Sauna room control method and system based on Internet of Things

Abstract

The invention relates to the field of sauna room control, and discloses a sauna room control method and system based on the Internet of Things, and the method comprises the steps: obtaining first physiological information of a user from the current moment to the predicted arrival moment in response to a sauna room reservation instruction and the predicted arrival moment input by the user at the current moment and obtained through the Internet of Things; determining reservation configuration parameters of the sauna room according to the first physiological information; the sauna room is controlled to be preheated according to the reserved configuration parameters from the current moment to the predicted arrival moment; acquiring an actual use time when the user starts to use the sauna room, and acquiring second physiological information of the user in a preset use time period from the actual use time; determining use adjustment parameters of the sauna room according to the first physiological information and the second physiological information; the first physiological information and the second physiological information comprise the gender, the age, the time sequence heart rhythm and the time sequence body surface temperature of the user. According to the application, the sauna room can be adaptively adjusted according to the individual physiological characteristics of the user.

Description

Technical Field

[0001] This application relates to the field of sauna room control technology, and more specifically, to a sauna room control method and system based on the Internet of Things. Background Technology

[0002] Currently, sauna rooms offer remote booking functionality, achieved through the coordinated operation of a mobile application, network communication module, and sauna control unit. Users can log into the corresponding control platform using smart devices, pre-set usage time, reservation period, and other relevant parameters. The booking command is transmitted via the network to the sauna's control unit, which then prepares to start the sauna in advance, ensuring immediate use upon arrival without waiting or additional steps. Remote booking for sauna rooms has been implemented to some extent in commercial saunas (such as those in hotels and gyms) and home saunas, primarily enhancing user convenience.

[0003] Existing saunas, when booked remotely, still operate based on fixed parameters set by the user during the booking process. Key parameters such as temperature, humidity, and duration are predetermined and cannot be dynamically adjusted according to the user's actual physiological characteristics throughout the use. Different users have significant differences in age, physical condition, and health status, resulting in varying needs for sauna parameters. For example, elderly or physically weak users may not be able to tolerate high temperatures, easily experiencing dizziness, fatigue, or other discomfort, while younger or physically strong users may find the sauna experience unsatisfactory due to excessively low temperatures or short durations. Therefore, existing saunas lack an adaptive adjustment mechanism based on individual user physiological characteristics, making their operating model unable to meet the diverse needs of different users. Summary of the Invention

[0004] The purpose of this application is to provide a sauna room control method and system based on the Internet of Things, which solves the technical problem that existing sauna rooms cannot be adapted to the individual physiological characteristics of users, and achieves the technical effect that sauna rooms can be adapted to the individual physiological characteristics of users.

[0005] This application provides an Internet of Things (IoT)-based sauna control method, comprising: responding to a sauna reservation instruction and expected arrival time input by a user at the current time, obtained through the IoT; acquiring first physiological information of the user from the current time to the expected arrival time; determining reservation configuration parameters of the sauna based on the first physiological information; controlling the sauna to preheat according to the reservation configuration parameters from the current time to the expected arrival time; acquiring the actual time when the user starts using the sauna, and acquiring second physiological information of the user within a preset usage time period starting from the actual usage time; determining usage adjustment parameters of the sauna based on the first and second physiological information; wherein the first and second physiological information include the user's gender, age, temporal heart rate, and temporal body surface temperature.

[0006] In one possible implementation, determining the sauna room's usage adjustment parameters based on first physiological information and second physiological information includes: determining a user's first physiological information change value and a preset first physiological information change value based on the first physiological information; when the first physiological information change value is greater than or equal to the preset first physiological information change value, determining a first adjustment ratio based on the first physiological information and the first physiological information change value; determining the sauna room's basic usage parameters based on the first physiological information and second physiological information; and determining the product of the basic usage parameters and the first adjustment ratio as the sauna room's usage adjustment parameters.

[0007] In another possible implementation, the method further includes: determining the time period between the actual usage time and the expected arrival time as the reservation delay period; when the length of the reservation delay period is longer than the preset delay length, acquiring the user's first physiological information within the reservation delay period; segmenting the first physiological information to obtain multiple first sub-physiological information; determining the first sub-physiological information change value corresponding to each first sub-physiological information based on each first sub-physiological information; among the multiple first sub-physiological information change values, determining the target first sub-physiological information change value whose first sub-physiological information change value is greater than or equal to the preset first sub-physiological information change value, and multiple target first sub-physiological information corresponding to the multiple target first sub-physiological information change values; determining a first adjustment ratio based on the multiple target first sub-physiological information and the multiple target first sub-physiological information change values; determining the basic usage parameters of the sauna room based on the multiple target first sub-physiological information and the second physiological information; and determining the product of the basic usage parameters and the first adjustment ratio as the usage adjustment parameters of the sauna room.

[0008] In another possible implementation, the first physiological information is segmented to obtain multiple first sub-physiological information, including: obtaining the user's motion state switching time during the reservation delay period; and segmenting the first physiological information according to the motion state switching time to obtain multiple first sub-physiological information.

[0009] In another possible implementation, the first physiological information is segmented to obtain multiple first sub-physiological information, and the method further includes: obtaining the duration of the first sub-physiological information corresponding to each of the multiple first sub-physiological information; and removing the first sub-physiological information whose duration is less than a preset duration from the multiple first sub-physiological information.

[0010] In another possible implementation, a first adjustment ratio is determined based on multiple target first sub-physiological information and the change values ​​of multiple target first sub-physiological information, including: obtaining the target first sub-motion state corresponding to each target first sub-physiological information, and obtaining the first adjustment ratio weight corresponding to each target first sub-motion state; determining the first sub-adjustment ratio based on each target first sub-physiological information, the change value of the target first sub-physiological information, and the target first sub-motion state; and determining the sum of the products of the first sub-adjustment ratios and the first adjustment ratio weights corresponding to multiple target first sub-physiological information as the first adjustment ratio.

[0011] In another possible implementation, the method further includes: obtaining the reservation time slots corresponding to the sauna room reservation instructions of multiple users; constructing a temporal adjacency matrix of users-reservation time slots-sauna room equipment, wherein the row dimension of the temporal adjacency matrix includes user identifiers, and the column dimension includes reservation time slots divided in 30-minute units; the matrix elements of the temporal adjacency matrix are used to store the device identifier of the user reservation, the reservation time slot, and the remaining available time of the device in the reservation time slot; determining the total reserved time of each sauna room equipment in each reservation time slot based on the temporal adjacency matrix; and determining the first reservation time slot as the equipment overload period of the first sauna room equipment when the total reserved time of the first sauna room equipment in the first reservation time slot exceeds the maximum continuous use threshold of the first sauna room equipment. Specifically, the maximum continuous usage threshold is determined based on the equipment's rated power, heat dissipation efficiency, and maintenance requirements; multiple first users who booked the first sauna during the equipment overload period are obtained, along with their sauna usage information within a preset historical time period; when the target first user's sauna usage information includes sauna usage records after the equipment overload period, adjustment suggestions for the corresponding time period after the equipment overload period are pushed to the target first user; when the target first user's sauna usage information does not include sauna usage records after the equipment overload period, the adjustment time period after the equipment overload period is determined according to the principle of minimum time difference, and adjustment suggestions for the adjustment time period are pushed to the target first user.

[0012] In another possible implementation, when the sauna usage information of the target first user includes sauna usage records after the equipment overload period, a sauna adjustment suggestion for the time period corresponding to the sauna usage records after the equipment overload period is pushed to the target first user. This includes: when the sauna usage information of the target first user includes sauna usage records after the equipment overload period, obtaining the historical sauna configuration parameters corresponding to the sauna usage records after the equipment overload period; determining differentiated sauna configuration parameters that differ from the historical sauna configuration parameters based on the historical sauna configuration parameters corresponding to the sauna usage records; and pushing the time period corresponding to the sauna usage records after the equipment overload period and the differentiated sauna configuration parameters to the target first user as a sauna adjustment suggestion.

