A community intelligent retail management system

Abstract

The present invention discloses a community intelligent retail management system, which relates to the technical field of retail management. In the present invention, the pedestrian flow of all alternative nodes in the community is monitored, and the pedestrian flow of each alternative node is monitored. Then, the place with the highest pedestrian flow is selected and set as the preliminary point. With the preliminary point as the center, circles with radii R1 and R2 are respectively drawn to define the radiation area and the interference area. Outside the interference area, the sub-optimal points are extracted according to the pedestrian flow corresponding to the alternative nodes as the preliminary points until the total area of the defined radiation area is ≧ α*X1. Each preliminary point is a retail point, which ensures that users at all positions in the community can use it conveniently while taking into account the influence of pedestrian flow on the retail point. By calculating the evaluation value of the performance, pedestrian flow and profit of each retail point, if the evaluation value is lower than the preset value, it is used as an elimination point. When the number of elimination points exceeds 3 or other numbers, the overall retail location of the entire community is adjusted to reduce the long-term losses caused by inaccurate site selection.

Description

Technical Field

[0001] The present invention belongs to the technical field of retail management, and particularly relates to a community intelligent retail management system. Background Art

[0002] Retail management includes commodity management, sales management, etc. However, during the use of current vending machines, due to market fluctuations, fluctuations in the number of people, etc., the management of retail points is rather cumbersome.

[0003] Existing new retail sales management platforms for commodities basically adopt the principle of proximity, that is, using the most central or the location near the entrance and exit as a retail point to supply daily necessities to residential users in the community, resulting in some users in the community who are far from the sales point being unable to use it normally, thus unable to achieve optimized sales management of the new retail sales management platform for commodities. Or manage the retail points through the consumption data of users. For example, Chinese Patent CN113393268A discloses a new retail intelligent sales management platform for commodities based on big data analysis and cloud computing. By statistically analyzing the historical purchase information of each household in the new retail community platform for commodities, calculating the monthly estimated total consumption of each daily necessity in the community, and notifying each registered merchant to supply and demand the corresponding daily necessities to the new retail community warehouse, the optimized sales management of the new retail sales management platform for commodities is achieved.

[0004] Another example is that Chinese Patent CN107239927A discloses an intelligent retail management system and method, which uploads the information received by the retail trays in the system to the server for unified management and statistics to improve management efficiency, and so on. All of these are based on the sales situation of commodities for retail management, lacking a management technology for intelligent retail points. Now, a community intelligent retail management system is provided. Summary of the Invention

[0005] The purpose of the present invention is to provide a community intelligent retail management system, which manages by selecting retail locations in the community, and at the same time evaluates the intelligent retail points set at each location, and replaces the unreasonable positions, solving the problem of the existing retail management system only managing retail based on the sales situation.

[0006] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0007] The present invention is a community intelligent retail management system, including:

[0008] A location selection module: which is used to select retail locations in the community as alternative nodes;

[0009] A node monitoring module: which monitors the number of people flowing at each alternative node and sorts each alternative node according to the number of people flowing;

[0010] Enclosing module: It encloses retail points according to the pedestrian flow.

[0011] Supervision module: It is used to supervise the conversion rate obtained by each retail service area.

[0012] Optimization module: It obtains evaluation values according to the conversion rate and profit.

[0013] Adjustment module: It adjusts retail points according to the evaluation values.

[0014] Furthermore, it further includes a user terminal, which is used for users to upload preselected nodes and transmit them to the location selection module through the controller. The preselected nodes are the positions of retail points expected by users.

[0015] Furthermore, the steps for the location selection module to select a retail location in the community as an alternative node are as follows:

[0016] Step S1: Obtain all path information in the community;

[0017] Step S2: Obtain the intersections between all paths;

[0018] Step S3: Arbitrarily select a path, and obtain the path segments between two adjacent intersections, the path segments between the intersection and the path end point, and the path segments between the intersection and the path start point as the necessary segments;

[0019] Step S4: Extract the midpoints of the necessary segments as alternative nodes;

[0020] Step S5: Repeat steps S3 - S4 until all path analyses are completed to obtain several alternative nodes.

