Vending machine visual goods arrangement method and system

Abstract

The invention discloses a visual goods delivery method and system for a vending machine, and the method comprises the steps: receiving a user checking calculation request sent by a front end of the vending machine through REST API, the parameters of the user checking calculation request comprise a model ID, a goods channel parameter and a goods parameter, and carrying out the format verification and necessary item inspection of the parameters of the user checking calculation request; according to the model ID, obtaining a corresponding checking calculation implementation class from a strategy factory, loading a checking calculation rule of a set model, and initializing a checking calculation environment and related parameters; and executing a checking calculation process which comprises basic parameter verification, model characteristic verification and commodity matching verification, summarizing checking calculation results, generating a checking calculation report, and returning response data in a standard format to a user at the front end of the vending machine. The problems that in the prior art, standard criteria are lacked, real-time preview verification cannot be achieved, and manual checking calculation is low in efficiency and prone to errors are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of automatic vending machines, and in particular relates to a method and system for visually arranging goods for automatic vending machines. Background Art

[0002] With the widespread adoption of vending machines, issues with aisle layout and product matching are becoming increasingly prominent. Aisle designs vary significantly across different vending machine models, resulting in complex verification rules that are difficult for humans to accurately master. Furthermore, the industry lacks unified, standardized verification criteria, leading to frequent mismatches between products and aisles. This not only impacts product delivery, but can also damage equipment and reduce product quality.

[0003] Furthermore, traditional scheduling methods lack the ability to preview and verify scheduling results in a timely manner. After completing scheduling, operators often have to wait until actual sales begin to discover any issues, which wastes significant time and manpower. Furthermore, manual verification is inefficient and prone to errors, making it difficult to guarantee accurate results when faced with a large volume of product and channel information.

[0004] In summary, the existing vending machine aisle verification and product arrangement methods can no longer meet the needs of industry development. An intelligent solution is urgently needed to improve the rationality of aisle layout and product adaptability. Summary of the Invention

[0005] To this end, the present invention provides a method and system for visual arrangement of goods for vending machines, which solve the problems existing in the prior art such as lack of standard criteria, inability to preview and verify in real time, and inefficient and error-prone manual verification.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a method for visually arranging goods for a vending machine, comprising:

[0007] Receive a user verification request sent by the vending machine front end through the REST API. The parameters of the user verification request include the machine model ID, channel parameters, and product parameters. Perform format verification and mandatory field check on the parameters of the user verification request.

[0008] Obtain the corresponding verification implementation class from the strategy factory based on the model ID, load the verification rules for the set model, and initialize the verification environment and related parameters;

[0009] Execute the verification process, including basic parameter verification, model feature verification, and product matching verification. The basic parameter verification includes checking aisle size parameters, verifying product specifications, and calculating basic matching. The model feature verification includes verifying aisle load capacity, checking temperature control requirements, and evaluating space utilization. The product matching verification includes calculating the compatibility of products and aisles, evaluating product placement, and generating optimization suggestions.

[0010] Summarize the verification results, generate a verification report, and return response data in a standard format to the user at the vending machine front end.

[0011] As a preferred solution for the visual arrangement method of vending machines, in the basic parameter verification, the formula for calculating the basic matching degree M is:

[0012]

[0013] Among them, V s is the volume of the product, V h is the volume that the cargo lane can accommodate, α and β are weight coefficients, 0<α, β<1 and ɑ+β=1, S jc is the contact area between the product and the bottom of the aisle, S hd is the bottom area of the cargo aisle.

[0014] As the preferred solution for the visual arrangement method of vending machines, during the process of verifying the product specification parameters, the product weight W s and the load-bearing capacity of the cargo lane W c The relationship between s ≤W c ×γ is used for verification, where γ is the safety bearing factor 0<γ<1.

[0015] As a preferred solution for the visual arrangement method of vending machines, in the model characteristic verification, the formula for evaluating the space utilization U is:

[0016]

[0017] Among them, n is the number of goods in the aisle, V si is the volume of the i-th product, V hz is the total volume of the cargo aisle.

[0018] As a preferred solution for the visual arrangement method of vending machines, in the product matching verification, the formula for calculating the compatibility between the product and the aisle is:

[0019]

[0020] Among them, L s 、W s 、H s They are the length, width and height of the product respectively. h 、W h 、H h are the length, width and height of the cargo aisle respectively; ω1, ω2 and ω3 are weight factors, 0<ω1, ω2, ω3<1 and ω1+ω2+ω3=1.

[0021] As a preferred solution for the method of visual arrangement of goods for vending machines, during the process of checking the size parameters of the goods aisle, the length L of the goods aisle is checked. h , width W h , height H h Parameter, if L min ≤L h ≤L max , and W min ≤W h ≤W max , H min ≤H h ≤H max , then the cargo lane size parameters meet the standards, L min , L max 、W min 、W max 、H min 、H max These are the standard minimum and maximum values for the length, width, and height of the aisle respectively.

[0022] As a preferred solution for the method of visual arrangement of goods for vending machines, during the process of verifying the commodity specification parameters, the length L of the commodity is verified. s 、Width W s , high H s and weight W s Parameter, if L smin ≤L s ≤L smax , and W smin ≤W s ≤W smax , H smin ≤H s ≤H smax , W s ≤W xz , then the product specifications are determined to be in compliance with the regulations, L smin , L smax 、W smin 、W smax 、H smin 、H smax The distribution is the minimum and maximum values allowed for the length, width, and height of the product, W xz The maximum weight allowed for the product.