[0013] In another possible implementation, when the sauna usage information of the target first user includes sauna usage records after the equipment overload period, the system pushes sauna adjustment suggestions for the time period corresponding to the sauna usage records after the equipment overload period to the target first user. This also includes: obtaining the target first user's first physiological information from the current moment to the expected arrival time; obtaining historical sauna configuration parameters corresponding to the sauna usage records and historical physiological information corresponding to the target first user; determining the physiological differences between the first physiological information and the historical physiological information; determining a differential adjustment ratio based on the physiological differences; determining initial differential sauna configuration parameters that differ from the historical sauna configuration parameters; determining the product of the initial differential sauna configuration parameters and the differential adjustment ratio as the corrected differential sauna configuration parameters; and pushing the time period corresponding to the sauna usage records after the equipment overload period and the corrected differential sauna configuration parameters to the target first user as sauna adjustment suggestions.

[0014] This application also provides an Internet of Things (IoT)-based sauna control system, including a unit for implementing the above-described IoT-based sauna control method.

[0015] The beneficial effects of the embodiments in this application compared with the prior art are:

[0016] This application provides an IoT-based sauna control method, comprising: responding to a sauna reservation instruction and expected arrival time input by a user at the current time, obtained via the IoT; acquiring first physiological information of the user from the current time to the expected arrival time; determining reservation configuration parameters for the sauna based on the first physiological information; controlling the sauna to preheat according to the reservation configuration parameters from the current time to the expected arrival time; acquiring the actual time when the user begins using the sauna, and acquiring second physiological information of the user within a preset usage time period starting from the actual usage time; and determining usage adjustment parameters for the sauna based on the first and second physiological information. By combining the changes in the user's physiological information before reservation and during use, this application embodiment can dynamically adjust the sauna's usage parameters, adapting promptly to changes in the user's physiological state during use, and improving comfort and personalization during the usage phase. Attached Figure Description

[0017] This specification describes in detail the implementation of the technical solution, including steps 1 to 5.

[0018] Figure 1 A flowchart illustrating the first IoT-based sauna control method provided in this application embodiment;

[0019] Figure 2 A schematic diagram illustrating the workflow of the first IoT-based sauna control method provided in this application embodiment;

[0020] Figure 3 A flowchart illustrating the second IoT-based sauna control method provided in this application embodiment;

[0021] Figure 4 A schematic diagram illustrating the workflow of a second IoT-based sauna control method provided in this application embodiment;

[0022] Figure 5 A flowchart illustrating the third IoT-based sauna control method provided in this application embodiment;

[0023] Figure 6 A schematic diagram illustrating the workflow of the third IoT-based sauna control method provided in this application embodiment;

[0024] Figure 7 A flowchart illustrating the fourth IoT-based sauna control method provided in this application embodiment;

[0025] Figure 8 A flowchart illustrating the fifth IoT-based sauna control method provided in this application embodiment;

[0026] Figure 9A flowchart illustrating the sixth IoT-based sauna control method provided in this application embodiment;

[0027] Figure 10 A flowchart illustrating the seventh IoT-based sauna control method provided in this application embodiment;

[0028] Figure 11 A schematic diagram illustrating the workflow of the seventh IoT-based sauna control method provided in this application embodiment;

[0029] Figure 12 This is a schematic diagram of the logical structure of a sauna control system based on the Internet of Things, provided as an embodiment of this application. Detailed Implementation

[0030] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0031] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0032] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0033] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0034] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0035] When making remote reservations, existing sauna rooms still operate under fixed parameters set by the user during the reservation process, lacking an adaptive adjustment mechanism based on the individual physiological characteristics of the user. This makes it impossible for sauna rooms to meet the differentiated needs of different users.

[0036] Based on the above reasons, this application provides an Internet of Things (IoT)-based sauna control method. The method includes: responding to a sauna reservation instruction and expected arrival time input by a user at the current time, obtained via the IoT; acquiring first physiological information of the user from the current time to the expected arrival time; determining reservation configuration parameters for the sauna based on the first physiological information; controlling the sauna to preheat according to the reservation configuration parameters from the current time to the expected arrival time; acquiring the actual time when the user begins using the sauna, and acquiring second physiological information of the user within a preset usage time period starting from the actual usage time; and determining usage adjustment parameters for the sauna based on the first and second physiological information. By combining the changes in the user's physiological information before reservation and during use, this application can dynamically adjust the sauna's usage parameters, adapting promptly to changes in the user's physiological state during use, and improving comfort and personalization during use.

[0037] In some scenarios, the IoT-based sauna control method of this application embodiment can be applied to commercial or home sauna control systems, which can improve the control effect of IoT-based saunas and the user experience.

[0038] The following describes in detail, with specific examples, an IoT-based sauna control method provided in this application.

[0039] Figure 1 A flowchart illustrating the first IoT-based sauna control method provided in this application embodiment is shown below. Figure 1 As shown in the embodiment of this application, a sauna room control method based on the Internet of Things is provided, including S110 to S120. S110 to S120 will be described in detail below.

[0040] S110. In response to the sauna room reservation instruction and estimated arrival time input by the user at the current moment, obtained through the Internet of Things, acquire the user's first physiological information from the current moment to the estimated arrival time. Based on the first physiological information, determine the reservation configuration parameters for the sauna room. Control the sauna room to preheat according to the reservation configuration parameters from the current moment to the estimated arrival time.

[0041] Figure 2 A schematic diagram illustrating the workflow of the first IoT-based sauna control method provided in this application embodiment is shown below. Figure 2 As shown, in this implementation, the reservation instructions sent by the user (such as the reservation application submitted by the mobile APP) can be received through the Internet of Things platform. The instructions include the expected arrival time filled in by the user (e.g., "arrive at 19:00").

[0042] In this implementation, IoT devices such as smart bracelets and watches worn by the user are used to continuously collect physiological data from the current moment to the expected arrival time, serving as primary physiological information. The collection frequency can be set to once per minute to ensure that temporal changes in heart rate and body surface temperature are captured, providing a real-time data foundation for subsequent parameter configuration.

[0043] For example, the gender, age, temporal heart rate, and temporal body surface temperature in the first physiological information can be matched with a pre-stored experience value table. The experience value table is constructed based on physiological and medical research and user feedback, and includes sauna preheating parameters (temperature, humidity, preheating rate) corresponding to different genders (male / female), age ranges (e.g., 18-25 years, 26-40 years, 41-60 years), heart rate ranges (e.g., 60-70 beats / minute, 71-80 beats / minute), and body surface temperature ranges (e.g., 36.0-36.5℃, 36.6-37.0℃).

[0044] For example, for male users aged 26-40 with a heart rate of 65 beats per minute and a body surface temperature of 36.8°C, the reservation configuration parameters matched by the experience value table are "preheating temperature increases from 25°C to 40°C in 5°C increments every 10 minutes, while maintaining 60% humidity".

[0045] It should be noted that the experience value table can be optimized for specific groups of people. For example, for users over 60 years old, their body surface temperature is usually 0.2-0.5℃ lower than that of younger people, and their heart rate is 5-10 beats / minute slower. The corresponding preheating rate in the experience value table will be reduced to 3℃ / 10 minutes, and the target temperature will be lowered to 38℃ to avoid discomfort such as dizziness and palpitations caused by a sudden increase in temperature in elderly users.

[0046] In this implementation, the reservation configuration parameters can be converted into control commands and sent to the sauna's temperature controller and humidity regulator. For example, if the reservation configuration parameters are "temperature increases from 22℃ to 39℃ at 4℃ / 10 ​​minutes, humidity 65%", the temperature controller can gradually heat the sauna at this rate (22℃, 26℃, 30℃, ..., 39℃), and the humidity regulator can maintain 65% humidity through the atomization system, ensuring that the sauna environment is perfectly suited to the user's physiological characteristics at the expected arrival time.

[0047] S120. Obtain the actual time when the user starts using the sauna, and obtain the second physiological information of the user within a preset usage time period starting from the actual usage time. Based on the first and second physiological information, determine the sauna usage adjustment parameters. The first and second physiological information include the user's gender, age, temporal heart rate, and temporal body surface temperature.