[0021] Furthermore, arbitrarily select a preselected node, and obtain the path where the preselected node is located as a popular path;

[0022] Obtain the shortest distance between the preselected node and the alternative nodes on the popular path where it is located;

[0023] If the shortest distance ≥ L1, then mark the corresponding preselected node as an alternative node as well, otherwise, delete the corresponding preselected node.

[0024] Furthermore, the steps for the enclosing module to enclose retail points according to the pedestrian flow are as follows:

[0025] Q001: Mark each alternative node sorted in descending order of pedestrian flow as: Jbi, where i = 1, 2, 3,..., n, with a total of n alternative nodes;

[0026] Q002: Take the alternative node Jb1 as the preliminary point;

[0027] Q003: Draw a circle with the initial point as the center and a preset radiation radius R1 to define the radiation area;

[0028] Q004: Draw a circle with the initial point as the center and a preset interference radius R2 to define the interference area;

[0029] Q005: Outside the interference area, extract secondary optimal points as initial points according to the pedestrian flow corresponding to the alternative nodes;

[0030] Repeat Q003 - Q005 until the total area of the defined radiation area ≥ α * X1;

[0031] Each initial point is a retail point;

[0032] Wherein, R2 ≥ 2R1, X1 is the total area of the community, α is a preset value, and 0.85 ≤ α < 1.

[0033] Further, if after the enclosure according to Q003 - Q005, the total area of the defined radiation area < α * X1, then select the alternative nodes outside the radiation area as reserve points in order of pedestrian flow size;

[0034] Obtain the shortest distance L2 between the reserve point and the edge line of the radiation area;

[0035] If L2 ≤ X2, then include the range defined by drawing a circle with the reserve point as the center and a preset radius R3 into the corresponding radiation area until the total area of the defined radiation area ≥ α * X1;

[0036] Wherein, X2 is a preset value.

[0037] Further, the secondary optimal point in Q005 is:

[0038] Obtain all alternative nodes outside the interference area and mark them as secondary selection points;

[0039] Obtain the minimum distance between the secondary selection points and the boundary line of the interference area, and mark the distances as CLj, j = 1, 2, 3,..., m; there are m secondary selection points in total;

[0040] Obtain the pedestrian flow corresponding to the secondary selection points, and mark the pedestrian flows of the secondary selection points as WLj;

[0041] Calculate the secondary optimal value according to the formula CYj = 0.631 * WLj + 0.369 * CLj;

[0042] Then the secondary optimal point is the secondary selection point corresponding to the maximum secondary optimal value.

[0043] Further, the method for the supervision module to obtain the conversion rate is:

[0044] Obtain the average daily performance Es and the average daily pedestrian flow Qs of each retail point in the past month;

[0045] Conversion rate = β * Es + γ * Qs;

[0046] Wherein, β + γ = 1, and β ≥ γ, and both β and γ are preset values.

[0047] Furthermore, the preference module obtains an evaluation value according to the conversion rate and profit. Specifically:

[0048] Obtain the monthly profit Ys of each retail point within the past month;

[0049] Evaluation value = β * Ys + γ * conversion rate;

[0050] Wherein, β + γ = 1, and β ≥ γ, and both β and γ are preset values.

[0051] Furthermore, the adjustment module adjusts the retail points according to the evaluation value in the following manner:

[0052] Take the retail points with the evaluation value ≤ X3 as elimination points;

[0053] When the number of elimination points in a community ≥ X4, re - demarcate the retail points. During the re - demarcation process, the preset radiation radius R1 is expanded to θ * R1;

[0054] Wherein, X3, X4, and θ are preset reference values, and θ > 1.

