Retail machine goods arrangement visualization method and system

Abstract

The invention discloses a retail machine goods arrangement visualization method and system, and the method comprises the steps: building a goods channel topological relation matrix through analyzing the physical structure of a retail machine, and initializing a goods channel attribute data table; a visual page is generated based on the topological relation, the goods channel type and the inventory state are visually displayed through color coding and a dynamic progress bar, and dragging interaction operation is supported; performing multi-level verification on user operation through a progressive verification mechanism, including temperature compatibility, path compliance and topological connectivity detection, and avoiding physical constraint conflicts; after the verification is passed, updating inventory data in real time and dynamically reconstructing a cargo channel topological relation; analyzing features such as inventory turnover rate and goods channel visibility by using a pre-trained DQN network, and generating intelligent decisions such as goods channel merging and splitting and goods positioning; finally, dynamic updating of the interface is achieved through the differential rendering technology, and the response performance is optimized in combination with double buffering and local redrawing. The problems of fragmentation of management information, decision lag and the like of a traditional retail machine are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of retail equipment management, and in particular to a method and system for visualizing the arrangement of goods in retail machines. Background Art

[0002] With the development of the retail industry, especially the rise of unmanned retail models, the application of retail machines is becoming more and more widespread. For operators, efficiently managing the inventory of goods in retail machines is crucial.

[0003] Currently, traditional retail machine management methods make it difficult for sales personnel to intuitively and conveniently access detailed information about the products within the machines, such as the aisle in which the product is located, the aisle type, sales volume, and inventory status. The process of removing and removing products from shelves, replacing items, or adjusting aisle layouts is cumbersome and inefficient, requiring significant time and labor costs. Furthermore, the lack of intuitive visualization tools makes it difficult for sales personnel to quickly make informed stocking decisions based on real-time sales and inventory information, resulting in inappropriate product displays that impact sales performance and the customer shopping experience.

[0004] Therefore, how to invent and develop a retail machine inventory visualization method that can intuitively display retail machine inventory information and facilitate business personnel's operation has become an urgent problem to be solved. Summary of the Invention

[0005] To this end, the present invention provides a method and system for visualizing the inventory arrangement of retail machines. By constructing a channel space-data mapping model, a panoramic visualization of the inventory arrangement status inside the retail machine is achieved, solving the problems existing in the existing retail machine inventory arrangement management process, such as non-intuitive information, inconvenient operation, and lack of data support for decision-making.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for visualizing product placement in a retail machine, comprising:

[0007] Obtaining physical structure data of the retail machine by performing structural analysis on the retail machine; constructing an aisle topology relationship matrix based on the physical structure data; initializing an aisle attribute data table to obtain an initialized aisle attribute data table;

[0008] Generate a visualization page based on the topological relationship of the cargo lane topological relationship matrix and the initialized cargo lane attribute data table;

[0009] Based on the visualization page and the initialized cargo lane attribute data table, progressively verify the user operation event;

[0010] After the verification is passed, the inventory data is updated to obtain updated inventory data; the cargo lane topology relationship matrix is ​​reconstructed to generate a new cargo lane topology relationship matrix;

[0011] Generate an adjustment decision through a pre-trained DQN network based on the updated inventory data and the new channel topology relationship matrix;

[0012] According to the adjustment decision, differential rendering is performed to dynamically adjust the visualization page.

[0013] As a preferred solution for a retail machine product arrangement visualization method, the mathematical expression of the aisle topology relationship matrix is:

[0014] G=(V,E)

[0015] Where G is the aisle topological relationship matrix; V is the vertex set, representing the aisles; and E is the edge set, representing the adjacent relationship between aisles.

[0016] As a preferred solution for a method for visualizing the arrangement of goods in a retail machine, the contents of the initialized aisle attribute data table include: aisle ID, type, volume threshold, and temperature range.

[0017] As a preferred solution for a method of visualizing product arrangement in a retail machine, in the process of generating the visualization page:

[0018] Based on the adjacency matrix of the aisle topology relationship matrix, the position of the aisle graphic element is calculated by a force-directed algorithm; the calculation formula of the force-directed algorithm is:

[0019] F layout =k·∑ i＜j (|x i -x j |-d ij ) 2

[0020] Where, F layout is the total energy of the entire layout system; k is the elastic coefficient, which controls the force between the cargo lanes; ∑ i＜j is the sum of all cargo lane pairs (i, j); |x i -x j | is the actual distance between lanes i and j; d ij is the ideal distance between lanes i and j;

[0021] The aisle color code is determined by mapping the type field in the initialized aisle attribute data table; if the aisle type is refrigerated, the aisle color code is:

[0022] Color=RGB(0,0.5·T current ,1)

[0023] Where, T current The real-time temperature.

