frequent item sets from the historical sales data and generating association rules for the frequent item sets;

[0092] Calculating the confidence of the association rule, and combining the confidence threshold to filter out the target association rule;

[0093] Based on the target rule, the sales trend analysis result of the target commodity is determined.

[0094] In the specific implementation, the historical sales data is converted into transaction data form suitable for association rule mining, and then the FP-Growth algorithm is used to construct a frequent pattern tree, recursively mine frequent item sets according to the FP tree, and generate association rules for each frequent item set. For each association rule, its confidence is calculated, and finally, according to the pre-set confidence threshold, the target association rules are screened out, combined with the target products in the current target meal vending cabinet, to obtain the corresponding sales trend analysis results.

[0095] When using a clustering algorithm for analysis, based on the historical sales data, the sales trend analysis results of all the target products are obtained, including:

[0096] Using a clustering algorithm, the historical sales data is classified to obtain clustering results of multiple consumer groups;

[0097] The clustering result and the target product are associated, and the sales trend analysis result of the target product is determined according to the consumer preference change information in the clustering result.

[0098] In the specific implementation, the K-Means clustering algorithm is used to perform cluster analysis on customers in historical sales data, identify different sales groups, and then combine the target products to obtain their sales trend analysis results.

[0099] S307: Adjust the inventory level according to the sales trend analysis result.

[0100] A method for controlling commodities in a meal vending cabinet disclosed in an embodiment of the present invention obtains historical environmental data of a meal vending cabinet, as well as the inventory, historical sales data, and historical waste data of a target commodity in the meal vending cabinet; based on the historical environmental data and the historical waste data, determines the commodity status analysis results of all the target commodities under the current environmental data; when the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory is adjusted; the abnormal commodities include spoiled commodities or expired commodities; based on the historical sales data, the sales trend analysis results of all the target commodities are obtained; and according to the sales trend analysis results, the inventory is adjusted. Through a variety of preset algorithms, analysis is performed based on historical sales data to obtain the sales trend analysis results of the target commodities, thereby ensuring the quality and safety of the target commodities, reducing food waste, and improving user experience while ensuring a reasonable inventory.

[0101] Embodiment 4

[0102] This embodiment provides a computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented, and the method is applied to the meal vending cabinet commodity management and control system described in the above embodiment 1, and the method includes:

[0103] Obtaining historical environmental data of a meal vending cabinet, as well as inventory, historical sales data, and historical waste data of a target product in the meal vending cabinet;

[0104] Determine commodity status analysis results of all the target commodities under current environmental data based on the historical environmental data and the historical waste data;

[0105] When the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory quantity is adjusted; the abnormal commodities include spoiled commodities or expired commodities;

[0106] Based on the historical sales data, obtain sales trend analysis results of all the target commodities;

[0107] The inventory level is adjusted according to the sales trend analysis result.

[0108] In an optional embodiment, based on the historical environmental data and the historical waste data, determining the commodity status analysis results of all the target commodities under the current environmental data includes:

[0109] Dividing the historical environmental data into a plurality of temperature and humidity change sequences of the same duration;

[0110] Using the temperature and humidity change sequence as training samples and the historical waste data as labels, the constructed commodity state prediction model is trained to obtain a target commodity state prediction model;

[0111] The current environment data is input into the target commodity state prediction model to obtain the commodity state analysis result.

[0112] In an optional embodiment, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0113] Performing seasonal separation on the historical sales data to obtain seasonally adjusted historical sales data;

[0114] Using the seasonally adjusted historical sales data to train the initially constructed first sales trend analysis and prediction model to obtain a first target sales trend analysis and prediction model;

[0115] The sales trend analysis result at the current time point is obtained through the first target sales trend analysis and prediction model.

[0116] In an optional embodiment, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0117] Extracting frequent item sets from the historical sales data and generating association rules for the frequent item sets;

[0118] Calculating the confidence of the association rule, and combining the confidence threshold to filter out the target association rule;

[0119] Based on the target rule, the sales trend analysis result of the target commodity is determined.

[0120] In an optional embodiment, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0121] Using a clustering algorithm, the historical sales data is classified to obtain clustering results of multiple consumer groups;

[0122] The clustering result and the target product are associated, and the sales trend analysis result of the target product is determined according to the consumer preference change information in the clustering result.

[0123] Embodiment 5

[0124] This embodiment provides a computer program product, including a computer program / instruction. When the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented. The computer program is applied to the meal vending cabinet commodity management and control system described in the above embodiment 1. The method includes:

[0125] Obtaining historical environmental data of a meal vending cabinet, as well as inventory, historical sales data, and historical waste data of a target product in the meal vending cabinet;

[0126] Determine commodity status analysis results of all the target commodities under current environmental data based on the historical environmental data and the historical waste data;

[0127] When the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory quantity is adjusted; the abnormal commodities include spoiled commodities or expired commodities;

[0128] Based on the historical sales data, obtain sales trend analysis results of all the target commodities;

[0129] The inventory level is adjusted according to the sales trend analysis result.

[0130] In an optional embodiment, based on the historical environmental data and the historical waste data, determining the commodity status analysis results of all the target commodities under the current environmental data includes:

[0131] Dividing the historical environmental data into a plurality of temperature and humidity change sequences of the same duration;

[0132] Using the temperature and humidity change sequence as training samples and the historical waste data as labels, the constructed commodity state prediction model is trained to obtain a target commodity state prediction model;

[0133] The current environment data is input into the target commodity state prediction model to obtain the commodity state analysis result.