[0055] The present invention has the following beneficial effects:

[0056] The present invention monitors the pedestrian flow of all alternative nodes within the community. Within the community range, monitors the pedestrian flow of each alternative node, then selects the place with the highest pedestrian flow and sets it as the preliminary point. Draw a circle with the preliminary point as the center and the preset radiation radius R1 to demarcate the radiation area, and draw a circle with the preliminary point as the center and the preset interference radius R2 to demarcate the interference area. Outside the interference area, then extract the sub - optimal points as the preliminary points according to the pedestrian flow corresponding to the alternative nodes until the total area of the demarcated radiation area ≥ α * X1. Each preliminary point is a retail point, ensuring that users at all positions within the community can use it conveniently while taking into account the influence of pedestrian flow on the retail points;

[0057] By calculating the performance and pedestrian flow of each retail point, obtain the conversion rate; take the conversion rate as one factor and profit as another factor. After considering both of them together, calculate with weights to obtain an evaluation value. Those with an evaluation value lower than the preset value are used as elimination points. When the number of elimination points exceeds 3 or other numbers, the overall retail locations in the community are adjusted as a whole, reducing the long - term losses caused by inaccurate site selection.

[0058] Of course, it is not necessary for any product implementing the present invention to achieve all the above - mentioned advantages simultaneously. Brief Description of the Drawings

[0059] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0060] Figure 1 It is a schematic structural diagram of the community intelligent retail management system of the present invention;

[0061] Figure 2 It is a schematic diagram for the selection of alternative nodes. Detailed implementation manners

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0063] Please refer to Figure 1-2 As shown, the present invention is a community intelligent retail management system, including: a location selection module for selecting a retail location within the community as an alternative node; a node monitoring module for monitoring the pedestrian flow of each alternative node and sorting each alternative node according to the pedestrian flow; an enclosure module for enclosing retail points according to the pedestrian flow; a supervision module for supervising each retail service area to obtain the conversion rate; an optimization module for obtaining an evaluation value according to the conversion rate and profit; and an adjustment module for adjusting the retail points according to the evaluation value to improve the management efficiency.

[0064] As an embodiment provided by the present invention, preferably, the method for the supervision module to obtain the conversion rate is:

[0065] Obtain the average daily performance value Es and the average daily pedestrian flow value Qs of each retail point within the past month;

[0066] Conversion rate = β * Es + γ * Qs;

[0067] Wherein, β + γ = 1, and β ≥ γ, and both β and γ are preset values.

[0068] As an embodiment provided by the present invention, preferably, the optimization module obtains an evaluation value according to the conversion rate and profit. Specifically:

[0069] Obtain the monthly profit Ys of each retail point within the past month;

[0070] Evaluation value = β * Ys + γ * conversion rate;

[0071] Among them, β + γ = 1, and β ≥ γ, where both β and γ are preset values.

[0072] As an embodiment provided by the present invention, preferably, the manner in which the adjustment module adjusts the retail points according to the evaluation value is as follows:

[0073] Take the retail points with an evaluation value ≤ X3 as elimination points;

[0074] When the number of elimination points in a community ≥ X4, re - demarcate the retail points. During the re - demarcation process, the preset radiation radius R1 is expanded to θ * R1, and continuously optimize the management of retail points to maximize the benefits of retail points;

[0075] Among them, X3, X4, and θ are preset reference values, and θ > 1.

[0076] As an embodiment provided by the present invention, preferably, it further includes a user terminal, and the user terminal is used for the user to upload pre - selected nodes, which are transmitted to the location selection module through the controller, and the pre - selected nodes are the positions of retail points expected by the user.

[0077] As Figure 2 shown, as an embodiment provided by the present invention, preferably, the steps for the location selection module to select retail locations in the community as alternative nodes are as follows:

[0078] Step S1: Obtain all path information in the community;

[0079] Step S2: Obtain the intersection points between all paths, as shown by the intersection point (black dot) between two paths in Figure 2 ;

[0080] Step S3: Arbitrarily select a path, and obtain the path segments between two adjacent intersection points, the path segments between the intersection point and the path end point, and the path segments between the intersection point and the path start point as necessary segments;

[0081] Step S4: Extract the mid - points of the necessary segments (as shown at the diamond position in Figure 2 ) as alternative nodes;

[0082] Step S5: Repeat steps S3 - S4 until all path analyses are completed to obtain several alternative nodes.

[0083] As an embodiment provided by the present invention, preferably, arbitrarily select a pre - selected node and obtain the path where the pre - selected node is located as a popular path;

[0084] Obtain the shortest distance between the pre - selected node and the alternative nodes on the popular path where it is located;

[0085] If the shortest distance ≥ L1, mark the corresponding preselected node as an alternative node; otherwise, delete the corresponding preselected node.