[0024] As a preferred solution for a method for visualizing product placement in a retail machine, during the process of performing the progressive verification of user operation events:

[0025] Based on the initialized channel attribute data table, a first level check is performed to determine whether the temperature range of the target channel meets the storage requirements of the goods; if the lowest temperature of the target channel Greater than the lowest storage temperature T i min Or the highest temperature of the target cargo lane Lower than the maximum storage temperature T i max The operation stops and an error log is generated;

[0026] Based on the visualization page, a second level check is performed on the moving path of the commodity from the original cargo aisle to the target cargo aisle; if there is a prohibited area on the moving path, a new moving path is generated for detour.

[0027] As a preferred solution for a retail machine inventory scheduling visualization method, the expression of the updated inventory data is:

[0028]

[0029] Where K new is the new inventory; K old is the original inventory; ΔQ is the change in the quantity of goods involved in the user operation; is the maximum physical carrying capacity of cargo lane j; It is an indicator function, and its value is 1 when the condition in the brackets is met.

[0030] As a preferred solution for a retail machine inventory visualization method, in the process of performing differentiated rendering based on the adjustment decision:

[0031] Change the flag Δ according to the data data Perform differential rendering;

[0032] If Δ data If the channel attributes are changed, the force-directed layout parameters are recalculated;

[0033] If Δ data If only the inventory changes, the progress bar will be smoothly transitioned through interpolation algorithm:

[0034]

[0035] Where H(t) is the height of the progress bar corresponding to time point t; H0 is the initial height of the progress bar; H new is the target height after the operation is completed; t max The total duration of the animation.

[0036] The present invention also provides a retail machine product arrangement visualization system, comprising:

[0037] The aisle topology relationship matrix construction and attribute data initialization module is used to obtain the physical structure data of the retail machine by performing structural analysis on the retail machine; construct the aisle topology relationship matrix based on the physical structure data; and initialize the aisle attribute data table to obtain an initialized aisle attribute data table;

[0038] A visualization page generation module, configured to generate a visualization page based on the topological relationship of the cargo lane topological relationship matrix and the initialized cargo lane attribute data table;

[0039] A user operation event verification module, configured to perform progressive verification of user operation events based on the visualization page and the initialized cargo lane attribute data table;

[0040] The data update and channel topology relationship matrix reconstruction module is used to update the inventory data after verification to obtain updated inventory data; reconstruct the channel topology relationship matrix to generate a new channel topology relationship matrix;

[0041] An adjustment decision generation module, configured to generate an adjustment decision using a pre-trained DQN network based on the updated inventory data and the new channel topology relationship matrix;

[0042] The visualization page dynamic adjustment module is used to perform differential rendering according to the adjustment decision and dynamically adjust the visualization page.

[0043] As a preferred solution for a retail machine product arrangement visualization system, in the aisle topology relationship matrix construction and attribute data initialization module, the mathematical expression of the aisle topology relationship matrix is:

[0044] G=(V,E)

[0045] Where G is the aisle topological relationship matrix; V is the vertex set, representing the aisles; and E is the edge set, representing the adjacent relationship between aisles.

[0046] As a preferred solution for a retail machine inventory visualization system, in the aisle topology relationship matrix construction and attribute data initialization module, the contents of the initialized aisle attribute data table include: aisle ID, type, volume threshold and temperature range.

[0047] As a preferred solution of a retail machine product arrangement visualization system, in the visualization page generation module, during the process of generating the visualization page:

[0048] Based on the adjacency matrix of the aisle topology relationship matrix, the position of the aisle graphic element is calculated by a force-directed algorithm; the calculation formula of the force-directed algorithm is:

[0049] F layout =k·∑ i＜j (|x i -x j |-d ij ) 2

[0050] Where, F layout is the total energy of the entire layout system; k is the elastic coefficient, which controls the force between the cargo lanes; ∑ i＜j is the sum of all cargo lane pairs (i, j); |x i -x j | is the actual distance between lanes i and j; d ij is the ideal distance between lanes i and j;

[0051] The aisle color code is determined by mapping the type field in the initialized aisle attribute data table; if the aisle type is refrigerated, the aisle color code is:

[0052] Color=RGB(0,0.5·T current ,1)

[0053] Where, T current The real-time temperature.