[0048] In this implementation, the user's entry time can be detected by the sauna's door magnetic sensor or the user's control panel (e.g., the user swipes their card to open the door at 19:00, and the actual usage time is 19:00). Subsequently, physiological data for a preset time period (e.g., the first 15 minutes) from that time can be collected again through the user's smart device as secondary physiological information.

[0049] It should be noted that the data collected may include time-series heart rate and time-series body surface temperature to ensure the continuity and comparability of the data.

[0050] In this implementation, the dynamic parameter changes of the first and second physiological information (such as the magnitude of heart rate increase and the rate of body surface temperature increase) can be compared, and the adjustment parameters to be used can be determined by combining the adjustment strategies in the empirical value table.

[0051] For example, the user's first physiological information is: 25-year-old female, heart rate 60 beats / minute, body surface temperature 36.2℃; the second physiological information is: after 5 minutes of use, heart rate 75 beats / minute, body surface temperature 37.5℃. Based on the experience value table, it is judged as "mild heat stress", and the corresponding adjustment parameters are "temperature decrease by 2℃ (from 39℃→37℃), humidity increase by 5% (from 65%→70%), and low-level ventilation".

[0052] It should be noted that the adjustment strategy can be based on a combination of multiple parameters. For example, if the user is female, 30 years old, and has a heart rate of 62 beats / minute and a body surface temperature of 36.4℃ as the first physiological information, and a heart rate of 80 beats / minute and a body surface temperature of 38℃ as the second physiological information, the experience value table can adjust three parameters at the same time: "temperature, humidity, and ventilation", rather than a single parameter, to ensure a more accurate adjustment effect.

[0053] In this implementation, both the first and second physiological information include gender, age, temporal heart rate, and temporal body surface temperature. Gender and age are static basic characteristics that determine the user's basic physiological tolerance (e.g., women are more sensitive to high temperatures, and tolerance decreases with age). Temporal heart rate and temporal body surface temperature are dynamic state parameters that reflect the user's physiological changes in real time (e.g., increased heart rate = possible stuffiness, sudden rise in body surface temperature = excessively hot environment). Combining the two can comprehensively depict the user's "basic characteristics and real-time state," and can more accurately match sauna parameters compared to single data (e.g., only looking at temperature). For example, with the same "heart rate of 80 beats / minute," a 25-year-old male might be experiencing "normal stress," while a 60-year-old male might be experiencing "excessive stress." Combining age can avoid misjudgment.

[0054] This implementation method obtains the user's first physiological information from the current time to the expected arrival time, determines the reservation configuration parameters of the sauna room based on the first physiological information, and controls the sauna room to preheat according to the reservation configuration parameters from the current time to the expected arrival time. This allows the sauna room to complete preheating based on the user's own physiological characteristics before the user arrives, avoiding user waiting or initial environmental discomfort, and improving the preparation efficiency and adaptability of the reservation stage.

[0055] This implementation method obtains the user's second physiological information within a preset usage period starting from the actual usage time. Based on the first and second physiological information, the usage adjustment parameters of the sauna room are determined. By combining the changes in the user's physiological information before and during use, the usage parameters of the sauna room can be dynamically adjusted to adapt to the changes in the user's physiological state during use, thereby improving the comfort and personalization of the usage phase.

[0056] Figure 3 A flowchart illustrating the second IoT-based sauna control method provided in this application embodiment is shown below. Figure 3 As shown, in some implementations, in the above-mentioned S120, the usage adjustment parameters of the sauna room are determined based on the first physiological information and the second physiological information, including S121 to S122. S121 to S122 will be explained in detail below.

[0057] S121. Based on the first physiological information, determine the user's first physiological information change value and a preset first physiological information change value. When the first physiological information change value is greater than or equal to the preset first physiological information change value, determine a first adjustment ratio based on the first physiological information and the first physiological information change value.

[0058] Figure 4 A schematic diagram of the workflow of the second IoT-based sauna control method provided in this application embodiment is shown below. Figure 4As shown, in this implementation, the change value of the first physiological information can be calculated based on the time-series data (such as time-series heart rate and time-series body surface temperature) in the first physiological information. For example, the difference between the maximum and minimum values ​​of the time-series heart rate, the mean change of the time-series body surface temperature, etc., can be used to quantify the degree of physiological fluctuation of the user during the reservation stage.

[0059] In this implementation, fixed attributes such as gender and age in the first physiological information can be combined with the statistical results of physiological information changes in similar groups to determine the preset value of the first physiological information change, such as the threshold for heart rate change and body surface temperature change in people of the same gender and age in similar time periods, as a benchmark for judging whether the physiological changes are significant.

[0060] For example, the preset first physiological information change value can be selected from statistical indicators, such as the average heart rate change value (8 beats / minute) of men aged 30-40 within 30 minutes, the 95th percentile (1.5℃) of the body surface temperature change of women of the same age, etc. These indicators are derived from the statistical analysis of physiological information data of a large number of similar users.

[0061] In this implementation, when the change value of the first physiological information is greater than or equal to the preset change value of the first physiological information, the first adjustment ratio can be determined by an empirical value table. The empirical value table can store the adjustment ratios corresponding to different first physiological information (such as gender and age) and different change values ​​of the first physiological information in advance. For example, for male users aged 30-40, the adjustment ratio is 1.2 when the heart rate change value is 10 beats / minute and 1.3 when the heart rate change value is 12 beats / minute.

[0062] For example, in the experience value table, for female users (25-35 years old), when the first physiological information change value (body surface temperature change) is 2℃, the first adjustment ratio is 1.1; when the change value is 2.5℃, the adjustment ratio is 1.2. Based on the user's gender, age and specific change value, the corresponding first adjustment ratio can be quickly found.

[0063] S122. Based on the first and second physiological information, determine the basic usage parameters of the sauna room. The product of the basic usage parameters and the first adjustment ratio is used as the sauna room's usage adjustment parameters.

[0064] In this implementation, the basic usage parameters can be determined by combining the first physiological information (gender, age, temporal heart rate, and temporal body surface temperature during the reservation phase) and the second physiological information (the same type of physiological data at the beginning of use). For example, the age (30 years old) and male attribute in the first physiological information determine the initial value of the basic temperature (40℃), and the temporal heart rate (78 beats / minute) and temporal body surface temperature (36.8℃) at the beginning of use in the second physiological information further adjust the basic temperature to 41℃, which serves as the basic usage parameter.

[0065] In this implementation, the product of the basic usage parameters and the first adjustment ratio can be used as the usage adjustment parameters. For example, if the basic usage parameters are temperature 41℃ and the first adjustment ratio is 1.2, the product of the two, 49.2℃, is the usage adjustment parameter. If the basic usage parameters are humidity 60% and the first adjustment ratio is 1.1, the product of the two, 66%, is the humidity usage adjustment parameter. By combining the basic benchmark and the change adjustment, the final adjustment parameters that fit the user's physiological changes can be obtained.

[0066] For example, if the basic operating parameters are a wind speed of 3 m / s and the first adjustment ratio is 1.1, the operating adjustment parameter is 3 × 1.1 = 3.3 m / s; if the basic operating parameters are a heating power of 1000 W and the first adjustment ratio is 0.9, the operating adjustment parameter is 1000 × 0.9 = 900 W. The operating adjustment parameter can be calculated by multiplying the parameters.

[0067] This implementation method first quantifies the degree of change in the user's physiological information during the reservation period, determines whether adjustment is needed by using a preset threshold, and then converts the degree of change into an adjustment ratio. This accurately reflects the impact of changes in the user's physiological state during the reservation period on the sauna room usage parameters, making the determination of adjustment parameters more consistent with the fluctuations in the user's physiological state during the reservation period, and improving the adaptability of the adjustment parameters to the user's previous physiological changes.

[0068] This implementation method combines physiological information from the user's reservation stage and the initial stage of actual use to comprehensively reflect the user's overall physiological state from reservation to use. This serves as the basis for adjusting parameters. The basic usage parameters are determined by combining physiological information from the reservation stage and the initial stage of use, so that the benchmark for adjusting parameters more comprehensively reflects the user's physiological state across stages and improves the rationality of the basic parameters.