[0086] As an embodiment provided by the present invention, preferably, the step of the delineating module delineating a retail point according to the flow of people is as follows:

[0087] Q001: Mark each alternative node sorted in descending order of the flow of people as: Jbi, where i = 1, 2, 3,..., n, with a total of n alternative nodes;

[0088] Q002: Take the alternative node Jb1 as the initial point;

[0089] Q003: Draw a circle with the initial point as the center and a preset radiation radius R1 to delineate the radiation area;

[0090] Q004: Draw a circle with the initial point as the center and a preset interference radius R2 to delineate the interference area;

[0091] Q005: Outside the interference area, extract the second-best point as the initial point according to the flow of people corresponding to the alternative nodes;

[0092] Repeat Q003 - Q005 until the total area of the delineated radiation area ≥ α * X1;

[0093] Each initial point is a retail point;

[0094] Among them, R2 ≥ 2R1, X1 is the total area of the community, α is a preset value, and 0.85 ≤ α < 1.

[0095] As an embodiment provided by the present invention, preferably, if after delineation according to Q003 - Q005, the total area of the delineated radiation area < α * X1, then select alternative nodes outside the radiation area as reserve points in order of the flow of people size;

[0096] Obtain the shortest distance L2 between the reserve point and the edge line of the radiation area;

[0097] If L2 ≤ X2, then draw a circle with the reserve point as the center and a preset radius R3 to delineate the corresponding range into the radiation area until the total area of the delineated radiation area ≥ α * X1;

[0098] Among them, X2 is a preset value.

[0099] As an embodiment provided by the present invention, preferably, the second-best point in Q005 is:

[0100] Obtain all alternative nodes outside the interference area and mark them as secondary selection points;

[0101] Obtain the minimum distance between the secondary selected points and the boundary line of the interference area, and mark the distances as CLj respectively, where j = 1, 2, 3, …, m; there are m secondary selected points in total.

[0102] Obtain the pedestrian flow corresponding to the secondary selected points, and mark the pedestrian flows of the secondary selected points as WLj respectively.

[0103] Calculate the sub-optimal value according to the formula CYj = 0.631 * WLj + 0.369 * CLj.

[0104] Then the secondary optimal point is the secondary selected point corresponding to the maximum sub-optimal value.

[0105] A community intelligent retail management system monitors the pedestrian flow of all alternative nodes within the community. Within the community scope, monitor the pedestrian flow of each alternative node, and then select the place with the highest pedestrian flow and set it as the preliminary point. Draw a circle to define the radiation area with the preliminary point as the center and a preset radiation radius R1, and draw a circle to define the interference area with the preliminary point as the center and a preset interference radius R2. Outside the interference area, then extract the secondary optimal points as the preliminary points according to the pedestrian flow corresponding to the alternative nodes until the total area of the circled radiation area ≧. Each preliminary point is a retail point, ensuring that users at all positions within the community can use it conveniently while taking into account the impact of pedestrian flow on the retail points; by calculating the performance and pedestrian flow of each retail point, obtain the conversion rate; take the conversion rate as one factor and profit as one factor, and after considering the two together, calculate with weights to obtain an evaluation value. Those with an evaluation value lower than the preset value are used as elimination points. When the number of elimination points exceeds 3 or other numbers, the overall retail locations in the community are adjusted as a whole to reduce the long-term losses caused by inaccurate site selection.

