Disinfecting apparatus, control method, device and medium based on blood glucose monitoring

Abstract

The application discloses a disinfection equipment, a control method, a device and a medium based on blood glucose monitoring. The method comprises the following steps: according to each preset meal period updated the previous day, according to the stage in which the real-time time is located in each preset meal period, the disinfection equipment is controlled to perform a corresponding preset action; the blood glucose concentration change of the user monitored by the intelligent wearable device is acquired and recorded by the networking module every day; according to the blood glucose concentration change, the actual meal time point of the use waiting stage in each preset meal period formed after the use of the day is determined; according to the blood glucose concentration change, the actual meal time point of the use waiting stage in each preset meal period formed after the use of the day is determined; according to each target meal time point, the target time period of the use waiting stage in each preset meal period is determined. By using the above method, the automatic update of the working time of the disinfection equipment is realized, and the conflict between the working process of the disinfection equipment and the actual meal time of the user is avoided.

Description

Technical Field

[0001] This invention relates to the technical field of kitchen utensils, and more particularly to a disinfection device, control method, apparatus, and medium based on blood glucose monitoring. Background Technology

[0002] With the development of the times, people are paying more and more attention to the quality of life and will use disinfection equipment to disinfect, sterilize, dry, keep warm and moisturize, and store tableware, clothing, medical devices, etc. through ultraviolet rays, infrared rays, high temperature and ozone.

[0003] Automation and intelligence have become a trend in home appliances. In the category of disinfection equipment, most still rely on manual clicks to select functions. Users often forget to click the disinfection function after meals or click it before meals, resulting in tableware being too hot to use immediately after disinfection. Summary of the Invention

[0004] This invention provides a disinfection device, control method, apparatus, and medium based on blood glucose monitoring. By acquiring changes in blood glucose concentration monitored by the user through a smart wearable device via a network module, the user's actual eating habits can be determined, and the target time period for the disinfection device during the waiting phase can be accurately determined, thereby improving the automation and intelligence of the disinfection device.

[0005] According to one aspect of the present invention, a method for controlling a disinfection device based on blood glucose monitoring is provided, wherein the disinfection device includes a disinfection component, a temperature control component, and a networking module;

[0006] The control method includes:

[0007] Each day, according to the preset meal cycles updated the previous day, the disinfection equipment is controlled to perform corresponding preset actions based on the real-time time in each preset meal cycle. The preset meal cycle includes a waiting period, and the preset actions corresponding to the waiting period include controlling the disinfection component to stand still and controlling the temperature control component to perform a heat preservation program.

[0008] The network module is used to acquire and record daily changes in the user's blood glucose concentration monitored by the smart wearable device.

[0009] Based on the user's blood glucose concentration changes, determine the actual meal time point of the waiting phase in each of the preset meal cycles formed after the user's use on the same day;

[0010] When the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the target dining time in the waiting phase of each preset dining cycle is calculated based on the actual dining time and the initial dining time, which are within the preset difference range.

[0011] Based on the target dining time points, determine the target time period of the waiting phase in each preset dining cycle, so as to update the preset dining cycles used on that day.

[0012] Optionally, the preset dining cycle further includes a preparation stage; in terms of time, the waiting stage is located after the preparation stage; the preset action corresponding to the preparation stage includes controlling the disinfection component to continuously perform a disinfection procedure once.

[0013] Based on each target dining time point, the target time period of the waiting phase in each preset dining cycle is determined. After updating each preset dining cycle used on that day, the method further includes:

[0014] Based on the target time period of the waiting phase in each of the preset dining cycles, the target time period of the preparation phase in each of the preset dining cycles is set ahead of time by a first preset time, so as to update each of the preset dining cycles used on that day.

[0015] Optionally, based on the user's blood glucose concentration changes, the actual meal time point in the waiting phase of each preset meal cycle formed after the user's use on the same day is determined, including:

[0016] The time point when the user's blood glucose concentration reaches the preset concentration threshold is determined as the actual meal time point of the waiting phase in each preset meal cycle formed after the user's use on that day.

[0017] Optionally, based on each of the target dining times, a target time period for the waiting phase in each of the preset dining cycles is determined to update each of the preset dining cycles used that day, including:

[0018] Based on each of the target dining time points, the time point that is a first preset time in advance is determined as the start time, and the time point that is a second preset time delayed is determined as the end time.

[0019] The time period from the start time to the end time is determined as the actual time period of the waiting phase in the preset dining cycle formed by the user on the same day.

[0020] Optionally, before controlling the disinfection equipment to perform corresponding preset actions each day according to the preset meal cycles updated the previous day, based on the real-time stage within each preset meal cycle, the method further includes:

[0021] The network module is used to acquire and record the location and real-time time of the user monitored through the smart wearable device;

[0022] The initial preset dining cycle is determined based on the user's location and real-time time;

[0023] Each day, based on the preset meal cycles updated the previous day, and according to the real-time stage within each preset meal cycle, the disinfection equipment is controlled to perform corresponding preset actions, including:

[0024] On the first day, according to the initial preset dining cycle, the disinfection equipment is controlled to perform the corresponding preset actions based on the real-time stage within each initial preset dining cycle.

[0025] Optionally, when the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the target dining time in the waiting phase of each preset dining cycle is calculated based on the actual dining time and the initial dining time within the preset difference range, including:

[0026] When the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the similarity between the actual dining time and the initial dining time is calculated.

[0027] Based on the similarity between the actual dining time and the initial dining time, a corresponding preset first iteration correction value is determined; wherein, the preset first iteration correction value is negatively correlated with the similarity.

[0028] Based on the initial iteration value, the actual iteration value is calculated according to the first iteration correction value; wherein, the meal time point of the waiting stage in each of the preset meal cycles corresponds to a preset iteration value, the iteration value corresponding to the initial meal time point of the waiting stage in the preset meal cycle updated the previous day is the initial iteration value, and the iteration value corresponding to the actual meal time point of the waiting stage in the preset meal cycle formed after the user uses it on the same day is the actual iteration value.

[0029] Based on the initial iteration value and the actual iteration value, calculate the weights of the corresponding initial dining time point and the actual dining time point relative to the target dining time point, respectively.

[0030] Based on the weights of the initial dining time and the actual dining time relative to the target dining time, the relative position of the target dining time with respect to the initial dining time and the actual dining time in the time dimension is determined, thereby determining the target dining time.

[0031] Optionally, calculating the similarity between the actual dining time and the initial dining time includes:

[0032] Calculate the absolute value of the difference between the actual dining time and the initial dining time, and use it as the similarity between the actual dining time and the initial dining time.

[0033] Optionally, the preset first iteration correction value satisfies:

[0034] When the similarity is within a first preset similarity interval, the corresponding first iteration correction value is positive, and the first iteration correction value is negatively correlated with the similarity.

[0035] When the similarity is within the second preset similarity interval, the corresponding first iteration correction value is negative, and the absolute value of the first iteration correction value is positively correlated with the similarity.

[0036] The first preset similarity interval and the second preset similarity interval do not overlap, and the similarity of the first preset similarity interval is greater than the similarity of the second preset similarity interval.

[0037] Optionally, the iterative value has a preset upper limit value and a preset lower limit value;

[0038] Based on the initial iteration value and according to the first iteration correction value, the actual iteration value is calculated, including:

[0039] When the initial iteration value reaches the preset upper limit value and the first iteration correction value is positive, the actual iteration value is assigned the preset upper limit value;

[0040] When the initial iteration value reaches the preset lower limit and the first iteration correction value is negative, the actual iteration value is assigned the preset lower limit.

[0041] Optionally, based on the initial iteration value and the actual iteration value, the weights of the corresponding initial dining time point and the actual dining time point relative to the target dining time point are calculated, including:

[0042] The weight Q of the initial dining time point relative to the target dining time point is calculated according to the formula Q = D / (D + D').

[0043] Calculate the weight Q' of the actual dining time point relative to the target dining time point according to the formula Q'=D' / (D+D');

[0044] Where D is the initial iteration value and D' is the actual iteration value.

[0045] Optionally, determining the target dining time point by determining its relative position in the time dimension with respect to the initial dining time point and the actual dining time point based on their weights relative to the target dining time point includes:

[0046] The target dining time point Ts” is calculated according to the following formula: Ts” / (Ts+Ts')=Q / (Q+Q'); where Ts is the initial dining time point and Ts' is the actual dining time point.

[0047] Optionally, when the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the target dining time in the waiting phase of each preset dining cycle is calculated based on the actual dining time and the initial dining time within the preset difference range, including:

[0048] When the actual dining time and the initial dining time of the waiting phase in the two preset dining cycles updated the previous day are within a preset difference range, the target dining time of the waiting phase in the two preset dining cycles is calculated based on the actual dining time and the initial dining time, which are within the preset difference range.

[0049] Optionally, when the actual dining time and the initial dining time of the waiting phase in the two preset dining cycles updated the previous day are within a preset difference range, after calculating the target dining time of the waiting phase in the two preset dining cycles based on the actual dining time and the initial dining time which are within the preset difference range, the method further includes:

[0050] When the target dining time of the waiting phase in the two preset dining cycles is within a preset difference range, the two preset dining cycles are merged into one preset dining cycle, and the target dining time of the waiting phase in the merged preset dining cycle is calculated based on the target dining time of the waiting phase in the two preset dining cycles.

