Water drinking device control method and device based on internet of things

Abstract

The application relates to the technical field of device control, and discloses a water drinking device control method and device based on the Internet of Things, which comprises the following steps: determining user water drinking habit information according to historical use information of a water drinking device by the user; determining current water drinking demand information of a target user based on user information, water drinking habit information and device information of other intelligent devices in the same scene; and then determining water drinking device control parameters according to the current water drinking demand information and controlling the water drinking device. It can be seen that the application can obtain various information based on the Internet of Things, intelligently control the water drinking device, improve the fitting degree of the water drinking device control parameters and the user water drinking demand, improve the control intelligence and flexibility of the water drinking device, improve the use convenience of the user for the water drinking device, improve the use experience of the user for the water drinking device, and enhance the user stickiness.

Description

Technical Field

[0001] This invention relates to the field of equipment control technology, and in particular to a method and apparatus for controlling drinking water equipment based on the Internet of Things. Background Technology

[0002] With the continuous development of science and technology and the continuous improvement of people's living standards, more and more smart home devices are gradually entering thousands of households, providing convenience for people's lives. Smart water dispensers, with their features of fast hot water dispensing and ease of use, have become frequently used drinking water devices in people's daily lives.

[0003] In real life, people have increasingly higher demands for the intelligence and convenience of controlling and using smart devices. However, the adjustment of parameters such as water temperature and operating mode in existing water dispensers generally requires users to manually adjust them according to their needs, resulting in low intelligence and convenience, which is detrimental to users' use of the water dispensers. Therefore, it is particularly important to propose a technical solution that can improve the intelligence and convenience of controlling water dispensers. Summary of the Invention

[0004] This invention provides a method and apparatus for controlling drinking water equipment based on the Internet of Things, which can help improve the intelligence and convenience of controlling drinking water equipment.

[0005] To address the aforementioned technical problems, the first aspect of this invention discloses a method for controlling drinking water equipment based on the Internet of Things (IoT), the method comprising:

[0006] Acquire user information of the target user and device information of the target device in the current scenario. The target device includes a water dispenser and at least one other smart device. The device information of the water dispenser includes the target user’s historical usage information of the water dispenser within a preset historical time period.

[0007] Based on the historical usage information, the target user's drinking habits information is determined;

[0008] Based on the target user's user information, the drinking habits information, and the device information of each of the other smart devices, the target user's current drinking needs information is determined;

[0009] Based on the target user's current drinking water needs, control parameters for the drinking water equipment are generated, and the drinking water equipment is controlled based on these control parameters.

[0010] As an optional implementation, in the first aspect of the present invention, the user information of the target user includes the physiological information of the target user;

[0011] The step of determining the target user's current drinking water needs based on the target user's user information, the drinking water habit information, and the device information of each of the other smart devices includes:

[0012] Based on the target user's physiological information, determine the target user's physical health information;

[0013] Based on the drinking habits information and the device information of each of the other smart devices, at least one recommended drinking plan is generated for the target user;

[0014] Based on the target user's health information and each of the recommended drinking water plans, the target user's current drinking water needs are determined.

[0015] As an optional implementation, in the first aspect of the present invention, the device information of each of the other smart devices includes the device operating status information of the other smart device, and the method further includes:

[0016] Obtain the scene environment information corresponding to the current scene, including scene temperature and / or scene humidity;

[0017] And, the step of generating at least one recommended drinking water plan for the target user based on the drinking water habit information and the device information of each of the other smart devices includes:

[0018] Based on the drinking habits information, predict the target user's standard drinking plan within a preset drinking cycle. The standard drinking plan includes at least one of standard drinking volume, standard drinking frequency, and standard drinking time points.

[0019] Determine the first impact coefficient of the device operating status information of each of the other smart devices on the target user's drinking water, and determine the second impact coefficient of the scene environment information on the target user's drinking water;

[0020] Based on the standard drinking water plan, the first drinking water influence coefficient, and the second drinking water influence coefficient, at least one recommended drinking water plan is generated for the target user.

[0021] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0022] When device abnormality information of at least one of the other smart devices in the current scenario is detected, for each other smart device, an abnormality identifier corresponding to the device abnormality information of the other smart device is determined. The device abnormality information includes at least one of device fault information, device offline information, and device power failure information.

[0023] The abnormality identifier is used to determine the operational interference information of the drinking water equipment based on a preset mapping relationship;

[0024] Based on the operational interference information, it is determined whether the drinking water equipment meets the current drinking water needs of the target user. When the drinking water equipment does not meet the current drinking water needs, the drinking water equipment correction parameters are generated based on the operational interference information, and the drinking water equipment control parameters are updated based on the drinking water equipment correction parameters.

[0025] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0026] Determine other user information for at least one other user outside the current scene, the other user information including user location information and user movement information;

[0027] For each of the other users, the relative movement information of the other user relative to the current scene is determined based on the user movement information of that other user;

[0028] For each of the other users, when the relative movement information of the other user indicates that the other user is moving toward the current scene, the arrival time information of the other user to the current scene is predicted based on the user location information and user movement information of the other user.

[0029] For each of the other users, based on the other user's drinking habits and arrival time information, predict the other user's predicted drinking needs when arriving at the current scene;

[0030] For each of the other users, predictive control parameters for the drinking water equipment are generated based on the predicted drinking water demand information of the other user, and the drinking water equipment is controlled according to the predictive control parameters.

[0031] As an optional implementation, in the first aspect of the present invention, after controlling the drinking water device based on the control parameters of the drinking water device, the method further includes:

[0032] The system monitors the target user's current usage information of the drinking water device and analyzes the target user's current drinking water information based on the current usage information. The current drinking water information includes at least one of the following: current water consumption, current number of times of drinking water, and current drinking time.

[0033] Calculate the difference between the current drinking water information and the current drinking water demand information, and determine whether the difference is greater than a preset difference threshold;

[0034] When the difference in drinking water exceeds the difference threshold, a healthy drinking water reminder is generated based on the difference, and the target user is reminded based on the healthy drinking water reminder.

[0035] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0036] For each of the other smart devices, determine the degree of association between the other smart device and the water drinking device, and determine the association relationship between the other smart device and the water drinking device based on the degree of association. The association relationship includes a linkage control relationship or a non-linkage control relationship.

[0037] For each of the other smart devices, a control influence coefficient of the water drinking device on the other smart device is determined based on the association between the other smart device and the water drinking device. The control influence coefficient includes a linkage control influence coefficient or a non-linkage control influence coefficient.

[0038] For each of the other smart devices, smart device control parameters are generated based on the control influence coefficient corresponding to the other smart device and the drinking device control parameters of the drinking device, and the other smart device is controlled based on the smart device control parameters.