[0069] This implementation combines the baseline and the adjustment ratio caused by physiological changes during the user's reservation phase. The adjustment range is quantified through multiplication, so that the adjusted parameters are based on the overall physiological state baseline and reflect the impact of physiological changes during the reservation phase. This achieves a quantitative combination of the overall physiological state baseline and the impact of physiological changes during the reservation phase, improving the accuracy and relevance of the adjustment parameters.

[0070] Figure 5 A flowchart illustrating the third IoT-based sauna control method provided in this application embodiment is shown below. Figure 5 As shown, in some implementations, the above method also includes S210 to S230, which will be described in detail below.

[0071] S210. Determine the time period between the actual usage time and the expected arrival time as the reservation delay period. When the length of the reservation delay period is longer than the preset delay length, obtain the user's first physiological information within the reservation delay period. Segment the first physiological information to obtain multiple first sub-physiological information. Based on each first sub-physiological information, determine the change value of the first sub-physiological information corresponding to each first sub-physiological information.

[0072] Figure 6 A schematic diagram of the workflow of the third IoT-based sauna control method provided in this application embodiment is shown below. Figure 6 As shown in this implementation, the time interval between the actual time a user starts using the sauna and the scheduled arrival time can be calculated as the reservation delay period. For example, if a user expects to arrive at 15:00 but actually starts using the sauna at 15:20, the reservation delay period is 20 minutes.

[0073] It should be noted that the preset delay duration can be set according to the user's common delay situations, such as 10 minutes. If it exceeds this, physiological information during the delay period needs to be processed.

[0074] In this implementation, when the duration of the time period is longer than the preset delay duration (e.g., 10 minutes), the user's first physiological information within these 20 minutes can be collected, including gender, age, temporal heart rate per minute, and temporal body surface temperature.

[0075] In this implementation, the first physiological information within the scheduled delay period can be further divided into multiple segments at fixed time intervals (e.g., 5 minutes), with each segment being a first sub-physiological information. For example, 20 minutes of physiological information can be divided into four 5-minute sub-information segments, corresponding to data in time periods such as 15:00-15:05 and 15:05-15:10.

[0076] In this implementation, the change value of physiological indicators in each sub-information can be calculated as the change value of the first sub-physiological information corresponding to each first sub-physiological information. For example, if the heart rate increases from 70 beats / min to 75 beats / min in 5 minutes, the change value is 5 beats / min; if the body surface temperature increases from 36.5℃ to 37℃, the change value is 0.5℃.

[0077] It should be noted that the statistical indicators of the first sub-physiological information can be determined as the change value of the first sub-physiological information. The statistical indicators of the change value of the first sub-physiological information may include heart rate difference, body surface temperature difference, etc. For example, the heart rate change value is 5 beats / min and the body surface temperature change value is 0.5℃. These indicators can intuitively reflect the changes in physiological state.

[0078] S220. Among multiple first sub-physiological information change values, determine the target first sub-physiological information change value whose first sub-physiological information change value is greater than or equal to the preset first sub-physiological information change value, and the multiple target first sub-physiological information corresponding to the multiple target first sub-physiological information change values. Determine the first adjustment ratio based on the multiple target first sub-physiological information and the multiple target first sub-physiological information change values.

[0079] In this implementation, the preset first sub-physiological information change value can be determined based on the statistical data of users of the same gender and age group, such as the preset heart rate of 3 beats / min and the preset body surface temperature of 0.3℃.

[0080] In this implementation, each change value of the first sub-physiological information can be compared with another first sub-physiological information change value. If the change value is greater than or equal to the first sub-physiological information change value, then the change value of the first sub-physiological information change value is the target first sub-physiological information change value, and the sub-information corresponding to the first sub-physiological information change value is the target first sub-physiological information. For example, a 5-minute heart rate change value of 5 beats / min (≥3 beats / min) and a body surface temperature change value of 0.5℃ (≥0.3℃) are both target change values, and the corresponding sub-information is the target sub-information.

[0081] In this implementation, a first adjustment ratio can be determined based on multiple target first sub-physiological information and the change values ​​of multiple target first sub-physiological information. Specifically, the first adjustment ratio can be determined through an empirical value table. The empirical value table can be pre-set with ratios corresponding to different genders, ages, and target change values. For example, a heart rate change value of 5 beats / min for a 25-year-old male user corresponds to 1.1, and a body surface temperature change value of 0.5℃ corresponds to 1.05. The combined first adjustment ratio of 1.1 is obtained.

[0082] It should be noted that when determining the first adjustment ratio using the experience value table, the experience value table can cover different combinations of gender, age and change values. For example, a heart rate change value of 4 beats / min for a 30-year-old woman corresponds to an adjustment ratio of 1.08, ensuring that the adjustment ratio matches the user characteristics.

[0083] S230. Based on the first and second physiological information of multiple targets, determine the basic usage parameters of the sauna room. The product of the basic usage parameters and the first adjustment ratio is determined as the usage adjustment parameter of the sauna room.

[0084] In this implementation, the basic usage parameters, such as heart rate and body surface temperature within 10 minutes, can be determined by combining the target's first sub-physiological information and second physiological information (physiological information within a preset time period after the user starts using the device).

[0085] In this implementation, the baseline temperature of 40℃ and the baseline humidity of 60% can be obtained by matching the physiological indicators in the first sub-physiological information of the target (such as the highest heart rate of 75 beats / min during the delay period) and the indicators in the second physiological information (such as the initial heart rate of 78 beats / min) through an empirical value table.

[0086] It should be noted that the empirical value table for determining the basic usage parameters can be linked to the physiological indicators of the target sub-information and the second physiological information. For example, the target sub-information of a maximum heart rate of 75 beats / min and the second physiological information of a heart rate of 78 beats / min correspond to a baseline temperature of 40℃, making the basic parameters more suitable for the user's current state.

[0087] In this implementation, the product of the basic usage parameters and the first adjustment ratio is determined as the usage adjustment parameters of the sauna room. These parameters are obtained by multiplying the basic usage parameters by the first adjustment ratio. For example, a basic temperature of 40℃ × 1.1 = 44℃ and a basic humidity of 60% × 1.1 = 66% are the usage adjustment parameters of the sauna room.

[0088] This implementation method allows for more precise segmentation and target filtering of physiological information during the reservation delay period, enabling more accurate capture of the dynamic changes in the user's physiological state during the delay time. This makes the determination of the subsequent first adjustment ratio and basic usage parameters more closely aligned with the user's real-time physiological condition, effectively improving the adaptability of sauna room usage adjustment parameters.

[0089] This implementation method, when determining the first adjustment ratio, does not directly use the overall change value of the first physiological information during the reservation delay period. Instead, it filters out the target first sub-physiological information change values ​​and corresponding target first sub-physiological information whose change values ​​are greater than or equal to preset first sub-physiological information change values. The first adjustment ratio is then calculated based on these target information and change values. This approach, focusing on the significant changes in the user's physiological state, avoids the key physiological changes that might be masked by overall averaging. This makes the first adjustment ratio more accurately reflect the significant differences in the user's physiological state during the reservation delay period, improving the accuracy of the first adjustment ratio and providing a more reliable basis for the subsequent reasonable determination of adjustment parameters.

[0090] This implementation combines multiple target-specific physiological information (first and second sub-physiological information) to determine the basic usage parameters. The target-specific physiological information refers to the portion of physiological state that shows significant changes during the reservation delay. Compared to methods using only the first and second physiological information, this adds a reference dimension for significant physiological changes in the user during the reservation delay. This avoids the problem of physiological state changes caused by delays not being fully considered, improves the matching degree between basic usage parameters and the user's current physiological state, and thus makes the sauna usage adjustment parameters more accurately meet user needs.

[0091] Figure 7A flowchart illustrating the fourth IoT-based sauna control method provided in this application embodiment is shown below. Figure 7 As shown, in some implementations, in the above-mentioned S210, the first physiological information is segmented to obtain multiple first sub-physiological information, including S211 to S212. S211 to S212 will be explained in detail below.