[0051] Optionally, after determining the actual meal time point of the waiting phase in each of the preset meal cycles formed after the user's use on the same day, based on the user's blood glucose concentration changes, the method further includes:

[0052] When the initial dining time in the waiting phase of the actual dining time period and the preset dining cycle updated the previous day are not within a preset difference range, the initial iteration value is corrected using a preset second iteration correction value. This ensures that the initial dining time is not within a preset difference range from the actual dining time of the current day for a consecutive preset number of days. After correction using the preset second iteration correction value, the initial iteration value is lower than a preset iteration value threshold. Each dining time in the waiting phase of the preset dining cycle corresponds to a preset iteration value, and the iteration value corresponding to the initial dining time in the waiting phase of the preset dining cycle updated the previous day is the initial iteration value.

[0053] When the initial iteration value is lower than a preset iteration value threshold, the initial meal time point and the preset meal cycle corresponding to the initial meal time point are deleted.

[0054] According to another aspect of the present invention, a disinfection equipment control device based on blood glucose monitoring is provided, the disinfection equipment including a disinfection component, a temperature control component, and a networking module;

[0055] The control device includes:

[0056] The control module is used to control the disinfection equipment to perform corresponding preset actions each day according to the preset meal cycles updated the previous day, based on the real-time time in each preset meal cycle stage; the preset meal cycle includes a waiting period, and the preset actions corresponding to the waiting period include controlling the disinfection component to stand still and controlling the temperature control component to perform a heat preservation program;

[0057] A recording module is used to acquire and record daily changes in the user's blood glucose concentration monitored by the smart wearable device using the network module.

[0058] The time point determination module is used to determine the actual meal time point of the waiting phase in each preset meal cycle formed after the user's use on the same day, based on the changes in the user's blood glucose concentration.

[0059] The calculation module is used to calculate the target dining time point of the waiting phase in each preset dining cycle when the actual dining time point and the initial dining time point in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, based on the actual dining time point and the initial dining time point within the preset difference range.

[0060] The update module is used to determine the target time period of the waiting phase in each of the preset dining cycles based on each of the target dining time points, so as to update each of the preset dining cycles used on that day.

[0061] According to another aspect of the present invention, a disinfection device is provided, the disinfection device comprising:

[0062] At least one processor; and

[0063] A memory communicatively connected to the at least one processor; wherein,

[0064] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the blood glucose monitoring-based disinfection device control method according to any embodiment of the present invention.

[0065] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the blood glucose monitoring-based disinfection device control method according to any embodiment of the present invention.

[0066] The technical solution of this invention firstly involves controlling the disinfection equipment to perform corresponding preset actions each day according to the preset meal cycles updated the previous day, based on the real-time stage within each preset meal cycle. Then, a network module is used to acquire and record the user's blood glucose concentration changes monitored by a smart wearable device each day. Next, based on the user's blood glucose concentration changes, the actual meal time point during the waiting phase of each preset meal cycle formed after the user's use that day is determined. Finally, based on each target meal time point, the target time period for the waiting phase in each preset meal cycle is determined to update the preset meal cycles used that day. Using the above method, by connecting with smart wearable devices and based on the initial meal time of the user's meal cycle updated the previous day and the user's actual meal time on the current day, the target meal time that reflects the user's actual dining habits can be accurately determined. This allows for the determination of the waiting phase for the target meal time, enabling the updating of the preset meal cycle for the day. This facilitates the automatic disinfection process of the disinfection equipment, optimizes its operating time, and makes each preset meal cycle more compatible with the user's actual dining habits. It avoids conflicts between the disinfection equipment's operation and the user's actual meal time, improving the automation and intelligence of the disinfection equipment and enhancing the user experience.

[0067] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0068] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0069] Figure 1 This is a schematic diagram of the structure of a disinfection device provided in an embodiment of the present invention;

[0070] Figure 2 A flowchart illustrating a disinfection equipment control method based on network connectivity, provided as an embodiment of the present invention;

[0071] Figure 3 This is a schematic diagram of a structure for a preset dining cycle provided in an embodiment of the present invention;

[0072] Figure 4 A graph showing the change in blood glucose concentration in a human body over a day, provided as an embodiment of the present invention;

[0073] Figure 5 A flowchart illustrating a second method for controlling a disinfection device based on blood glucose monitoring, as provided in an embodiment of the present invention;

[0074] Figure 6 A flowchart illustrating a third method for controlling a disinfection device based on blood glucose monitoring, provided in an embodiment of the present invention;

[0075] Figure 7 A flowchart illustrating the fourth method for controlling a disinfection device based on blood glucose monitoring, provided in an embodiment of the present invention;

[0076] Figure 8 A schematic diagram of a disinfection equipment control device based on blood glucose monitoring provided in an embodiment of the present invention;

[0077] Figure 9 A structural block diagram of a disinfection device provided in an embodiment of the present invention;

[0078] Among them, 10-disinfection equipment, 11-processor, 12-read-only memory, 13-random access memory, 14-bus, 15-input / output (I / O) interface, 16-input unit, 17-output unit, 18-storage unit, 19-communication unit, 20-ultraviolet lamp, 30-heating lamp, 40-temperature sensor, 50-network module, 60-door control switch, 70-cooling fan;

[0079] 110 - Control module, 120 - Recording module, 130 - Time point determination module, 140 - Calculation module, 150 - Update module. Detailed Implementation

[0080] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0081] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0082] In one embodiment, Figure 1 This is a schematic diagram of the structure of a disinfection device provided in an embodiment of the present invention. Figure 2 A flowchart illustrating a disinfection equipment control method based on network connectivity, provided in an embodiment of the present invention. Figure 3This is a schematic diagram of a preset meal cycle provided in an embodiment of the present invention. This embodiment is applicable to situations where the target meal time point during the waiting phase in the disinfection equipment is accurately determined, so as to automatically update the initial meal time point updated the previous day, making each preset meal cycle of the disinfection equipment more suitable for the user's actual meal time. This method can be executed by a disinfection equipment control device based on network functionality. This disinfection equipment control device based on network functionality can be implemented in hardware and / or software form, and can be configured in the disinfection equipment. Figures 1 to 3 As shown, the disinfection equipment can specifically be a disinfection cabinet, which includes a disinfection component, a temperature control component, and a networking module. The disinfection component may include an ultraviolet lamp 20, which generates ultraviolet light for disinfecting tableware; the disinfection component may also include a heating lamp 30, which heats the cavity, removes surface moisture from the tableware, and also has a certain disinfection effect. The temperature control component may include a temperature sensor 40, which detects the ambient temperature within the disinfection equipment, thereby identifying the surface temperature of the tableware. The networking module 50 is mainly used to connect the machine to a network, which can be the Internet or a local area network; additionally, the networking module 50 can be used to connect other kitchen appliances to the automatic disinfection equipment for information transmission. The control method includes:

[0083] S110. Each day, according to the preset meal cycles updated the previous day, the disinfection equipment is controlled to perform the corresponding preset actions based on the real-time time at each preset meal cycle stage.

[0084] Among them, reference Figure 3 The preset dining cycle includes a waiting period, and the preset actions corresponding to the waiting period include controlling the sterilization component to remain still and controlling the temperature control component to execute the heat preservation program.

[0085] Specifically, when using sterilization equipment to sterilize tableware, a user's meal cycle can be divided into several stages, such as before, during, and after the meal. Therefore, the preset meal cycle of the sterilization equipment needs to meet the user's various needs under different circumstances before and after the meal. For example, the preset meal cycle can include the preparation stage before each meal when the user sterilizes the equipment, the waiting stage when the user needs to remove the tableware from the sterilization equipment during the meal, and the cycle interval stage when the user puts the tableware back into the sterilization equipment after finishing the meal and waits for the next meal cycle. For the same meal, the user can use the preset meal cycles updated the previous day each day. If the sterilization equipment is being used for the first time by the user, the preset meal cycles updated the previous day can be the system's automatic default preset meal cycle or the preset meal cycle that the user manually set before using the sterilization equipment, without any restrictions. When the current time is detected to be within the waiting phase of a preset dining cycle, this phase includes the user's meal preparation, dining, and tableware washing time. For example, if the current time is between T2 and T3, it indicates that the tableware has been disinfected and the user needs to remove the tableware for meal preparation or dining. In this case, the disinfection component in the disinfection equipment can be controlled to remain stationary and not perform disinfection, while the temperature control component can be controlled to perform a heat preservation action to keep the tableware at a comfortable human temperature. In this embodiment, to ensure that the user experiences a comfortable temperature when using the tableware, the temperature control component can be controlled to maintain the tableware temperature at a comfortable human temperature, such as 38℃-45℃, thereby improving the user's dining experience. Furthermore, it can be understood that since each preparation phase in this embodiment of the invention includes the user's dining process, a dining time point can be set within it as a representative of the entire preparation phase, reflecting the user's dining time.

[0086] For example, refer to Figure 3 Users set the number of meals per day, which is the preset meal cycle. This cycle is distinguished by letters such as A, B, C, and D. For example, if three meals are set for a day, then the three meals are represented by the letters A, B, and C.

[0087] in, Figure 3 The preset time points are as follows:

[0088] Ts: represents the user's meal time point, XTs represents the X meal time point, X represents a set meal cycle, X = A / B / C / ..., such as three meals a day, then ATs, BTs, CTs represent the three meal time points;

[0089] Tx: The time for one cycle of the disinfection mode; the recommended time is 60 minutes.

[0090] T2: The point of deviation from the meal time, which represents the point of deviation from the meal time Ts;

[0091] T3: The lower deviation time point of the meal time. This point represents the lower deviation time point of the meal time Ts. Since users generally do not eat exactly at the Ts time point, T2 and T3 are set to add range judgment for the user's usage time. It is recommended that T2 be 30 minutes before Ts and T3 be 30 minutes after Ts.

