An autonomous network community management system based on blockchain technology

Abstract

The present invention discloses an autonomous network community management system based on blockchain technology. The network management system includes a customer identification module, a commodity sampling module, and a network navigation module. The customer identification module is used to identify the customer flow in each area of the community supermarket. The commodity sampling module is used to calculate the sales situation of the commodities on the floor stacks in each area. The network navigation module is used to move the positions of the floor stacks in each area according to the customer flow and the sales situation of each commodity floor stack. The customer identification module includes an infrared sensing module, a counting module, and a timing module. The commodity sampling module includes a quality sensing module and a popularity analysis module. The network navigation module includes a positioning module, an arrangement matching module, and a mobile navigation module. The popularity analysis module is electrically connected to the arrangement matching module. The present invention has the characteristic of controlling the movement of the floor stacks for placing commodities according to the actions of customers taking and putting back.

Description

Technical Field

[0001] The present invention relates to the technical field of network community management, and particularly to an autonomous network community management system based on blockchain technology. Background Art

[0002] In order to meet the daily needs of the residents in various communities, many community supermarkets have emerged like mushrooms after rain. Product floor displays are an important way for community supermarkets to promote the sale of products, which can often quickly catch the attention of passing customers and increase the probability of product sales.

[0003] However, there are significant differences between community supermarkets and large supermarkets. The popular products in community supermarkets are independent, and they cannot be displayed in the same way as traditional large supermarkets. What is popular in large supermarkets may not be popular in some communities. In this case, product floor displays magnify the problem of lack of interaction with customers, resulting in an inability to accurately grasp customers' satisfaction with products. As a result, some products with poor sales occupy the prime locations with high foot traffic in community supermarkets in vain, greatly reducing the revenue and efficiency of community supermarkets. Therefore, it is necessary to design an autonomous network community management system based on blockchain technology that matches floor displays with the passenger flow area according to customers' picking actions. Summary of the Invention

[0004] The purpose of the present invention is to provide an autonomous network community management system based on blockchain technology to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solution: An autonomous network community management system based on blockchain technology, including a customer identification module, a product sampling module, and a network navigation module. The customer identification module is used to identify the customer foot traffic in each area of the community supermarket. The product sampling module is used to calculate the sales situation of products on the floor displays in each area. The network navigation module is used to move the positions of floor displays in each area according to the foot traffic and the sales situation of each product floor display.

[0006] According to the above technical solution, the customer identification module includes an infrared sensing module, a counting module, and a timing module. The product sampling module includes a quality sensing module and a popularity analysis module. The network navigation module includes a positioning module, an arrangement matching module, and a movement navigation module. The popularity analysis module is electrically connected to the arrangement matching module;

[0007] The infrared induction module is used to draw the infrared induction thermal imaging of customers in the community supermarket through infrared induction. The counting module is used to record the number of customers. The timing module is used to record time. The quality induction module is used to sense the change in the quantity of goods on the floor stack. The popularity analysis module is used to analyze the sales situation of the floor stack goods in the community supermarket. The positioning module is used to position the floor stack. The arrangement matching module is used to perform area matching on the goods floor stack according to the goods sales situation. The mobile navigation module is used to move the floor stack and navigate it to the matching area.

[0008] According to the above technical solution, the specific working process of the network community management system includes the following steps:

[0009] S1. Multiple goods floor stacks are distributed in the community supermarket. When a customer enters the community supermarket, the infrared induction module performs infrared induction recognition on customers in each area of the community supermarket, and the customer recognition module recognizes the passenger flow H in the area with an area of P near the floor stack.

[0010] S2. The quality induction module senses the change in the quality of the goods on the floor stack, judges the actions of the user picking up and putting back the goods and picking up the goods without putting them back. The popularity analysis module calculates the hesitation degree W of the customer for the goods. The goods sampling module calculates the sales situation S of the floor stack goods in the community supermarket according to the passenger flow.