[0092] S212. Obtain the time when the user's movement status changes during the scheduled delay period.

[0093] In this implementation, the user's movement state switching time during the scheduled delay period can be obtained. This time is the point in time when the user's movement state changes, such as from being stationary to walking, or from walking to running. It is directly related to the fluctuation of the user's physiological information and provides accurate time nodes for subsequent physiological information segmentation.

[0094] For example, the moment of motion state switching can be obtained through wearable devices, such as smartwatches or fitness trackers worn by users. These devices have built-in accelerometers and gyroscopes to monitor motion state in real time. When a sudden change in acceleration, step count, or motion posture is detected, the corresponding moment is recorded as the moment of motion state switching.

[0095] S212. Based on the moment of motion state switching, the first physiological information is segmented to obtain multiple first sub-physiological information.

[0096] In this implementation, the first physiological information can be segmented according to the moment of motion state switching, and the physiological information of the entire reservation delay period can be divided into multiple continuous segments. Each segment corresponds to the physiological data of the user in a certain stable motion state. For example, from time T1 to T2 corresponds to the stationary state, and from T2 to T3 corresponds to the walking state. Each segment is a first sub-physiological information.

[0097] This implementation method directly links changes in the user's physiological information, such as heart rate and body surface temperature, to changes in the movement state. This segmentation is based on changes in the user's actual movement state, avoiding indiscriminate segmentation and making subsequent processing based on the first sub-physiological information more targeted, thus improving the rationality of the segmentation process. The obtained first sub-physiological information more accurately reflects the user's physiological characteristics under different movement states, improving the effectiveness of the first sub-physiological information and providing a more reliable basis for subsequently determining the change value of the target first sub-physiological information and the target first sub-physiological information.

[0098] Through this implementation, the first sub-physiological information after segmentation accurately reflects the physiological changes of users under different exercise states. Therefore, the adjustment parameters based on this can more accurately adapt to the physiological differences caused by changes in the user's exercise state, improve the rationality of sauna room usage parameter adjustment, and make the parameters when users use the sauna more in line with their actual physiological state, thereby enhancing the user experience.

[0099] Figure 8 A flowchart illustrating the fifth IoT-based sauna control method provided in this application embodiment is shown below. Figure 8 As shown, in some implementations, in the above-mentioned S210, the first physiological information is segmented to obtain multiple first sub-physiological information, and S213 to S214 are also included. S213 to S214 will be explained in detail below.

[0100] S213. Obtain the duration of the first sub-physiological information corresponding to multiple first sub-physiological information.

[0101] In this implementation, after the first physiological information within the reservation delay period is segmented according to the motion state switching time and multiple first sub-physiological information is obtained, the duration corresponding to each first sub-physiological information can also be obtained. Each first sub-physiological information corresponds to the physiological data of a user in a certain stable motion state, and the duration of each first sub-physiological information is the time difference from the start time to the end time of the motion state.

[0102] For example, if a user switches from walking to jogging at 14:05 and to brisk walking at 14:12 within the scheduled delay period, the duration of the first sub-physiological information corresponding to the jogging state is 7 minutes; if the user switches from brisk walking to stillness at 14:15 and ends stillness at 14:20, the duration of the first sub-physiological information corresponding to the stillness state is 5 minutes.

[0103] S214. From multiple first sub-physiological information, remove the first sub-physiological information whose duration is less than the preset duration of the first sub-physiological information.

[0104] In this implementation, a preset duration for the first sub-physiological information can be set, and the first sub-physiological information with a duration less than the preset value can be removed from multiple first sub-physiological information. The preset duration is set based on the physiological information stability requirements to ensure that the retained first sub-physiological information corresponds to the physiological data of the user in a stable movement state.

[0105] For example, if the duration of the first sub-physiological information is preset to 3 minutes, and if a user switches from jogging to running but only stays at that state for 2 minutes before switching back to walking, this 2-minute duration of the first sub-physiological information will be removed.

[0106] It should be noted that the short-term first sub-physiological information usually corresponds to the transition phase of the exercise state. At this time, physiological information such as heart rate and body surface temperature has not yet stabilized and cannot reflect the typical physiological characteristics of the user in this state. By removing such short-term data, we can avoid the interference of transitional data with subsequent physiological state analysis and ensure that the first sub-physiological information used for calculation comes from valid and stable segments.

[0107] For example, a user switches from a static state to brisk walking at 14:30 within the scheduled delay period, but stops after only 1 minute and 30 seconds. The corresponding first sub-physiological information duration is 1 minute and 30 seconds, which is less than the preset 3 minutes. In this data, the user's heart rate increases from 70 beats / minute to 90 beats / minute (before reaching the stable heart rate of approximately 100 beats / minute during brisk walking), and the body surface temperature is also not stable. Retaining this data would lead to biases in subsequent physiological characteristic judgments, so it needs to be removed.

[0108] With this implementation, the first sub-physiological information in a short period of time is usually difficult to accurately reflect the stable physiological state changes of the user within that time period. If it is retained, it may introduce invalid data to interfere with subsequent analysis. This processing ensures that the first sub-physiological information used for subsequent calculations has sufficient time dimension validity, avoids interference from short-term fluctuation data on physiological state analysis, and improves the quality of the first sub-physiological information.

[0109] Through this implementation, the first adjustment ratio is determined based on multiple target first sub-physiological information and corresponding change values. After invalid short-term data is removed, the data source used to calculate the first adjustment ratio can better reflect the user's true physiological state, reducing the bias caused by inaccurate data and thus improving the accuracy of the first adjustment ratio. It can more accurately match the user's actual physiological state after the reservation is delayed, so that the final adjustment parameters are more in line with the user's current physiological state, improving the personalization of sauna room control and its applicability to the user's actual needs.

[0110] Figure 9 A flowchart illustrating the sixth IoT-based sauna control method provided in this application embodiment is shown below. Figure 9 As shown, in some implementations, in the above-mentioned S220, a first adjustment ratio is determined based on multiple target first sub-physiological information and multiple target first sub-physiological information change values, including S221 to S222. S221 to S222 will be explained in detail below.

[0111] S221. Obtain the target's first sub-motion state corresponding to the target's first sub-physiological information, and obtain the first adjustment ratio weight corresponding to each target's first sub-motion state. Determine the first sub-adjustment ratio based on each target's first sub-physiological information, the change value of the target's first sub-physiological information, and the target's first sub-motion state.

[0112] In this implementation, for each target first sub-physiological information, its corresponding target first sub-motion state can be obtained. This motion state is the user's actual motion state within the time period corresponding to the target first sub-physiological information, such as walking, sitting, or jogging. At the same time, based on the degree of influence of different motion states on the adjustment of sauna parameters, the first adjustment ratio weight corresponding to each target first sub-motion state can be obtained. For example, the weight of jogging is higher than the weight of sitting.

[0113] In this implementation, the first adjustment ratio can be determined by combining the specific value of the first sub-physiological information of each target, the corresponding change value of the first sub-physiological information of the target, and the motion state corresponding to the first sub-physiological information of the target through an empirical value table.

[0114] For example, when the target first sub-physiological information is the temporal heart rate of a 30-year-old user (80 beats per minute), the change value is an increase of 10 beats per minute in heart rate, and the exercise state is jogging, the experience value table stores the corresponding first sub-adjustment ratio.

[0115] S222. Determine the sum of the products of the first sub-adjustment ratio and the weight of the first adjustment ratio corresponding to the first sub-physiological information of multiple targets, and use it as the first adjustment ratio.

[0116] In this implementation, the product of the first sub-adjustment ratio corresponding to the first sub-physiological information of each target and the weight of the motion state can be calculated, and then all products can be added together to obtain the first adjustment ratio.

[0117] For example, there are two target first sub-physiological information. The first corresponds to the jogging state, with a sub-adjustment ratio of 0.1, a weight of 0.6, and a product of 0.06. The second corresponds to the walking state, with a sub-adjustment ratio of 0.05, a weight of 0.4, and a product of 0.02. The sum of the two, 0.08, is the first adjustment ratio.