[0092] T1: Pre-meal disinfection start time. This point represents the ideal state, i.e., the recommended pre-meal disinfection start time under the premise that the user does not interfere with the disinfection mode and the disinfection mode has ended. T1 is a period of time earlier than T2. ​​This period is one disinfection cycle Tx plus the time for the cavity to cool to 38℃~45℃ after disinfection. The cooling time of this automatic disinfection equipment is 30 minutes, which means that T1 is 90 minutes earlier than T2. ​​The period from T1 to T3 represents a preset meal cycle.

[0093] Based on the above time points, the time period T1 to T2 is called the tableware preparation stage; the time period T2 to T3 is called the tableware waiting stage; the time period T3 to NT1 is called the cycle interval stage; the time period T1 to T3 is called the meal cycle; and the time period XT1 to XT3 represents the X meal cycle time period, where X represents a set meal cycle, i.e., X = A / B / C / ... If three meals are set for a day, then the three meals are represented by the three letters A, B, and C.

[0094] Tn: represents the time points in the current tableware usage cycle, where n = 1 / 2 / 3;

[0095] LTn; represents the time points of the previous tableware usage cycle, where n = 1 / 2 / 3;

[0096] NTn; represents the time points of the next tableware usage cycle, where n = 1 / 2 / 3;

[0097] XTn: Represents the time points of a certain tableware usage cycle, where X represents a set dining usage cycle, i.e. X = A / B / C / ...;

[0098] Tw: This indicates the time period during which the door will remain closed after the door control detects that the door is closed. If the time exceeds this period, it will be assumed that the user will not take the tableware again in the future. The recommended time is 10 minutes.

[0099] For example, after a user sets up a smart wearable device to connect to the network, the system will generate default meal times based on the user's location. Due to time differences in various regions, the system sets meal times for most users in several major cities. Taking Beijing time as an example, the system will generate the meal times for most families: ATs (7:30) corresponds to breakfast, BTs (11:30) corresponds to lunch, and CTs (18:00) corresponds to dinner; and generate the following preset times:

[0100] AT1(5:30)AT2(7:00)ATs(7:30)AT3(8:00)BT1(9:30)BT2(11:00)BTs(11:30)BT3(12:00)CT1(16:00)CT2(17:30)CTs(18:00)CT3(18:30).

[0101] For example, taking lunch as an example, the time period for the preparation stage of each preset meal cycle updated the previous day is BT2 (11:00)-BT3 (12:00). If the real time at this time is 11:30, it means that the user needs to use tableware to prepare and eat the meal. In this case, the sterilization component is controlled not to work, and the temperature control component is controlled to perform the heat preservation program to avoid the ultraviolet lamp irradiation from harming the user. In addition, the tableware is kept at a comfortable temperature every time the user opens the sterilization equipment to take out the tableware, thus improving the user experience.

[0102] S120: Use the network module to acquire and record the changes in blood glucose concentration of users monitored by smart wearable devices every day.

[0103] The smart wearable device can be a smart bracelet, smartwatch, or similar device with blood glucose monitoring capabilities, allowing the wearer to track changes in blood glucose levels while wearing the device. This step essentially involves connecting to the internet or local area network via a network module to read data from other smart wearable devices also connected to the internet or local area network, monitoring the user's blood glucose levels.

[0104] S130. Based on the user's blood glucose concentration changes, determine the actual meal time points during the waiting phase of each preset meal cycle formed after the user's use on the same day.

[0105] Figure 4 The blood glucose concentration change curve of a human body within a day is provided as an embodiment of the present invention, such as... Figure 4As shown, under normal circumstances, the fasting blood glucose level of a human body should range from 3.9 to 6.1 mmol / L. It reaches its highest value approximately 30 to 60 minutes after the start of eating, generally between 6.7 and 11.1 mmol / L, and returns to the normal range about 2 hours after the start of eating. Due to the body's blood glucose regulation mechanism, blood glucose levels fluctuate. Based on these blood glucose changes, the system can read the changes in the user's blood glucose concentration monitored by the smart wearable device via a network module. Then, based on these changes, the system can analyze and obtain the meal time points that represent the user's meal stage. In other words, this step essentially determines the user's actual meal time for the day by analyzing changes in the user's blood glucose concentration. Therefore, it is possible to determine the actual meal time points during the waiting phase of each preset meal cycle formed after the user uses the disinfection equipment that day.

[0106] Understandably, this step of determining the actual mealtime during the waiting period for using the disinfection equipment is mainly to determine the user's actual dining habits, so that the waiting period in each preset meal cycle updated the previous day can be automatically updated based on the user's actual dining habits.

[0107] S140. When the actual meal time and the initial meal time in the waiting phase of the preset meal cycle updated the previous day are within a preset difference range, calculate the target meal time in the waiting phase of each preset meal cycle based on the actual meal time and the initial meal time within the preset difference range.

[0108] Specifically, when the actual meal time and the initial meal time in the waiting phase of the preset meal cycle updated the previous day are within a preset difference range, it indicates that the two meal times are relatively similar, and also reflects that the user eats within their habitual time fluctuation range. For example, taking lunch as an example, if the actual meal time As' in the waiting phase is 12:30, and the initial meal time As in the waiting phase of the preset meal cycle updated the previous day is 12:00, then the difference between the two time points is 30 minutes. The preset difference range can be set to 120 minutes. In this case, 30 minutes is less than the preset difference range, indicating that the two meal times are relatively similar.

[0109] When the actual meal time and the initial meal time in the preset meal cycle updated the previous day are within the preset difference range, in order to ensure that the waiting phase in the preset meal cycle every day is more in line with the user's dining habits, this step uses the actual meal time of the previous day and the actual meal time determined on the current day to determine the target meal time that is more in line with the user's dining habits, and uses this as a reference for updating the preset meal cycle on the current day.

[0110] S150. Based on each target dining time, determine the target time period for the waiting phase in each preset dining cycle, so as to update each preset dining cycle used on that day.

[0111] This step involves determining the waiting period for a user's meal based on a target meal time that better aligns with their dining habits, and then updating the entire preset meal cycle. In essence, the newly determined waiting period and the updated preset meal cycle more closely reflect the user's actual dining habits. This allows for daily updates to the preset meal cycle, preventing conflicts between the disinfection equipment's operation and the user's actual mealtime, and improving the automation and intelligence of the disinfection equipment.

[0112] The technical solution of this invention firstly involves controlling the disinfection equipment to perform corresponding preset actions each day according to the preset meal cycles updated the previous day, based on the real-time time within each preset meal cycle. Then, a network module is used to acquire and record the user's blood glucose concentration changes monitored by a smart wearable device each day. Next, based on the user's blood glucose concentration changes, the actual meal time point during the waiting phase of each preset meal cycle formed after the user's use that day is determined. Furthermore, when the actual meal time point and the initial meal time point during the waiting phase of the preset meal cycle updated the previous day are within a preset difference range, the target meal time point during the waiting phase of each preset meal cycle is calculated based on the actual meal time point and the initial meal time point within the preset difference range. Finally, when the actual meal time point is similar to the initial meal time point during the waiting phase of the preset meal cycle updated the previous day, the target meal time point during the waiting phase of each preset meal cycle is calculated based on the actual meal time point and the initial meal time point, thereby updating each preset meal cycle used that day. Using the above method, by connecting with smart wearable devices and based on the initial meal time of the user's meal cycle updated the previous day and the user's actual meal time on the current day, the target meal time that reflects the user's actual dining habits can be accurately determined. This allows for the determination of the waiting phase for the target meal time, enabling the updating of the preset meal cycle for the day. This facilitates the automatic disinfection process of the disinfection equipment, optimizes its operating time, and makes each preset meal cycle more compatible with the user's actual dining habits. It avoids conflicts between the disinfection equipment's operation and the user's actual meal time, improving the automation and intelligence of the disinfection equipment and enhancing the user experience.

[0113] In another specific embodiment, optionally, after determining the actual meal time points during the waiting phase of each preset meal cycle formed after the user's use on the same day based on the user's blood glucose concentration changes, S130 further includes:

[0114] S131. When the actual meal time and the initial meal time in the waiting phase of the preset meal cycle updated the previous day are not within the preset difference range, the initial iteration value is corrected using the preset second iteration correction value, so that the initial meal time is not within the preset difference range of the actual meal time of the day for a consecutive preset number of days, and after correction using the preset second iteration correction value, the initial iteration value is lower than the preset iteration value threshold; wherein, the meal time in the waiting phase of each preset meal cycle corresponds to a preset iteration value, and the iteration value corresponding to the initial meal time in the waiting phase of the preset meal cycle updated the previous day is the initial iteration value.

[0115] S132. When the initial iteration value is lower than the preset iteration value threshold, delete the initial meal time point and the preset meal cycle corresponding to the initial meal time point.

[0116] In step S131, the preset second iteration correction value can be determined based on a preset number of days and an initial iteration value. For example, the preset number of days can be 3 days, or 72 hours, and the initial iteration value can be 5, so the calculated preset second iteration correction value can be 5 / 3. Additionally, the preset iteration value threshold can be 0.