[0023] As a preferred solution for the method of visual arrangement of goods for vending machines, in the verification of the characteristics of the model, the load-bearing capacity of the goods channel is verified to be the maximum load-bearing capacity W determined according to the material and structure of the goods channel. c , judge W s ≤W c Is it established to determine whether the cargo lane can bear the weight of the goods;

[0024] The temperature control requirement is to determine the current temperature T of the cargo channel.h Is it within the temperature range required for product storage [T min ,T max ], that is, T min ≤T h ≤T max , if the temperature environment of the cargo aisle meets the storage requirements of the goods.

[0025] As a preferred solution for the method of visual arrangement of goods for vending machines, when generating optimization suggestions, if the compatibility between the goods and the aisle F is lower than the set threshold F yz , it is recommended to adjust the product placement angle, the adjustment formula is θ x =θ y +Δθ,θ x is the adjusted product placement angle, θ y is the product placement angle before adjustment, and Δθ is the angle adjustment amount determined by the adaptability difference and the aisle space conditions.

[0026] The present invention also provides a system for visually arranging goods for a vending machine, which adopts the above-mentioned method for visually arranging goods for a vending machine, comprising:

[0027] A request receiving module is used to receive user verification requests sent by the vending machine front end through the REST API. The parameters of the user verification request include the machine model ID, channel parameters, and product parameters, and perform format verification and mandatory field checking on the parameters of the user verification request;

[0028] The strategy selection module is used to obtain the corresponding verification implementation class from the strategy factory according to the model ID, load the verification rules of the set model, and initialize the verification environment and related parameters;

[0029] The verification execution module is used to execute the verification process, including basic parameter verification, model feature verification, and product matching verification. The basic parameter verification includes checking the aisle size parameters, verifying the product specification parameters, and calculating the basic matching degree; the model feature verification includes verifying the aisle load capacity, checking the temperature control requirements, and evaluating the space utilization rate; the product matching verification includes calculating the compatibility of the product and the aisle, evaluating the product placement method, and generating optimization suggestions;

[0030] The result response module is used to summarize the verification results, generate a verification report, and return response data in a standard format to the user at the front end of the vending machine.

[0031] As a preferred solution for the visual arrangement system of vending machines, the formula for calculating the basic matching degree M in the verification execution module is:

[0032]

[0033] Among them, Vs is the volume of the product, V h is the volume that the cargo lane can accommodate, α and β are weight coefficients, 0<α, β<1 and α+β=1, S jc is the contact area between the product and the bottom of the aisle, S hd is the bottom area of the cargo aisle.

[0034] As a preferred solution for the visual arrangement system of vending machines, in the verification execution module, for the weight of the product W s and the load-bearing capacity of the cargo lane W c The relationship between s ≤W c ×γ is used for verification, where γ is the safety bearing factor 0<γ<1.

[0035] As a preferred solution for the visual arrangement system of vending machines, the formula for evaluating the space utilization U in the verification execution module is:

[0036]

[0037] Among them, n is the number of goods in the aisle, V si is the volume of the i-th product, V hz is the total volume of the cargo aisle.

[0038] As a preferred solution for the visual arrangement system of vending machines, the formula for calculating the compatibility between goods and aisles in the verification execution module is:

[0039]

[0040] Among them, L s 、W s 、H s They are the length, width and height of the product respectively. h 、W h 、H h are the length, width and height of the cargo aisle respectively; ω1, ω2 and ω3 are weight factors, 0<ω1, ω2, ω3<1 and ω1+ω2+ω3=1.

[0041] As a preferred solution for the visual arrangement system of vending machines, the length L of the aisle is checked in the verification execution module. h , width W h , height H h Parameter, if L min ≤L h ≤L max , and W min ≤W h ≤W max , H min ≤H h ≤H max, then the cargo lane size parameters meet the standards, L min , L max 、W min 、W max 、H min 、H max These are the standard minimum and maximum values for the length, width, and height of the aisle respectively.

[0042] As a preferred solution for the vending machine visual arrangement system, the verification execution module verifies the length L of the product. s 、Width W s , high H s and weight W s Parameter, if L smin ≤L s ≤L smax , and W smin ≤W s ≤W smax , H smin ≤H s ≤H smax , W s ≤W xz , then it is determined that the product specifications meet the requirements, L smin , L smax 、W smin 、W smax 、H smin 、H smax The distribution is the minimum and maximum values allowed for the length, width, and height of the product, W xz The maximum weight allowed for the product.

[0043] As the preferred solution of the vending machine visual arrangement system, in the verification execution module, the load-bearing capacity of the cargo channel is verified to be the maximum load-bearing capacity W determined according to the material and structure of the cargo channel. c , judge W s ≤W c Is it established to determine whether the cargo lane can bear the weight of the goods;

[0044] The temperature control requirement is to determine the current temperature T of the cargo channel. h Is it within the temperature range required for product storage [T min ,T max ], that is, T min ≤T h ≤T max , if the temperature environment of the cargo aisle meets the storage requirements of the goods.

[0045] As a preferred solution for the visual arrangement system of vending machines, in the verification execution module, if the compatibility degree F between the product and the aisle is lower than the set threshold F yz , it is recommended to adjust the product placement angle, the adjustment formula is θx =θ y +Δθ,θ x is the adjusted product placement angle, θ y is the product placement angle before adjustment, and Δθ is the angle adjustment amount determined by the adaptability difference and the aisle space conditions.