[0134] In an optional embodiment, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0135] Performing seasonal separation on the historical sales data to obtain seasonally adjusted historical sales data;

[0136] Using the seasonally adjusted historical sales data to train the initially constructed first sales trend analysis and prediction model to obtain a first target sales trend analysis and prediction model;

[0137] The sales trend analysis result at the current time point is obtained through the first target sales trend analysis and prediction model.

[0138] In an optional embodiment, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0139] Extracting frequent item sets from the historical sales data and generating association rules for the frequent item sets;

[0140] Calculating the confidence of the association rule, and combining the confidence threshold to filter out the target association rule;

[0141] Based on the target rule, the sales trend analysis result of the target commodity is determined.

[0142] In an optional embodiment, based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including:

[0143] Using a clustering algorithm, the historical sales data is classified to obtain clustering results of multiple consumer groups;

[0144] The clustering result and the target product are associated, and the sales trend analysis result of the target product is determined according to the consumer preference change information in the clustering result.

[0145] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components to execute the method in the above embodiments.

[0146] The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, and the computer-readable storage medium may include but is not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0147] The computer-readable storage medium may also store at least one computer executable program / instruction, which may be, for example, a computer-readable instruction. The computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The computer-readable storage medium may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0148] In addition, the computer device may also include (but not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.), etc.

[0149] The processor may communicate with external devices via an I / O bus via a wired or wireless network.

[0150] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0151] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0152] It should be noted that in the present disclosure, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element limited by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0153] Although the embodiments disclosed in the present disclosure are as above, the above contents are only embodiments adopted for facilitating the understanding of the present disclosure and are not intended to limit the present disclosure. Any technician in the technical field to which the present disclosure belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present disclosure, but the scope of patent protection of the present disclosure shall still be subject to the scope defined in the attached claims.

Claims

1. A food vending cabinet commodity management and control system, characterized in that: include: An identification device, used to identify a target commodity in a meal vending cabinet and obtain commodity information of the target commodity; A monitoring device, used to monitor environmental data in a meal vending cabinet, wherein the environmental data includes temperature and humidity data; A management control device, configured to receive the commodity information fed back by the identification device and the environmental data fed back by the monitoring device, and to generate an environmental adjustment instruction when the environmental data does not meet the storage conditions of the target commodity; and to determine whether the target commodity is an abnormal commodity based on the shelf life information in the commodity information, and to generate a waste disposal instruction when an abnormal commodity exists; the abnormal commodity includes a spoiled commodity or an expired commodity; The waste treatment device, in response to the waste treatment instruction issued by the management control device, classifies and stores the abnormal commodities.

2. The meal vending cabinet commodity management and control system according to claim 1, characterized in that: It also includes remote communication devices and cloud equipment; The management and control device is communicatively connected to the cloud device via the remote communication device, and is used to upload relevant data to the cloud device, wherein the relevant data includes environmental data, commodity sales data, and abnormal commodity data, and to send a recycling service request to the cloud device to notify the service provider to recycle the abnormal commodities in the waste treatment device.

3. The meal vending cabinet commodity management and control system according to claim 1, characterized in that: Also includes: An information display device is electrically connected to the management control device.

4. A meal vending cabinet commodity control method implemented based on the meal vending cabinet commodity control system according to claims 1 to 3, characterized in that: The method comprises: Obtaining historical environmental data of a meal vending cabinet, as well as inventory, historical sales data, and historical waste data of a target product in the meal vending cabinet; Determine commodity status analysis results of all the target commodities under current environmental data based on the historical environmental data and the historical waste data; When the commodity status analysis result shows that there are abnormal commodities, the abnormal commodities are classified and recycled, and the inventory quantity is adjusted; the abnormal commodities include spoiled commodities or expired commodities; Based on the historical sales data, obtain sales trend analysis results of all the target commodities; The inventory level is adjusted according to the sales trend analysis result.

5. The method for controlling the commodities in the meal vending cabinet according to claim 4, characterized in that: Based on the historical environmental data and the historical waste data, determining commodity status analysis results of all the target commodities under the current environmental data, including: Dividing the historical environmental data into a plurality of temperature and humidity change sequences of the same duration; Using the temperature and humidity change sequence as training samples and the historical waste data as labels, the constructed commodity state prediction model is trained to obtain a target commodity state prediction model; The current environment data is input into the target commodity state prediction model to obtain the commodity state analysis result.

6. The method for controlling the commodities in the meal vending cabinet according to claim 4, characterized in that: Based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including: Performing seasonal separation on the historical sales data to obtain seasonally adjusted historical sales data; Using the seasonally adjusted historical sales data to train the initially constructed first sales trend analysis and prediction model to obtain a first target sales trend analysis and prediction model; The sales trend analysis result at the current time point is obtained through the first target sales trend analysis and prediction model.

7. The method for controlling the commodities in the meal vending cabinet according to claim 4, characterized in that: Based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including: Extracting frequent item sets from the historical sales data and generating association rules for the frequent item sets; Calculating the confidence of the association rule, and combining the confidence threshold to filter out the target association rule; Based on the target association rule, the sales trend analysis result of the target commodity is determined.

8. The method for controlling food vending cabinet commodities according to claim 4, characterized in that: Based on the historical sales data, the sales trend analysis results of all the target commodities are obtained, including: Using a clustering algorithm, the historical sales data is classified to obtain clustering results of multiple consumer groups; The clustering result and the target product are associated, and the sales trend analysis result of the target product is determined according to the consumer preference change information in the clustering result.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 4 to 8 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 4 to 8 are implemented.

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