[0054] As a preferred solution of a retail machine inventory visualization system, in the user operation event verification module, during the process of performing the progressive verification of user operation events:

[0055] Based on the initialized channel attribute data table, a first level check is performed to determine whether the temperature range of the target channel meets the storage requirements of the goods; if the lowest temperature of the target channel Greater than the lowest storage temperature T i min Or the highest temperature of the target cargo lane Lower than the maximum storage temperature T i max The operation stops and an error log is generated;

[0056] Based on the visualization page, a second level check is performed on the moving path of the commodity from the original cargo aisle to the target cargo aisle; if there is a prohibited area on the moving path, a new moving path is generated for detour.

[0057] As a preferred solution for a retail machine inventory visualization system, in the data update and channel topology matrix reconstruction module, the expression of the updated inventory data is:

[0058]

[0059] Where K new is the new inventory; K old is the original inventory; ΔQ is the change in the quantity of goods involved in the user operation; is the maximum physical carrying capacity of cargo lane j; It is an indicator function, and its value is 1 when the condition in the brackets is met.

[0060] As a preferred solution for a retail machine inventory visualization system, in the visualization page dynamic adjustment module, during the process of performing differentiated rendering based on the adjustment decision:

[0061] Change the flag Δ according to the data data Perform differential rendering;

[0062] If Δ data If the channel attributes are changed, the force-directed layout parameters are recalculated;

[0063] If Δ data If only the inventory changes, the progress bar will be smoothly transitioned through interpolation algorithm:

[0064]

[0065] Where H(t) is the height of the progress bar corresponding to time point t; H0 is the initial height of the progress bar; H new is the target height after the operation is completed; t max The total duration of the animation.

[0066] The present invention has the following advantages: the present invention obtains the physical structure data of the retail machine by structural analysis of the retail machine; constructs the aisle topology relationship matrix based on the physical structure data; initializes the aisle attribute data table to obtain the initialized aisle attribute data table; generates a visualization page based on the topological relationship of the aisle topology relationship matrix and the initialized aisle attribute data table; performs progressive verification of user operation events based on the visualization page and the initialized aisle attribute data table; after verification, updates the inventory data to obtain updated inventory data; reconstructs the aisle topology relationship matrix to generate a new aisle topology relationship matrix; generates adjustment decisions based on the updated inventory data and the new aisle topology relationship matrix through a pre-trained DQN network; performs differential rendering based on the adjustment decisions and dynamically adjusts the visualization page. Through visual page simulation and convenient operation functions, the present invention enables business personnel to quickly complete operations such as putting goods on and off shelves, replacing goods, and merging and splitting aisles. Compared with traditional operation methods, it greatly saves time and labor costs and improves work efficiency. The present invention provides a wealth of aisle and product information, including product sales and inventory, whether it is out of stock, whether the aisle needs to be adjusted, etc., as well as product sales and inventory rankings, to help business personnel fully understand the sales and inventory situation of goods, so as to make more scientific and reasonable stocking decisions, optimize the product display layout, and improve product sales and inventory turnover. The present invention presents the stocking situation inside the retail machine to business personnel in an intuitive and visual manner, so that business personnel can clearly see the overall layout of the machine and the detailed information of each aisle, thereby enhancing the visualization of management, reducing the difficulty of management, and improving the accuracy and timeliness of management. The present invention has a flexible data processing and updating mechanism, which can respond to sales data and inventory changes in real time, and at the same time support business personnel to adjust aisles and operate goods according to actual business needs, adapt to the characteristics of rapid changes in retail business, and provide strong support for the sustainable development of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] 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.

[0068] 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.

[0069] Figure 1 This is a flow chart of a method for visualizing product arrangement for a retail machine provided in Example 1 of the present invention;

[0070] Figure 2 This is a schematic diagram of a specific implementation process framework of a method for visualizing product arrangement for retail machines provided in Example 1 of the present invention;

[0071] Figure 3 This is a schematic diagram of the architecture of a retail machine inventory visualization system provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0072] 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.

[0073] Example 1

[0074] See also Figure 1 and Figure 2 Embodiment 1 of the present invention provides a method for visualizing product placement in a retail machine, comprising the following steps:

[0075] S1. Obtain physical structure data of the retail machine by performing structural analysis on the retail machine; construct an aisle topology relationship matrix based on the physical structure data; initialize the aisle attribute data table to obtain an initialized aisle attribute data table;

[0076] S2. Generate a visualization page based on the topological relationship of the cargo lane topological relationship matrix and the initialized cargo lane attribute data table;

[0077] S3. Based on the visualization page and the initialized cargo lane attribute data table, progressively verify the user operation event;

[0078] S4. After verification, the inventory data is updated to obtain updated inventory data; the channel topology relationship matrix is ​​reconstructed to generate a new channel topology relationship matrix;

[0079] S5. Generate an adjustment decision using a pre-trained DQN network based on the updated inventory data and the new channel topology relationship matrix;

[0080] S6. Perform differential rendering according to the adjustment decision and dynamically adjust the visualization page.