[0118] This implementation takes into account the different impacts of different exercise states on the user's physiological state, and distinguishes importance by weight, so that the first adjustment ratio more accurately reflects the impact of physiological information changes under different exercise states on the adjustment of sauna parameters, and improves the matching degree between the adjustment ratio and the user's actual state; it avoids the deviation of the sub-adjustment ratio caused by a single factor, and makes the first sub-adjustment ratio more comprehensively and accurately reflect the user's actual needs for parameter adjustment under specific exercise states.

[0119] Figure 10 A flowchart illustrating the seventh IoT-based sauna control method provided in this application embodiment is shown below. Figure 10 As shown, in some implementations, the above method also includes S310 to S330, which will be described in detail below.

[0120] S310. Obtain the reservation time slots corresponding to the sauna room reservation instructions of multiple users. Construct a temporal adjacency matrix of users-reservation time slots-sauna room devices. The row dimension of the temporal adjacency matrix includes user identifiers, and the column dimension includes reservation time slots divided into 30-minute units. The matrix elements of the temporal adjacency matrix are used to store the device identifier of the user's reservation, the reservation time slot, and the remaining available time of the device in the reservation time slot.

[0121] Figure 11 A schematic diagram of the workflow of the seventh IoT-based sauna control method provided in the embodiments of this application is shown below. Figure 11 As shown, in this implementation, multiple sauna reservation instructions submitted by users through the Internet of Things can be collected, and the corresponding reservation time slot can be extracted from each instruction, such as the specific time slot when the user plans to use the sauna.

[0122] In this implementation, a temporal adjacency matrix can be constructed, consisting of users, reserved time slots, and sauna equipment. Rows in this matrix represent unique identifiers for different users, and columns represent reserved time slots divided into 30-minute intervals (e.g., starting at 00:00 daily, with each 30-minute interval as a unit). Each element in the matrix can store three pieces of information: the sauna equipment identifier reserved by the user, the specific time slot corresponding to that reservation, and the remaining available time for that equipment within that time slot. This structured storage method allows for the rapid association of user, time slot, and equipment information, providing a foundation for subsequent statistics and analysis.

[0123] For example, the temporal adjacency matrix can be a two-dimensional table, where rows are user IDs (e.g., U001, U002) and columns are reservation time slots (e.g., 08:00-08:30, 08:30-09:00). For instance, U001 corresponds to the location storage device identifier S001 for 08:00-08:30, the reservation time slot is 08:00-08:30, and the remaining available time is 0 minutes (indicating that the device has been fully reserved by U001 during this time slot); U002 corresponds to the location storage device identifier S002 for 08:30-09:00, the reservation time slot is 08:30-09:00, and the remaining available time is 30 minutes (indicating that the device still has 30 minutes available during this time slot).

[0124] S320. Based on the temporal adjacency matrix, determine the total reserved duration for each sauna room device within each reservation period. When the total reserved duration for the first sauna room device within the first reservation period exceeds the maximum continuous usage threshold of the first sauna room device, the first reservation period is determined as the overload period for the first sauna room device. The maximum continuous usage threshold is determined based on the device's rated power, heat dissipation efficiency, and maintenance requirements.

[0125] In this implementation, each column (each reservation time period) and each row (each user) of the temporal adjacency matrix can be traversed to calculate the total reservation duration of each sauna room device by different users within each reservation time period, thus obtaining the total reservation duration of each device within each time period.

[0126] In this implementation, for a specific device (such as the first sauna room device) during a certain reservation period (such as the first reservation period), the total reserved duration can be compared with the maximum continuous usage threshold of the device. If the total reserved duration exceeds this threshold, this reservation period can be marked as the device's overload period.

[0127] In this implementation, the maximum continuous use threshold can be determined empirically by combining the device's rated power, heat dissipation efficiency, and maintenance requirements. The higher the rated power, the more heat is generated during continuous operation; the lower the heat dissipation efficiency, the faster the heat accumulates; and the more frequent the maintenance requirements, the shorter the continuous use interval is needed. These three factors together determine the threshold size.

[0128] For example, assuming the rated power of the first sauna room equipment is 10kW, and its heat dissipation efficiency is to reduce the internal temperature by 5°C per hour (the temperature will exceed the safe value after 2 hours of continuous operation), and the maintenance manual stipulates that a 30-minute break is required after every 2 hours of continuous use, then the maximum continuous use threshold can be 120 minutes. If the total reservation time of this equipment during the first reservation period (14:00-14:30) is 150 minutes, which is greater than 120 minutes, it can be determined that 14:00-14:30 is the equipment overload period.

[0129] For example, when determining the preset maximum continuous use threshold, the maximum safe operating time of the device at rated power (calculated based on heat dissipation efficiency) can be calculated, along with the continuous use interval time specified in the maintenance procedure, and the smaller of the two values ​​can be taken as the threshold. For instance, if heat dissipation allows for continuous operation for 150 minutes and maintenance requires continuous operation for 120 minutes, then the maximum continuous use threshold is 120 minutes.

[0130] S330: Obtain multiple first users who booked the first sauna room during the equipment overload period, and obtain sauna room usage information for these first users within a preset historical time period. When the sauna room usage information of the target first user includes sauna room usage records after the equipment overload period, push sauna room adjustment suggestions for the time period corresponding to the sauna room usage records after the equipment overload period to the target first user. When the sauna room usage information of the target first user does not include sauna room usage records after the equipment overload period, determine the adjustment time period after the equipment overload period according to the principle of minimum time difference, and push sauna room adjustment suggestions for the adjustment time period to the target first user.

[0131] In this implementation, all users who booked the first sauna room during the equipment overload period can be selected from the temporal adjacency matrix. These users are the multiple first users. At the same time, sauna room usage information of these first users in a preset historical time period (such as the past 30 days) can be retrieved, including the time period, equipment identification, usage duration and other records.

[0132] In this implementation, for one of the target users, if their historical usage information contains usage records after the device overload period (e.g., the device overload period is 14:00-14:30, and the user previously used the same device from 15:00-15:30), the time period corresponding to the usage records after the overload period will be pushed to the user as an adjustment suggestion. For example, it may be suggested to reschedule for the same device or other available devices during that time period. This suggestion based on historical habits can improve the user's acceptance of the adjustment.

[0133] For example, the historical usage record of the target user U001 shows that he used the first sauna equipment S001 from 15:00 to 15:30 in the past 30 days, while the current overload period of the equipment is 14:00 to 14:30. Therefore, an adjustment suggestion is pushed to U001: "S001 still has available time during the 15:00 to 15:30 period that you used before. It is recommended to switch to this period."

[0134] In this implementation, when the target user's historical usage information does not contain any usage records after the device overload period, the available time period with the smallest time difference after the device overload period can be found, that is, the unbooked time period with the shortest time interval to the end of the overload period. This time period is then pushed to the user as the adjustment time period, which can minimize the time cost for the user to reschedule and improve the convenience of adjustment.

[0135] For example, if the target user U002 has no usage records after the device overload period (14:00-14:30) in its historical usage records, then the system searches for available time slots for S001 after 14:30 and finds that 14:30-15:00 is the available time slot with the smallest time difference (30-minute interval). Therefore, the system pushes a suggestion to U002: "S001 is available during the 14:30-15:00 time slot, and the time difference with your original reserved time slot is the smallest. It is recommended to adjust to this time slot."

[0136] This implementation method uses a temporal adjacency matrix to calculate the total reservation duration of each sauna room device within each reservation period. Then, it obtains multiple first users who reserved the device during the device overload period, as well as their sauna room usage information within a preset historical time period. If the target first user has usage records after the device overload period, it pushes adjustment suggestions for the corresponding time period. The adjustment time period after the device overload period is determined according to the principle of minimum time difference, and suggestions are pushed. This method can accurately identify device overload periods, avoid device wear and tear due to continuous over-threshold use, optimize device resource allocation, and extend device life.