[0011] S3. The arrangement matching module arranges the passenger flow H at the floor stack position and the sales situation S of the floor stack goods respectively, and then performs matching according to the arrangement order.

[0012] S4. The mobile navigation module is installed at the bottom of the floor stack and goes to the area corresponding to the floor stack according to the result of the arrangement matching module.

[0013] According to the above technical solution, the specific working process of the customer recognition module in the above step S1 includes the following steps:

[0014] S1-1. Multiple goods floor stacks are distributed in the community supermarket. The infrared induction unit is installed in the floor stack. When a customer enters the community supermarket, the infrared induction module performs infrared induction recognition on customers in each area of the community supermarket and draws the human body infrared induction thermal imaging.

[0015] S1-2. The counting unit counts the number of customers n in the area with an area of P near the current floor stack, and the timing module records the total number of customers N passing through this area within the sampling time Δt.

[0016] S1-3. The customer recognition module calculates the passenger flow in this area where k is the customer passing coefficient, which is related to calculating the passenger flow through the number of people passing through this area.

[0017] According to the above technical solution, the specific working process of the commodity sampling module includes the following steps:

[0018] S2-1. The quality sensing module records the quality M of the commodities on the floor stack. When a user picks up a commodity, the quality sensing module records the change Δm in the quality of the commodity.

[0019] S2-2. The quality sensing module determines the actions of the user picking up and not putting back the commodity and picking up and putting back the commodity based on the increase and decrease Δm in the quality of the commodities on the floor stack. That is, for every decrease of Δm in quality, it means a customer has picked up a commodity, and for every increase of Δm in quality, it means a customer has put back a commodity. The quality sensing module records the number of customers who pick up and do not put back as x1 and the number of customers who pick up and put back as x2 within the sampling time Δt.

[0020] S2-3. The popularity analysis module calculates the hesitation degree of customers in this area towards this commodity. The commodity sampling module calculates the sales situation of the floor stack commodities in the regional floor stacks of the community supermarket according to the passenger flow, specifically:

[0021]

[0022] where M is the area of this area.

[0023] According to the above technical solution, the positioning module is installed on each floor stack for positioning. The arrangement matching module arranges the passenger flow H at the floor stack position and the sales situation S of the floor stack commodities respectively, and then matches the floor stack and the area according to the arrangement order, that is, matches the floor stack with good sales to the area with large passenger flow, and matches the floor stack commodities with poor sales to the area with small passenger flow.

[0024] According to the above technical solution, the mobile navigation module includes a path navigation module and a mobile module. The path navigation module is used to perform path navigation on the area where the floor stack is going to, and the mobile module is used to control the movement of the floor stack. The specific working process of the mobile navigation unit in step S4 includes the following steps:

[0025] S4-1. The positioning module locates the position of the floor stack and determines whether the area where the floor stack is located is consistent with the matching result area of the arrangement matching module.

[0026] S4-2. If not, the path navigation module performs path navigation on the area where the floor stack is going to, and the mobile module starts to work. At this time, the mobile module lowers the tires and moves the base of the floor stack.

[0027] S4-3. After the positioning module determines that each floor stack has reached the matched area, the mobile navigation module stops working.

[0028] According to the above technical solution, the network navigation module includes a protection module. The protection unit is used to prevent the ground stack from colliding with customers during movement. The protection module includes a distance analysis unit and a speed control unit. The distance analysis unit is used to analyze the distance between the ground stack and customers, and the speed control unit is used to control the moving speed of the ground stack. The specific working process of the protection module includes the following steps:

[0029] S5-1. During the movement of the ground stack, the distance analysis unit calculates the distance d from the ground stack to the infrared induction thermal imaging of the customer according to the positioning of the ground stack by the positioning unit;

[0030] S5-2. The speed control unit controls the movement of the ground stack at the initial speed v0. When the distance d is less than the preset value d0 of the protection module, the speed control unit reduces the speed to 0, and continues to move forward after the customer leaves.