[0081] In this embodiment, in step S1, the physical structure data of the retail machine is obtained by performing structural analysis on the retail machine; based on the physical structure data, a channel topology relationship matrix is ​​constructed; and the channel attribute data table is initialized to obtain an initialized channel attribute data table.

[0082] Specifically, the physical structural parameters of the retail machine are obtained through the machine's built-in sensors or preset configuration files, including: the aisle hierarchy distribution (number of floors, number of aisles per floor), the aisle physical dimensions (length, width, height), and the connection relationship between adjacent aisles (spatial location topology). Based on the physical structural parameters of the retail machine, an aisle topology relationship matrix is ​​constructed. The mathematical expression of the aisle topology relationship matrix is:

[0083] G=(V,E)

[0084] Where G is the aisle topological relationship matrix; V is the vertex set, representing the aisles; and E is the edge set, representing the adjacent relationship between aisles.

[0085] In this embodiment, the aisle attribute data table is initialized to obtain an initialized aisle attribute data table. The initialized aisle attribute data table includes the aisle ID, type, volume threshold, and temperature range. Initial data is synchronized from the retail machine database to ensure that the aisle attributes are consistent with the physical state.

[0086] In this embodiment, in step S2, a visualization page is generated based on the topological relationship of the cargo lane topological relationship matrix and the initialized cargo lane attribute data table;

[0087] Specifically, based on the adjacency relationship of the aisle topology matrix G, the force-directed layout algorithm ForceAtlas2 is used to calculate the screen coordinates of the aisle nodes, so that the visual layout is consistent with the physical structure space ratio.

[0088] The calculation formula of the force-directed algorithm is:

[0089] F layout =k·∑ i＜j (|x i -x j |-d ij ) 2

[0090] Where, F layoutis the total energy of the entire layout system; k is the elastic coefficient, which controls the force between the cargo lanes; ∑ i＜j is the sum of all cargo lane pairs (i, j); |x i -x j | is the actual distance between lanes i and j; d ij is the ideal distance between lanes i and j;

[0091] In this embodiment, the aisle graphic element design includes: size, color coding, and dynamic progress bar.

[0092] The size is scaled according to the volume threshold, and the larger the volume, the larger the graphic area;

[0093] The color coding is: refrigerated aisle (blue), hot chain aisle (red), and normal temperature aisle (green);

[0094] The dynamic progress bar shows the current inventory ratio.

[0095] Specifically, the aisle color code is determined by mapping the type field in the initialized aisle attribute data table; if the aisle type is refrigerated, the aisle color code is:

[0096] Color=RGB(0,0.5·T current ,1)

[0097] Where, T current The real-time temperature.

[0098] In this embodiment, by binding an event listener to each aisle element, click (displaying a pop-up window of details), drag (moving goods), and multiple selection (merging / splitting aisles) operations are supported, thereby realizing the embedding of interactive functions in the visualization page.

[0099] In this embodiment, in step S3, based on the visualization page and the initialized channel attribute data table, the user operation event is progressively verified;

[0100] Specifically, the progressive verification of user operation events includes first-level verification and second-level verification;

[0101] Among them, the first level of verification is property compliance verification, which specifically includes temperature compatibility verification and volume over-limit warning.

[0102] Temperature compatibility check: When the user drags the product to the target aisle, check whether the temperature range of the target aisle meets the storage requirements of the product; if the lowest temperature of the target aisle Greater than the lowest storage temperature T i min Or the highest temperature of the target cargo lane Lower than the maximum storage temperature T imax , the operation stops and an error log is generated;

[0103] Volume overlimit warning: If the inventory after the operation exceeds the maximum volume of the target aisle, the operation will be blocked and a prompt will be given: "Insufficient aisle capacity".

[0104] The second level of verification is path compliance verification, which includes path conflict detection and dynamic topology adjustment.

[0105] Path conflict detection: Calculates the product movement path and automatically generates a detour if the path crosses a restricted area (such as a maintenance passage);

[0106] Dynamic topology adjustment: When lanes are merged / split, verify whether the new topology results in isolated nodes or loops, ensuring logical connectivity.