[0117] Specifically, if the initial dining time in the waiting phase of the preset dining cycle updated the previous day is not within a preset difference range (i.e., dissimilar) to the actual dining time in the waiting phase of each preset dining cycle formed by the user on the current day, and the initial iteration value is greater than the preset iteration value, then the initial dining time for a consecutive preset number of days can be retained. The initial iteration value is then corrected using a preset second iteration correction value. If the actual dining times recorded in the consecutive preset number of days are dissimilar to the initial dining time updated the previous day, the initial iteration value is further corrected using the preset second iteration correction value until the corrected initial iteration value is lower than the preset iteration value threshold. When the initial iteration value is lower than the preset iteration value threshold, it indicates that the user has not dined at that similar dining time for three consecutive days. Therefore, it is automatically considered that the initial dining time does not belong to the user's dining habits, and thus the initial dining time and the corresponding preset dining cycle are deleted. In addition, if the actual meal time determined by blood glucose concentration in a consecutive preset number of days is similar to the initial meal time updated the previous day, the above correction method will be stopped, and the target meal time will be calculated by using the initial meal time and the actual meal time and the preset meal cycle will be updated accordingly.

[0118] For example, taking breakfast as an example, let's take the initial meal time during the waiting period as ATs (6:30) and the actual meal time determined on the same day as ATs' (9:00). It can be seen that the difference between the initial meal time and the actual meal time exceeds 120 minutes, meaning they are not similar. Therefore, a preset second iteration correction value can be used to correct the initial iteration value. If the preset number of days is 3, the initial iteration value is 5, and the preset second iteration correction value is 5 / 3. That is, the corrected initial iteration value for the first day is 5 - 5 / 3 = 10 / 3. On the second day, the actual meal time (in example, ATs' (8:50)) is still not similar to the initial meal time (ATs (6:30)). Therefore, the preset second iteration correction value (5 / 3) is used again to correct the initial iteration value, resulting in a corrected initial iteration value of 10 / 3 - 5 / 3 = 5 / 3. If the actual meal time determined on the third day (e.g., ATs'(8:55)) is still not similar to the initial meal time (ATs(6:30)), then the initial iteration value is corrected using the preset second iteration correction value (5 / 3). The corrected initial iteration value is 0. At this time, the initial iteration value reaches the preset iteration value threshold, indicating that the initial meal time does not belong to the user's normal dining habits. At this time, the initial meal time ATs(6:30) can be identified as an invalid meal time. Then, the initial meal time is deleted, and the preset meal cycle corresponding to the initial meal time is also deleted, so as to realize the automation and intelligence of the disinfection equipment.

[0119] Furthermore, based on the above embodiments, before controlling the disinfection equipment to perform corresponding preset actions according to the stage of each preset meal cycle updated the previous day in S110, the following steps can be added:

[0120] S101. Use the network module to obtain and record the location and real-time time of the user monitored through the smart wearable device;

[0121] S102. Determine the initial preset dining cycle based on the user's location and real-time time;

[0122] Therefore, in the above embodiment S110, each day according to the preset meal cycles updated the previous day, the disinfection equipment is controlled to perform corresponding preset actions based on the stage of the real-time time within each preset meal cycle. Specifically, this may include:

[0123] S111. On the first day, according to the initial preset meal cycle, the disinfection equipment is controlled to perform the corresponding preset actions based on the real-time time at each initial preset meal cycle stage.

[0124] Steps S101 and S102 above essentially supplement the process of determining the meal cycle when the disinfection device performs the disinfection procedure according to the meal cycle on the first day. Similarly, the smart wearable device can not only monitor changes in the user's blood glucose concentration but also perform location and timing. Therefore, the disinfection device can obtain location and timing information through the network module via the networked smart wearable device to determine the user's location and real-time time. It can be understood that when the smart wearable device performs the disinfection process according to the preset meal cycle for the first time, it cannot automatically update the preset meal cycle based on the user's blood glucose. Therefore, it needs to provide a basic, original preset meal cycle in advance, i.e., an initial preset meal cycle, so that subsequent daily updates can be made based on this basic, original preset meal cycle. Based on the user's location and time, the user's local eating habits and meal times can be determined, and the initial preset meal cycle can be set accordingly. Therefore, step S102 is essentially the process of determining a preset meal cycle that conforms to the user's local eating habits and meal times based on the user's location and time. Step S111 is the process of performing the disinfection procedure on the first day based on the initial preset meal cycle determined in the above manner.

[0125] Figure 5 This is a flowchart of a second method for controlling a disinfection device based on blood glucose monitoring, provided by an embodiment of the present invention. This embodiment refines the above embodiment, and the preset meal cycle also includes a preparation stage. In terms of time, the waiting stage is located after the preparation stage. The preset actions corresponding to the preparation stage include controlling the disinfection component to continuously execute a disinfection procedure once.

[0126] For details, please refer to Figure 3 The preparation stage precedes the waiting stage in terms of time. For example, the preparation stage is T1-T2. This stage includes the time for the sterilization equipment to sterilize and cool the tableware. Under normal circumstances, the sterilization equipment will control the sterilization components to continuously perform a sterilization program on the tableware during the preparation stage. This sterilization program includes sterilization and cooling. The sterilization time Tx can be set to 60 minutes, and the cooling time can be 30 minutes to cool the tableware to 60℃~70℃. This prevents the tableware from being damaged by excessively high temperatures or from having poor drying effects due to excessively low temperatures, ensuring that the tableware can be used at a comfortable temperature during the waiting stage.

[0127] It should be noted that the reference Figure 1The disinfection equipment also includes a door control switch 60 and a cooling fan 70. The door control switch 60 is used to detect the open / closed status of the disinfection equipment. The cooling fan 70 is located at the top of the disinfection equipment and its main function is to accelerate the airflow inside the disinfection equipment cavity. When the heating lamp 30 is turned on, the cooling fan 70 can accelerate the heating inside the cavity; when the heating lamp 30 is turned off, the cooling fan 70 can accelerate the cooling inside the cavity. During the preparation stage, the tableware undergoes a disinfection program continuously, assuming that the user will not open the disinfection equipment during this stage. However, in actual use, the user may open the disinfection equipment at any time during the preparation stage to take out the tableware. When the door control switch 60 detects that the disinfection equipment is open, it immediately controls the ultraviolet lamp 20 and the heating lamp 30 in the disinfection component to stop working and can, depending on the situation, control the cooling fan 70 to start, so that the tableware cools down quickly to prevent harm to the user. At the same time, since the environment inside the disinfection equipment is contaminated when the door is open, the disinfection component stops the execution time of the disinfection program and resets the time. The disinfection program will restart when the door is closed.

[0128] Furthermore, in the above embodiment S150, after determining the target time period of the waiting phase in each preset dining cycle based on each target dining time point, and updating each preset dining cycle used on that day, the following steps were added:

[0129] Based on the target time period for the waiting phase in each preset dining cycle, the target time period for the preparation phase in each preset dining cycle is set ahead of the first preset time period, so as to update each preset dining cycle used on that day.

[0130] Furthermore, the above embodiment S130, which determines the actual meal time points during the waiting phase of each preset meal cycle formed after the user's use on the same day based on the user's blood glucose concentration changes, is further refined as follows:

[0131] The time point when a user's blood glucose concentration reaches a preset concentration threshold is determined as the actual meal time point during the waiting phase of each preset meal cycle formed after the user's use on that day.

[0132] Furthermore, in embodiment S150 above, the target time period for the waiting phase in each preset dining cycle is determined based on each target dining time point, so as to update each preset dining cycle used on that day, specifically as follows:

[0133] Based on the target dining time, the time point that is a first preset time in advance is determined as the start time, and the time point that is a second preset time delayed is determined as the end time.

[0134] A set of time periods from start time to end time is defined as the actual time period of the waiting phase during a preset dining cycle formed by the user on the same day.

[0135] For details not covered in this embodiment, please refer to the previous embodiment.

[0136] like Figure 5 As shown, the control method includes:

[0137] S210. Each day, according to the preset meal cycles updated the previous day, the disinfection equipment is controlled to perform the corresponding preset actions based on the real-time time at each preset meal cycle stage.

[0138] S220: Utilizes a network module to acquire and record daily changes in blood glucose concentration monitored by a smart wearable device.

[0139] S230. The time point when the user's blood glucose concentration reaches the preset concentration threshold is determined as the actual meal time point during the waiting phase of each preset meal cycle formed after the user's use on the same day.

[0140] This step essentially involves determining the actual meal time during the waiting phase within a pre-defined meal cycle formed after the user's blood glucose concentration that day. The pre-defined concentration threshold, determined through pre-experimentation and simulation, is a specific concentration value that reflects the increase in blood glucose concentration after eating. In other words, this threshold distinguishes whether the user has eaten. When the user's blood glucose concentration exceeds this threshold, it indicates that the user is eating or has just eaten. Correspondingly, the moment when the user's blood glucose concentration exceeds the threshold is the moment when the user is eating or has just finished eating, falling within the entire user's meal time. Therefore, this time point can be used as a baseline time point for the user's meal that day, i.e., the actual meal time point.

[0141] S240. When the actual meal time and the initial meal time in the waiting phase of the preset meal cycle updated the previous day are within a preset difference range, calculate the target meal time in the waiting phase of each preset meal cycle based on the actual meal time and the initial meal time within the preset difference range.

[0142] S251. Based on each target dining time, the time point that is a first preset time in advance is determined as the start time, and the time point that is a second preset time delayed is determined as the end time.

[0143] S252. Determine a set of time periods from start time to end time as the actual time period of the waiting phase during a preset dining cycle formed by the user on the same day.