[0031] According to the above technical solution, the quality induction module includes a reminder unit. The reminder unit is used to remind the community supermarket staff to replenish the goods on the ground stack. When the quality induction module senses that the quality of the goods is lower than the preset value M0, the reminder unit determines that the quantity of the goods on the ground stack is insufficient and sends a stock-out reminder to the staff.

[0032] According to the above technical solution, the network community management system includes a reset unit. The reset unit is used to reset the stored data after the ground stack moves to the matched area, and so on.

[0033] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: The present invention matches the ground stack goods with the passenger flow area according to the actions of customers taking and putting back, so that the popular goods are always placed in the area with large passenger flow, increasing the revenue efficiency of the community supermarket. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0035] Figure 1 is a schematic diagram of the system module of the present invention;

[0036] Figure 2 is a schematic diagram of the moving structure of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0037] 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 a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0038] Please refer to Figure 1-2 , the present invention provides a technical solution: an autonomous network community management system based on blockchain technology. The whole robot adopts a network community management system, including a customer identification module, a commodity sampling module, and a network navigation module. The customer identification module is used to identify the customer flow in each area of the community supermarket. The commodity sampling module is used to calculate the sales situation of the commodities on the floor stacks in each area. The network navigation module is used to move the floor stack positions in each area according to the customer flow and the sales situation of each commodity floor stack.

[0039] The customer identification module includes an infrared sensing module, a counting module, and a timing module. The commodity sampling module includes a quality sensing module and a popularity analysis module. The network navigation module includes a positioning module, an arrangement matching module, and a mobile navigation module. The popularity analysis module is electrically connected to the arrangement matching module;

[0040] The infrared sensing module is used to draw an infrared sensing thermal image of the customers in the community supermarket through infrared sensing. The counting module is used to record the number of customers. The timing module is used to record the time. The quality sensing module is used to sense the change in the quantity of the commodities on the floor stack. The popularity analysis module is used to analyze the sales situation of the floor stack commodities in the areas of the community supermarket. The positioning module is used to position the floor stack. The arrangement matching module is used to perform area matching on the commodity floor stack according to the commodity sales situation. The mobile navigation module is used to move the floor stack and navigate it to the matching area;

[0041] The specific working process of the network community management system includes the following steps:

[0042] S1. Multiple commodity floor stacks are distributed in the community supermarket. When customers enter the community supermarket, the infrared sensing module performs infrared sensing and identification on the customers in each area of the community supermarket. The customer identification module identifies the customer flow H in the area with an area of P near the floor stack, determines the customer flow in each area of the community supermarket, and identifies which areas in the community supermarket are more valuable;

[0043] S2. The quality induction module senses the change in the quality of the goods on the floor display, determines the actions of the user picking up and putting back the goods and picking up the goods without putting them back. The popularity analysis module calculates the hesitation degree W of the customers towards the goods. The goods sampling module calculates the sales situation S of the floor display goods in the regional area of the community supermarket according to the passenger flow. When the customer picks up the goods and then puts them back, it indicates that the customer is not satisfied with the goods. When the customer picks up the goods without putting them back, it indicates that the customer is satisfied with the goods. Thus, the overall sales situation of the goods can be inferred;

[0044] S3. The arrangement matching module arranges the passenger flow H at the floor display position and the sales situation S of the floor display goods respectively, and then matches them according to the arrangement order, so that the popular goods can always be placed in the area with large passenger flow, making the efficiency of the community supermarket better;

[0045] S4. The mobile navigation module is installed at the bottom of the floor display. According to the result of the arrangement matching module, it moves to the corresponding area of the floor display. The floor display moves automatically without incurring additional labor costs, achieving high efficiency;

[0046] The specific working process of the customer recognition module in the above step S1 includes the following steps:

[0047] S1-1. Multiple floor displays are distributed in the community supermarket. The infrared induction unit is installed in the floor display. When the customer enters the community supermarket, the infrared induction module performs infrared induction recognition on the customers in each area of the community supermarket and draws the human body infrared induction thermal imaging;