[0039] A second aspect of the present invention discloses an Internet of Things (IoT) based control device for drinking water equipment, the device comprising:

[0040] The first acquisition module is used to acquire user information of the target user and device information of the target device in the current scene. The target device includes a water drinking device and at least one other smart device. The device information of the water drinking device includes the target user's historical usage information of the water drinking device within a preset historical time period.

[0041] The determination module is used to determine the target user's drinking habits information based on the historical usage information;

[0042] The determining module is further configured to determine the current drinking water demand information of the target user based on the user information of the target user, the drinking water habit information, and the device information of each of the other smart devices;

[0043] The first generation module is used to generate drinking water equipment control parameters for the drinking water equipment based on the current drinking water demand information of the target user, and to control the drinking water equipment based on the drinking water equipment control parameters.

[0044] As an optional implementation, in a second aspect of the present invention, the user information of the target user includes the physiological information of the target user;

[0045] The method by which the determining module determines the current drinking water needs of the target user based on the user information of the target user, the drinking water habit information, and the device information of each of the other smart devices specifically includes:

[0046] Based on the target user's physiological information, determine the target user's physical health information;

[0047] Based on the drinking habits information and the device information of each of the other smart devices, at least one recommended drinking plan is generated for the target user;

[0048] Based on the target user's health information and each of the recommended drinking water plans, the target user's current drinking water needs are determined.

[0049] As an optional implementation, in a second aspect of the invention, the device information of each of the other smart devices includes the device operating status information of the other smart device, and the apparatus further includes:

[0050] The second acquisition module is used to acquire scene environment information corresponding to the current scene, the scene environment information including scene temperature and / or scene humidity;

[0051] Furthermore, the method by which the determining module generates at least one recommended drinking water plan for the target user based on the drinking water habit information and the device information of each of the other smart devices specifically includes:

[0052] Based on the drinking habits information, predict the target user's standard drinking plan within a preset drinking cycle. The standard drinking plan includes at least one of standard drinking volume, standard drinking frequency, and standard drinking time points.

[0053] Determine the first impact coefficient of the device operating status information of each of the other smart devices on the target user's drinking water, and determine the second impact coefficient of the scene environment information on the target user's drinking water;

[0054] Based on the standard drinking water plan, the first drinking water influence coefficient, and the second drinking water influence coefficient, at least one recommended drinking water plan is generated for the target user.

[0055] As an optional implementation, in a second aspect of the present invention, the determining module is further configured to, when detecting device abnormality information of at least one of the other smart devices in the current scenario, determine an abnormality identifier corresponding to the device abnormality information of each other smart device, wherein the device abnormality information includes at least one of device fault information, device offline information, and device power failure information;

[0056] The determining module is further configured to determine the operational interference information of the abnormal identifier on the drinking water equipment according to a preset mapping relationship;

[0057] The device further includes:

[0058] The judgment module is used to determine whether the water dispenser meets the current drinking water needs of the target user based on the operational interference information. When the water dispenser does not meet the current drinking water needs, the module generates water dispenser correction parameters based on the operational interference information and updates the water dispenser control parameters based on the water dispenser correction parameters.

[0059] As an optional implementation, in a second aspect of the present invention, the determining module is further configured to determine other user information of at least one other user outside the current scene, the other user information including user location information and user movement information;

[0060] The determining module is further configured to, for each of the other users, determine the relative movement information of the other user relative to the current scene based on the user movement information of the other user;

[0061] The device further includes:

[0062] The prediction module is used to predict the arrival time of each other user when the relative movement information of the other user indicates that the other user is moving towards the current scene, based on the user location information and user movement information of the other user.

[0063] The prediction module is also used to predict the predicted drinking water demand information of each other user when it arrives at the current scene, based on the other user's drinking water habit information and the arrival time information.

[0064] The first generation module is further configured to generate predictive control parameters for the drinking water device for each of the other users based on the other users' predicted drinking water demand information, and control the drinking water device according to the predictive control parameters.

[0065] As an optional implementation, in a second aspect of the invention, the apparatus further includes:

[0066] The monitoring module is used to monitor the current usage information of the target user on the drinking water device after the first generation module controls the drinking water device based on the control parameters of the drinking water device, and to analyze the current drinking water information of the target user based on the current usage information. The current drinking water information includes at least one of the following: current water consumption, current number of times of drinking water, and current drinking time node.

[0067] The calculation module is used to calculate the difference between the current drinking water information and the current drinking water demand information, and to determine whether the difference between the drinking water information and the current drinking water demand information is greater than a preset difference threshold.

[0068] The first generation module is further configured to generate a healthy drinking water reminder message based on the drinking water difference when the difference is greater than the difference threshold, and to remind the target user based on the healthy drinking water reminder message.

[0069] As an optional implementation, in a second aspect of the present invention, the determining module is further configured to, for each of the other smart devices, determine the degree of association between the other smart device and the drinking water device, and determine the association relationship between the other smart device and the drinking water device based on the degree of association, wherein the association relationship includes a linkage control relationship or a non-linkage control relationship;

[0070] The determining module is further configured to, for each of the other smart devices, determine the control influence coefficient of the drinking water device on the other smart device based on the association relationship between the other smart device and the drinking water device, wherein the control influence coefficient includes a linkage control influence coefficient or a non-linkage control influence coefficient;

[0071] The device further includes:

[0072] The second generation module is used to generate intelligent device control parameters for each of the other intelligent devices based on the control influence coefficient corresponding to the other intelligent device and the drinking device control parameters of the drinking device, and to perform device control on the other intelligent device based on the intelligent device control parameters.

[0073] A third aspect of the present invention discloses another IoT-based drinking water equipment control device, the device comprising:

[0074] Memory containing executable program code;

[0075] A processor coupled to the memory;

[0076] The processor calls the executable program code stored in the memory to execute the IoT-based drinking water equipment control method disclosed in the first aspect of the present invention.

[0077] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the Internet of Things-based drinking water equipment control method disclosed in the first aspect of the present invention.

[0078] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0079] In this embodiment of the invention, the user's drinking habits are determined based on the user's historical usage information of the drinking water equipment. Based on the user information, drinking habits, and equipment information of other smart devices in the same scenario, the target user's current drinking water needs are determined. Then, the control parameters of the drinking water equipment are determined based on the current drinking water needs, and the equipment is controlled accordingly. Therefore, implementing this invention enables intelligent control of drinking water equipment by acquiring information from multiple sources through the Internet of Things, improving the alignment between the control parameters and the user's drinking water needs, enhancing the intelligence and flexibility of the control, improving the ease of use for the user, improving the user experience, and increasing user loyalty. Attached Figure Description

[0080] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0081] Figure 1 This is a schematic diagram illustrating an application scenario of a water-drinking equipment control method based on the Internet of Things disclosed in an embodiment of the present invention.

