A method, system, electronic device and readable medium for recommending clothes drying equipment

Abstract

The present invention relates to a method, system, electronic device and readable medium for recommending drying equipment. A method for recommending drying equipment includes: obtaining demand data; the demand data includes balcony parameters and house area information; according to the demand data, device parameters of a recommended drying equipment are obtained by matching in platform data. By using the method for recommending drying equipment provided by the present invention, a user only inputs the demand data into the system, and then automatic recommendation of drying equipment can be achieved through big data matching of the demand data in the platform data. Moreover, the automatically recommended drying equipment is obtained based on big data matching, which conforms to the designs of most users' residential balconies. The recommended result is more objective and rapid, and there is great progress in the field of recommending drying equipment.

Description

Technical Field

[0001] The present invention relates to electronic devices, and in particular to a method, system, electronic device, and readable medium for recommending clothes drying devices. Background Art

[0002] With the improvement of the living environment in China, especially for residents in urban areas, more and more users choose electric clothes dryers, and there are various sizes of clothes dryers available in the market for users to choose from. When choosing the size of a clothes dryer, users need to calculate the size of the balcony and the floor height to select a suitable clothes dryer.

[0003] Currently, the way to recommend clothes dryers to users is basically that the obligatory personnel, after hearing the balcony data reported by the users, recommend corresponding clothes dryers to the users according to experience, and cannot definitely give the most suitable clothes dryer size to the users. Summary of the Invention

[0004] In view of the deficiencies of the above-mentioned prior art, one of the purposes of the present invention is to provide a method for recommending clothes drying devices, which can automatically recommend suitable clothes drying devices to users on the basis of objectivity and rapidity according to the balcony parameters input by the users.

[0005] Another purpose of the present invention is to provide a system for recommending clothes drying devices.

[0006] Another purpose of the present invention is to provide an electronic device.

[0007] Another purpose of the present invention is to provide a computer-readable medium.

[0008] To achieve the above purposes, the present invention adopts the following technical solutions:

[0009] On the one hand, the present invention provides a method for recommending clothes drying devices, including:

[0010] Obtaining demand data; the demand data includes balcony parameters and house area information;

[0011] According to the demand data, matching in the platform data to obtain the device parameters of the recommended clothes drying device.

[0012] Further, in the method for recommending clothes drying devices, the house area information includes house location data;

[0013] The steps for obtaining the house location data are as follows:

[0014] Obtained by map positioning or selecting data information of the country, province, city, and district to which it belongs.

[0015] Further, in the method for recommending clothes drying devices, before matching the demand data in the platform data, it further includes:

[0016] Obtain the average lighting duration, temperature, and humidity for each month in the corresponding region based on the house location data;

[0017] Combined with the balcony parameters, obtain the lighting duration, temperature, and humidity of the corresponding balcony every day.

[0018] Further, for the clothes drying equipment recommendation method, the matching in the platform data specifically includes:

[0019] Perform data matching in the platform data according to the balcony parameters, lighting duration, temperature, and humidity of the balcony;

[0020] Obtain the equipment parameters of the recommended clothes drying equipment.

[0021] Further, for the clothes drying equipment recommendation method, the balcony parameters include orientation data, floor height data, length data, width data, and height data.

[0022] Further, for the clothes drying equipment recommendation method, the demand data further includes height information; the equipment parameters further include first lifting data representing the maximum lifting length of the drying rod;

[0023] When obtaining the clothes drying parameters of the recommended clothes drying equipment, it further includes:

[0024] Match and obtain the first lifting data according to the height information and the balcony parameters.

[0025] Further, for the clothes drying equipment recommendation method, after obtaining the equipment parameters of the recommended clothes drying equipment, the following steps are further executed:

[0026] Display the installation effect diagram of the recommended clothes drying equipment in the form of pictures or three-dimensional diagrams.

[0027] On the other hand, the present invention provides a clothes drying equipment recommendation system using any one of the foregoing clothes drying equipment recommendation methods, including:

[0028] An acquisition module for acquiring demand data; the demand data includes balcony parameters and house area information;

[0029] A processing module for obtaining the equipment parameters of the recommended clothes drying equipment through big data matching according to the demand data by using platform data.

[0030] On the other hand, the present invention provides an electronic device, including:

[0031] One or more memories storing computer programs;

[0032] One or more processors;

[0033] When one or more processors execute the computer program, the method for recommending a drying device described in any one of the foregoing is implemented.