[0048] S1-2. The counting unit counts the number of customers n in the area with an area of P near the current floor display, and the timing module records the total number of customers N passing through this area within the sampling time Δt;

[0049] S1-3. The customer recognition module calculates the passenger flow in this area where k is the customer passing coefficient, which is related to calculating the passenger flow through the number of people passing through this area, determines the passenger flow in each area of the community supermarket, and identifies which areas in the community supermarket are more precious;

[0050] The specific working process of the goods sampling module includes the following steps:

[0051] S2-1. The quality induction module records the quality M of the goods on the floor display. When the user picks up the goods, the quality induction module records the change in the quality of the goods Δm;

[0052] S2-2. The mass sensing module determines the actions of users picking up and putting back or just picking up goods on the floor stack based on the increase and decrease of the mass of goods on the floor stack, Δm. That is, for every decrease of Δm in mass, it means one customer has picked up a good, and for every increase of Δm in mass, it means one customer has put back a good. The mass sensing module records the number of customers who pick up and do not put back as x1 and the number of customers who pick up and then put back as x2 within the sampling time Δt. When a customer picks up and then puts back a good, it indicates that the customer is not satisfied with the good, and when a customer picks up and does not put back a good, it indicates that the customer is satisfied with the good. From this, the overall sales situation of the good can be inferred;

[0053] S2-3. The popularity analysis module calculates the hesitation degree of customers in this area towards this good The commodity sampling module calculates the sales situation of the floor stack goods in the area of the community supermarket according to the passenger flow, specifically as follows:

[0054]

[0055] where M is the area of this area;

[0056] The positioning module is installed on each floor stack for positioning. The arrangement matching module arranges the passenger flow H at the floor stack position and the sales situation S of the floor stack goods respectively, and then matches the floor stack and the area according to the arrangement order, that is, matches the floor stack with good sales to the area with large passenger flow, and matches the floor stack goods with poor sales to the area with small passenger flow, so that the popular goods can always be placed in the area with large passenger flow, making the efficiency of the community supermarket better;

[0057] The mobile navigation module includes a path navigation module and a mobile module. The path navigation module is used to navigate the path to the area that the floor stack is going to, and the mobile module is used to control the movement of the floor stack. The specific working process of the mobile navigation unit in step S4 includes the following steps:

[0058] S4-1. The positioning module locates the position of the floor stack and determines whether the area where the floor stack is located is consistent with the matching result area of the arrangement matching module, so as to determine whether the floor stack needs to move;

[0059] S4-2. If they are inconsistent, the path navigation module navigates the path to the area that the floor stack is going to, and the mobile module starts to work. At this time, the mobile module lowers the tires and moves the base of the floor stack, and the floor stack moves automatically, without incurring additional labor costs, achieving high efficiency;

[0060] S4-3. After the positioning module determines that each floor stack has reached the matched area, the mobile navigation module stops working

[0061] The network navigation module includes a protection module. The protection unit is used to prevent the floor stack from colliding with customers during movement. The protection module includes a distance analysis unit and a speed control unit. The distance analysis unit is used to analyze the distance between the floor stack and customers, and the speed control unit is used to control the moving speed of the floor stack. The specific working process of the protection module includes the following steps:

[0062] S5-1. During the movement of the floor stack, the distance analysis unit calculates the distance d from the floor stack to the infrared induction thermal imaging of customers based on the positioning of the floor stack by the positioning unit;

[0063] S5-2. The speed control unit controls the movement of the floor stack at the initial speed v0. When the distance d is less than the preset value d0 of the protection module, the speed control unit reduces the speed to 0. After the customer leaves, it continues to move forward, protecting the personal safety of customers;

[0064] The quality induction module includes a reminder unit. The reminder unit is used to remind the staff of the community supermarket to replenish the goods on the floor stack. When the quality induction module senses that the quality of the goods is lower than the preset value M0, the reminder unit determines that the quantity of goods on the floor stack is insufficient and sends a shortage reminder to the staff;

[0065] The network community management system includes a reset unit. The reset unit is used to reset the stored data after the floor stack moves to the matching area, and so on.