[0082] Figure 2 This is a schematic flowchart of a water drinking equipment control method based on the Internet of Things disclosed in an embodiment of the present invention;

[0083] Figure 3 This is a schematic flowchart of another IoT-based drinking water equipment control method disclosed in an embodiment of the present invention;

[0084] Figure 4 This is a schematic diagram of the structure of a drinking water equipment control device based on the Internet of Things disclosed in an embodiment of the present invention;

[0085] Figure 5 This is a schematic diagram of another IoT-based drinking water equipment control device disclosed in an embodiment of the present invention;

[0086] Figure 6 This is a schematic diagram of another IoT-based drinking water equipment control device disclosed in an embodiment of the present invention. Detailed Implementation

[0087] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0088] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0089] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0090] This invention discloses a water dispenser control method and device based on the Internet of Things (IoT). It can acquire information from multiple sources via the IoT to intelligently control the water dispenser, improving the alignment of control parameters with user drinking needs, enhancing the intelligence and flexibility of control, increasing user convenience, improving the user experience, and strengthening user loyalty. Detailed descriptions follow.

[0091] To better understand the IoT-based drinking water equipment control method and apparatus described in this invention, the applicable scenario for the IoT-based drinking water equipment control method is first described. Specifically, this scenario can be as follows: Figure 1 As shown, Figure 1 This is a schematic diagram illustrating an application scenario of a water dispenser control method based on the Internet of Things (IoT) disclosed in an embodiment of the present invention. For example... Figure 1As shown in the diagram, this scenario represents a home setting, which includes a target user and target devices. Target devices include a water dispenser and other smart devices, such as smart lights, mobile phones, and smart air conditioners. These other smart devices can include linked devices (like mobile phones and smart air conditioners) that have a control relationship with the water dispenser, or non-linked devices (like smart lights) that don't have a control relationship with it. User information about the target user can be obtained through smart devices like mobile phones and smart air conditioners. The water dispenser can intelligently record the target user's drinking information and analyze their drinking habits based on this information. It can then intelligently control the water dispenser according to the user information and drinking habits, and simultaneously adjust other smart devices based on the control parameters of the water dispenser.

[0092] It should be noted that, Figure 1 The scenario diagram shown is only intended to illustrate the applicable scenarios for the IoT-based water dispenser control method. The target users, mobile phones, smart air conditioners, smart lights, and water dispensers involved are also only for illustrative purposes. Figure 1 The illustrated scenario is not limited to this. Furthermore, the above describes the applicable scenarios for the IoT-based drinking water equipment control method. The following section provides a detailed description of the IoT-based drinking water equipment control method and device.

[0093] Example 1

[0094] Please see Figure 2 , Figure 2 This is a flowchart illustrating a method for controlling drinking water equipment based on the Internet of Things (IoT) disclosed in an embodiment of the present invention. Figure 2 The described IoT-based drinking water equipment control method can be applied to IoT-based drinking water equipment control devices. These devices may include a device control unit for generating drinking water equipment control parameters. The device control unit may include any one of a user device, a smart server, or a smart platform. User devices include, but are not limited to, at least one of smartphones (Android phones, iOS phones, etc.), smartwatches, and smart home devices (such as smart drinking water equipment, smart refrigerators, smart speakers, smart TVs, smart range hoods, etc.). The smart server may include a local server or a cloud server; however, this embodiment of the invention does not limit the scope of the method. Figure 2 As shown, the IoT-based drinking water equipment control method may include the following operations:

[0095] 101. Obtain user information of the target user and device information of the target device in the current scenario. The target device includes a water dispenser and at least one other smart device. The device information of the water dispenser includes the target user's historical usage information of the water dispenser within a preset historical time period.

[0096] In this embodiment of the invention, optionally, the current scenario can be the usage scenario of the drinking water equipment. The current scenario can include one of the following: home scenario, office scenario, public usage scenario, etc. The user information of the target user can include the physiological information of the target user, and can also include the movement status information of the target user. The physiological information of the target user can include one or more of the following: heart rate, body temperature, blood pressure, respiratory rate, osmotic pressure, etc., which are not limited by this invention.

[0097] In this embodiment of the invention, optionally, the target device in the current scenario may include a water dispenser and at least one other smart device. Taking a home scenario as an example, the other smart devices may include one or more of the following: a smart refrigerator, a smart speaker, a smart TV, a smart range hood, and a smart lighting device. The device information of the water dispenser may include the target user's historical usage information of the water dispenser within a preset historical time period, and may also include the historical operation information of the water dispenser within the historical time period. The preset historical time period may be one day, two days, one week, two weeks, or one month, or it may be a user-defined time period. The historical usage information may include the target user's historical usage information. The information may include one or more of the following: the number of times a user uses the water dispenser within a preset historical time period; the time of each use; the amount of water consumed each time; and the water temperature each time. Historical operation information may include one or more of the following: the operating time of the water dispenser within the preset historical time period; the operating mode; and the water volume processed. The operating mode may include one or more of the following: heating mode; heat preservation mode; cooling mode; filtration mode; and sterilization mode. The device information of other smart devices may include device operation status information, which may include at least one of the following: other device operation mode; and other device operating time. This invention is not limited to these.

[0098] 102. Based on historical usage information, determine the drinking habits of target users.

[0099] In this embodiment of the invention, optionally, the target user's drinking habit information may include the target user's drinking habit information within a preset drinking cycle. A preset drinking cycle may be a day or a week, or it may be a user-defined duration. This invention uses a preset drinking cycle of one day as an example. The target user's drinking habit information within a preset drinking cycle may include the target user's comprehensive drinking habit information and special drinking habit information. The comprehensive drinking habit information may include one or more of the target user's habitual drinking frequency, habitual drinking volume, habitual drinking time, and habitual drinking temperature. The special drinking habit information may include the target user's habitual drinking information after performing specific activities. For example, the target user may habitually drink water at a specific temperature and in a specific amount, such as 300ml of water at 45℃, within a preset duration after waking up or after a meal. This invention does not impose any limitations.

[0100] 103. Based on the target user's user information, drinking habits information, and device information of each other smart device, determine the target user's current drinking water needs.

[0101] In this embodiment of the invention, optionally, the target user's current drinking water demand information may include the target user's current drinking water volume demand, drinking water temperature demand, etc., and may also include the target user's drinking water demand information within a preset drinking water cycle after the current time point. This invention does not limit this.

[0102] 104. Based on the target user's current drinking water demand information, generate drinking water equipment control parameters for the drinking water equipment, and control the drinking water equipment based on the drinking water equipment control parameters.