[0046] The beneficial effects of the present invention are as follows:

[0047] First, by receiving verification requests through the REST API and using the Policy Factory to load specific verification rules for different models, we achieve automated and intelligent aisle verification. Compared to traditional manual verification, this can quickly process a large number of requests, significantly improving efficiency and reducing inventory verification time from hours or even days to minutes. It also effectively avoids manual errors, reducing the error rate to an extremely low level, and ensuring the precise matching of products and aisles.

[0048] Second, it provides real-time verification and feedback on stocking plans. Through multiple steps, including basic parameter verification, model feature verification, and product matching verification, it comprehensively assesses the compatibility of products and aisles. Once problems are identified, optimization suggestions are immediately generated, such as adjusting product placement angles or changing aisles. This helps operators adjust stocking plans promptly, avoiding problems such as aisle congestion and product damage during actual operations, thereby improving the accuracy and reliability of stocking plans.

[0049] Third, precise aisle calculations and optimized product placement can improve aisle space utilization and reduce damage and waste caused by improper product placement. This also avoids equipment failures and repair costs caused by aisle blockages, reducing resource consumption and operational costs. Standardized calculation processes and methods make aisle layouts and product matching comparable and universal across different companies' vending machines, promoting the healthy development of the industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and those skilled in the art can, without inventive effort, derive other implementation drawings based on the provided drawings.

[0051] The structures, proportions, sizes, etc. illustrated in this specification are intended solely to complement the contents disclosed herein and to facilitate understanding and reading by persons skilled in the art. They are not intended to limit the conditions under which the present invention may be implemented and therefore have no substantive technical significance. Any structural modifications, changes in proportions, or adjustments in sizes, without affecting the efficacy and objectives of the present invention, shall remain within the scope of the technical contents disclosed herein.

[0052] Figure 1 A schematic diagram of the process flow of a method for visually arranging goods for a vending machine provided by an embodiment of the present invention;

[0053] Figure 2 An interactive flow chart of a method for visually arranging goods for a vending machine provided by an embodiment of the present invention;

[0054] Figure 3 The application architecture of the method for visually arranging goods for a vending machine provided in an embodiment of the present invention;

[0055] Figure 4 This is a schematic diagram of the architecture of a visual inventory arrangement system for vending machines provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following describes the implementation of the present invention using specific embodiments. Those skilled in the art will readily understand the other advantages and benefits of the present invention from the disclosure herein. Obviously, the embodiments described are only a portion of the present invention, not all of it. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are intended to fall within the scope of protection of the present invention.

[0057] Example 1

[0058] See also Figure 1 Embodiment 1 of the present invention provides a method for visually arranging goods for a vending machine, comprising the following steps:

[0059] S1. Receive the user verification request sent by the vending machine front end through the REST API. The parameters of the user verification request include the machine model ID, channel parameters, and product parameters. Perform format verification and mandatory item check on the parameters of the user verification request.

[0060] Specifically, the REST API (Representational State Transfer Application Programming Interface) is a lightweight API design style based on the HTTP protocol, characterized by simplicity, efficiency, and ease of extensibility. In the vending machine visual scheduling system, the REST API is used to receive verification requests from the front-end, enabling convenient communication with various front-end devices and systems. The vending machine front-end encapsulates the user's verification request into an HTTP request compliant with the REST API specification and sends it to the back-end system. The model ID in the request parameter is used to identify different vending machine models, as different models may have different aisle parameters and verification rules. Aisle parameters include information such as aisle dimensions, load capacity, and temperature; product parameters include product dimensions, weight, and temperature requirements. Format validation and mandatory field checking are performed on these parameters to ensure the completeness and accuracy of the received request data, preventing errors from causing subsequent verification processes. For example, if the product weight parameter is formatted incorrectly or omitted, it may affect the verification results of the aisle's load capacity.

[0061] S2. Obtain the corresponding verification implementation class from the strategy factory according to the model ID, load the verification rules of the set model, and initialize the verification environment and related parameters.

[0062] Specifically, the strategy factory pattern is a design pattern that can separate the creation and use of objects, and create different types of objects through a factory class. In the present invention, the strategy factory selects a suitable class from the pre-defined verification implementation class based on the model ID. Different models may have different aisle designs and verification rules. For example, the aisle size, load-bearing capacity and temperature control requirements of small snack vending machines and large beverage vending machines are different. The corresponding verification implementation class can be accurately found through the model ID, which encapsulates the specific verification rules of the model. After loading these rules, the system will initialize the verification environment and related parameters, such as setting the initial weight coefficient, threshold, etc., to prepare for the subsequent verification process. The advantage of this is that the system has good scalability. When a new model is added, it is only necessary to register the corresponding verification implementation class in the strategy factory.

[0063] S3. Execute the verification process, including basic parameter verification, model feature verification, and product matching verification. The basic parameter verification includes checking aisle size parameters, verifying product specification parameters, and calculating basic matching degree. The model feature verification includes verifying aisle load capacity, checking temperature control requirements, and evaluating space utilization. The product matching verification includes calculating the compatibility between products and aisles, evaluating product placement, and generating optimization suggestions.

[0064] Specifically, the verification process is a core component of the entire stocking scheduling method, ensuring that products are appropriately placed in the aisles through multiple verification dimensions. Basic parameter verification is the most fundamental verification step. Checking aisle dimensions ensures that the aisle is large enough to accommodate the products. Verifying product specifications ensures that product size and weight meet aisle requirements. Calculating basic fit comprehensively considers product volume and contact area with the aisle floor, providing a comprehensive assessment of the initial compatibility between products and aisles. Model feature verification considers the specific requirements of different aircraft models. Verifying aisle load capacity prevents damage to the aisles due to excessive weight. Checking temperature control requirements ensures that products are stored at appropriate temperatures to prevent spoilage. Assessing space utilization improves aisle efficiency and reduces wasted space. Product matching verification further refines product-aisle compatibility, calculating product-aisle fit based on multiple dimensions: length, width, and height. Evaluating product placement identifies the optimal placement solution, facilitating smoother shipments. Optimization suggestions provide improvement strategies for situations where fit requirements are not met.