[0066] Embodiment: Suppose there are multiple floor stacks of goods distributed in the community supermarket. The counting unit counts that the number of customers n = 10 in the area with an area of P = 50m 2 at one of the current floor stacks. The timing module records that the total number of customers N = 30 passing through this area within the sampling time Δt = 1h; The customer recognition module calculates the passenger flow H1 = 0.4 in this area, and the passenger flow in the area where the second floor stack is located is H2 = 0.5. The quality induction module judges the actions of customers picking up and putting back and picking up without putting back the goods based on the increase and decrease Δm of the goods quality on the floor stack, and records that the number of customers picking up without putting back within the sampling time Δt = 1h is x1 = 5, and the number of customers picking up and putting back is x2 = 10. The popularity analysis module calculates the hesitation degree W = 2 of customers in the area of the first floor stack for this commodity. The commodity sampling module calculates the sales situation S1 = 5 of the floor stack goods in the area of the community supermarket according to the passenger flow, and the sales situation S2 = 4 of the goods on the second floor stack. The arrangement matching module arranges the passenger flow H at the floor stack position and the sales situation S of the floor stack goods respectively, and judges that the sales situation of the goods on the first and second floor stacks does not match the passenger flow, and needs to exchange positions. The path navigation module conducts path navigation for the area where the floor stack is about to go, and the mobile module starts to work. At this time, the mobile module lowers the tires and moves the base of the floor stack. After the positioning module determines that each floor stack reaches the matching area, the mobile navigation module stops working.

[0067] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0068] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An autonomous network community management system based on blockchain technology, characterized in that: The network community management system includes a customer identification module, a commodity sampling module, and a network navigation module. The customer identification module is used to identify the customer flow in each area of the community supermarket. The commodity sampling module is used to calculate the sales situation of the commodities on the floor stacks in each area. The network navigation module is used to move the positions of the floor stacks in each area according to the customer flow and the sales situation of each commodity floor stack; The customer identification module includes an infrared sensing module, a counting module, and a timing module. The commodity sampling module includes a quality sensing module and a popularity analysis module. The network navigation module includes a positioning module, an arrangement matching module, and a mobile navigation module. The popularity analysis module is electrically connected to the arrangement matching module; The infrared sensing module is used to draw an infrared sensing thermal image of the customers in the community supermarket through infrared sensing. The counting module is used to record the number of customers. The timing module is used to record the time. The quality sensing module is used to sense the change in the quantity of the commodities on the floor stack. The popularity analysis module is used to analyze the sales situation of the regional floor stack commodities in the community supermarket. The positioning module is used to position the floor stack. The arrangement matching module is used to perform area matching on the commodity floor stack according to the commodity sales situation. The mobile navigation module is used to move the floor stack and navigate it to the matching area; The specific working process of the network community management system includes the following steps: S1. Multiple commodity floor stacks are distributed in the community supermarket. When a customer enters the community supermarket, the infrared sensing module performs infrared sensing and identification on the customers in each area of the community supermarket. The customer identification module identifies the customer flow H in the area with an area of P near the floor stack; S2. The quality sensing module senses the change in the quality of the commodities on the floor stack, judges the actions of the user picking up and putting back the commodity and picking up the commodity without putting it back. The popularity analysis module calculates the hesitation degree W of the customer for the commodity. The commodity sampling module calculates the sales situation S of the regional floor stack commodities in the community supermarket according to the customer flow; S3. The arrangement matching module arranges the customer flow H at the floor stack position and the sales situation S of the floor stack commodities respectively, and then performs matching according to the arrangement order; S4. The mobile navigation module is installed at the bottom of the floor stack and goes to the area corresponding to the floor stack according to the result of the arrangement matching module; The specific working process of the customer identification module in the above step S1 includes the following steps: S1-1. Multiple commodity floor stacks are distributed in the community supermarket. The infrared sensing unit is installed in the floor stack. When a customer enters the community supermarket, the infrared sensing module performs infrared sensing and identification on the customers in each area of the community supermarket and draws the human body infrared sensing thermal image; S1-2. The counting unit counts the number of customers n in the area with an area of P near the current floor stack. The timing module records the total number of customers N passing through this area within the sampling time Δt; S1-3. The customer identification module calculates the passenger flow in this area. where k is the customer passing coefficient, which is related to calculating the passenger flow based on the number of people passing through this area; The specific working process of the commodity sampling module includes the following steps: S2-1. The quality sensing module records the quality M of the commodities on the floor stack. When the user picks up a commodity, the quality sensing module records the change in the quality of the commodity Δm; S2-2. The mass sensing module determines the actions of users picking up and putting back or just picking up goods on the floor stack based on the increase and decrease of the mass of goods on the floor stack, Δm. That is, for every decrease of Δm in mass, it means a customer has picked up a good, and for every increase of Δm in mass, it means a customer has put back a good. The mass sensing module records the number of customers who pick up and do not put back as x1, and the number of customers who pick up and then put back as x2 within the sampling time Δt. S2-3. The popularity analysis module calculates the hesitation degree of customers in this area towards this product. The product sampling module calculates the sales of the in-store display products in the community supermarket according to the passenger flow, specifically: Where M is the area of this region.