[0144] Steps S251 and S252 described above utilize a target dining time point recalculated on the same day, representing the user's dining habits, to further expand and determine the waiting period within the preset dining cycle in which the target dining time point falls. Specifically, since the target dining time point is a point in time during the user's actual dining process, the user's entire dining time can be defined by extending it forward and backward by a certain duration. Extending it forward by a certain duration means determining the initial moment as a time point a first preset time earlier than the target dining time point; extending it backward by a certain duration means determining the termination moment as a time point a second preset time later than the target dining time point. Of course, the duration of forward and backward extensions using this time point as a base time can be specifically determined through experiments, sampling surveys, etc., and this embodiment of the invention does not impose limitations. For example, the determined target dining time point can be used as the midpoint of the user's entire dining time, i.e., the waiting period for the disinfection equipment. Taking a 1-hour waiting period as an example, extending it forward and backward by half an hour each time determines the duration of the entire waiting period.

[0145] S260. Based on the target time period for the waiting stage in each preset dining cycle, the target time period for the preparation stage in each preset dining cycle is set to be the first preset time period in advance, so as to update each preset dining cycle used on that day.

[0146] Specifically, after calculating the target time period for the waiting phase in each preset dining cycle, it is also necessary to confirm the target time period for the preparation phase. Typically, the target time period for the preparation phase is determined by advancing the target time period for the waiting phase by a first preset duration. That is, T1 is the time period before T2 by the first preset duration. This first preset duration is one disinfection cycle Tx plus the cooling time required for the disinfection equipment to cool to 38℃~45℃ after disinfection. The cooling time is usually 30 minutes, and the default disinfection time for one disinfection cycle Tx is 60 minutes. Therefore, the first preset duration can be 90 minutes, meaning the target time period for the preparation phase is 90 minutes before the target time period for the waiting phase. These determined preset dining cycles are then set as the preset dining cycles for the current day, thus achieving automatic updates to the preset dining cycles updated the previous day.

[0147] The technical solution of this invention specifically determines the actual meal time point of the waiting phase in each preset meal cycle formed after the user's blood glucose concentration changes on the same day. It also specifies the target time period of the waiting phase in each preset meal cycle based on each target meal time point. This provides a more practical and feasible solution for updating the preset meal cycle on the same day based on the user's blood glucose concentration. It can accurately and effectively obtain preset meal cycles that better match the user's eating habits, thereby effectively avoiding conflicts between the disinfection equipment's operation and the user's actual meal time, further improving the automation and intelligence of the disinfection equipment, and enhancing the user experience.

[0148] Figure 6 This is a flowchart of the third disinfection equipment control method based on blood glucose monitoring provided by the embodiments of the present invention. In this embodiment, regarding the above embodiment S140, when the actual meal time and the initial meal time in the waiting stage of the preset meal cycle updated the previous day are within a preset difference range, the target meal time in the waiting stage of each preset meal cycle is calculated based on the actual meal time and the initial meal time within the preset difference range. This can be further refined as follows:

[0149] When the actual meal time and the initial meal time in the waiting phase of the preset meal cycle updated the previous day are within a preset difference range, calculate the similarity between the actual meal time and the initial meal time.

[0150] Based on the similarity between the actual dining time and the initial dining time, a corresponding preset first iteration correction value is determined; wherein, the preset first iteration correction value is positively correlated with the similarity.

[0151] Based on the initial iteration value, the actual iteration value is calculated according to the first iteration correction value. Among them, the meal time point of the waiting stage in each preset meal cycle corresponds to a preset iteration value. The iteration value corresponding to the initial meal time point of the waiting stage in the preset meal cycle updated the previous day is the initial iteration value, and the iteration value corresponding to the actual meal time point of the waiting stage in the preset meal cycle formed after the user uses it on the same day is the actual iteration value.

[0152] Based on the initial iteration value and the actual iteration value, calculate the weights of the corresponding initial dining time point and the actual dining time point relative to the target dining time point, respectively.

[0153] Based on the weights of the initial dining time and the actual dining time relative to the target dining time, the relative position of the target dining time with respect to the initial dining time and the actual dining time is determined in the time dimension, thus identifying the target dining time.

[0154] For details not covered in this embodiment, please refer to the previous embodiment.

[0155] refer to Figure 3 and Figure 6 As shown, the control method includes:

[0156] S310. Each day, according to the preset meal cycles updated the previous day, the disinfection equipment is controlled to perform corresponding preset actions based on the real-time time at each preset meal cycle stage.

[0157] S320: Uses a network module to acquire and record daily changes in blood glucose concentration monitored by a smart wearable device.

[0158] S330. The time point when the user's blood glucose concentration reaches the preset concentration threshold is determined as the actual meal time point during the waiting phase of each preset meal cycle formed after the user's use on the same day.

[0159] S341. When the actual meal time and the initial meal time in the waiting phase of the preset meal cycle updated the previous day are within a preset difference range, calculate the similarity between the actual meal time and the initial meal time.

[0160] This step can be further broken down into: calculating the absolute value of the difference between the actual meal time and the initial meal time, which is used as the similarity between the actual meal time and the initial meal time.

[0161] The similarity score represents the degree of similarity between the user's actual meal time determined on the current day and the initial meal time updated the previous day. The absolute value of the difference between the two is used as the similarity score; the smaller the score, the more similar the two are, indicating stable user dining habits. This similarity calculation step aims to facilitate the subsequent determination of the target meal time to be updated on the same day. This step relies on the premise that the two scores are relatively similar, indicating that the user is dining with the same habits. Therefore, the meal time can be updated based on these habits, making the preset meal cycle more consistent with the user's dining habits. The method for determining similarity is to ensure that the difference between the two scores is within a set range. This range, as mentioned earlier, can be set to 120 minutes. If the difference between the two meal times exceeds 120 minutes, the similarity calculation for the target meal time is stopped; if the difference is less than 120 minutes, the similarity calculation continues, and the target meal time is then calculated.

[0162] S342. Determine the corresponding preset first iteration correction value based on the similarity between the actual dining time and the initial dining time.

[0163] In this embodiment, the preset first iteration correction value is negatively correlated with the similarity, and the preset first iteration correction value can be positive or negative. When the similarity is within the first preset similarity interval, the corresponding first iteration correction value is positive, and the first iteration correction value is negatively correlated with the similarity; when the similarity is within the second preset similarity interval, the corresponding first iteration correction value is negative, and the absolute value of the first iteration correction value is positively correlated with the similarity; the first preset similarity interval and the second preset similarity interval do not overlap, and the similarity of the first preset similarity interval is greater than the similarity of the second preset similarity interval.

[0164] For example, similarity can be represented by Ch. The smaller the similarity Ch, the more similar the actual meal time point and the initial meal time point are, and the higher the corresponding first iteration correction value P. The larger the similarity Ch, the less similar the two time points are, and the lower the corresponding first iteration correction value P. Let XPn represent the first iteration correction value P (X = A / B / C...) for the X time period determined on day n. The following are the recommended first iteration correction values ​​P for each similarity level: 120min > Ch ≥ 100min, P = -1; 100min > Ch ≥ 80min, P = -0.5; 80min > Ch ≥ 40min, P = 0; 40min > Ch ≥ 20min, P = 0.5; Ch < 20min, P = 1. The first preset similarity interval is (80, 0], and the corresponding first iteration correction value P is positive. The similarity Ch and the first iteration correction value P are negatively correlated, that is, the smaller the similarity, the larger the first iteration correction value P. The second preset similarity interval is (120, 80], and the corresponding first iteration correction value P is negative. The absolute value of the similarity Ch and the first iteration correction value P are positively correlated, that is, the smaller the similarity, the smaller the absolute value of the first iteration correction value P.

[0165] Specifically, based on the similarity Ch between the actual meal time and the initial meal time, the corresponding preset first iteration correction value P can be determined. For example, taking lunch as an example, the actual meal time As' is 12:30, and the initial meal time As in the preset meal cycle updated the previous day using the waiting phase is 12:00. The absolute value of the difference between the two time points is 30 minutes. According to the first iteration correction value P corresponding to each similarity level recommended above, the corresponding first iteration correction value AP is 0.5.

[0166] S343. Based on the initial iteration value, calculate the actual iteration value according to the first iteration correction value.

[0167] The iteration value D represents the similarity between the actual dining time and the initial dining time. When the actual dining time is similar to the initial dining time, the initial dining time needs to be updated. Each update of the initial dining time increases or decreases the iteration value D. A larger iteration value D indicates that the dining time is closer to the user's usage habits. Each preset dining cycle has a corresponding preset iteration value for the dining time during the waiting phase. The iteration value corresponding to the initial dining time during the waiting phase of the preset dining cycle updated the previous day is the initial iteration value. The iteration value corresponding to the actual dining time during the waiting phase of the preset dining cycle formed after the user's use on that day is the actual iteration value. Additionally, XD can represent the initial iteration value of the initial dining time X (X = A / B / C...), XD' represents the updated actual iteration value of the initial dining time X; and XDn can represent the initial iteration value of the initial dining time X updated on the nth day (X = A / B / C...).

[0168] Specifically, based on the initial iteration value D, and according to the first iteration correction value P, the initial iteration value D and the first iteration correction value P are calculated to obtain the actual iteration value D'. The calculation method can include addition or multiplication, etc., and can be determined according to the actual situation; no limitation is made here. In this embodiment, since the system's initial setting value has no iteration process, the initial iteration value is the system default, and the default initial iteration value D can be 1. The value can be adjusted according to actual usage; no limitation is made here. After the system has performed an iteration process, the initial iteration value is updated to the actual iteration value obtained in the previous calculation.

[0169] For example, taking addition calculation as an example, the actual iteration value calculation formula is D'=D+P, where n≥1. When it is lunchtime, AP=0.5 and AD=1, then the corresponding actual iteration value AD'=AD+AP=1+0.5=1.5.