[0137] This implementation method, after determining the equipment overload period, first obtains the sauna room usage information of the first user who booked the equipment within a preset historical time period. If the user has usage records after the equipment overload period, a sauna room adjustment suggestion for the corresponding time period is pushed to them. If not, the adjustment time period is determined according to the principle of minimum time difference before pushing the suggestion. This suggestion push method based on the user's historical usage habits makes the adjustment suggestions more in line with the user's needs, increases the user's acceptance of the suggestions, reduces the user's frustration due to equipment overload, optimizes the user's sauna room booking experience, improves the efficiency of sauna room booking resource scheduling, reduces the time cost of manual intervention, quickly resolves resource conflicts caused by equipment overload, and improves the overall rationality of booking scheduling.

[0138] In some implementations, in S330 above, when the sauna usage information of the target first user includes sauna usage records after the equipment overload period, a sauna adjustment suggestion for the time period corresponding to the sauna usage records after the equipment overload period is pushed to the target first user, including S331 to S332. S331 to S332 will be explained in detail below.

[0139] S331. When the sauna usage information of the target first user includes sauna usage records after the equipment overload period, obtain the historical sauna configuration parameters corresponding to the sauna usage records after the equipment overload period.

[0140] In this implementation, for the target first user with usage records after the equipment overload period, the historical sauna configuration parameters corresponding to the record can be extracted from their sauna usage information. These historical parameters are the settings when the user used the sauna in the past during that period, which can reflect the user's past usage habits and provide a reference basis for generating adjustment suggestions in the future.

[0141] For example, the historical sauna room configuration parameters corresponding to the sauna room usage records after the equipment overload period may include the sauna room temperature, humidity and usage duration previously set by the user. For instance, in a certain usage after the equipment overload period, the historical configuration parameters of a user were 45°C, 60% relative humidity and 30 minutes of single usage.

[0142] S332. Based on the historical sauna room configuration parameters corresponding to the sauna room usage records, determine differentiated sauna room configuration parameters that differ from the historical sauna room configuration parameters. Push the time period corresponding to the sauna room usage records after the equipment overload period and the differentiated sauna room configuration parameters to the target primary user as a sauna room adjustment suggestion.

[0143] In this implementation, historical sauna room configuration parameters can be used as a benchmark. Differentiated configuration parameters can be determined by adjusting the range of parameter values. The differentiated parameters must be significantly different from the historical parameters while remaining within the safe operating range of the sauna room. This provides users with new configuration options, avoids duplicate suggestions, and improves the user's sauna experience.

[0144] For example, when determining the configuration parameters for a differentiated sauna room, historical parameters can be adjusted up or down, or configuration parameters different from historical parameters can be selected directly from the differentiated parameter block. For instance, if the historical parameters are 45°C, 60% humidity, and 30 minutes, the differentiated parameters could be 42°C, 55% humidity, and 25 minutes, or 48°C, 65% humidity, and 35 minutes, ensuring that there are differences from historical parameters while still meeting the equipment's operating requirements.

[0145] In this implementation, the usage records corresponding to the time period after the device overload period, along with the determined differentiated sauna room configuration parameters, can be pushed to the target primary user. This adjustment suggestion includes both the user's familiar time period and provides new configuration options, which can improve the user's acceptance of the suggestion.

[0146] For example, once the target user agrees to the adjustment suggestion, the sauna room configuration parameters corresponding to the time period after the user's reserved equipment overload period can be automatically modified to differentiated parameters. For example, the original historical configuration was 45℃, and now it is adjusted to 42℃. A confirmation message is sent to the user to complete the reservation adjustment.

[0147] This implementation first retrieves the historical sauna room configuration parameters corresponding to the usage record, then determines differentiated sauna room configuration parameters based on the historical parameters, and finally pushes the time period and differentiated parameters corresponding to the usage record to the user as adjustment suggestions. By combining the user's own historical usage configuration, it avoids recommending duplicate content, making the adjustment suggestions more in line with the user's past usage habits, and improving the targeting and relevance of the suggestions. By providing configuration options different from the past, it breaks the single recommendation mode, increases the diversity of adjustment suggestions, and can better meet the user's possible new needs or changing usage preferences.

[0148] In some implementations, S330 above includes sauna room usage information for the target first user that includes sauna room usage records after the equipment overload period. In this implementation, sauna room adjustment suggestions for the time period corresponding to the sauna room usage records after the equipment overload period are pushed to the target first user. S333 to S334 are also included. S333 to S334 are explained in detail below.

[0149] S333. Obtain the first physiological information of the target first user from the current time to the expected arrival time. Obtain the historical sauna configuration parameters corresponding to the sauna usage records and the historical physiological information corresponding to the target first user.

[0150] In this implementation, two types of information can be obtained to support the accurate correction of adjustment suggestions. One type is the first physiological information of the target first user from the current moment to the expected arrival time. This type of information includes the user's gender, age, temporal heart rate, and temporal body surface temperature, which directly reflects the user's current physiological state. The other type is the historical sauna configuration parameters (such as temperature and humidity during historical use) corresponding to the sauna usage records, as well as the historical physiological information of the target first user (i.e., the gender, age, temporal heart rate, and temporal body surface temperature data of the user during the same time period when using the sauna in the past). This information can provide a data basis for comparing the differences between the current and historical physiological states.

[0151] For example, the target first user's current first physiological information can be male, age 35, current time-series average heart rate of 75 beats / minute, and current time-series average body surface temperature of 36.5℃; the corresponding historical sauna room configuration parameters can be temperature 40℃, humidity 60%, and historical physiological information can be current time-series average heart rate of 70 beats / minute and current time-series average body surface temperature of 36.2℃.

[0152] S334. Determine the physiological differences between the initial physiological information and historical physiological information. Determine the differential adjustment ratio based on the differential physiological information. Determine the initial differential sauna configuration parameters, different from the historical sauna configuration parameters. Determine the product of the initial differential sauna configuration parameters and the differential adjustment ratio as the corrected differential sauna configuration parameters. Push the sauna usage records corresponding to the time period after the equipment overload period and the corrected differential sauna configuration parameters to the target first user as sauna adjustment suggestions.

[0153] In this implementation, the difference between the first physiological information and the historical physiological information can be calculated first. For the same dimension (such as time-series heart rate and time-series body surface temperature), the difference between the current average value and the historical average value can be calculated. These differences are integrated into the difference physiological information. Subsequently, the difference adjustment ratio can be determined according to the dimension value of the difference physiological information. The change of the adjustment ratio can better reflect the impact of physiological state on the configuration parameters.

[0154] For example, the differential physiological information could be a temporal heart rate difference of 5 beats / minute or a temporal body surface temperature difference of 0.3°C; based on these differences, the determined differential adjustment ratio could be 1.05, which is used to subsequently correct configuration parameters.

[0155] With this implementation method, when determining the differential adjustment ratio based on differential physiological information, the differential adjustment ratio can be determined through an empirical value table.

[0156] In this implementation, the initial differentiated sauna configuration parameters can be determined based on the historical sauna configuration parameters in S331 to S332 above. The initial differentiated configuration parameters and the differentiated adjustment ratio are then multiplied to obtain the corrected differentiated sauna configuration parameters. Through physiological difference correction, the parameters are made to adapt to the user's current physiological state changes.

[0157] For example, the initial differential temperature is 42°C, which is multiplied by the differential adjustment ratio of 1.05 to get 44.1°C; the initial differential humidity is 65%, which is multiplied by 1.05 to get 68.25%, and these are integrated into the corrected configuration parameters.

[0158] In this implementation, the sauna usage records after the equipment overload period can be pushed to the target primary user along with the corrected differentiated sauna configuration parameters. This preserves the user's historical usage time habits and corrects the configuration parameters based on physiological differences, making it more in line with the user's current physiological needs.

[0159] For example, the push notification could be something like, "It is recommended to use the sauna between 18:00 and 19:00 after the device is overloaded. The corrected configuration parameters are 44.1℃ and 68.25%", to help users use a sauna configuration that is more in line with their current physiological state during the appropriate time period.