[0103] In this embodiment of the invention, optionally, when the current drinking water demand information includes the target user's current drinking water volume demand, drinking water temperature demand, etc., the drinking water equipment control parameters for the drinking water equipment may include one or more of the following: drinking water equipment operation mode control parameters, drinking water equipment operation time control parameters, drinking water equipment water temperature control parameters, and drinking water equipment water volume control parameters. When the current drinking water demand information includes the target user's drinking water demand information within a preset drinking water cycle after the current time node, the drinking water equipment control parameters for the drinking water equipment may include at least one operation time node control parameter of the drinking water equipment within a preset drinking water cycle after the current time node, and one or more of the following: drinking water equipment operation duration control parameters, operation mode control parameters, water temperature control parameters, and water volume control parameters at each operation time node. This invention does not impose any limitations.

[0104] It is evident that implementation Figure 2The described IoT-based water dispenser control method can determine a user's drinking habits based on the user's historical usage information of the water dispenser, improving the accuracy of this determination. Based on user information, drinking habits, and device information from other smart devices in the same scenario, it determines the target user's current drinking needs. Then, based on these current needs, it determines the control parameters for the water dispenser and controls it. This method leverages IoT to acquire multifaceted information, enabling intelligent control of the water dispenser, improving the alignment between control parameters and user needs, enhancing the intelligence and flexibility of control, increasing user convenience, improving the user experience, and strengthening user loyalty.

[0105] In an optional embodiment, the IoT-based drinking water device control method may further include the following operations:

[0106] When device abnormality information of at least one other smart device in the current scene is detected, for each other smart device, the abnormality identifier corresponding to the device abnormality information of the other smart device is determined. The device abnormality information includes at least one of device fault information, device offline information and device power failure information.

[0107] The abnormality flags are used to determine the operational interference information of the drinking water equipment based on the preset mapping relationship.

[0108] Based on the operational interference information, determine whether the drinking water equipment meets the current drinking water needs of the target user. When the drinking water equipment does not meet the current drinking water needs, generate corrective parameters for the drinking water equipment based on the operational interference information, and update the control parameters of the drinking water equipment based on the corrective parameters.

[0109] In this optional embodiment, the device abnormality information of other smart devices may include one or more of the following: device fault information, device offline information, and device power failure information. Device fault information may include device hardware fault information and / or device software fault information. Device offline information may indicate that the wireless communication connection between the device and other devices (such as water dispensers) has been lost, but the device itself is operating normally. The abnormality identifiers corresponding to the device abnormality information of other smart devices correspond one-to-one with the device abnormality information, that is, the device fault information, device offline information, and device power failure information correspond to a unique abnormality identifier. This embodiment does not limit this.

[0110] In this optional embodiment, the operation interference information indicates the interference of other smart devices' abnormal device information on the normal operation of the drinking water device. For example, when the water supply equipment corresponding to the drinking water device malfunctions, it will affect the normal operation of the drinking water device. When the drinking water device does not meet the current drinking water demand information, the drinking water device correction parameters can be used to control the drinking water device to operate according to the current maximum water supply capacity so that the drinking water device can meet part of the target user's current drinking water demand information. This embodiment does not limit this.

[0111] As can be seen, implementing this optional embodiment can update and correct the control parameters of the drinking water equipment based on the abnormal equipment information of other smart devices and the interference information of the drinking water equipment, so that the drinking water equipment can meet the drinking water needs of the target user within the allowable range, improve the control intelligence of the drinking water equipment, and at the same time, meet the drinking water needs of the target user as much as possible when equipment abnormality occurs, thereby improving the user's experience of using the drinking water equipment.

[0112] In another optional embodiment, after controlling the drinking water equipment based on the drinking water equipment control parameters, the IoT-based drinking water equipment control method may further include the following operations:

[0113] Monitor the target user's current usage information of the drinking water equipment, and analyze the target user's current drinking information based on the current usage information. The current drinking information includes at least one of the following: current water consumption, current number of times of drinking, and current drinking time.

[0114] Calculate the difference between the current drinking water information and the current drinking water demand information, and determine whether the difference is greater than a preset difference threshold;

[0115] When the difference in drinking water exceeds a threshold, a healthy drinking water reminder is generated based on the difference, and the target user is reminded based on the healthy drinking water reminder.

[0116] In this optional embodiment, monitoring the target user's current usage information of the drinking water device may include monitoring the target user's most recent usage information of the drinking water device after controlling the drinking water device, or it may include monitoring the target user's current usage information of the drinking water device within a preset time period after controlling the drinking water device. The preset time period may include a preset drinking cycle, and the current drinking information may include at least one of the following: current drinking volume, current drinking frequency, current drinking temperature, and current drinking time node. This embodiment does not limit this.

[0117] In this optional embodiment, the difference between the current drinking water information and the current drinking water demand information may include at least one of the following: difference in drinking volume, difference in drinking frequency, difference in drinking temperature, and difference in drinking time. The difference threshold may include at least one of the following: drinking volume difference threshold, drinking frequency difference threshold, drinking temperature difference threshold, and drinking time difference threshold. A difference greater than the difference threshold may include at least one difference in the drinking water difference being greater than the threshold. Taking drinking volume as an example, a difference greater than the difference threshold may include the target user's drinking volume being less than the target user's minimum drinking volume threshold or the target user's drinking volume being greater than the target user's maximum drinking volume threshold. When the target user's drinking volume is less than the target user's minimum drinking volume threshold, the target user is reminded to appropriately increase their drinking volume and a suggested drinking volume is given. When the target user's drinking volume is greater than the target user's maximum drinking volume threshold, the target user is reminded to pause drinking and the pause duration is given. This embodiment does not impose any limitations.

[0118] It is evident that implementing this optional embodiment can provide health drinking reminders to target users when they drink too little or too much water, thereby improving the health of target users when using drinking water equipment and enhancing the user experience of the drinking water equipment.

[0119] In yet another optional embodiment, the IoT-based drinking water device control method may further include the following operations:

[0120] For each other smart device, determine the degree of association between the other smart device and the water dispenser, and determine the relationship between the other smart device and the water dispenser based on the degree of association. The relationship includes linkage control relationship or non-linkage control relationship.

[0121] For each other smart device, the control influence coefficient of the water drinking device on the other smart device is determined according to the association between the other smart device and the water drinking device. The control influence coefficient includes the linkage control influence coefficient or the non-linkage control influence coefficient.

[0122] For each other smart device, based on the control influence coefficient corresponding to the other smart device and the drinking water device control parameters, smart device control parameters are generated for that other smart device, and device control is performed on the other smart device based on the smart device control parameters.

[0123] In this optional embodiment, the correlation between other smart devices and the water dispenser can represent the degree of mutual influence between the operation of other smart devices and the operation of the water dispenser. The correlation between other smart devices and the water dispenser can include a linkage control relationship or a non-linkage control relationship. When the correlation between other smart devices and the water dispenser is a linkage control relationship, the other smart device is an associated device of the water dispenser. When the correlation between other smart devices and the water dispenser is a non-linkage control relationship, the other smart device is a non-associated device of the water dispenser. This embodiment does not impose any limitations.