[0107] In this embodiment, in step S4, after the verification is passed, the inventory data is updated to obtain updated inventory data; the channel topology relationship matrix is ​​reconstructed to generate a new channel topology relationship matrix;

[0108] Specifically, the reconstruction of the cargo lane topology relationship matrix includes merging operations and splitting operations.

[0109] The merging operation is to merge multiple lane nodes into a super node, and update the edge weight of the adjacency matrix to the distance between the merged lane centers.

[0110] The split operation is to split the original channel node into a set of child nodes, redistribute them to new channels according to product categories, and rebuild the adjacency relationship.

[0111] In this embodiment, the update of inventory data includes the operation of putting items on the shelves and the operation of removing items from the shelves. The expression of the updated inventory data is:

[0112]

[0113] Where K new is the new inventory; K old is the original inventory; ΔQ is the change in the quantity of goods involved in the user operation; is the maximum physical carrying capacity of cargo lane j; It is an indicator function, and its value is 1 when the condition in the brackets is met.

[0114] In this embodiment, in step S5, an adjustment decision is generated by a pre-trained DQN network based on the updated inventory data and the new channel topology relationship matrix;

[0115] Specifically, state feature extraction is performed based on the updated inventory data and the new channel topology relationship matrix. Inputs are the updated inventory data, the new topology matrix, and historical sales data;

[0116] The expression of dynamic eigenvector is:

[0117] S t =[α,β,γ]

[0118] Where α is the sales growth rate of goods in the channel; β is the inventory turnover rate; and γ is the channel visibility index. The action space in the pre-trained DQN network is:

[0119] A={add aisle, split aisle, merge aisle}

[0120] Select the optimal action by calculating the Q value:

[0121] Q(s,a)=DQN(S t )→a * =argmaxQ

[0122] Where a * To make output action decisions.

[0123] The decision instructions output by the pre-trained DQN network are sent to the visualization interface and execution terminal.

[0124] In this embodiment, in step S6, differential rendering is performed according to the adjustment decision, and the visualization page is dynamically adjusted.

[0125] Specifically, differentiated dynamic rendering is performed according to the received decision instructions, including local rendering optimization and global rendering optimization.

[0126] Among them, local rendering optimization includes inventory changes and aisle position adjustments.

[0127] Specifically, for inventory changes, the progress bar is smoothly transitioned using an interpolation algorithm:

[0128]

[0129] Where H(t) is the height of the progress bar corresponding to time point t; H0 is the initial height of the progress bar; H new is the target height after the operation is completed; t max The total duration of the animation is 500ms.

[0130] Aisle position adjustment: Based on the new topology matrix, the layout is recalculated and Bezier curve movement trajectory animation is added.

[0131] Global rendering optimization:

[0132] Double buffering technology: pre-render the changed content in the background buffer and replace the foreground display after completion to avoid interface flickering;

[0133] Incremental updates: Only affected channel elements are redrawn, reducing rendering calculations and improving response speed to ≤50ms.

[0134] In a possible embodiment, a specific retail machine inventory visualization example is provided as follows:

[0135] T1. Retail machine structure analysis and data modeling: By analyzing the physical structural parameters of the retail machine (number of layers, aisle distribution, size specifications, etc.), a digital model of the topological connection relationship between aisles is established, and the aisle attribute data table is initialized to fully record the core parameters of each aisle, such as type, volume threshold, temperature range, etc., providing a structured data foundation for visualization and operation verification.

[0136] T2. Dynamic generation of visual interface: Based on the aisle topology and attribute data, a 2D / 3D visual page is automatically generated. The aisle type, inventory status, and spatial layout are intuitively displayed through visual elements such as color coding and dynamic progress bars. Interactive operations such as clicking to view details and dragging and dropping to adjust products are supported, achieving accurate mapping of physical aisles to digital interfaces.

[0137] T3. Multi-level operational compliance verification: When users perform operations such as moving goods and adjusting aisles, the system performs progressive verification: first, it checks basic attributes such as temperature compatibility and volume restrictions, then checks whether the operation path is compliant (such as avoiding restricted areas), and finally verifies the logical connectivity after the topology change, ensuring that each operation complies with the physical constraints of the device and business rules.

[0138] T4. Real-time Data Update and Topology Reconstruction: After verification, the system automatically updates inventory data and synchronizes it to the database, dynamically adjusting the channel topology matrix. The merge operation consolidates multiple channels into supernodes, while the split operation reallocates channel resources based on product attributes, ensuring real-time consistency between the data layer and the physical state.