[0160] This implementation method identifies the physiological differences between the current primary physiological information and historical physiological information, and determines the differential adjustment ratio based on these differences. It then determines initial differential sauna room configuration parameters that differ from historical parameters. Finally, it multiplies these initial differential sauna room configuration parameters by the differential adjustment ratio to obtain corrected differential sauna room configuration parameters. By combining the differences between the user's current and historical physiological information to correct the adjustment parameters, this method solves the problem that relying solely on historical difference parameters may not align with the user's current physiological state, making the adjustment suggestions more closely match the user's current actual physiological needs. This ensures that the adjustment suggestions are no longer limited to differences in historical configurations but are more aligned with the user's real-time physiological condition, thus enhancing the personalization of the adjustment suggestions.

[0161] This application also provides an Internet of Things (IoT)-based sauna control system, including a unit for implementing the above-described IoT-based sauna control method.

[0162] Figure 12 A schematic diagram of the logical structure of an IoT-based sauna control system provided in this application embodiment is shown below. Figure 12 As shown, the system 1 of this embodiment includes a processing unit 11, a storage unit 12, and a transceiver unit 13. The processing unit 11 is used to process data, the storage unit 12 is used to store data, and the transceiver unit 13 is used to send and receive data. The processing unit 11, the storage unit 12, and the transceiver unit 13 cooperate with each other to implement the above-described method. The beneficial effects of the embodiments of this application have been described in the above-described method and will not be repeated here.

[0163] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0164] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0165] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0166] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0167] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0168] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0169] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0170] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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. Such 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 this application, and should all be included within the protection scope of this application.

Claims

1. A sauna room control method based on the Internet of Things, characterized in that, The method includes: In response to the user's sauna reservation instruction and expected arrival time obtained through the Internet of Things at the current moment, the system acquires the user's first physiological information from the current moment to the expected arrival time; based on the first physiological information, it determines the reservation configuration parameters of the sauna; and controls the sauna to preheat according to the reservation configuration parameters from the current moment to the expected arrival time. The system obtains the actual time when the user starts using the sauna and the second physiological information of the user within a preset usage period starting from the actual time of use; based on the first and second physiological information, it determines the usage adjustment parameters of the sauna; wherein, the first and second physiological information include the user's gender, age, temporal heart rate, and temporal body surface temperature.

2. The method according to claim 1, characterized in that, Based on the first and second physiological information, determine the adjustment parameters for the use of the sauna, including: Based on the first physiological information, determine the user's first physiological information change value and the preset first physiological information change value; when the first physiological information change value is greater than or equal to the preset first physiological information change value, determine the first adjustment ratio based on the first physiological information and the first physiological information change value; Based on the first and second physiological information, the basic usage parameters of the sauna room are determined; the product of the basic usage parameters and the first adjustment ratio is determined as the usage adjustment parameters of the sauna room.

3. The method according to claim 2, characterized in that, The method further includes: The time period between the actual usage time and the expected arrival time is determined as the reservation delay period. When the length of the reservation delay period is longer than the preset delay length, the user's first physiological information within the reservation delay period is obtained. The first physiological information is segmented to obtain multiple first sub-physiological information. Based on each first sub-physiological information, the change value of the first sub-physiological information corresponding to each first sub-physiological information is determined. Among multiple first sub-physiological information change values, determine the target first sub-physiological information change value whose first sub-physiological information change value is greater than or equal to the preset first sub-physiological information change value, and the multiple target first sub-physiological information corresponding to the multiple target first sub-physiological information change values; determine the first adjustment ratio based on the multiple target first sub-physiological information and the multiple target first sub-physiological information change values; Based on the first and second physiological information of multiple targets, the basic usage parameters of the sauna room are determined; the product of the basic usage parameters and the first adjustment ratio is determined as the usage adjustment parameters of the sauna room.

4. The method according to claim 3, characterized in that, The first physiological information is segmented to obtain multiple first sub-physiological information, including: Get the time when the user's activity status changes during the scheduled delay period; Based on the moment of motion state switching, the first physiological information is segmented to obtain multiple first sub-physiological information.

5. The method according to claim 4, characterized in that, The first physiological information is segmented to obtain multiple first sub-physiological information, which also include: Obtain the duration of the first sub-physiological information corresponding to multiple first sub-physiological information items; From multiple first sub-physiological information, remove the first sub-physiological information whose duration is less than the preset duration.

6. The method according to claim 5, characterized in that, Based on the first sub-physiological information of multiple targets and the changes in the first sub-physiological information of multiple targets, a first adjustment ratio is determined, including: Obtain the target's first sub-motion state corresponding to the first sub-physiological information of each target, and obtain the first adjustment ratio weight corresponding to the first sub-motion state of each target; determine the first sub-adjustment ratio based on the target's first sub-physiological information, the change value of the target's first sub-physiological information, and the target's first sub-motion state; The sum of the products of the first sub-adjustment ratio and the weight of the first adjustment ratio corresponding to the first sub-physiological information of multiple targets is determined as the first adjustment ratio.

7. The method according to claim 6, characterized in that, The method further includes: Retrieve the reservation time slots corresponding to the sauna room reservation instructions of multiple users; construct a temporal adjacency matrix of user-reservation time slot-sauna room equipment. The row dimension of the temporal adjacency matrix includes user identifiers, and the column dimension includes reservation time slots divided into 30-minute units. The matrix elements of the temporal adjacency matrix are used to store the device identifier of the user reservation, the reservation time slot, and the remaining available time of the device in the reservation time slot. Based on the temporal adjacency matrix, the total reservation duration of each sauna room device within each reservation period is determined; when the total reservation duration of the first sauna room device within the first reservation period exceeds the maximum continuous usage threshold of the first sauna room device, the first reservation period is determined as the overload period of the first sauna room device; wherein, the maximum continuous usage threshold is determined by the rated power of the device, heat dissipation efficiency and maintenance requirements. The system acquires information on multiple first users who booked the first sauna room during the equipment overload period, and obtains sauna room usage information for these first users within a preset historical time period. When the sauna room usage information of the target first user includes sauna room usage records after the equipment overload period, the system pushes sauna room adjustment suggestions for the time period corresponding to the sauna room usage records after the equipment overload period to the target first user. When the sauna room usage information of the target first user does not include sauna room usage records after the equipment overload period, the system determines the adjustment time period after the equipment overload period according to the principle of minimum time difference, and pushes sauna room adjustment suggestions for the adjustment time period to the target first user.

8. The method according to claim 7, characterized in that, When the sauna usage information of the target user includes sauna usage records after the equipment overload period, a sauna adjustment suggestion for the time period corresponding to the sauna usage records after the equipment overload period is pushed to the target user, including: When the sauna usage information of the target first user includes sauna usage records after the equipment overload period, obtain the historical sauna configuration parameters corresponding to the sauna usage records after the equipment overload period. Based on the historical sauna room configuration parameters corresponding to the sauna room usage records, differentiated sauna room configuration parameters that differ from the historical sauna room configuration parameters are determined; the time period corresponding to the sauna room usage records after the equipment overload period and the differentiated sauna room configuration parameters are pushed to the target first user as sauna room adjustment suggestions.

9. The method according to claim 8, characterized in that, When the sauna usage information of the target user includes sauna usage records after the equipment overload period, the system pushes sauna adjustment suggestions for the time period corresponding to the sauna usage records after the equipment overload period to the target user, and also includes: Obtain the first physiological information of the target user from the current time to the expected arrival time; obtain the historical sauna configuration parameters corresponding to the sauna usage records and the historical physiological information corresponding to the target user. Identify the physiological differences between primary physiological information and historical physiological information; determine the differential adjustment ratio based on the physiological differences; determine the initial differential sauna configuration parameters that differ from the historical sauna configuration parameters; determine the product of the initial differential sauna configuration parameters and the differential adjustment ratio as the corrected differential sauna configuration parameters; push the sauna usage records corresponding to the time period after the equipment overload period and the corrected differential sauna configuration parameters to the target primary user as sauna adjustment suggestions.

10. A sauna room control system based on the Internet of Things, characterized in that, Includes units for implementing the method of any one of claims 1 to 9.

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