[0124] In this optional embodiment, the control influence coefficient of the water dispenser on other smart devices may include a linkage control influence coefficient or a non-linkage control influence coefficient. The control influence coefficient can represent a quantitative representation of the impact of the water dispenser's operating information on the operation of other smart devices, for example... Figure 1 As shown, Figure 1 The smart air conditioner can be an associated device of the water dispenser, while the smart lights and mobile phones can be unassociated devices. For example, when the control parameters of the water dispenser indicate that the target user has a low demand for water temperature, it can be determined that the current ambient temperature is high or the target user needs cold water to cool down. In this case, the smart air conditioner can be controlled to run and cool down. Or, when the control parameters of the water dispenser indicate that the target user needs to drink water at night, the smart lights or mobile phones can be controlled to turn on to provide drinking light for the target user. This embodiment does not impose any limitations.

[0125] As can be seen, implementing this optional embodiment can determine the control influence coefficient of the water dispenser on other smart devices based on the correlation between the water dispenser and other smart devices, and control other smart devices based on the control influence coefficient and the control parameters of the water dispenser. This enables the linkage control of the water dispenser and other smart devices, improves the intelligence and convenience of controlling the water dispenser and other smart devices, and enhances the user's experience with the water dispenser.

[0126] Example 2

[0127] Please see Figure 3 , Figure 3 This is a flowchart illustrating a method for controlling drinking water equipment based on the Internet of Things (IoT) disclosed in an embodiment of the present invention. Figure 3The described IoT-based drinking water equipment control method can be applied to IoT-based drinking water equipment control devices. These devices may include a device control unit for generating drinking water equipment control parameters. The device control unit may include any one of a user device, a smart server, or a smart platform. User devices include, but are not limited to, at least one of smartphones (Android phones, iOS phones, etc.), smartwatches, and smart home devices (such as smart drinking water equipment, smart refrigerators, smart speakers, smart TVs, smart range hoods, etc.). The smart server may include a local server or a cloud server; however, this embodiment of the invention does not limit the scope of the method. Figure 3 As shown, the IoT-based drinking water equipment control method may include the following operations:

[0128] 201. Obtain user information of the target user and device information of the target device in the current scenario. The target device includes a water dispenser and at least one other smart device. The device information of the water dispenser includes the target user's historical usage information of the water dispenser within a preset historical time period.

[0129] 202. Based on historical usage information, determine the drinking habits of target users.

[0130] 203. Determine the target user's physical health information based on the target user's physiological information.

[0131] In this embodiment of the invention, optionally, the target user's user information may include the target user's physiological information, which may include one or more of the target user's heart rate, body temperature, blood pressure, respiratory rate, osmotic pressure, etc. The target user's physical health information may include one or more of the target user's physical fitness information, disease information, physical health status information, etc. The invention does not limit this.

[0132] 204. Based on drinking habits information and device information of each other smart device, generate at least one recommended drinking plan for the target user.

[0133] In this embodiment of the invention, optionally, at least one recommended drinking water plan for a target user may include one or more of the following: recommended water intake, recommended drinking frequency, recommended drinking temperature, recommended drinking time points, etc., and the invention does not limit these.

[0134] 205. Based on the target user's health information and each recommended drinking water plan, determine the target user's current drinking water needs.

[0135] In this embodiment of the invention, optionally, the target user's current drinking water demand information may include the target user's current drinking water volume demand, drinking water temperature demand, etc., and may also include the target user's drinking water demand information within a preset drinking water cycle after the current time point. This invention does not limit this.

[0136] 206. Based on the target user's current drinking water demand information, generate drinking water equipment control parameters for the drinking water equipment, and control the drinking water equipment based on the drinking water equipment control parameters.

[0137] In this embodiment of the invention, for other descriptions of steps 202, 202 and 206, please refer to the detailed description of steps 101, 102 and 104 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0138] It is evident that implementation Figure 3 The described IoT-based water dispenser control method can determine users' drinking habits based on their historical usage information, improving the accuracy of this determination. Based on users' health information and recommended drinking plans, it can determine the target user's current drinking needs, improving the accuracy and reliability of this determination. Based on these current needs, it determines the control parameters for the water dispenser and controls it accordingly. This method leverages IoT to acquire information from multiple sources, enabling intelligent control of the water dispenser, improving the alignment between control parameters and user needs, enhancing the intelligence and flexibility of control, increasing user convenience, improving the user experience, and strengthening user loyalty.

[0139] In an optional embodiment, the device information of each other smart device includes the device operating status information of that other smart device, and the IoT-based drinking water equipment control method may further include the following operations:

[0140] Obtain the scene environment information corresponding to the current scene, including scene temperature and / or scene humidity;

[0141] Furthermore, generating at least one recommended drinking water plan for the target user based on drinking water habit information and device information of each other smart device may include the following operations:

[0142] Based on drinking habits information, predict the target user's standard drinking plan within a preset drinking cycle. The standard drinking plan includes at least one of the following: standard drinking volume, standard drinking frequency, and standard drinking time points.

[0143] Determine the first impact coefficient of the device operating status information of each other smart device on the target user's drinking water, and determine the second impact coefficient of the scene environment information on the target user's drinking water;

[0144] Based on the standard drinking water plan, the first drinking water impact coefficient, and the second drinking water impact coefficient, at least one recommended drinking water plan is generated for the target user.

[0145] In this optional embodiment, the device information of other smart devices may include device operating status information, which may include at least one of other device operating modes, other device running time, etc. The scene environment information corresponding to the current scene may include scene external environment information and / or scene internal environment information. Scene external environment information may include one or more of scene temperature, scene humidity, scene weather, etc., and scene internal environment information may include scene temperature and / or scene humidity. This embodiment does not limit this.

[0146] In this optional embodiment, the target user's standard drinking plan within a preset drinking cycle may include at least one of the following: standard water intake, standard drinking frequency, standard drinking temperature, and standard drinking time. The device operating status information of other smart devices can represent the first drinking influence coefficient on the target user's water intake, drinking temperature, and drinking frequency. For example, when the smart air conditioner is operating in heating / drying mode, the target user's water intake and drinking frequency will increase; when the smart air conditioner is operating in cooling / humidifying mode... In this scenario, the target user's drinking water temperature will decrease. The second drinking water influence coefficient of the scene environment information can represent the influence coefficient of the scene environment information on the target user's drinking volume, drinking water temperature, drinking frequency, etc. For example, if the current scene temperature and humidity are high, the target user will feel stuffy, so the target user's drinking volume and drinking frequency will increase, and the drinking water temperature will decrease. At least one recommended drinking water plan for the target user may include one or more of the following: recommended drinking volume, recommended drinking frequency, recommended drinking temperature, recommended drinking time node, etc. This embodiment does not limit it.