[0139] T5. Intelligent decision-making engine driven optimization: Based on updated inventory data and aisle topology status, the pre-trained deep reinforcement learning model analyzes key indicators such as sales trends and inventory turnover rates, and automatically generates optimization suggestions such as adding and deleting aisles and relocating products, breaking through the limitations of human experience and achieving data-driven accurate decision-making.

[0140] T6. Differentiated dynamic rendering optimization: Differentiated rendering strategies are adopted for different operation results: inventory changes are smoothly animated, aisle merging / splitting is enhanced with particle effects for visual feedback, and double buffering and local redrawing technology are used to improve rendering efficiency, ensuring smooth interface response in large-scale aisle scenarios and operation feedback delays of less than 100ms.

[0141] In summary, the present invention obtains the physical structure data of the retail machine by performing structural analysis on the retail machine; constructs the aisle topology relationship matrix based on the physical structure data; initializes the aisle attribute data table to obtain the initialized aisle attribute data table; generates a visualization page based on the topological relationship of the aisle topology relationship matrix and the initialized aisle attribute data table; performs progressive verification of user operation events based on the visualization page and the initialized aisle attribute data table; after verification, updates the inventory data to obtain updated inventory data; reconstructs the aisle topology relationship matrix to generate a new aisle topology relationship matrix; generates adjustment decisions based on the updated inventory data and the new aisle topology relationship matrix through a pre-trained DQN network; performs differential rendering based on the adjustment decision and dynamically adjusts the visualization page. Through visual page simulation and convenient operation functions, the present invention enables business personnel to quickly complete operations such as putting goods on and off shelves, replacing goods, and merging and splitting aisles. Compared with traditional operation methods, it greatly saves time and labor costs and improves work efficiency. The present invention provides a wealth of aisle and product information, including product sales and inventory, whether it is out of stock, whether the aisle needs to be adjusted, etc., as well as product sales and inventory rankings, to help business personnel fully understand the sales and inventory situation of goods, so as to make more scientific and reasonable stocking decisions, optimize the product display layout, and improve product sales and inventory turnover. The present invention presents the stocking situation inside the retail machine to business personnel in an intuitive and visual manner, so that business personnel can clearly see the overall layout of the machine and the detailed information of each aisle, thereby enhancing the visualization of management, reducing the difficulty of management, and improving the accuracy and timeliness of management. The present invention has a flexible data processing and updating mechanism, which can respond to sales data and inventory changes in real time, and at the same time support business personnel to adjust aisles and operate goods according to actual business needs, adapt to the characteristics of rapid changes in retail business, and provide strong support for the sustainable development of the enterprise.

[0142] It should be noted that the method of the embodiments of the present disclosure can be performed by a single device, such as a computer or server. The method of the embodiments of the present disclosure can also be applied in a distributed scenario, where multiple devices cooperate to perform the method. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiments of the present disclosure, and the multiple devices will interact with each other to complete the method.

[0143] It should be noted that the above description is limited to some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0144] Example 2

[0145] See also Figure 3 Embodiment 2 of the present invention further provides a retail machine product arrangement visualization system, including:

[0146] The aisle topology relationship matrix construction and attribute data initialization module 001 is used to obtain the physical structure data of the retail machine by performing structural analysis on the retail machine; construct the aisle topology relationship matrix based on the physical structure data; initialize the aisle attribute data table to obtain an initialized aisle attribute data table;

[0147] A visualization page generation module 002 is configured to generate a visualization page based on the topological relationship of the cargo lane topological relationship matrix and the initialized cargo lane attribute data table;

[0148] User operation event verification module 003, used to perform progressive verification on user operation events based on the visualization page and the initialized cargo lane attribute data table;

[0149] The data updating and channel topology relationship matrix reconstruction module 004 is used to update the inventory data after verification to obtain updated inventory data; reconstruct the channel topology relationship matrix to generate a new channel topology relationship matrix;

[0150] An adjustment decision generating module 005 is configured to generate an adjustment decision using a pre-trained DQN network based on the updated inventory data and the new channel topology relationship matrix;

[0151] The visualization page dynamic adjustment module 006 is used to perform differential rendering according to the adjustment decision and dynamically adjust the visualization page.

[0152] In this embodiment, in the channel topology relationship matrix construction and attribute data initialization module 001, the mathematical expression of the channel topology relationship matrix is:

[0153] G=(V,E)

[0154] Where G is the aisle topological relationship matrix; V is the vertex set, representing the aisles; and E is the edge set, representing the adjacent relationship between aisles.