[0065] S4. Summarize the verification results, generate a verification report, and return response data in a standard format to the user at the front end of the vending machine.

[0066] Specifically, after completing all the verification steps, the results of each verification link are summarized. The results of basic parameter verification, model feature verification, and product matching verification are integrated to analyze the overall compatibility of products and aisles. Generating a verification report can intuitively display the verification results. The report may include the matching score between products and aisles, items that do not meet the requirements, and corresponding optimization suggestions. Returning response data in a standard format to the user at the front end of the vending machine is to facilitate the front-end system to process and display the results. Data in a standard format can ensure that different front-end devices and systems can correctly parse and use these results, thereby improving the versatility and compatibility of the system. For example, the front-end system can display the verification results in the form of charts or text on the interface based on the response data, so that users can clearly understand the compatibility of products and aisles.

[0067] In a possible embodiment, in step S3, in the basic parameter verification, the formula for calculating the basic matching degree is: Among them, V s is the volume of the product, V h is the volume that the cargo lane can accommodate, ɑ and β are weight coefficients, 0<ɑ, β<1 and ɑ+β=1, S jc is the contact area between the product and the bottom of the aisle, S hd is the bottom area of the cargo aisle.

[0068] Specifically, the basic matching degree M is used to measure the initial degree of adaptation between the product and the aisle in terms of volume and contact area. It indicates the ratio of the product volume to the aisle's capacity. The larger the ratio, the closer the product is to the aisle's capacity. However, if it exceeds a certain range, it may lead to aisle space shortage or the inability to properly place the product. This represents the ratio of the contact area between the product and the aisle floor to the total area of the aisle floor. This ratio reflects the stability of the product within the aisle; the larger the contact area, the more stable the product placement within the aisle. The weighting coefficients ɑ and β adjust the importance of the volume ratio and contact area ratio in the basic matching degree calculation. Since ɑ + β = 1, the combined impact of these two factors on the basic matching degree is determined. For example, if ɑ is large, the volume factor plays a higher role in the basic matching degree; if β is large, the contact area factor is more important. By appropriately setting the weighting coefficients, the basic matching degree calculation method can be flexibly adjusted according to actual conditions.

[0069] In a possible embodiment, in step S3, during the process of verifying the product specification parameters, the product weight W s And the load-bearing capacity of the cargo channel W c The relationship between s ≤W c ×γ is used for verification, where γ is the safety bearing factor, 0<γ<1.

[0070] Specifically, when verifying product specifications, the relationship between product weight and the load-bearing capacity of the cargo aisle is crucial. The load-bearing capacity of the cargo aisle is the maximum weight it can bear, determined by its material and structure. However, in order to ensure the long-term stable use and safety of the cargo aisle, a safety load-bearing factor γ needs to be introduced. c The value obtained by ×γ is the actual weight that the cargo lane can bear within the safety range. s ≤W c Whether ×γ holds true can determine whether the product weight is within the safe aisle load range. If the product weight exceeds this safe range, the aisle may deform or be damaged, affecting the normal shipment of goods and the lifespan of the vending machine. The safe load factor γ ranges from 0 < γ < 1. Smaller values indicate higher safety requirements for the aisle load; larger values relax the load restrictions on the aisle, but also increase the risk of damage. Therefore, it is necessary to reasonably set the safe load factor based on actual conditions.

[0071] In a possible embodiment, in step S3, in the model characteristic verification, the formula for evaluating the space utilization U is: Among them, n is the number of goods in the aisle, V si is the volume of the i-th product, V hz is the total volume of the cargo aisle.

[0072] Specifically, the space utilization rate U is used to measure the efficiency of space usage within the cargo aisle. Indicates the total volume of all goods in the aisle, V hz is the total volume of the aisle. By calculating the ratio of the two and multiplying by 100%, we can obtain the percentage of space utilization. A higher space utilization rate indicates that the space in the aisle is being fully utilized. However, excessive space utilization may lead to crowded product placement, affecting smooth shipment. Therefore, it is necessary to maximize space utilization while ensuring normal shipment. For example, by rationally planning product placement and selecting the right product mix, aisle space utilization can be improved.

[0073] In a possible embodiment, in step S3, during the product matching verification, the formula for calculating the compatibility F between the product and the channel is: Among them, L s 、W s 、H s They are the length, width and height of the product respectively. h 、W h 、H h are the length, width and height of the cargo aisle respectively; ω1, ω2 and ω3 are weight factors, 0<ω1, ω2, ω3<1 and ω1+ω2+ω3=1.

[0074] Specifically, the fit F between the product and the aisle comprehensively considers the proportional relationship between the length, width, and height of the product and the corresponding dimensions of the aisle. and The weighting factors ω1, ω2, and ω3 are used to adjust the importance of the length, width, and height ratios in the aisle's length, width, and height, respectively. These ratios reflect the product's fit within the aisle along each dimension. Since ω1 + ω2 + ω3 = 1, they collectively determine the combined impact of the three dimensions on fit. For example, if ω1 is large, the product's length plays a larger role in fit; if ω2 is large, the width factor is more important. By properly setting these weighting factors, the fit calculation method can be flexibly adjusted based on the characteristics of different products and the actual aisle conditions, allowing for a more accurate assessment of the fit between products and aisles.