[0147] As can be seen, implementing this optional embodiment can predict the target user's standard drinking plan based on drinking habit information, and generate at least one recommended drinking plan for the target user based on the influence of other smart devices and environmental information on the target user. This can improve the accuracy of the generated recommended drinking plan and the degree of matching with the target user, thereby improving the accuracy and intelligence of controlling the drinking equipment, enhancing the user's experience with the drinking equipment, and increasing user stickiness.

[0148] In another optional embodiment, the IoT-based drinking water device control method may further include the following operations:

[0149] Identify other user information for at least one other user outside the current scene. This other user information includes user location information and user movement information.

[0150] For each other user, determine the relative movement information of that other user relative to the current scene based on that other user's user movement information;

[0151] For each other user, when the relative movement information of that other user indicates that the other user is moving toward the current scene, the arrival time information of that other user to the current scene is predicted based on the user's location information and user movement information.

[0152] For each other user, based on that other user's drinking habits and arrival time information, predict the other user's predicted drinking needs when arriving at the current scene;

[0153] For each other user, predictive control parameters for the drinking water equipment are generated based on the predicted drinking water demand information of that other user, and the drinking water equipment is controlled according to the predictive control parameters.

[0154] In this optional embodiment, the other user information may include the other user's location information and motion information, as well as the other user's physiological information. The motion information may include speed information, movement information, etc. The relative movement information of the other user and the current scene may include the other user being relatively closer to the current scene or the other user being relatively farther away from the current scene, and may also include the relative movement speed of the other user and the current scene. This embodiment does not limit this.

[0155] In this optional embodiment, when the relative movement information of another user indicates that the other user is moving towards the current scene, the arrival time information of the other user in the current scene is predicted based on the user's location information and movement information. For example, when the other user is about to go home after work, the arrival time information of the other user in the current scene is predicted based on the user's movement route from their workplace to the current scene and the user's way home. Based on the other user's drinking habits information and arrival time information, the predicted drinking water demand information of the other user when they arrive at the current scene is predicted. For example, it is predicted whether the other user needs to drink water when they return home. If they need to drink water, the water temperature demand, water volume demand, etc., are predicted when the other user returns home. Predictive control parameters for the drinking water equipment are generated, and the drinking water equipment is controlled according to the predictive control parameters so that the other user can drink water when they return home, thereby improving the user experience. This embodiment is not limited to this.

[0156] As can be seen, implementing this optional embodiment can predict the drinking water needs of other users when they arrive at the target scene based on their location information, movement information, and drinking habits information. This allows for the control of the drinking water equipment, improving the intelligence level of the control. It also enables the drinking water equipment to cover and serve relevant users both inside and outside the current scene, improving the efficiency of the drinking water equipment, enhancing the user experience, and increasing user stickiness.

[0157] Example 3

[0158] Please see Figure 4 , Figure 4 This is a schematic diagram of a water supply equipment control device based on the Internet of Things (IoT) disclosed in an embodiment of the present invention. Figure 4 The described IoT-based drinking water equipment control device may include a device control device for generating drinking water equipment control parameters. The device control device may include any one of user equipment, a smart server, or a smart platform. User equipment includes, but is not limited to, at least one of smartphones (Android phones, iOS phones, etc.), smartwatches, and smart home devices (such as smart drinking water equipment, smart refrigerators, smart speakers, smart TVs, smart range hoods, etc.). The smart server may include a local server or a cloud server; this embodiment of the invention is not limited to any particular type. Figure 4 As shown, the IoT-based drinking water equipment control device may include:

[0159] The first acquisition module 301 is used to acquire user information of the target user and device information of the target device in the current scenario. The target device includes a water drinking device and at least one other smart device. The device information of the water drinking device includes the target user's historical usage information of the water drinking device within a preset historical time period.

[0160] The determination module 302 is used to determine the drinking habits information of the target user based on historical usage information;

[0161] The determining module 302 is also used to determine the current drinking water demand information of the target user based on the user information, drinking water habit information and device information of each other smart device of the target user;

[0162] The first generation module 303 is used to generate drinking water equipment control parameters for the drinking water equipment based on the current drinking water demand information of the target user, and to control the drinking water equipment based on the drinking water equipment control parameters.

[0163] It is evident that implementation Figure 4The described IoT-based drinking water equipment control device can determine a user's drinking habits based on the user's historical usage information of the drinking water equipment, improving the accuracy of this determination. Based on user information, drinking habits, and equipment information from other smart devices in the same scenario, it determines the target user's current drinking water needs. Then, based on these needs, it determines the control parameters for the drinking water equipment and controls it accordingly. This device leverages IoT to acquire information from multiple sources, enabling intelligent control of the drinking water equipment, improving the alignment between control parameters and user needs, enhancing the intelligence and flexibility of equipment control, increasing user convenience, improving the user experience, and strengthening user loyalty.

[0164] In an optional embodiment, such as Figure 5 As shown, the target user's user information includes the target user's physiological information;

[0165] The specific methods by which module 302 determines the target user's current drinking water needs based on the target user's user information, drinking water habit information, and device information of each other smart device include:

[0166] Determine the target user's physical health information based on the target user's physiological information;

[0167] Based on drinking habits information and device information of each other smart device, generate at least one recommended drinking plan for the target user;

[0168] Based on the target user's health information and each recommended drinking water plan, determine the target user's current drinking water needs.

[0169] It is evident that implementation Figure 5 The described IoT-based drinking water equipment control device can determine a user's drinking habits based on the user's historical usage information of the drinking water equipment, improving the accuracy of this determination. Based on the user's health information and recommended drinking water plans, it can determine the target user's current drinking water needs, improving the accuracy and reliability of this determination. Based on these needs, it determines the control parameters for the drinking water equipment and controls it accordingly. By acquiring information from multiple sources via the IoT, it enables intelligent control of the drinking water equipment, improving the alignment between the control parameters and the user's drinking water needs. This enhances the intelligence and flexibility of the control, increases the ease of use for the user, improves the user experience, and strengthens user loyalty.

[0170] In another alternative embodiment, such as Figure 5As shown, the device information for each other smart device includes the device operating status information of that other smart device. The IoT-based drinking water equipment control device may also include:

[0171] The second acquisition module 304 is used to acquire scene environment information corresponding to the current scene, including scene temperature and / or scene humidity.

[0172] Furthermore, the specific methods by which the determining module 302 generates at least one recommended drinking water plan for the target user based on drinking water habit information and device information of each other smart device include:

[0173] Based on drinking habits information, predict the target user's standard drinking plan within a preset drinking cycle. The standard drinking plan includes at least one of the following: standard drinking volume, standard drinking frequency, and standard drinking time points.