[0170] It is understandable that the iterative value has a preset upper limit and a preset lower limit. The preset upper limit can be 5, and the preset lower limit can be 0, i.e., 0 ≤ D ≤ 5. This means that when the actual iterative value reaches the preset upper limit of 5, it will not continue to increase, and when the actual iterative value reaches the preset lower limit of 0, it will not continue to decrease. When calculating the actual iterative value, if the initial iterative value reaches the preset upper limit and the first iteration correction value is positive, the actual iterative value obtained by addition will be greater than the preset upper limit of 5. To ensure the accuracy of the data updated at each time point, the actual iterative value is no longer increased but instead assigned the preset upper limit value. This assigned preset upper limit value is the actual iterative value. Similarly, if the initial iterative value reaches the preset lower limit and the first iteration correction value is negative, the actual iterative value obtained by addition will be less than the preset lower limit of 0. To ensure the accuracy of the data updated at each time point, the actual iterative value is no longer decreased but instead assigned the preset lower limit value. This preset lower limit value is the actual iterative value.

[0171] S344. Based on the initial iteration value and the actual iteration value, calculate the weights of the corresponding initial meal time point and the actual meal time point relative to the target meal time point.

[0172] This step can be broken down as follows: Calculate the weight Q of the initial dining time point relative to the target dining time point according to the formula Q = D / (D + D'); calculate the weight Q' of the initial dining time point relative to the target dining time point according to the formula Q' = D' / (D + D'); where D is the initial iteration value and D' is the actual iteration value.

[0173] Here, the weight Q is determined by comparing the iterative value D' of the actual meal time with the initial iterative value D of the initial meal time, to decide which meal time data should be closer to when updating the initial meal time. Let XQ represent the weight Q of the initial meal time (X = A / B / C...), and let XQn represent the weight Q of the initial meal time X updated on day n (X = A / B / C...).

[0174] Specifically, after determining the initial iteration value D and the actual iteration value D', the weight Q of the initial dining time point relative to the target dining time point can be calculated according to the formula Q = D / (D+D'), and the weight Q' of the actual dining time point relative to the target dining time point can be calculated according to the formula Q' = D' / (D+D').

[0175] For example, taking breakfast as an example, the initial iteration value AD = 1, the actual iteration value AD' = 1.5, according to the formula Q = D / (D+D'), we calculate Q = 1 / (1+1.5) = 2 / 5, and according to the formula Q' = D' / (D+D'), we calculate Q' = 1.5 / (1+1.5) = 3 / 5.

[0176] S345. Based on the weights of the initial dining time and the actual dining time relative to the target dining time, determine the relative position of the target dining time with respect to the initial dining time and the actual dining time in the time dimension, so as to determine the target dining time.

[0177] This step can be further broken down as follows: Calculate the target dining time point Ts” according to the following formula: Ts” / (Ts+Ts')=Q / (Q+Q'); where Ts is the initial dining time point and Ts' is the actual dining time point.

[0178] Specifically, after determining the weights Q and Q' of the initial dining time and the actual dining time relative to the target dining time, the target dining time is determined to be closer to the initial dining time or the actual dining time during the waiting period based on the magnitude of Q and Q', and the specific location of the target dining time is calculated according to the formula.

[0179] For example, taking lunch as an example, if the calculated weights Q = 2 / 5 and Q' = 3 / 5, it can be seen that Q < Q', indicating that the initial meal time is more important, and the updated target meal time Ts” needs to be closer to the actual meal time Ts'. According to the formula Ts” / (Ts+Ts') = Q / (Q+Q'), the target meal time Ts” can be calculated as [Q / (Q+Q')]*(Ts+Ts') = [(2 / 5) / (2 / 5+3 / 5)]*[Ts(12:00)+Ts'(12:30)] = 12:12. Therefore, the target meal time Ts” is 12:12.

[0180] S351. Based on each target dining time, the time point that is a first preset time in advance is determined as the start time, and the time point that is a second preset time delayed is determined as the end time.

[0181] S352. Determine a set of time periods from start time to end time as the actual time period of the waiting phase during a preset dining cycle formed by the user on the same day.

[0182] For example, taking the target meal time Ts” (12:12) for lunch calculation as an example, with the first preset time being 30 minutes and the second preset time being 30 minutes, the actual time period for the waiting stage of lunch can be obtained as 11:42 to 12:42.

[0183] The technical solution of this invention calculates the similarity between the actual dining time and the initial dining time when they are similar; determines a corresponding preset first iteration correction value based on the similarity; calculates an actual iteration value based on the first iteration correction value and the initial iteration value; calculates the weights of the corresponding actual dining time and the initial dining time relative to the target dining time based on the initial and actual iteration values; and determines the relative position of the target dining time with respect to the initial and actual dining time based on the weights of the actual and initial dining times relative to the target dining time. Through this method, the target dining time is accurately determined based on the user's actual dining habits, thereby enabling automatic updates of the dining time in the disinfection equipment. This makes the disinfection equipment's operation more adaptable to the user's actual dining habits, improving the automation and intelligence of the disinfection equipment and enhancing the user experience.

[0184] Figure 7 This is a flowchart of the fourth disinfection equipment control method based on blood glucose monitoring provided by the present invention. This embodiment refines the specific implementation of S140 of the above embodiment, where, when the actual meal time and the initial meal time in the waiting phase of the preset meal cycle updated the previous day are within a preset difference range, the method of calculating the target meal time in the waiting phase of each preset meal cycle based on the actual meal time and the initial meal time within the preset difference range is as follows:

[0185] When the actual meal time and the initial meal time of the waiting phase in the two preset meal cycles updated the previous day are within a preset difference range, the target meal time for the waiting phase in the two preset meal cycles is calculated based on the actual meal time and the initial meal time, which are within the preset difference range.

[0186] For details not covered in this embodiment, please refer to the above embodiments.

[0187] refer to Figure 3 and Figure 7 As shown, the control method includes:

[0188] S410. Each day, according to the preset meal cycles updated the previous day, the disinfection equipment is controlled to perform the corresponding preset actions based on the real-time time at each preset meal cycle stage.

[0189] S420: Uses a network module to acquire and record daily changes in blood glucose concentrations monitored by a smart wearable device.

[0190] S430: Based on the user's blood glucose concentration changes, determine the actual meal time points during the waiting phase of each preset meal cycle formed after the user's use on the same day.

[0191] S441. When the actual meal time and the initial meal time of the waiting phase in the two preset meal cycles updated the previous day are within a preset difference range, calculate the target meal time for the waiting phase in the two preset meal cycles based on the actual meal time and the initial meal time that are within the preset difference range.

[0192] Specifically, when the actual meal time and the initial meal time of the waiting phase in the two preset meal cycles updated the previous day fall within a preset difference range, it indicates that the actual meal time is quite similar to the meal time in the two preset meal cycles updated the previous day. In this case, the target meal time in the first preset meal cycle using the waiting phase can be calculated according to the previous embodiment. Simultaneously, the target meal time in the second preset meal cycle using the waiting phase can also be calculated. The two calculated target meal times are then used to update the two initial meal times used on that day.

[0193] For example, taking breakfast and lunch as examples, the initial meal time point of the waiting phase in the preset meal cycle of breakfast updated the previous day is ATs (9:00), and the initial meal time point of the waiting phase in the preset meal cycle of lunch is BTs (12:00). The actual meal time point determined according to blood glucose concentration on the same day is ATs' (10:30). Then the difference between the actual meal time point and the initial meal time points ATs (9:00) and BTs (12:00) of the previous day is 90 minutes, which is within the preset difference range of 120 minutes. It is possible that the user occasionally combines breakfast and lunch into one meal. Therefore, the target meal time points ATs" and BTs corresponding to ATs (9:00) and BTs (12:00) can be calculated separately. Referring to the calculation process of the previous embodiment, the target meal time point ATs" of breakfast that needs to be updated on the same day is (9:30), and the target meal time point BTs" of lunch on the same day is (11:30).

[0194] S442. When the target dining time of the waiting phase in the two preset dining cycles is within the preset difference range, the two preset dining cycles are merged into one preset dining cycle, and the target dining time of the waiting phase in the merged preset dining cycle is calculated based on the target dining time of the waiting phase in the two preset dining cycles.

[0195] Specifically, when the target dining time of the waiting phase in two preset dining cycles is also within the preset difference range, the two preset dining cycles can be calculated according to the calculation method of the previous embodiment, and the two preset dining cycles can be merged into one preset dining cycle to calculate the target dining time of the waiting phase in the merged preset dining cycle.

[0196] For example, taking breakfast and lunch as examples, the initial meal time point of the waiting phase in the preset meal cycle of breakfast updated the previous day is ATs (9:00), and the initial meal time point of the waiting phase in the preset meal cycle of lunch is BTs (11:00). The actual meal time point determined according to blood glucose concentration on the same day is ATs' (10:00). The difference between the actual meal time point and the initial meal time points ATs (9:00) and BTs (11:00) of the previous day is 60 minutes, which is within the preset difference range of 120 minutes. The target meal time points ATs" and BTs corresponding to ATs (9:00) and BTs (11:00) can be calculated respectively. Referring to the calculation process of the previous embodiment, the target meal time point ATs" of breakfast that needs to be updated on the same day is (9:30), and the target meal time point BTs" of lunch on the same day is (10:30). Furthermore, the difference between ATs (9:30) and BTs (10:30) is within the preset difference range of 120 minutes. This suggests that users frequently combine breakfast and lunch into one meal, causing the timing of updated breakfast and lunch to gradually converge. It also indicates that users are accustomed to combining breakfast and lunch rather than eating them separately. To align with user habits, these two preset meal cycles can be merged into one. Specifically, based on the calculation method in the previous embodiment, the target time period for the waiting phase in the merged preset meal cycle can be calculated as (9:50-11:20), and the calculated target meal time ATs is (10:00).