[0075] In a possible embodiment, in step S3, during the process of checking the aisle size parameters, the length L of the aisle is checked. h , width W h , height H h Parameter, if L min ≤L h ≤L max , and W min ≤W h ≤W max , H min ≤Hh ≤H max , then the cargo lane size parameters meet the standards, L min , L max 、W min 、W max 、H min 、H max These are the standard minimum and maximum values for the length, width, and height of the aisle respectively.

[0076] Specifically, checking the size parameters of the cargo aisle is the basis for ensuring that the cargo aisle can be used normally. Each cargo aisle has its own standard size range. By setting L min , L max 、W min 、W max 、H min 、H max To define this range. If the length, width, and height parameters of the aisle are within the corresponding standard range, the aisle dimensions meet the requirements and can be used to place goods normally. If the aisle dimensions exceed the standard range, it may prevent the goods from being properly placed or make shipment difficult. For example, if the aisle length is shorter than the length of the goods, the goods will not fit in the aisle; if the aisle width is too large, the goods may shake in the aisle, affecting the stability of shipment.

[0077] In a possible embodiment, in step S3, during the verification of product specification parameters, the length L of the product is verified. s 、Width W s , high H s and weight W s Parameter, if L smin ≤L s ≤L smax , and W smin ≤W s ≤W smax , H smin ≤H s ≤H smax , W s ≤W xz , then the product specifications are determined to be in compliance with the regulations, L smin , L smax 、W smin 、W smax 、H smin 、H smax The distribution is the minimum and maximum values allowed for the length, width, and height of the product, W xz The maximum weight allowed for the product.

[0078] Specifically, the purpose of verifying product specifications is to ensure that the size and weight of the product meet the requirements of the channel. Each product has its own reasonable size and weight range. By setting Lsmin , L smax 、W smin 、W smax 、H smin 、H smax and W xz To define this range. If the length, width, height, and weight of the product are within the corresponding allowable range, it means that the product specifications meet the regulations and can be safely placed in the aisle. If the product is too large or too heavy, it may cause the aisle to be blocked, damaged, or unable to be shipped normally. For example, if the height of the product exceeds the height of the aisle, the product will not be able to be placed in the aisle; if the weight of the product exceeds the load-bearing capacity of the aisle, the aisle may be damaged. Therefore, strict verification of product specifications can improve the operational efficiency and reliability of vending machines.

[0079] In a possible embodiment, in step S3, in the aircraft model characteristic verification, it is verified that the load-bearing capacity of the cargo lane is the maximum load-bearing capacity W determined according to the material and structure of the cargo lane. c , judge W s ≤W c Is it established to determine whether the cargo aisle can bear the weight of the goods; the temperature control requirement is to determine the current temperature T of the cargo aisle h Is it within the temperature range required for product storage [T min ,T max ], that is, T min ≤T h ≤T max , if the temperature environment of the cargo aisle meets the storage requirements of the goods.

[0080] Specifically, the maximum load-bearing capacity of the cargo channel is W c It is determined based on its material and structural design, and by judging the weight of the product W s Is it less than or equal to W? c , you can determine whether the aisle can bear the weight of the goods. If the weight of the goods exceeds the maximum load-bearing capacity of the aisle, it may cause the aisle to deform or be damaged, affecting the normal delivery of the goods and the service life of the vending machine. Checking the temperature control requirements is to ensure that the goods are stored in a suitable temperature environment. Different goods have different requirements for storage temperature. By setting the temperature range [T min ,T max ] to define the appropriate temperature for commodity storage. Determine the current temperature T of the aisle h Is it within this range? If it is, it means the temperature environment in the aisle can meet the storage requirements of the goods, helping to maintain the quality and shelf life of the goods. For example, for refrigerated foods, the aisle temperature needs to be controlled within a lower range to prevent food spoilage.

[0081] In a possible embodiment, in step S3, when generating the optimization suggestion, if the compatibility F between the product and the channel is lower than the set threshold F yz , it is recommended to adjust the product placement angle, the adjustment formula is θ x =θ y +Δθ,θ x is the adjusted product placement angle, θ y is the product placement angle before adjustment, and Δθ is the angle adjustment amount determined by the adaptability difference and the aisle space conditions.

[0082] Specifically, the purpose of generating optimization suggestions is to improve the compatibility between products and channels. When the compatibility between products and channels F is lower than the set threshold F yz When θ is less than θ, it indicates that the current fit between the product and the aisle is poor and needs to be adjusted. Adjusting the product placement angle is an effective optimization method. By adjusting the product placement angle, the space occupied and stability of the product in the aisle can be changed, thereby improving the fit. x =θ y +Δθ represents the product placement angle θ before adjustment y Based on the above, add an angle adjustment Δθ to get the adjusted product placement angle θ x The angle adjustment amount, Δθ, is determined based on the fit difference and aisle space availability. A larger fit difference indicates a potentially larger adjustment. Aisle space availability also influences the angle adjustment amount. For example, if the aisle is spacious, the adjustment can be increased; if space is limited, adjustments require caution. By properly adjusting the product placement angle, the compatibility of products within the aisle can be improved without changing the aisle or the products, reducing operating costs.

[0083] See also Figure 2 and Figure 3 , an application process of an embodiment of the present invention is as follows:

[0084] (1) The client initiates a request

[0085] The client represents a terminal device or application that uses the vending machine's inventory placement function, such as a management terminal operated by an operator. When an operator wants to verify the placement of a specific product in the aisle of a specific vending machine, the client sends a verification request. This request includes key parameters such as the model ID (which identifies the vending machine model), aisle parameters (including aisle dimensions, load capacity, temperature control range, etc.), and product parameters (product size, weight, temperature requirements, etc.).