[0155] In this embodiment, in the cargo lane topology relationship matrix construction and attribute data initialization module 001, the contents of the initialized cargo lane attribute data table include: cargo lane ID, type, volume threshold and temperature range.

[0156] In this embodiment, in the visualization page generation module 002, during the process of generating the visualization page:

[0157] Based on the adjacency matrix of the aisle topology relationship matrix, the position of the aisle graphic element is calculated by a force-directed algorithm; the calculation formula of the force-directed algorithm is:

[0158] F layout =k·∑ i＜j (|x i -x j |-d ij ) 2

[0159] Where, F layout is the total energy of the entire layout system; k is the elastic coefficient, which controls the force between the cargo lanes; ∑ i＜j is the sum of all cargo lane pairs (i, j); |x i -x j | is the actual distance between lanes i and j; d ij is the ideal distance between lanes i and j;

[0160] The aisle color code is determined by mapping the type field in the initialized aisle attribute data table; if the aisle type is refrigerated, the aisle color code is:

[0161] Color=RGB(0,0.5·T current ,1)

[0162] Where, T current The real-time temperature.

[0163] In this embodiment, in the user operation event verification module 003, during the process of performing the progressive verification on the user operation event:

[0164] Based on the initialized channel attribute data table, a first level check is performed to determine whether the temperature range of the target channel meets the storage requirements of the goods; if the lowest temperature of the target channel Greater than the lowest storage temperature T i min Or the highest temperature of the target cargo lane Lower than the maximum storage temperature T i max , the operation stops and an error log is generated;

[0165] Based on the visualization page, a second level check is performed on the moving path of the commodity from the original cargo aisle to the target cargo aisle; if there is a prohibited area on the moving path, a new moving path is generated for detour.

[0166] In this embodiment, in the data updating and channel topology relationship matrix reconstruction module 004, the expression of the updated inventory data is:

[0167]

[0168] Where K new is the new inventory; K old is the original inventory; ΔQ is the change in the quantity of goods involved in the user operation; is the maximum physical carrying capacity of cargo lane j; It is an indicator function, and its value is 1 when the condition in the brackets is met.

[0169] In this embodiment, in the visualization page dynamic adjustment module 006, in the process of performing differential rendering according to the adjustment decision:

[0170] Change the flag Δ according to the data data Perform differential rendering;

[0171] If Δ data If the channel attributes are changed, the force-directed layout parameters are recalculated;

[0172] If Δ data If only the inventory changes, the progress bar will be smoothly transitioned through interpolation algorithm:

[0173]

[0174] Where H(t) is the height of the progress bar corresponding to time point t; H0 is the initial height of the progress bar; H new is the target height after the operation is completed; t max The total duration of the animation.

[0175] It should be noted that the information interaction, execution process, etc. between the modules of the above-mentioned system are based on the same concept as the method embodiment in Example 1 of the present application, and the technical effects they bring are the same as those of the method embodiment of the present application. For specific contents, please refer to the description in the method embodiment shown above in the present application, and no further details will be given here.

[0176] Example 3

[0177] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which a program code for a method for visualizing the arrangement of goods for a retail machine is stored. The program code includes instructions for executing the method for visualizing the arrangement of goods for a retail machine according to embodiment 1 or any possible implementation thereof.

[0178] 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)).

[0179] Example 4

[0180] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0181] 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 a retail machine inventory visualization method of embodiment 1 or any possible implementation thereof.

[0182] 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.

[0183] 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 systems. 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.

[0184] 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 system. They can be centralized on a single computing system or distributed across a network of multiple computing systems. Alternatively, they can be implemented using program code executable by a computing system, and thus, they can be stored in a storage system and executed by the computing system. In some cases, the steps shown or described herein can be performed in a different order than that shown, or they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0185] 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 visualizing product placement in a retail machine, characterized in that: include: Obtaining physical structure data of the retail machine by performing structural analysis on the retail machine; Based on the physical structure data, construct a cargo lane topology relationship matrix; Initialize the cargo lane attribute data table to obtain the initialized cargo lane attribute data table; Generate a visualization page based on the topological relationship of the cargo lane topological relationship matrix and the initialized cargo lane attribute data table; Based on the visualization page and the initialized cargo lane attribute data table, progressively verify the user operation event; After the verification is passed, the inventory data is updated to obtain updated inventory data; the cargo lane topology relationship matrix is ​​reconstructed to generate a new cargo lane topology relationship matrix; Generate an adjustment decision through a pre-trained DQN network based on the updated inventory data and the new channel topology relationship matrix; According to the adjustment decision, differential rendering is performed to dynamically adjust the visualization page.

