Self-service clothes washing intelligent service system

Abstract

The invention discloses a self-service clothes washing intelligent service system, which comprises an equipment end, a data processing center and a user interaction end, and is characterized in that the data processing center is in data connection with the equipment end and the user interaction end; according to the invention, the preferential strategy is formulated by using the preferential strategy formulating unit, so that the price of the device side with the use frequency lower than the average level is reduced, and the price of the device side with the use frequency higher than the average level is increased, thereby ensuring that each device side can be used; the user preference analysis unit can automatically recommend idle equipment terminals within the clothes washing time preferred by the user, the equipment selection interface can display idle equipment online, and the order state display interface can display the clothes washing remaining time online, so that convenience is brought to the user to use, and the user experience is improved. The situation that the income of an operator is reduced due to the fact that the equipment end is occupied can be prevented through a clothes taking overtime charging mechanism, and the user feedback collection module provides an opinion feedback window for the user so as to improve the service quality and the user experience.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, in particular to a self-service laundry intelligent service system. Background Art

[0002] In order to meet the students' laundry needs, self-service washing machines are often installed in dormitories on existing university campuses. Early campus self-service washing machines mainly used coin-operated payment, but with the development of electronic technology and information technology, card payment and online payment have gradually become popular. These payment methods are more convenient and safe, convenient for students to use, and convenient for operators to manage and settle funds. However, the existing self-service washing machines still have the following shortcomings when in use: First, there is a lack of laundry equipment recommendation function, which causes some washing machines to have a shorter service life due to excessive use, which increases maintenance costs. There is a lack of laundry time recommendation function, which causes users to be unable to obtain idle equipment information in time during the preferred laundry time, thus affecting the user experience; second, users cannot obtain the use status and laundry completion status of the washing machine, and need to go to the site to confirm, which causes inconvenience in use. At the same time, since users cannot put away the washed clothes in time, the washing machine is occupied, which affects the operator's revenue; third, there is a lack of effective feedback mechanism. Problems encountered during use or suggestions cannot be fed back in time. For some potential safety hazards, such as leakage, water leakage, etc., if they cannot be fed back in time, they may pose a serious threat to the safety of users' lives and property, resulting in a decline in service quality and user experience. Summary of the invention

[0003] The object of the present invention is to provide a self-service laundry intelligent service system to solve the problems raised in the above background technology.

[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a self-service laundry intelligent service system, including a device end, a data processing center and a user interaction end, the data processing center establishes data connections with the device end and the user interaction end respectively, and the data processing center includes a device control module, a device status monitoring module, a data storage module, an intelligent recommendation module, an order processing module and a user feedback processing module.

[0005] Preferably, the intelligent recommendation module includes a usage count unit, a preferential strategy formulation unit, a user preference analysis unit and a recommendation execution unit, and the usage count unit establishes a data connection with the preferential strategy formulation unit, and the recommendation execution unit establishes data connections with the preferential strategy formulation unit and the user preference analysis unit respectively.

[0006] Preferably, the preferential policy formulation unit adopts the following algorithm formula:

[0007]

[0008] like The preferential strength

[0009] like So:

[0010] If d i ′≤M, then the preferential strength d i =d i ′; if d i ′>M, then the preferential strength d i =M;

[0011] Final discounted price:

[0012] P i =P0-d i

[0013] In the formula, n is the number of devices, u is i is the number of times the device is used. is the average number of times the device is used, d i ′ is the initial preferential strength, d i is the preferential strength, M is the preset maximum preferential strength, P i is the final discounted price, P0 is the original price, k is the price increase coefficient, and k≥1.

[0014] Preferably, the order processing module includes an order receiving unit, an order status updating unit and an order fee calculating unit.

[0015] Preferably, the user feedback processing module includes a text preprocessing unit, a key information extraction unit, a question classification unit, a question processing unit and a feedback reply unit.

[0016] Preferably, the text preprocessing unit establishes a data connection with the key information extraction unit, the key information extraction unit establishes a data connection with the question classification unit, and the question classification unit establishes a data connection with the question processing unit.

[0017] Preferably, the problem classification unit adopts the following algorithm formula:

[0018]

[0019] In the formula, is the vector obtained after preprocessing the feedback text T, C j is the classifier for the problem type, is the cosine similarity.

[0020] Preferably, the user interaction terminal includes an interaction interface module and a message notification module.