[0086] (2) API Gateway performs parameter verification

[0087] As the entry point for requests, the API gateway provides unified management and control. It first verifies the parameters of the verification request sent by the client, including format verification and mandatory field checking. For example, it checks whether the model ID is a valid identifier and whether the channel and product parameters are complete and conform to the specified data format. If there are any problems with the parameters, the API gateway rejects the request and returns an error message to the client, requiring it to correct the problem and resend the request. Only after the parameter verification passes will the subsequent process continue.

[0088] (3) Verify that the factory creates an instance and obtains parameters

[0089] Requests that pass verification prompt the API gateway to send instructions to the verification factory to create a verification instance. The verification factory obtains the corresponding model parameters from the policy unit based on the model ID in the request. The policy unit is like a rule library, storing various attributes and verification rules for different models. At the same time, the policy unit interacts with the data layer, which stores detailed data about models, aisles, and products. The policy unit extracts the parameter configuration related to the model ID from the data layer and returns it to the verification factory, so that the verification factory has the basic information required for subsequent verification.

[0090] (4) Strategy unit executes verification strategy

[0091] After the verification factory receives the parameter configuration, the strategy unit begins to execute the specific verification strategy. This process is divided into three main verification steps:

[0092] Basic parameter verification: Check the aisle size parameters (such as whether the length, width, and height meet the standard range) and product specification parameters (whether the length, width, height, and weight of the product are within the allowable range), and calculate the basic matching degree (taking into account factors such as the ratio of the product volume to the aisle's capacity, and the ratio of the contact area between the product and the bottom of the aisle).

[0093] Model feature verification: Verify the aisle's load-bearing capacity (determine whether the weight of the goods is within the maximum load-bearing range determined by the aisle's material and structure), check temperature control requirements (whether the current aisle temperature is within the temperature range required for product storage), and evaluate space utilization (calculate the ratio of the total volume of goods in the aisle to the total volume of the aisle).

[0094] Product matching verification: Calculate the compatibility of products and aisles (taking into account the proportional relationship between the length, width, and height of the product and the corresponding dimensions of the aisle), evaluate the product placement method, and generate optimization suggestions based on the compatibility (if the compatibility is lower than the set threshold, it is recommended to adjust the product placement angle, etc.).

[0095] (5) Result return and response

[0096] After the strategy unit completes all verification steps, it sends the results to the verification factory. The verification factory then passes the results to the API gateway, which finally sends the response data back to the client. After receiving the response data, the client presents it to the operations staff in a visual format, such as the product-channel compatibility score, whether there are any items that do not meet the requirements, and corresponding optimization suggestions, to help operations staff make reasonable scheduling decisions.

[0097] To demonstrate the effectiveness of this method for visualizing inventory placement for vending machines, the following example data is provided:

[0098] Comparison of inventory scheduling efficiency

[0099] 50 vending machines managed by a certain operating company were randomly divided into two groups. Group A (25 machines) used traditional manual inventory scheduling and verification, while Group B (25 machines) used the method of the present invention. Under the same product placement task (a total of 1,000 products need to be arranged in the aisles), the inventory scheduling time was recorded:

[0100] Group A: Manually measure the size of products and aisles one by one, calculate the matching degree, etc. It takes an average of 4 hours to complete the stocking of each vending machine, and a total of 100 hours for 50 machines.

[0101] Group B: The system quickly calculated the request after receiving it, taking only 20 minutes per vending machine on average, and a total of about 8.3 hours for 50 machines.

[0102] It can be seen that the present invention greatly improves the efficiency of goods placement, which is about 91.7% higher than the traditional method.

[0103] Comparison of adaptation accuracy

[0104] In a simulation environment, 100 products of different specifications and 50 different aisle types were set up. Product-aisle matching was determined using both traditional experience and the system of the present invention, and the correct number of judgments was recorded:

[0105] Traditional method: relying on experience and judgment, 70 groups were correctly matched, with an error rate of 30%.

[0106] The system of the present invention: After the processes of basic parameter verification, model feature verification and product matching verification, 95 groups were correctly matched with an error rate of only 5%.

[0107] This shows that the present invention can more accurately achieve the adaptation of goods and channels, reducing the risk of shipping problems caused by improper adaptation.

[0108] Space utilization comparison

[0109] Ten vending machines of the same model were selected, each with 30 aisles. The aisle space utilization was measured and calculated by first arranging the goods in a traditional way and then rearranging them using the method of the present invention:

[0110] Traditional method: The average space utilization rate is 60%.

[0111] The method of the present invention: by optimizing the placement of goods and selecting appropriate aisles, the average space utilization rate is increased to 85%.

[0112] This shows that the present invention can effectively improve the utilization rate of the aisle space, allowing the vending machine to display more goods and increase sales opportunities.

[0113] Cost Savings Comparison

[0114] Taking the operating cycle (1 year) of 100 vending machines in a certain area as the statistical period, the operating costs before and after adopting the present invention are compared, including equipment maintenance costs and product loss costs caused by shipping failures:

[0115] Before adoption: Due to shipment failures, the total cost of equipment maintenance is 50,000 yuan, and the cost of product loss is 30,000 yuan, totaling 80,000 yuan each year.

[0116] After adoption: shipment failures were significantly reduced, total equipment maintenance costs were reduced to 10,000 yuan, and product loss costs were reduced to 5,000 yuan, totaling 15,000 yuan.