[0034] On the other hand, the present invention provides a computer-readable medium storing a computer program, which, when executed by a processor, implements the method for recommending a drying device described in any one of the foregoing.

[0035] Compared with the prior art, the method, system, electronic device and readable medium for recommending a drying device provided by the present invention have the following beneficial effects:

[0036] Using the method for recommending a drying device provided by the present invention, a user only needs to input demand data into the system, and then through big data matching of the demand data in the platform data, automatic recommendation of the drying device can be achieved. Moreover, the automatically recommended drying device is obtained based on big data matching, which conforms to the designs of most users' residential balconies. The recommended result is more objective and rapid, representing a great progress in the field of drying device recommendation. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flowchart of the method for recommending a drying device provided by the present invention;

[0038] Figure 2 is a block diagram of the structure of the system for recommending a drying device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] To make the objectives, technical solutions and effects of the present invention clearer and more definite, the following further describes the present invention in detail with reference to the accompanying drawings and by way of examples. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention.

[0040] Those skilled in the art should understand that the foregoing general description and the following detailed description are exemplary and illustrative specific embodiments of the present invention and are not intended to limit the present invention.

[0041] As used herein, the term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process or method including a list of steps not only includes those steps but may also include other steps not expressly listed or inherent to such process or method. Throughout the specification, the appearances of the phrases "in one embodiment", "in another embodiment" and similar language may, but do not necessarily, all refer to the same embodiment.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0043] Please refer to Figure 1, the present invention provides a method for recommending drying equipment, which can be applied to mobile devices, servers or the cloud. By receiving demand data and through big data matching, drying equipment suitable for the demand data is obtained and recommended to users, enabling users to quickly determine the drying equipment suitable for themselves. Among them, when applied to a mobile device, a platform needs to be loaded onto the mobile terminal, so as to ensure real-time recommendation whether connected to the network or not. The real-time mobile terminal is applicable to fixed specialty stores and shopping malls to meet purchasers. When applied to a server or the cloud, the demand data can be obtained by input through a corresponding APP installed on the terminal, or can be input when the terminal accesses a web page; among them, the terminal includes a mobile terminal (such as a mobile phone or other mobile devices with the function of loading APPs), a computer, etc.

[0044] In a specific implementation, the user can input corresponding demand data on the APP or the web page, and then the drying equipment recommendation system will output the equipment parameters of the most suitable drying equipment according to the demand data. Of course, if the number of drying equipment that meets the demand parameters is multiple, a list of multiple adaptable drying equipment will be displayed for the user to select.

[0045] The method for recommending drying equipment includes:

[0046] Obtain demand data; the demand data includes balcony parameters and house area information; generally, the demand data is used to characterize the basic situation of the user's drying space, including information such as the space size of the balcony and the sunshine duration that the balcony space can receive, which is convenient for subsequently matching in the platform data to obtain recommended drying equipment.

[0047] Furthermore, in some embodiments, the demand data is obtained through the APP of the mobile terminal. The APP provides a parameter data input location or an option selection location, such as the balcony orientation (obtained through option selection as east, south, west, north, southwest, etc.), the length, width, and height of the balcony (obtained through the data input location, used to calculate the area of the balcony and the space height of the balcony, such as an area of 3 square meters and a distance from the ground to the roof of 2 meters). The house area information can provide the home location through the GPS positioning function or the Beidou positioning function of the mobile terminal in the APP, or determine the specific location of the house by selecting it on the map, or the user selects the country, province, city, and district (such as Panyu District, Guangzhou City, Guangdong Province), or the user describes the specific location of the house to the street or community in words (such as a certain street and a certain community in Panyu District, Guangzhou City, Guangdong Province).

[0048] Furthermore, in some embodiments, the demand data is obtained by input through the web page of the intelligent terminal (including the mobile terminal and the PC terminal). The specific input method is the same as that of the above mobile terminal and will not be elaborated.

[0049] According to the demand data, device parameters of the recommended drying equipment are obtained by matching in the platform data. In this embodiment, the platform data is obtained by acquiring the operation data and installation data of a number of drying equipment, specifically: the mapping relationship between different balcony parameters, house area information, and the installed drying equipment is counted, and at the same time, the evaluation results of the drying effects of different models of drying equipment in the same installation environment (the same or similar balcony parameters and house area information) are mapped and stored. When recommending drying equipment, as long as the demand data is matched one by one in the platform data, the information of the best drying equipment can be quickly obtained, and then the corresponding device parameters can be obtained.