[0021] Preferably, the interactive interface module includes a device selection interface, a laundry mode selection interface, an order creation interface, an order payment interface, an order status display interface and a feedback interface.

[0022] Preferably, the message notification module includes an order status notification unit, a recommendation information notification unit and a feedback result notification unit.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention utilizes a preferential strategy formulation unit to formulate preferential strategies, reduce the price of equipment ends with usage times below the average level, and increase the price of equipment ends with usage times above the average level, thereby ensuring that each equipment end can be used; the user preference analysis unit can automatically recommend idle equipment ends within the user's preferred laundry time; the equipment selection interface can display idle equipment online; the order status display interface can display the remaining laundry time online for user convenience; the overtime billing mechanism for picking up clothes can prevent the operator's revenue from being reduced due to the equipment end being occupied; the user feedback collection module provides a feedback window for users to improve service quality and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a system structure block diagram of the present invention;

[0025] Figure 2 This is a structural block diagram of the intelligent recommendation module of the present invention;

[0026] Figure 3 It is a structural block diagram of the order processing module of the present invention;

[0027] Figure 4 It is a structural block diagram of the user feedback processing module of the present invention;

[0028] Figure 5 It is a structural block diagram of the interactive interface module of the present invention;

[0029] Figure 6 This is a structural block diagram of the message notification module of the present invention.

[0030] In the figure: 1. Device end; 2. Data processing center; 21. Device control module; 22. Device status monitoring module; 23. Data storage module; 24. Intelligent recommendation module; 241. Usage times statistics unit; 242. Discount strategy formulation unit; 243. User preference analysis unit; 244. Recommendation execution unit; 25. Order processing module; 251. Order receiving unit; 252. Order status update unit; 253. Order cost calculation unit; 26. User feedback processing module; 261. Text preprocessing unit; 2 62. Key information extraction unit; 263. Problem classification unit; 264. Problem processing unit; 265. Feedback response unit; 3. User interaction terminal; 31. Interaction interface module; 311. Equipment selection interface; 312. Washing mode selection interface; 313. Order creation interface; 314. Order payment interface; 315. Order status display interface; 316. Feedback interface; 32. Message notification module; 321. Order status notification unit; 322. Recommended information notification unit; 323. Feedback result notification unit. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Please refer to the attached Figure 1 -Attached Figure 6, an embodiment provided by the present invention: a self-service laundry intelligent service system, including a device end 1, a data processing center 2 and a user interaction end 3, the data processing center 2 establishes data connections with the device end 1 and the user interaction end 3 respectively, the data processing center 2 includes a device control module 21, a device status monitoring module 22, a data storage module 23, an intelligent recommendation module 24, an order processing module 25 and a user feedback processing module 26, the device end 1 is a laundry device, the data processing center 2 is used to analyze and process data, the user interaction end 3 is used to interact with the data processing center 2, the device control module 21 is used to control the device end 1, the device status monitoring module 22 is used to change the device end 1 status information displayed on the user interaction end 3, the data storage module 23 is used to store data, the intelligent recommendation module 24 is used to recommend the device end 1, the order processing module 2 5 is used to process orders, and the user feedback processing module 26 is used to process user feedback; the intelligent recommendation module 24 includes a usage count unit 241, a preferential strategy formulation unit 242, a user preference analysis unit 243 and a recommendation execution unit 244, and the usage count unit 241 establishes a data connection with the preferential strategy formulation unit 242, and the recommendation execution unit 244 establishes a data connection with the preferential strategy formulation unit 242 and the user preference analysis unit 243 respectively. The usage count unit 241 is used to count the usage times of the device end 1, the preferential strategy formulation unit 242 is used to generate preferential plans, the user preference analysis unit 243 is used to analyze the user's preferred laundry time, and the recommendation execution unit 244 is used to recommend the preferential device end 1 and the idle device end 1 within the preferred laundry time; the preferential strategy formulation unit 242 adopts the following algorithm formula:

[0033]

[0034] like The preferential strength

[0035] like So:

[0036] If d i ′≤M, then the preferential strength d i =d i ′; if d i ′>M, then the preferential strength d i =M;

[0037] Final discounted price:

[0038] P i =P0-d i

[0039] Where n is the number of device terminals 1, u i The number of times device 1 is used. is the average number of times device 1 is used, d i ′ is the initial preferential strength, d i is the preferential strength, M is the preset maximum preferential strength, P i is the final discounted price, P0 is the original price, k is the price increase coefficient, and k≥1; the order processing module 25 includes an order receiving unit 251, an order status updating unit 252 and an order fee calculation unit 253, the order receiving unit 251 is used to receive an order, the order status updating unit 252 is used to change the order status, and the order fee calculation unit 253 is used to calculate the order fee and the overtime clothing collection fee; the user feedback processing module 26 includes a text preprocessing unit 261, a key information extraction unit 262, a question classification unit 263, a question processing unit 264 and a feedback reply unit 265, the text The preprocessing unit 261 establishes a data connection with the key information extraction unit 262, the key information extraction unit 262 establishes a data connection with the question classification unit 263, the question classification unit 263 establishes a data connection with the question processing unit 264, the text preprocessing unit 261 is used to preprocess text information, the key information extraction unit 262 is used to extract text key information, the question classification unit 263 is used to classify questions, the question processing unit 264 is used to process the classified questions, the feedback reply unit 265 is used to reply the processing result to the user interaction terminal 3, and the question classification unit 263 adopts the following algorithm formula:

[0040]

[0041] In the formula, is the vector obtained after preprocessing the feedback text T, C j is the classifier for the problem type, is the cosine similarity; the user interaction terminal 3 includes an interaction interface module 31 and a message notification module 32, the interaction interface module 31 is used to provide functional interaction services, and the message notification module 32 is used to send message reminders; the interaction interface module 31 includes a device selection interface 311, a laundry mode selection interface 312, an order creation interface 313, an order payment interface 314, an order status display interface 315 and an opinion feedback interface 316, the device selection interface 311 is used to display the idle device terminal 1, the laundry mode selection interface 312 is used to select the laundry mode, and the order creation interface 313 is used When creating a laundry order, the order payment interface 314 is used to pay the laundry fees and overtime clothing pickup fees, the order status display interface 315 is used to display the order status, and the feedback interface 316 is used to fill in and upload feedback; the message notification module 32 includes an order status notification unit 321, a recommended information notification unit 322 and a feedback result notification unit 323. The order status notification unit 321 is used to send message reminders when the order status changes, the recommended information notification unit 322 is used to provide recommended message reminders, and the feedback result notification unit 323 is used to display the feedback results to the user.

[0042] Working principle: When using the present invention, the user establishes a connection with the data processing center 2 through the user interaction terminal 3, selects the device terminal 1 through the device selection interface 311 of the interactive interface module 31, and the device selection interface 311 only displays the device terminal 1 in an idle state. After selecting the device terminal 1, jump to the laundry mode selection interface 312, and after determining the laundry mode, jump to the order creation interface 313. After the order is determined, the order is sent to the order receiving unit 251 of the order processing module 25. The order receiving unit 251 stores the received order in the data storage module 23, and calculates the order fee through the order fee calculation unit 253, and then sends it to the user interaction terminal 3. The user interaction terminal 3 jumps to the order payment interface 314, and returns after the payment is successful. The information is sent to the order processing module 25, the order status update unit 252 changes the order status to pending, the device control module 21 sends an instruction to the device end 1 according to the order data, the washing machine lid of the device end 1 is automatically opened, and the order payment interface 314 will display the payment completion, and prompt the user to put the clothes in and close the lid. After the lid is closed, the device end 1 starts according to the washing mode of the order, and returns a signal to the data processing center 2, the order status update unit 252 changes the order status to in progress, and the user interaction end 3 jumps to the order status display interface 315. The order status display interface 315 displays the remaining time of the order. When the washing is completed, the order status update unit 252 changes the order status to pending, and the order status display interface 315 will display The countdown to the time to pick up the clothes and the option to complete the order. The user does not need to pay extra fees to pick up the clothes within the countdown. By clicking the option to complete the order, the lid of the washing machine on the device end 1 can be automatically opened. After the countdown is completed, the overtime billing will begin. The user clicks the option to complete the order to jump to the order payment interface 314. After paying the overtime fee, the lid of the washing machine on the device end 1 will automatically open. After opening, the lid of the washing machine will be closed within the set time. After the lid is closed, the device end 1 will send a signal to the data processing center 2, and the order status updating unit 252 will change the order status to completed. In the above process, the device status monitoring module 22 will change the device selection interface 311 according to the change of the order status, so that it only displays the idle device end 1, and the order of the message notification module 32 The order status notification unit 321 will automatically issue corresponding reminders according to the changes in the order status. After the order is completed, the order status display interface 315 will jump to the feedback interface 316. The user can fill in the feedback or skip it directly through the feedback interface 316. The result will be uploaded to the user feedback processing module 26. The text preprocessing unit 261 performs preprocessing operations such as cleaning, denoising, and word segmentation on the feedback text submitted by the user. The key information extraction unit 262 uses natural language processing technology to extract key information from the preprocessed feedback text. The question classification unit 263 classifies the extracted key information and sends the result to the question processing unit 264. The question processing unit 264 automatically replies to different questions according to the settings.The problems that need to be handled manually are sent to the management personnel for processing, and the processing results are sent to the feedback result notification unit 323 through the feedback reply unit 265; the intelligent recommendation module 24 of the present invention will recommend the device end 1 to be used and the recommended laundry time, specifically: the usage count unit 241 will record the usage times of each device end 1, and the preferential strategy formulation unit 242 will formulate a laundry preferential strategy based on the usage times, so that the laundry price of the device end 1 with a laundry frequency lower than the average level is lower, and the laundry price of the device end 1 with a laundry frequency higher than the average level is higher. The recommendation execution unit 244 will add a recommendation symbol to the display icon of the device end 1 with a laundry frequency lower than the average level on the device selection interface 311 to attract users to use it. The user preference analysis unit 243 analyzes the user order data and determines the user's preferred laundry time. The recommendation execution unit 244 recommends the idle device end 1 within the time and sends information to the recommendation information notification unit 322 for reminder. ,