[0174] Determine the first impact coefficient of the device operating status information of each other smart device on the target user's drinking water, and determine the second impact coefficient of the scene environment information on the target user's drinking water;

[0175] Based on the standard drinking water plan, the first drinking water impact coefficient, and the second drinking water impact coefficient, at least one recommended drinking water plan is generated for the target user.

[0176] It is evident that implementation Figure 5 The described IoT-based drinking water equipment control device can predict the target user's standard drinking water plan based on drinking water habit information, and generate at least one recommended drinking water plan for the target user based on the influence of other smart devices and environmental information on the target user. This can improve the accuracy of the generated recommended drinking water plan and its matching degree with the target user, thereby improving the accuracy and intelligence of the control of the drinking water equipment, enhancing the user's experience of the drinking water equipment, and increasing user stickiness.

[0177] In yet another alternative embodiment, such as Figure 5 As shown, the determining module 302 is further configured to, when detecting device abnormal information of at least one other smart device in the current scene, determine the abnormal identifier corresponding to the device abnormal information of each other smart device, wherein the device abnormal information includes at least one of device fault information, device offline information and device power failure information;

[0178] The determination module 302 is also used to determine the operational interference information of the abnormality identifier on the drinking water equipment according to the preset mapping relationship;

[0179] The IoT-based drinking water equipment control device may also include:

[0180] The judgment module 305 is used to determine whether the drinking water equipment meets the current drinking water needs of the target user based on the operation interference information. When the drinking water equipment does not meet the current drinking water needs, it generates drinking water equipment correction parameters based on the operation interference information and updates the drinking water equipment control parameters based on the drinking water equipment correction parameters.

[0181] It is evident that implementation Figure 5 The described IoT-based drinking water equipment control device can update and correct the drinking water equipment control parameters based on the abnormal equipment information of other smart devices and the interference information of the drinking water equipment operation. This enables the drinking water equipment to meet the drinking water needs of the target user within the allowable range, improves the intelligence of the drinking water equipment control, and at the same time, can try to meet the drinking water needs of the target user when equipment abnormalities occur, thereby improving the user's experience of using the drinking water equipment.

[0182] In yet another alternative embodiment, such as Figure 5 As shown, the determining module 302 is also used to determine other user information of at least one other user outside the current scene, including user location information and user movement information;

[0183] The determining module 302 is also used to determine the relative movement information of each other user relative to the current scene based on the user movement information of that other user;

[0184] The IoT-based drinking water equipment control device may also include:

[0185] The prediction module 306 is used to predict the arrival time of each other user when the relative movement information of the other user indicates that the other user is moving towards the current scene, based on the user location information and user movement information of the other user.

[0186] The prediction module 306 is also used to predict the predicted drinking water demand information of each other user when they arrive at the current scene, based on the other user's drinking habits information and arrival time information.

[0187] The first generation module 303 is also used to generate predictive control parameters for the drinking water equipment for each other user based on the predicted drinking water demand information of that other user, and to control the drinking water equipment according to the predictive control parameters.

[0188] It is evident that implementation Figure 5The described IoT-based drinking water equipment control device can predict the drinking water needs of other users when they arrive at the target scene based on their location, movement, and drinking habits. This allows the device to control the drinking water equipment, improving its intelligence and enabling it to serve relevant users both inside and outside the current scene. This increases the efficiency of the drinking water equipment, enhances the user experience, and strengthens user loyalty.

[0189] In yet another alternative embodiment, such as Figure 5 As shown, the IoT-based drinking water equipment control device may further include:

[0190] The monitoring module 307 is used to monitor the current usage information of the target user on the drinking water equipment after the first generation module controls the drinking water equipment based on the drinking water equipment control parameters, and to analyze the target user's current drinking water information based on the current usage information. The current drinking water information includes at least one of the following: current drinking volume, current drinking frequency, and current drinking time point.

[0191] The calculation module 308 is used to calculate the difference between the current drinking water information and the current drinking water demand information, and to determine whether the difference is greater than a preset difference threshold.

[0192] The first generation module 303 is also used to generate healthy drinking water reminder information based on the drinking water difference when the difference is greater than the difference threshold, and to remind the target user based on the healthy drinking water reminder information.

[0193] It is evident that implementation Figure 5 The described IoT-based drinking water equipment control device can remind target users to drink water healthily when they drink too little or too much, thereby improving the health of target users when using drinking water equipment and thus enhancing the user experience of drinking water equipment.

[0194] In yet another alternative embodiment, such as Figure 5 As shown, the determining module 302 is further configured to determine the degree of association between each other smart device and the water drinking device, and determine the association relationship between the other smart device and the water drinking device based on the degree of association, the association relationship including linkage control relationship or non-linkage control relationship;

[0195] The determining module 302 is also used to determine, for each other smart device, the control influence coefficient of the drinking water device on the other smart device based on the association between the other smart device and the drinking water device. The control influence coefficient includes the linkage control influence coefficient or the non-linkage control influence coefficient.

[0196] The IoT-based drinking water equipment control device may also include:

[0197] The second generation module 309 is used to generate intelligent device control parameters for each other intelligent device based on the control influence coefficient corresponding to the other intelligent device and the drinking water device control parameters of the drinking water device, and to perform device control on the other intelligent device based on the intelligent device control parameters.

[0198] It is evident that implementation Figure 5 The described IoT-based drinking water equipment control device can determine the control influence coefficient of the drinking water equipment on other smart devices based on the correlation between the drinking water equipment and other smart devices, and control other smart devices based on the control influence coefficient and the control parameters of the drinking water equipment. It can realize the linkage control of the drinking water equipment and other smart devices, improve the intelligence and convenience of controlling the drinking water equipment and other smart devices, and enhance the user's experience of using the drinking water equipment.

[0199] Example 4

[0200] Please see Figure 6 , Figure 6 This is a schematic diagram of another IoT-based drinking water equipment control device disclosed in an embodiment of the present invention. Figure 6 As shown, the IoT-based drinking water equipment control device may include:

[0201] Memory 401 storing executable program code;

[0202] Processor 402 coupled to memory 401;

[0203] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the IoT-based drinking water equipment control method described in Embodiment 1 or Embodiment 2 of the present invention.

[0204] Example 5

[0205] This invention discloses a computer storage medium storing computer instructions. When these computer instructions are invoked, they are used to execute the steps in the IoT-based drinking water equipment control method described in Embodiment 1 or Embodiment 2 of this invention.

[0206] Example 6

[0207] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the IoT-based drinking water device control method described in Embodiment 1 or Embodiment 2.