2. The autonomous network community management system based on blockchain technology according to claim 1, characterized in that: The positioning module is installed on each floor stack for positioning. The arrangement matching module arranges the passenger flow H at the floor stack position and the sales situation S of the floor stack goods respectively, and then matches the floor stack and the region according to the arrangement order, that is, matches the floor stack with good sales to the region with large passenger flow, and matches the floor stack goods with poor sales to the region with small passenger flow.

3. An autonomous network community management system based on blockchain technology according to claim 2, characterized in that: The mobile navigation module includes a path navigation module and a mobile module. The path navigation module is used to navigate the path of the floor stack to the region it is going to, and the mobile module is used to control the movement of the floor stack. The specific working process of the mobile navigation unit in step S4 includes the following steps: S4-1. The positioning module locates the position of the floor stack and determines whether the region where the floor stack is located is consistent with the matching result region of the arrangement matching module. S4-2. If not, the path navigation module navigates the path of the floor stack to the region it is going to, and the mobile module starts to work. At this time, the mobile module lowers the tires and moves the base of the floor stack. S4-3. After the positioning module determines that each floor stack has reached the matched region, the mobile navigation module stops working.

4. An autonomous network community management system based on blockchain technology according to claim 3, characterized in that: The network navigation module includes a protection unit, which is used to prevent the floor stack from colliding with customers during movement. The protection unit includes a distance analysis unit and a speed control unit. The distance analysis unit is used to analyze the distance between the floor stack and customers, and the speed control unit is used to control the moving speed of the floor stack. The specific working process of the protection unit includes the following steps: S5-1. During the movement of the floor stack, the distance analysis unit calculates the distance d from the floor stack to the infrared induction thermal imaging of customers based on the positioning of the floor stack by the positioning unit. S5-2. The speed control unit controls the movement of the floor stack at the initial speed v0. When the distance d is less than the preset value d0 of the protection unit, the speed control unit reduces the speed to 0, and continues to move forward after the customer leaves.

5. An autonomous network community management system based on blockchain technology according to claim 4, characterized in that: The mass sensing module includes a reminder unit, which is used to remind the community supermarket staff to replenish the goods on the floor stack. When the mass sensing module senses that the mass of the goods is lower than the preset value M0, the reminder unit determines that the quantity of goods on this floor stack is insufficient and sends a stock shortage reminder to the staff.

6. The autonomous network community management system based on blockchain technology according to claim 5, wherein: The network community management system includes a reset unit, which is used to reset the stored data after the floor stack moves to the matched region, and so on.

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