[0197] S450. Based on each target dining time, determine the target time period for the waiting phase in each preset dining cycle, so as to update each preset dining cycle used on that day.

[0198] The technical solution of this invention updates the preset dining cycles for the day by calculating the target dining time for the waiting phase in each of the two preset dining cycles when the actual dining time and the initial dining time of the waiting phase in the two preset dining cycles updated the previous day are within a preset difference range. When the target dining time of the waiting phase in the two preset dining cycles is within a preset difference range, the two preset dining cycles are merged into one preset dining cycle, and the target dining time of the waiting phase in the merged preset dining cycle is calculated based on the target dining time of the waiting phase in the two preset dining cycles. Using this method, the automatic updating of the preset dining cycles for the day is better achieved based on the user's actual dining habits, ensuring the automation and intelligence of the disinfection equipment and improving the user experience.

[0199] Figure 8 This is a schematic diagram of a disinfection equipment control device based on blood glucose monitoring, provided as an embodiment of the present invention. The disinfection equipment includes a disinfection component, a temperature control component, and a networking module. For details, please refer to the above embodiment. (Reference) Figure 8 As shown, the control device includes:

[0200] The control module 110 is used to control the disinfection equipment to perform corresponding preset actions according to the preset meal cycles updated the previous day and the stage in each preset meal cycle based on the real-time time. The preset meal cycle includes a waiting period, and the preset actions corresponding to the waiting period include controlling the disinfection component to stand still and controlling the temperature control component to perform a heat preservation program.

[0201] The recording module 120 is used to acquire and record the changes in blood glucose concentration of the user monitored by the smart wearable device every day using the network module;

[0202] The time point determination module 130 is used to determine the actual meal time point of the waiting stage in each preset meal cycle formed after the user's use on the same day, based on the changes in the user's blood glucose concentration.

[0203] The calculation module 140 is used to calculate the target dining time point in the waiting phase of each preset dining cycle when the actual dining time point and the initial dining time point in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range.

[0204] The update module 150 is used to determine the target time period of the waiting phase in each preset dining cycle based on each target dining time point, so as to update each preset dining cycle used on that day.

[0205] The disinfection equipment control device based on blood glucose monitoring provided in the embodiments of the present invention can execute the disinfection equipment control method based on blood glucose monitoring provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0206] In one embodiment, optionally, the preset dining cycle further includes a preparation stage; in terms of time, the waiting stage follows the preparation stage; the preset actions corresponding to the preparation stage include controlling the disinfection component to continuously perform a disinfection procedure once. Based on this, the update module 150, according to each target dining time point, determines the target time period of the waiting stage in each preset dining cycle, so that after updating each preset dining cycle used that day, it can also be used for:

[0207] Based on the target time period for the waiting phase in each preset dining cycle, the target time period for the preparation phase in each preset dining cycle is set ahead of the first preset time period, so as to update each preset dining cycle used on that day.

[0208] In one embodiment, optionally, the time point determination module 130 is specifically used for:

[0209] The time point when a user's blood glucose concentration reaches a preset concentration threshold is determined as the actual meal time point during the waiting phase of each preset meal cycle formed after the user's use on that day.

[0210] In one embodiment, optionally, the update module 150 is specifically used for:

[0211] Based on the target dining time, the time point that is a first preset time in advance is determined as the start time, and the time point that is a second preset time delayed is determined as the end time.

[0212] A set of time periods from start time to end time is defined as the actual time period of the waiting phase during a preset dining cycle formed by the user on the same day.

[0213] In one embodiment, optionally, before controlling the disinfection equipment to perform the corresponding preset actions each day according to the preset meal cycles updated the previous day and based on the stage of the real-time time in each preset meal cycle, the recording module 120 is further configured to: use the network module to obtain and record the location and real-time time of the user monitored by the smart wearable device.

[0214] The update module 150 is also used to: determine the initial preset dining cycle based on the user's location and real-time time;

[0215] The control module 110 is also used to: on the first day, according to the initial preset meal cycle, control the disinfection equipment to perform corresponding preset actions based on the real-time time at each initial preset meal cycle stage.

[0216] In one embodiment, the computing module 140 may optionally include:

[0217] The first calculation unit is used to calculate the similarity between the actual dining time and the initial dining time when the actual dining time and the initial dining time during the waiting period in the preset dining cycle updated the previous day are within a preset difference range.

[0218] The correction value determination unit is used to determine the corresponding preset first iteration correction value based on the similarity between the actual dining time and the initial dining time; wherein, the preset first iteration correction value is negatively correlated with the similarity.

[0219] The second calculation unit is used to calculate the actual iteration value based on the initial iteration value and the first iteration correction value. Among them, the meal time point of the waiting stage in each preset meal cycle corresponds to a preset iteration value. The iteration value corresponding to the initial meal time point of the waiting stage in the preset meal cycle updated the previous day is the initial iteration value, and the iteration value corresponding to the actual meal time point of the waiting stage in the preset meal cycle formed after the user uses it on the same day is the actual iteration value.

[0220] The third calculation unit is used to calculate the weights of the initial dining time point and the actual dining time point relative to the target dining time point based on the initial iteration value and the actual iteration value, respectively.

[0221] The target time point determination unit is used to determine the relative position of the target dining time point with respect to the initial dining time point and the actual dining time point in the time dimension, based on the weights of the initial dining time point and the actual dining time point relative to the target dining time point, so as to determine the target dining time point.

[0222] In one embodiment, optionally, the first computing unit is specifically used for:

[0223] Calculate the absolute value of the difference between the actual meal time and the initial meal time, and use it as the similarity between the actual meal time and the initial meal time.

[0224] In one embodiment, optionally, the preset first iteration correction value satisfies:

[0225] When the similarity is within the first preset similarity interval, the corresponding first iteration correction value is positive, and the first iteration correction value is negatively correlated with the similarity.

[0226] When the similarity is within the second preset similarity interval, the corresponding first iteration correction value is negative, and the absolute value of the first iteration correction value is positively correlated with the similarity.

[0227] The first preset similarity interval and the second preset similarity interval do not overlap, and the similarity of the first preset similarity interval is greater than the similarity of the second preset similarity interval.

[0228] In one embodiment, the iterative value may optionally have a preset upper limit value and a preset lower limit value;

[0229] Based on this, the second computing unit is specifically used for:

[0230] When the initial iteration value reaches the preset upper limit and the first iteration correction value is positive, the actual iteration value is assigned the preset upper limit.

[0231] When the initial iteration value reaches the preset lower limit and the first iteration correction value is negative, the actual iteration value is assigned the preset lower limit value.

[0232] In one embodiment, optionally, the third computing unit is specifically used for:

[0233] Calculate the weight Q of the initial dining time relative to the target dining time using the formula Q = D / (D + D').

[0234] Calculate the weight Q' of the actual dining time relative to the target dining time using the formula Q'=D' / (D+D');

[0235] Where D is the initial iteration value and D' is the actual iteration value.

[0236] In one embodiment, optionally, the target time point determination unit is specifically used for:

[0237] The target dining time point Ts” is calculated using the following formula: Ts” / (Ts+Ts')=Q / (Q+Q'); where Ts is the initial dining time point and Ts' is the actual dining time point.

[0238] In one embodiment, optionally, the calculation module 140 is specifically used for:

[0239] When the actual meal time and the initial meal time of the waiting phase in the two preset meal cycles updated the previous day are within a preset difference range, the target meal time for the waiting phase in the two preset meal cycles is calculated based on the actual meal time and the initial meal time, which are within the preset difference range.

[0240] In one embodiment, optionally, when the actual meal time and the initial meal time of the waiting phase in two preset meal cycles updated the previous day are within a preset difference range, after calculating the target meal time of the waiting phase in the two preset meal cycles based on the actual meal time and the initial meal time within the preset difference range, the calculation module 140 is further specifically used for:

[0241] When the target dining time of the waiting phase in the two preset dining cycles is within the preset difference range, the two preset dining cycles are merged into one preset dining cycle, and the target dining time of the waiting phase in the merged preset dining cycle is calculated based on the target dining time of the waiting phase in the two preset dining cycles.

[0242] In one embodiment, optionally, after determining the actual meal time points of the waiting phase in each preset meal cycle formed after the user's blood glucose concentration changes on the same day, the calculation module 140 is further configured to: when the actual meal time point is not within a preset difference range from the initial meal time point in the waiting phase of the preset meal cycle updated the previous day, use a preset second iteration correction value to correct the initial iteration value, so that the initial meal time point is not within a preset difference range from the actual meal time point of the day for a consecutive preset number of days, and after correction using the preset second iteration correction value, the initial iteration value is lower than a preset iteration value threshold; wherein, each meal time point in the waiting phase of each preset meal cycle corresponds to a preset iteration value, and the iteration value corresponding to the initial meal time point in the waiting phase of the preset meal cycle updated the previous day is the initial iteration value.

[0243] The update module 150 is also used to: delete the initial meal time point and the preset meal cycle corresponding to the initial meal time point when the initial iteration value is lower than the preset iteration value threshold.

[0244] In one embodiment, Figure 9 A structural block diagram of a disinfection device provided in an embodiment of the present invention is shown below. Figure 9 The diagram illustrates a structural schematic of a disinfection device 10 that can be used to implement embodiments of the present invention. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0245] like Figure 9As shown, the disinfection device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the disinfection device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0246] Multiple components in the disinfection device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, optical disk, etc.; and a communication unit 19, such as a network card, modem, wireless transceiver, etc. The communication unit 19 allows the disinfection device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0247] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a disinfection device control method based on blood glucose monitoring.