[0050] Furthermore, the device parameters are used to determine the size, type, etc. of the recommended drying equipment, specifically including the size parameters and function parameters of the drying equipment. The size parameters are for adapting to the sizes of different balconies, and the function parameters include disinfection, air drying, drying, etc., which are optimized and screened according to the drying equipment configured on balconies with similar sizes and orientations in the platform data.

[0051] Using the drying equipment recommendation method provided by the present invention, the user only needs to input the demand data into the system, and then through big data matching of the demand data in the platform data, the automatic recommendation of drying equipment can be realized. Moreover, the automatically recommended drying equipment is obtained based on big data matching, which conforms to the designs of most users' residential balconies, and the recommended results are more objective and rapid.

[0052] Furthermore, as a preferred solution, in this embodiment, the house area information includes house location data;

[0053] The steps for obtaining the house location data are as follows:

[0054] It is obtained through map positioning or by selecting the data information of the country, province, city, and district to which it belongs. In specific implementation, those skilled in the art can, on the basis of reading the technical solution of the present invention, appropriately select a suitable map positioning method or a method for selecting urban area data information to obtain the location data of the house.

[0055] Furthermore, as a preferred solution, in this embodiment, before matching the demand data in the platform data, it further includes:

[0056] The average sunshine duration, temperature, and humidity of each month in the corresponding region are obtained according to the house location data; generally, for the average sunshine duration, temperature, and humidity data of each month in multiple regions included in the platform data, they can be obtained and stored through data integration of historical data.

[0057] Combined with the balcony parameters, the corresponding daily sunlight duration, temperature, and humidity of the balcony are obtained. Generally, the platform data is stored in a big data platform (server or cloud). When the house location data is received, the big data platform combines the household address and the user's house area information to further calibrate the user's living environment. After determining the environmental parameters around the house, the size of the drying space, possible sunlight duration, temperature, and humidity of the user's house can be calculated based on the orientation of the user's household balcony, so as to facilitate the subsequent recommendation of drying equipment. For example, in a relatively humid environment, it is advisable to choose drying equipment made of corrosion-resistant materials, such as plastic. If it is a dry environment, drying equipment made of organic gel materials can be recommended.

[0058] Further, as a preferred solution, in this embodiment, the matching in the platform data specifically includes:

[0059] Perform data matching in the platform data according to the balcony parameters, sunlight duration, temperature, and humidity of the balcony;

[0060] Obtain the equipment parameters of the recommended drying equipment. Generally, the balcony parameters preferably include balcony space size data, which tend to recommend drying equipment of appropriate size for users; sunlight duration, temperature, and humidity tend to recommend drying equipment of appropriate materials or appropriate types (such as styles that can extend outside the balcony, styles with functions such as disinfection, air drying, and drying).

[0061] Further, as a preferred solution, in this embodiment, the balcony parameters include orientation data, floor height data (i.e., the floor where the balcony is located), length data, width data, and height data. Generally, the items included in the balcony parameters are used to characterize the basic attributes of the balcony, that is, the space size, ventilation status, sunlight duration, etc. of the current balcony can be determined through the orientation data, floor height data, length data, width data, and height data, and then can participate in the recommendation analysis operation of drying equipment.

[0062] Further, as a preferred solution, in this embodiment, the demand data further includes height information; the equipment parameters further include first lifting data representing the maximum lifting length of the drying rod;

[0063] When obtaining the drying parameters of the recommended drying equipment, it further includes:

[0064] Match the first lifting data according to the height information and the balcony parameters. Preferably, the first lifting data satisfies the following formula:

[0065] W ≤ Y - S;

[0066] S = h1 + a * h2;

[0067] Wherein, W is the first lifting data; Y is the height data in the balcony parameters; h1 is the thickness of the drying equipment; h2 is the height information; a is a predetermined ratio value. Further, the predetermined ratio value is preferably 60%-90%, more preferably 70%-80%, and even more preferably 75% or 78%.

[0068] Further, as a preferred solution, in this embodiment, after obtaining the equipment parameters of the recommended drying equipment, the following steps are further executed:

[0069] Display the installation effect diagram of the recommended drying equipment in the form of pictures or three-dimensional diagrams. In this embodiment, there are two implementation forms of the installation effect diagram: one is to adapt the composition to different balcony sizes and orientations according to the equipment parameters of the recommended drying equipment, and then store it in the server (or there are several compositions of several drying equipment stored in the platform data). When the recommended drying equipment is determined, the corresponding composition can be called for display; the other is to use different types of balcony parameters as the composition basis, that is, for different types of balcony types, give better and best recommended solutions for composition, and then store it in the server (or there are several compositions of several balcony types stored in the platform data). When the balcony parameters are determined, the better and best installation solutions can be directly determined, and the corresponding installation effect diagrams can be displayed.