[0043] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A self-service laundry intelligent service system, comprising a device end (1), a data processing center (2) and a user interaction end (3), characterized in that: The data processing center (2) establishes data connections with the device end (1) and the user interaction end (3) respectively. The data processing center (2) comprises a device control module (21), a device status monitoring module (22), a data storage module (23), an intelligent recommendation module (24), an order processing module (25) and a user feedback processing module (26).

2. A self-service laundry intelligent service system according to claim 1, characterized in that: The intelligent recommendation module (24) includes a usage count unit (241), a preferential policy formulation unit (242), a user preference analysis unit (243) and a recommendation execution unit (244), and the usage count unit (241) establishes a data connection with the preferential policy formulation unit (242), and the recommendation execution unit (244) establishes a data connection with the preferential policy formulation unit (242) and the user preference analysis unit (243), respectively.

3. A self-service laundry intelligent service system according to claim 2, characterized in that: The preferential policy formulation unit (242) adopts the following algorithm formula: like The preferential strength like So: If d i ′≤M, then the preferential strength d i =d i ′; if d i ′>M, then the preferential strength d i =M; Final discounted price: P i =P0-d i Where n is the number of devices (1), u i is the number of times the device (1) is used, is the average number of times the device (1) is used, d i ′ is the initial preferential strength, d i is the preferential strength, M is the preset maximum preferential strength, P i is the final discounted price, P0 is the original price, k is the price increase coefficient, and k≥1.

4. The self-service laundry intelligent service system according to claim 1, characterized in that: The order processing module (25) includes an order receiving unit (251), an order status updating unit (252) and an order fee calculating unit (253).

5. The self-service laundry intelligent service system according to claim 1, characterized in that: The user feedback processing module (26) includes a text preprocessing unit (261), a key information extraction unit (262), a question classification unit (263), a question processing unit (264) and a feedback reply unit (265).

6. The self-service laundry intelligent service system according to claim 5, characterized in that: The text preprocessing unit (261) establishes a data connection with the key information extraction unit (262), the key information extraction unit (262) establishes a data connection with the question classification unit (263), and the question classification unit (263) establishes a data connection with the question processing unit (264).

7. The self-service laundry intelligent service system according to claim 6, characterized in that: The problem classification unit (263) uses the following algorithm formula: In the formula, is the vector obtained after preprocessing the feedback text T, C j is the classifier for the problem type, is the cosine similarity.

8. The self-service laundry intelligent service system according to claim 1, characterized in that: The user interaction terminal (3) comprises an interaction interface module (31) and a message notification module (32).

9. The self-service laundry intelligent service system according to claim 8, characterized in that: The interactive interface module (31) comprises a device selection interface (311), a laundry mode selection interface (312), an order creation interface (313), an order payment interface (314), an order status display interface (315) and an opinion feedback interface (316).

10. The self-service laundry intelligent service system according to claim 8, characterized in that: The message notification module (32) includes an order status notification unit (321), a recommendation information notification unit (322) and a feedback result notification unit (323).

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