[0117] Data shows that the present invention significantly reduces operating costs, saving about 81.25% compared to before.

[0118] Example 2

[0119] See also Figure 4 Embodiment 2 of the present invention further provides a system for visually arranging goods for a vending machine, which adopts the above-mentioned method for visually arranging goods for a vending machine, and includes:

[0120] Request receiving module 001 is used to receive user verification requests sent by the vending machine front end through the REST API. The parameters of the user verification request include machine model ID, channel parameters, and product parameters, and perform format verification and mandatory field check on the parameters of the user verification request;

[0121] Strategy selection module 002, used to obtain the corresponding verification implementation class from the strategy factory according to the model ID, load the verification rules of the set model, and initialize the verification environment and related parameters;

[0122] Verification execution module 003 is used to execute the verification process, including basic parameter verification, model feature verification, and product matching verification. The basic parameter verification includes checking aisle size parameters, verifying product specifications, and calculating basic matching. The model feature verification includes verifying aisle load capacity, checking temperature control requirements, and evaluating space utilization. The product matching verification includes calculating the compatibility of products and aisles, evaluating product placement, and generating optimization suggestions.

[0123] The result response module 004 is used to summarize the verification results, generate a verification report, and return response data in a standard format to the user at the front end of the vending machine.

[0124] In a possible embodiment, in the verification execution module 003, the formula for calculating the basic matching degree M is:

[0125]

[0126] Among them, V s is the volume of the product, V h is the volume that the cargo lane can accommodate, α and β are weight coefficients, 0<α, β<1 and α+β=1, S jc is the contact area between the product and the bottom of the aisle, S hd is the bottom area of the cargo aisle.

[0127] In a possible embodiment, in the verification execution module 003, for the commodity weight W s and the load-bearing capacity of the cargo lane W c The relationship between s ≤W c ×γ is used for verification, where γ is the safety bearing factor 0<γ<1.

[0128] In a possible embodiment, in the verification execution module 003, the formula for evaluating the space utilization U is:

[0129]

[0130] Among them, n is the number of goods in the aisle, V si is the volume of the i-th product, V hz is the total volume of the cargo aisle.

[0131] In a possible embodiment, in the verification execution module 003, the formula for calculating the compatibility between the product and the channel is:

[0132]

[0133] Among them, L s 、W s 、H s They are the length, width and height of the product respectively. h 、W h 、H h are the length, width and height of the cargo aisle respectively; ω1, ω2 and ω3 are weight factors, 0<ω1, ω2, ω3<1 and ω1+ω2+ω3=1.

[0134] In a possible embodiment, in the verification execution module 003, the length L of the cargo lane is checked. h, width W h , height H h Parameter, if L min ≤L h ≤L max , and W min ≤W h ≤W max , H min ≤H h ≤H max , then the cargo lane size parameters meet the standards, L min , L max 、W min 、W max 、H min 、H max These are the standard minimum and maximum values for the length, width, and height of the aisle respectively.

[0135] In a possible embodiment, in the verification execution module 003, the length L of the product is verified. s 、Width W s , high H s and weight W s Parameter, if L smin ≤L s ≤L smax , and W smin ≤W s ≤W smax , H smin ≤H s ≤H smax , W s ≤W xz , then the product specifications are determined to be in compliance with the regulations, L smin , L smax 、W smin 、W smax 、H smin 、H smax The distribution is the minimum and maximum values allowed for the length, width, and height of the product, W xz The maximum weight allowed for the product.

[0136] In a possible embodiment, in the verification execution module 003, the load-bearing capacity of the cargo lane is verified to be the maximum load-bearing capacity W determined according to the material and structure of the cargo lane. c , judge W s ≤W c Is it established to determine whether the cargo lane can bear the weight of the goods;

[0137] The temperature control requirement is to determine the current temperature T of the cargo channel. h Is it within the temperature range required for product storage [T min ,T max ], that is, T min ≤Th ≤T max , if the temperature environment of the cargo aisle meets the storage requirements of the goods.

[0138] In a possible embodiment, in the verification execution module 003, if the compatibility F between the product and the channel is lower than the set threshold F yz , it is recommended to adjust the product placement angle, the adjustment formula is θ x =θ y +Δθ,θ x is the adjusted product placement angle, θ y is the product placement angle before adjustment, and Δθ is the angle adjustment amount determined by the adaptability difference and the aisle space conditions.

[0139] It should be noted that the information interaction, execution process and other contents between the modules of the above-mentioned system are based on the same concept as the method embodiment in Example 1 of this application, and the technical effects they bring are the same as those of the method embodiment of this application. For specific contents, please refer to the description in the method embodiment shown above in this application, and no further details will be given here.

[0140] Example 3

[0141] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which the program code of the method for visually arranging goods for a vending machine is stored. The program code includes instructions for executing the method for visually arranging goods for a vending machine of embodiment 1 or any possible implementation thereof.

[0142] Computer-readable storage media can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0143] Example 4

[0144] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0145] The processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the vending machine visual arrangement method of embodiment 1 or any possible implementation thereof.

[0146] Specifically, the processor can be implemented by hardware or by software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor, which is implemented by reading software code stored in a memory. The memory can be integrated into the processor or located outside the processor and exist independently.

[0147] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode.

[0148] Obviously, those skilled in the art will appreciate that the various modules or steps of the present invention described above can be implemented using a general-purpose computing device, centralized on a single computing device, or distributed across a network of multiple computing devices. Alternatively, they can be implemented using program code executable by a computing device, which can then be stored in a storage device and executed by the computing device. In some cases, the steps shown or described can be performed in a different order than that shown, or can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0149] Although the present invention has been described in detail above using general descriptions and specific embodiments, it will be apparent to those skilled in the art that modifications and improvements may be made thereto. Therefore, such modifications and improvements, without departing from the spirit of the present invention, are intended to be within the scope of protection claimed herein.