[0070] Further, as a preferred solution, in this embodiment, when the number of the recommended drying equipment is multiple, they are sorted and displayed in a predetermined manner. The predetermined manner is to sort them in size by the user praise rate or other evaluation indexes characterizing the customer use effect.

[0071] Further, as a preferred solution, in this embodiment, the equipment parameters further include the service life of the drying equipment and the life data of the steel wire rope. Of course, the service life and life data can be obtained by statistics of the use of the current drying equipment by users with balcony parameters similar to the house location data in the house location data, or can be calculated according to the average weight of the hanging objects plus the balcony parameters. Those skilled in the art can select the corresponding algorithm for calculation according to the requirements.

[0072] Further, after the drying equipment is installed, it is also bound to the user account through the APP, and sensors at both ends of the steel wire rope are used to detect the weight and load-bearing of the dried clothes in real time. After connecting to the network, the foregoing detection data is sent to the server, mobile terminal or cloud to calculate the life of the steel wire rope of the drying equipment and send the calculation result to the APP in the user mobile terminal for display in real time. The specific steps are as follows:

[0073] The big data platform analyzes the data uploaded by the drying equipment through calculation;

[0074] Obtain the local temperature and humidity in real time, further analyze the service life of the steel wire rope, and promptly inform the user to replace it. Those skilled in the art can select the calculation method (i.e., algorithm) of the service life of the steel wire rope in the art according to actual needs, and the present invention does not make any limitations.

[0075] After long-term use by the user, the steel wire rope may break. At present, there is only a prompt for the service life, but there is no technical solution for real-time prompting based on the actual environment where the user is located. After the technical solution of the present invention, the service life of the steel wire rope can be calculated in real time according to the weight of the hanging object when the user uses the clothes drying equipment and the environmental parameters around the balcony, so as to prevent the steel wire rope from breaking during the use process by the user.

[0076] In the prior art, a large amount of pre-sales analysis is carried out by the user, but the living environments of each user's family are very different. If the user does not have professional knowledge, the operation difficulty is great. Through the algorithm analysis of the big data platform, for different geographical locations and the size of the user's drying space, the appropriate size and type of the clothes drying machine are recommended to the user (for example, with certain additional functions, and the additional functions include disinfection, air drying, drying, etc.), and after-sales support is provided to reduce accidents caused by the expiration of the service life of the steel wire rope.

[0077] Please refer to Figure 2 , the present invention also provides a clothes drying equipment recommendation system using the clothes drying equipment recommendation method described in any one of the foregoing embodiments, including:

[0078] An acquisition module, configured to acquire demand data; the demand data includes balcony parameters and house area information;

[0079] A processing module, configured to obtain the equipment parameters of the recommended clothes drying equipment through big data matching based on the platform data according to the demand data.

[0080] Further, as a preferred solution, in this embodiment, the house area information includes house location data; the clothes drying equipment recommendation system further includes a positioning module, which is connected to the processing module. The positioning module is configured to acquire the current geographical location data and send it to the processing module.

[0081] The steps for obtaining the house location data are as follows:

[0082] The house location data is obtained by the processing through map positioning or selecting the data information of the country, province, city, and district to which it belongs.

[0083] Further, as a preferred solution, in this embodiment, before matching according to the demand data in the platform data, it further includes:

[0084] The processing module obtains the average sunlight duration, temperature, and humidity of each month in the corresponding area according to the house location data; and

[0085] Combined with the balcony parameters, the corresponding daily lighting duration, temperature and humidity of the balcony are obtained.

[0086] Furthermore, as a preferred solution, in this embodiment, the matching in the platform data specifically includes:

[0087] The processing module performs data matching in the platform data according to the daily lighting duration, temperature and humidity of the balcony; and then obtains the device parameters of the recommended drying equipment.

[0088] Furthermore, as a preferred solution, in this embodiment, the demand data further includes height information; the device parameters further include first lifting data representing the maximum lifting length of the drying rod;

[0089] When obtaining the drying parameters of the recommended drying equipment, it further includes:

[0090] The processing module matches and obtains the first lifting data according to the height information and the balcony parameters.