2. A method for visualizing product placement in a retail machine according to claim 1, characterized in that: The mathematical expression of the cargo lane topology relationship matrix is: G=(V,E) Where G is the aisle topological relationship matrix; V is the vertex set, representing the aisles; and E is the edge set, representing the adjacent relationship between aisles.

3. A method for visualizing product placement in a retail machine according to claim 2, characterized in that: The contents of the initialized cargo lane attribute data table include: cargo lane ID, type, volume threshold and temperature range.

4. A method for visualizing product placement in a retail machine according to claim 3, characterized in that: In the process of generating the visualization page: Based on the adjacency matrix of the aisle topology relationship matrix, the position of the aisle graphic element is calculated by a force-directed algorithm; the calculation formula of the force-directed algorithm is: F layout =k·∑ i＜j (|x i -x j |-d ij ) 2 Where, F layout is the total energy of the entire layout system; k is the elastic coefficient, which controls the force between the cargo lanes; ∑ i＜j is the sum of all cargo lane pairs (i, j); |x i -x j | is the actual distance between lanes i and j; d ij is the ideal distance between lanes i and j; The aisle color code is determined by mapping the type field in the initialized aisle attribute data table; if the aisle type is refrigerated, the aisle color code is: Color=RGB(0,0.5·T current ,1) Where, T current The real-time temperature.

5. A method for visualizing product placement in a retail machine according to claim 4, characterized in that: During the progressive verification of user operation events: Based on the initialized channel attribute data table, a first level check is performed to determine whether the temperature range of the target channel meets the storage requirements of the goods; if the lowest temperature of the target channel Greater than the lowest storage temperature T i min Or the highest temperature of the target cargo lane Lower than the maximum storage temperature T i max , the operation stops and an error log is generated; Based on the visualization page, a second level check is performed on the moving path of the commodity from the original cargo aisle to the target cargo aisle; if there is a prohibited area on the moving path, a new moving path is generated for detour.

6. A method for visualizing product placement in a retail machine according to claim 5, characterized in that: The expression of the updated inventory data is: Where K new is the new inventory; K old is the original inventory; ΔQ is the change in the quantity of goods involved in the user operation; is the maximum physical carrying capacity of cargo lane j; It is an indicator function, and its value is 1 when the condition in the brackets is met.

7. A method for visualizing product placement in a retail machine according to claim 6, characterized in that: During differential rendering based on the adjustment decision: Change the flag Δ according to the data data Perform differential rendering; If Δ data If the channel attributes are changed, the force-directed layout parameters are recalculated; If Δ data If only the inventory changes, the progress bar will be smoothly transitioned through interpolation algorithm: Where H(t) is the height of the progress bar corresponding to time point t; H0 is the initial height of the progress bar; H new is the target height after the operation is completed; t max The total duration of the animation.

8. A retail machine inventory visualization system, characterized in that: include: The module for constructing the topological relationship matrix of the cargo lane and initializing the attribute data is used to obtain the physical structure data of the retail machine by performing structural analysis on the retail machine; Based on the physical structure data, a cargo lane topology relationship matrix is ​​constructed; the cargo lane attribute data table is initialized to obtain an initialized cargo lane attribute data table; A visualization page generation module, configured to generate a visualization page based on the topological relationship of the cargo lane topological relationship matrix and the initialized cargo lane attribute data table; A user operation event verification module, configured to perform progressive verification of user operation events based on the visualization page and the initialized cargo lane attribute data table; The data update and channel topology relationship matrix reconstruction module is used to update the inventory data after verification to obtain updated inventory data; reconstruct the channel topology relationship matrix to generate a new channel topology relationship matrix; An adjustment decision generation module, configured to generate an adjustment decision using a pre-trained DQN network based on the updated inventory data and the new channel topology relationship matrix; The visualization page dynamic adjustment module is used to perform differential rendering according to the adjustment decision and dynamically adjust the visualization page.

9. A retail machine product arrangement visualization system according to claim 8, characterized in that: In the channel topology relationship matrix construction and attribute data initialization module, the mathematical expression of the channel topology relationship matrix is: G=(V,E) Where G is the aisle topological relationship matrix; V is the vertex set, representing the aisles; and E is the edge set, representing the adjacent relationship between aisles.

10. A retail machine product arrangement visualization system according to claim 9, characterized in that: In the channel topology relationship matrix construction and attribute data initialization module, the contents of the initialized channel attribute data table include: channel ID, type, volume threshold and temperature range.

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