Claims

1. A method for visually arranging goods for a vending machine, characterized in that: include: Receive a user verification request sent by the vending machine front end through the REST API. The parameters of the user verification request include the machine model ID, channel parameters, and product parameters. Perform format verification and mandatory field check on the parameters of the user verification request. Obtain the corresponding verification implementation class from the strategy factory based on the model ID, load the verification rules for the set model, and initialize the verification environment and related parameters; Execute the verification process, including basic parameter verification, model feature verification, and product matching verification. The basic parameter verification includes checking aisle size parameters, verifying product specifications, and calculating basic matching. The model feature verification includes verifying aisle load capacity, checking temperature control requirements, and evaluating space utilization. The product matching verification includes calculating the compatibility of products and aisles, evaluating product placement, and generating optimization suggestions. Summarize the verification results, generate a verification report, and return response data in a standard format to the user at the vending machine front end.

2. The method for visually arranging goods for a vending machine according to claim 1, characterized in that: In the basic parameter verification, the formula for calculating the basic matching degree M is: Among them, V s is the volume of the product, V h is the volume that the cargo lane can accommodate, α and β are weight coefficients, 0<α, β<1 and α+β=1, S jc is the contact area between the product and the bottom of the aisle, S hd is the bottom area of the cargo aisle.

3. The method for visually arranging goods for a vending machine according to claim 1, characterized in that: During the verification of product specifications, the product weight W s And the load-bearing capacity of the cargo channel W c The relationship between s ≤W c ×γ for verification, γ is the safety bearing factor 0<γ<1.

4. The method for visually arranging goods for a vending machine according to claim 1, characterized in that: In the model characteristics verification, the formula for evaluating space utilization U is: Among them, n is the number of goods in the aisle, V si is the volume of the i-th product, V hz is the total volume of the cargo aisle.

5. The method for visually arranging goods for a vending machine according to claim 1, characterized in that: In the product matching verification, the formula for calculating the compatibility between the product and the channel is: Among them, L s 、W s 、H s They are the length, width and height of the product respectively. h 、W h 、H h are the length, width and height of the aisle respectively, ω1, ω2 and ω3 are weight factors, 0<ω1, ω2, ω3<1 and ω1+ω2+ω3=1.

6. The method for visually arranging goods for a vending machine according to claim 1, characterized in that: During the process of checking the aisle size parameters, check the length L of the aisle. h , width W h , height H h Parameter, if L min ≤L h ≤L max , and W min ≤W h ≤W max , H min ≤H h ≤H max , then the cargo lane size parameters meet the standards, L min , L max 、W min 、W max 、H min 、H max These are the standard minimum and maximum values for the length, width, and height of the aisle respectively.

7. The method for visually arranging goods for a vending machine according to claim 1, characterized in that: During the verification of product specifications, the length L of the product is verified. s 、Width W s , high H s and weight W s Parameter, if L smin ≤L s ≤L smax , and W smin ≤W s ≤W smax , H smin ≤H s ≤H smax , W s ≤W xz , then it is determined that the product specifications meet the requirements, L smin , L smax 、W smin 、W smax 、H smin 、H smax The distribution is the minimum and maximum values allowed for the length, width, and height of the product, W xz The maximum weight allowed for the product.

8. The method for visually arranging goods for a vending machine according to claim 7, characterized in that: In the above model characteristic verification, the load-bearing capacity of the cargo lane is verified to be the maximum load-bearing capacity W determined based on the material and structure of the cargo lane. c , judge W s ≤W c Is it established to determine whether the cargo lane can bear the weight of the goods; The temperature control requirement is to determine the current temperature T of the cargo channel. h Is it within the temperature range required for product storage [T min , T max ], that is, T min ≤T h ≤T max , if the temperature environment of the cargo aisle meets the storage requirements of the goods.

9. The method for visually arranging goods for a vending machine according to claim 5, characterized in that: When generating optimization suggestions, if the compatibility between the product and the channel F is lower than the set threshold F yz , it is recommended to adjust the product placement angle, the adjustment formula is θ x =θ y +△θ,θ x is the adjusted product placement angle, θ y is the product placement angle before adjustment, and △θ is the angle adjustment amount determined by the adaptability difference and the aisle space conditions.

10. A visual product arrangement system for a vending machine, using the visual product arrangement method for a vending machine according to any one of claims 1 to 9, characterized in that: include: A request receiving module is used to receive user verification requests sent by the vending machine front end through the REST API. The parameters of the user verification request include the machine model ID, channel parameters, and product parameters, and perform format verification and mandatory field checking on the parameters of the user verification request; The strategy selection module is used to obtain the corresponding verification implementation class from the strategy factory according to the model ID, load the verification rules of the set model, and initialize the verification environment and related parameters; The verification execution module is used to execute the verification process, including basic parameter verification, model feature verification, and product matching verification. The basic parameter verification includes checking the aisle size parameters, verifying the product specification parameters, and calculating the basic matching degree; the model feature verification includes verifying the aisle load capacity, checking the temperature control requirements, and evaluating the space utilization rate; the product matching verification includes calculating the compatibility of the product and the aisle, evaluating the product placement method, and generating optimization suggestions; The result response module is used to summarize the verification results, generate a verification report, and return response data in a standard format to the user at the front end of the vending machine.

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