[0091] Furthermore, as a preferred solution, in this embodiment, the drying equipment recommendation system further includes a display module, which is connected to the processing module; after obtaining the device parameters of the recommended drying equipment, the following steps are further executed:

[0092] The processing module drives the display module to display the installation effect picture of the recommended drying equipment in the form of a picture or a three-dimensional stereogram.

[0093] The present invention also provides an electronic device, including:

[0094] One or more memories storing a computer program; the computer program architecture obtains the drying equipment recommendation system described in any of the foregoing embodiments.

[0095] One or more processors;

[0096] When one or more processors execute the computer program, the drying equipment recommendation method described in any of the foregoing embodiments is implemented.

[0097] The present invention also provides a computer-readable medium storing a computer program, and when the computer program is executed by a processor, the drying equipment recommendation method described in any of the foregoing embodiments is implemented.

[0098] More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0099] In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. And in this application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.

[0100] It can be understood that for those of ordinary skill in the art, equivalent substitutions or changes can be made according to the technical solutions and inventive concepts of the present invention, and all such changes or substitutions should fall within the protection scope of the claims appended to the present invention.

Claims

1. A method for recommending clothes drying equipment, characterized in that, Including: Obtain requirement data; the requirement data includes balcony parameters, house area information, and height information; According to the requirement data, match in the platform data to obtain the device parameters of the recommended clothes drying device, where the device parameters are used to determine the size and type of the recommended clothes drying device, and the device parameters include first lifting data representing the maximum lifting length of the drying rod; The platform data is obtained by acquiring the operation data and installation data of several clothes drying devices. Specifically, it is obtained by statistically mapping the relationship between different balcony parameters, house area information, and the installed clothes drying devices, and at the same time, mapping and storing the evaluation results of the clothes drying effects of different models of clothes drying devices in the same installation environment. Here, the same installation environment refers to an installation environment with the same or similar balcony parameters and house area information.

2. The clothes drying equipment recommendation method according to claim 1, wherein The house area information includes house location data; The steps for obtaining the house location data are as follows: Obtained by map positioning or selecting the data information of the country, province, city, and district to which it belongs.

3. The clothes drying equipment recommendation method according to claim 2, characterized in that, Before matching according to the requirement data in the platform data, it also includes: Obtain the average light duration, temperature, and humidity of each month in the corresponding area according to the house location data; Combine with the balcony parameters to obtain the light duration, temperature, and humidity of the corresponding balcony every day.

4. The method for recommending a clothes drying device according to claim 3, wherein The matching in the platform data specifically includes: Perform data matching in the platform data according to the balcony parameters, light duration, temperature, and humidity of the balcony; Obtain the device parameters of the recommended clothes drying device.

5. The method for recommending a clothes drying device according to claim 1, wherein, The balcony parameters include orientation data, storey height data, length data, width data, and height data.

6. The method for recommending a clothes drying device according to claim 5, characterized in that, When obtaining the clothes drying parameters of the recommended clothes drying device, it also includes: Match the first lifting data according to the height information and the balcony parameters.

7. The method for recommending clothes drying equipment according to claim 1, wherein After obtaining the device parameters of the recommended clothes drying device, the following steps are also executed: Display the installation effect diagram of the recommended clothes drying device in the form of pictures or 3D stereograms.

8. A clothes drying equipment recommendation system using the clothes drying equipment recommendation method according to any one of claims 1-7, characterized in that, Including: An acquisition module for acquiring requirement data; the requirement data includes balcony parameters, house area information, and height information; A processing module for, according to the requirement data, performing big data matching through the platform data to obtain the device parameters of the recommended clothes drying device, where the device parameters are used to determine the size and type of the recommended clothes drying device, and the device parameters include first lifting data representing the maximum lifting length of the drying rod; The platform data is obtained by acquiring the operation data and installation data of several clothes drying devices. Specifically, it is obtained by statistically mapping the relationship between different balcony parameters, house area information, and the installed clothes drying devices, and at the same time, mapping and storing the evaluation results of the clothes drying effects of different models of clothes drying devices in the same installation environment. Here, the same installation environment refers to an installation environment with the same or similar balcony parameters and house area information.

9. An electronic device, characterized in that, Including: One or more memories storing computer programs; one or more processors; When one or more processors execute the computer programs, the clothes drying device recommendation method according to any one of claims 1-7 is implemented.

10. A computer-readable medium, characterized in that, A computer program is stored, and when the computer program is executed by a processor, the method for recommending a clothes drying device according to any one of claims 1-7 is implemented.

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