[0106] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0107] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the relevant technical field can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A community intelligent retail management system, characterized in that, it includes: Location selection module: It is used to select a retail location within the community as an alternative node; Node monitoring module: It monitors the pedestrian flow of each alternative node and sorts each alternative node according to the pedestrian flow; Enclosure module: It encloses retail points according to the pedestrian flow; Supervision module: It is used to supervise and obtain the conversion rate of each retail service area; Optimization module: It obtains an evaluation value according to the conversion rate and profit; Adjustment module: It adjusts the retail points according to the evaluation value; The steps for the enclosure module to enclose retail points according to the pedestrian flow are as follows: Q001: Mark each alternative node sorted in descending order of pedestrian flow as: Jbi, i = 1, 2, 3,..., n, a total of n alternative nodes; Q002: Take the alternative node Jb1 as the initial point; Q003: Draw a circle with the initial point as the center and a preset radiation radius R1 to enclose the radiation area; Q004: Draw a circle with the initial point as the center and a preset interference radius R2 to enclose the interference area; Q005: Outside the interference area, extract the second-best point as the initial point according to the pedestrian flow corresponding to the alternative node; Repeat Q003 - Q005 until the total area of the enclosed radiation area ≧ α * X1; Each initial point is a retail point; wherein, R2 ≧ 2R1, X1 is the total area of the community, α is a preset value, 0.85 ≦ α < 1; If after enclosing according to Q003 - Q005, the total area of the enclosed radiation area < α * X1, then select alternative nodes outside the radiation area as reserve points in order of pedestrian flow size; Obtain the shortest distance L2 between the reserve point and the edge line of the radiation area; If L2 ≦ X2, then draw a circle with the reserve point as the center and a preset radius R3 to enclose the corresponding range into the radiation area until the total area of the enclosed radiation area ≧ α * X1; wherein, X2 is a preset value; The second-best point in Q005 is: Obtain all alternative nodes outside the interference area and mark them as secondary selection points; Obtain the minimum distance between the secondary selection points and the boundary line of the interference area, and mark the distances as CLj, j = 1, 2, 3,..., m; a total of m secondary selection points; Obtain the pedestrian flow corresponding to the secondary selection points, and mark the pedestrian flows of the secondary selection points as WLj; Calculate the second-best value according to the formula CYj = 0.631 * WLj + 0.369 * CLj; Then the second-best point is the secondary selection point corresponding to the largest second-best value.

2. A community intelligent retail management system according to claim 1, characterized in that, it further includes a user terminal, and the user terminal is used for the user to upload a preselected node, which is transmitted to the location selection module through the controller, and the preselected node is the location of the retail point expected by the user.

3. A community intelligent retail management system according to claim 2, characterized in that, The steps for the location selection module to select a retail location within the community as an alternative node are as follows: Step S1: Obtain all path information within the community; Step S2: Obtain the intersection points between all paths; Step S3: Arbitrarily select a path, and obtain the path segment between two adjacent intersection points, the path segment between the intersection point and the path end point, and the path segment between the intersection point and the path start point as the necessary segments; Step S4: Extract the midpoints of the necessary segments as candidate nodes; Step S5: Repeat Steps S3 - S4 until all path analyses are completed to obtain several candidate nodes.

4. A community intelligent retail management system according to claim 3, wherein: Arbitrarily select a preselected node, and obtain the path where the preselected node is located as a popular path; Obtain the shortest distance between the preselected node and the candidate nodes on its popular path; If the shortest distance ≥ L1, then mark the corresponding preselected node as a candidate node as well; otherwise, delete the corresponding preselected node.

5. A community intelligent retail management system according to claim 1, wherein, the method for the supervision module to obtain the conversion rate is: Obtain the average daily performance Es and the average daily traffic volume Qs of each retail point in the past month; Conversion rate = β * Es + γ * Qs; wherein, β + γ = 1, and β ≥ γ, and both β and γ are preset values.

6. A community intelligent retail management system according to claim 1, wherein, the optimization module obtains the evaluation value according to the conversion rate and profit, specifically: Obtain the monthly profit Ys of each retail point in the past month; Evaluation value = β * Ys + γ * conversion rate; wherein, β + γ = 1, and β ≥ γ, and both β and γ are preset values.

7. A community intelligent retail management system according to claim 6, wherein, the adjustment method for the adjustment module to adjust the retail points according to the evaluation value is: Take the retail points with an evaluation value ≤ X3 as elimination points; When the number of elimination points in a community ≥ X4, re - demarcate the retail points. During the re - demarcation process, the preset radiation radius R1 is expanded to θ * R1; wherein, X3, X4, and θ are preset reference values, and θ > 1.

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