[0208] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0209] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0210] Finally, it should be noted that the drinking water equipment control method and device based on the Internet of Things disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling drinking water equipment based on the Internet of Things, characterized in that, The method includes: Acquire user information of the target user and device information of the target device in the current scenario. The target device includes a water dispenser and at least one other smart device. The device information of the water dispenser includes the target user’s historical usage information of the water dispenser within a preset historical time period. Based on the historical usage information, the target user's drinking habits information is determined; Based on the target user's user information, the drinking habits information, and the device information of each of the other smart devices, the target user's current drinking needs information is determined; Based on the target user's current drinking water demand information, control parameters for the drinking water equipment are generated, and the drinking water equipment is controlled based on the control parameters. Furthermore, the user information of the target user includes the target user's physiological information; The step of determining the target user's current drinking water needs based on the target user's user information, the drinking water habit information, and the device information of each of the other smart devices includes: Based on the target user's physiological information, determine the target user's physical health information; Based on the drinking habits information and the device information of each of the other smart devices, at least one recommended drinking plan is generated for the target user; Based on the target user's health information and each of the recommended drinking water plans, the target user's current drinking water needs are determined; Furthermore, the device information for each of the other smart devices includes the device operating status information of that other smart device, and the method further includes: Obtain the scene environment information corresponding to the current scene, including scene temperature and / or scene humidity; And, the step of generating at least one recommended drinking water plan for the target user based on the drinking water habit information and the device information of each of the other smart devices includes: Based on the drinking habits information, predict the target user's standard drinking plan within a preset drinking cycle. The standard drinking plan includes at least one of standard drinking volume, standard drinking frequency, and standard drinking time points. Determine the first impact coefficient of the device operating status information of each of the other smart devices on the target user's drinking water, and determine the second impact coefficient of the scene environment information on the target user's drinking water; Based on the standard drinking water plan, the first drinking water influence coefficient, and the second drinking water influence coefficient, at least one recommended drinking water plan is generated for the target user.

2. The IoT-based drinking water equipment control method according to claim 1, characterized in that, The method further includes: When device abnormality information of at least one of the other smart devices in the current scenario is detected, for each other smart device, an abnormality identifier corresponding to the device abnormality information of the other smart device is determined. The device abnormality information includes at least one of device fault information, device offline information, and device power failure information. The abnormality identifier is used to determine the operational interference information of the drinking water equipment based on a preset mapping relationship; Based on the operational interference information, it is determined whether the drinking water equipment meets the current drinking water needs of the target user. When the drinking water equipment does not meet the current drinking water needs, the drinking water equipment correction parameters are generated based on the operational interference information, and the drinking water equipment control parameters are updated based on the drinking water equipment correction parameters.

3. The IoT-based drinking water equipment control method according to claim 1, characterized in that, The method further includes: Determine other user information for at least one other user outside the current scene, the other user information including user location information and user movement information; For each of the other users, the relative movement information of the other user relative to the current scene is determined based on the user movement information of that other user; For each of the other users, when the relative movement information of the other user indicates that the other user is moving toward the current scene, the arrival time information of the other user to the current scene is predicted based on the user location information and user movement information of the other user. For each of the other users, based on the other user's drinking habits and arrival time information, predict the other user's predicted drinking needs when arriving at the current scene; For each of the other users, predictive control parameters for the drinking water equipment are generated based on the predicted drinking water demand information of the other user, and the drinking water equipment is controlled according to the predictive control parameters.

4. The method for controlling drinking water equipment based on the Internet of Things according to claim 1, characterized in that, After controlling the drinking water equipment based on the control parameters of the drinking water equipment, the method further includes: The system monitors the target user's current usage information of the drinking water device and analyzes the target user's current drinking water information based on the current usage information. The current drinking water information includes at least one of the following: current water consumption, current number of times of drinking water, and current drinking time. Calculate the difference between the current drinking water information and the current drinking water demand information, and determine whether the difference is greater than a preset difference threshold; When the difference in drinking water exceeds the difference threshold, a healthy drinking water reminder is generated based on the difference, and the target user is reminded based on the healthy drinking water reminder.

5. The method for controlling drinking water equipment based on the Internet of Things according to claim 1, characterized in that, The method further includes: For each of the other smart devices, determine the degree of association between the other smart device and the water drinking device, and determine the association relationship between the other smart device and the water drinking device based on the degree of association. The association relationship includes a linkage control relationship or a non-linkage control relationship. For each of the other smart devices, the control influence coefficient of the water drinking device on the other smart device is determined according to the association relationship between the other smart device and the water drinking device. The control influence coefficient includes the linkage control influence coefficient or the non-linkage control influence coefficient. For each of the other smart devices, smart device control parameters are generated based on the control influence coefficient corresponding to the other smart device and the drinking device control parameters of the drinking device, and the other smart device is controlled based on the smart device control parameters.

6. A drinking water equipment control device based on the Internet of Things, characterized in that, The device includes: The first acquisition module is used to acquire user information of the target user and device information of the target device in the current scene. The target device includes a water drinking device and at least one other smart device. The device information of the water drinking device includes the target user's historical usage information of the water drinking device within a preset historical time period. The determination module is used to determine the target user's drinking habits information based on the historical usage information; The determining module is further configured to determine the current drinking water demand information of the target user based on the user information of the target user, the drinking water habit information, and the device information of each of the other smart devices; The first generation module is used to generate drinking water equipment control parameters for the drinking water equipment based on the current drinking water demand information of the target user, and to control the drinking water equipment based on the drinking water equipment control parameters; Furthermore, the user information of the target user includes the target user's physiological information; The method by which the determining module determines the current drinking water needs of the target user based on the user information of the target user, the drinking water habit information, and the device information of each of the other smart devices specifically includes: Based on the target user's physiological information, determine the target user's physical health information; Based on the drinking habits information and the device information of each of the other smart devices, at least one recommended drinking plan is generated for the target user; Based on the target user's health information and each of the recommended drinking water plans, the target user's current drinking water needs are determined; In addition, the device information for each of the other smart devices includes the device operating status information of that other smart device, and the device further includes: The second acquisition module is used to acquire scene environment information corresponding to the current scene, the scene environment information including scene temperature and / or scene humidity; Furthermore, the method by which the determining module generates at least one recommended drinking water plan for the target user based on the drinking water habit information and the device information of each of the other smart devices specifically includes: Based on the drinking habits information, predict the target user's standard drinking plan within a preset drinking cycle. The standard drinking plan includes at least one of standard drinking volume, standard drinking frequency, and standard drinking time points. Determine the first impact coefficient of the device operating status information of each of the other smart devices on the target user's drinking water, and determine the second impact coefficient of the scene environment information on the target user's drinking water; Based on the standard drinking water plan, the first drinking water influence coefficient, and the second drinking water influence coefficient, at least one recommended drinking water plan is generated for the target user.

7. A drinking water equipment control device based on the Internet of Things, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the IoT-based drinking water equipment control method as described in any one of claims 1-5.

8. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the IoT-based drinking water equipment control method as described in any one of claims 1-5.

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