[0248] In some embodiments, the blood glucose monitoring-based disinfection device control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the disinfection device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the blood glucose monitoring-based disinfection device control method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the blood glucose monitoring-based disinfection device control method by any other suitable means (e.g., by means of firmware).

[0249] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0250] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0251] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0252] To provide user interaction, the systems and techniques described herein can be implemented on a disinfection device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the disinfection device. Other types of devices can also be used to provide user interaction; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0253] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0254] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0255] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0256] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A blood glucose monitoring-based disinfection device control method, characterized by, The disinfection equipment includes a disinfection component, a temperature control component, and a network module; The control method includes: Each day, according to the preset meal cycles updated the previous day, the disinfection equipment is controlled to perform corresponding preset actions based on the real-time time in each preset meal cycle. The preset meal cycle includes a waiting period, and the preset actions corresponding to the waiting period include controlling the disinfection component to stand still and controlling the temperature control component to perform a heat preservation program. The network module is used to acquire and record daily changes in the user's blood glucose concentration monitored by the smart wearable device. Based on the user's blood glucose concentration changes, determine the actual meal time point of the waiting phase in each of the preset meal cycles formed after the user's use on the same day; When the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the target dining time in the waiting phase of each preset dining cycle is calculated based on the actual dining time and the initial dining time, which are within the preset difference range. Based on the target dining time points, determine the target time period of the waiting phase in each preset dining cycle, so as to update the preset dining cycles used on that day.

2. The method of claim 1, wherein, The preset dining cycle also includes a preparation phase; in terms of time, the waiting phase follows the preparation phase; the preset action corresponding to the preparation phase includes controlling the disinfection component to continuously perform a disinfection procedure once. Based on each target dining time point, the target time period of the waiting phase in each preset dining cycle is determined. After updating each preset dining cycle used on that day, the method further includes: Based on the target time period of the waiting phase in each of the preset dining cycles, the target time period of the preparation phase in each of the preset dining cycles is set ahead of time by a first preset time, so as to update each of the preset dining cycles used on that day.

3. The method of claim 1, wherein, Based on the user's blood glucose level changes, determine the actual meal time points during the waiting phase of each preset meal cycle formed after the user's use on the same day, including: The time point when the user's blood glucose concentration reaches the preset concentration threshold is determined as the actual meal time point of the waiting phase in each preset meal cycle formed after the user's use on that day.

4. The method of claim 1, wherein, Based on the target dining time points, determine the target time period of the waiting phase in each of the preset dining cycles, so as to update the preset dining cycles used on that day, including: Based on each of the target dining time points, the time point that is a first preset time in advance is determined as the start time, and the time point that is a second preset time delayed is determined as the end time. The time period from the start time to the end time is determined as the actual time period of the waiting phase in the preset dining cycle formed by the user on the same day.

5. The method of claim 1, wherein, Before controlling the disinfection equipment to perform corresponding preset actions each day, based on the preset meal cycles updated the previous day and the real-time time within each preset meal cycle, the following steps are also included: The network module is used to acquire and record the location and real-time time of the user monitored through the smart wearable device; The initial preset dining cycle is determined based on the user's location and real-time time; Each day, based on the preset meal cycles updated the previous day, and according to the real-time stage within each preset meal cycle, the disinfection equipment is controlled to perform corresponding preset actions, including: On the first day, according to the initial preset dining cycle, the disinfection equipment is controlled to perform the corresponding preset actions based on the real-time stage within each initial preset dining cycle.

6. The method according to claim 1, characterized in that, When the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the target dining time in the waiting phase of each preset dining cycle is calculated based on the actual dining time and the initial dining time, which are within the preset difference range, including: When the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the similarity between the actual dining time and the initial dining time is calculated. Based on the similarity between the actual dining time and the initial dining time, a corresponding preset first iteration correction value is determined; wherein, the preset first iteration correction value is negatively correlated with the similarity. Based on the initial iteration value, the actual iteration value is calculated according to the first iteration correction value; wherein, the meal time point of the waiting stage in each of the preset meal cycles corresponds to a preset iteration value, the iteration value corresponding to the initial meal time point of the waiting stage in the preset meal cycle updated the previous day is the initial iteration value, and the iteration value corresponding to the actual meal time point of the waiting stage in the preset meal cycle formed after the user uses it on the same day is the actual iteration value. Based on the initial iteration value and the actual iteration value, calculate the weights of the corresponding initial dining time point and the actual dining time point relative to the target dining time point, respectively. Based on the weights of the initial dining time and the actual dining time relative to the target dining time, the relative position of the target dining time with respect to the initial dining time and the actual dining time in the time dimension is determined, thereby determining the target dining time.

7. The method according to claim 6, characterized in that, Calculating the similarity between the actual dining time and the initial dining time includes: Calculate the absolute value of the difference between the actual dining time and the initial dining time, and use it as the similarity between the actual dining time and the initial dining time.

8. The method according to claim 6, characterized in that, The preset first iteration correction value satisfies: When the similarity is within a first preset similarity interval, the corresponding first iteration correction value is positive, and the first iteration correction value is negatively correlated with the similarity. When the similarity is within the second preset similarity interval, the corresponding first iteration correction value is negative, and the absolute value of the first iteration correction value is positively correlated with the similarity. The first preset similarity interval and the second preset similarity interval do not overlap, and the similarity of the first preset similarity interval is greater than the similarity of the second preset similarity interval.

9. The method according to claim 7, characterized in that, The iterative value has a preset upper limit value and a preset lower limit value; Based on the initial iteration value and according to the first iteration correction value, the actual iteration value is calculated, including: When the initial iteration value reaches the preset upper limit value and the first iteration correction value is positive, the actual iteration value is assigned the preset upper limit value; When the initial iteration value reaches the preset lower limit and the first iteration correction value is negative, the actual iteration value is assigned the preset lower limit.

10. The method according to claim 6, characterized in that, Based on the initial iteration value and the actual iteration value, calculate the weights of the corresponding initial dining time point and the actual dining time point relative to the target dining time point, including: The weight Q of the initial dining time point relative to the target dining time point is calculated according to the formula Q = D / (D + D'). Calculate the weight Q' of the actual dining time point relative to the target dining time point according to the formula Q'=D' / (D+D'); Where D is the initial iteration value and D' is the actual iteration value.

11. The method according to claim 6, characterized in that, Based on the weights of the initial dining time and the actual dining time relative to the target dining time, the relative position of the target dining time with respect to the initial dining time and the actual dining time is determined in the time dimension, thereby determining the target dining time, including: The target dining time point Ts” is calculated according to the following formula: Ts” / (Ts+Ts')=Q / (Q+Q'); where Ts is the initial dining time point and Ts' is the actual dining time point.

12. The method according to claim 1, characterized in that, When the actual dining time and the initial dining time in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, the target dining time in the waiting phase of each preset dining cycle is calculated based on the actual dining time and the initial dining time, which are within the preset difference range, including: When the actual dining time and the initial dining time of the waiting phase in the two preset dining cycles updated the previous day are within a preset difference range, the target dining time of the waiting phase in the two preset dining cycles is calculated based on the actual dining time and the initial dining time, which are within the preset difference range.

13. The method according to claim 12, characterized in that, When the actual meal time and the initial meal time of the waiting phase in the two preset meal cycles updated the previous day are within a preset difference range, after calculating the target meal time of the waiting phase in the two preset meal cycles based on the actual meal time and the initial meal time that are within the preset difference range, the process further includes: When the target dining time of the waiting phase in the two preset dining cycles is within a preset difference range, the two preset dining cycles are merged into one preset dining cycle, and the target dining time of the waiting phase in the merged preset dining cycle is calculated based on the target dining time of the waiting phase in the two preset dining cycles.

14. The method according to claim 1, characterized in that, After determining the actual meal time points during the waiting phase of each preset meal cycle formed after the user's blood glucose concentration changes on that day, the method further includes: When the initial dining time in the waiting phase of the actual dining time period and the preset dining cycle updated the previous day are not within a preset difference range, the initial iteration value is corrected using a preset second iteration correction value. This ensures that the initial dining time is not within a preset difference range from the actual dining time of the current day for a consecutive preset number of days. After correction using the preset second iteration correction value, the initial iteration value is lower than a preset iteration value threshold. Each dining time in the waiting phase of the preset dining cycle corresponds to a preset iteration value, and the iteration value corresponding to the initial dining time in the waiting phase of the preset dining cycle updated the previous day is the initial iteration value. When the initial iteration value is lower than a preset iteration value threshold, the initial meal time point and the preset meal cycle corresponding to the initial meal time point are deleted.

15. A disinfection equipment control device based on blood glucose monitoring, characterized in that, The disinfection equipment includes a disinfection component, a temperature control component, and a network module; The control device includes: The control module is used to control the disinfection equipment to perform corresponding preset actions each day according to the preset meal cycles updated the previous day, based on the real-time time in each preset meal cycle stage; the preset meal cycle includes a waiting period, and the preset actions corresponding to the waiting period include controlling the disinfection component to stand still and controlling the temperature control component to perform a heat preservation program; A recording module is used to acquire and record daily changes in the user's blood glucose concentration monitored by the smart wearable device using the network module. The time point determination module is used to determine the actual meal time point of the waiting phase in each preset meal cycle formed after the user's use on the same day, based on the changes in the user's blood glucose concentration. The calculation module is used to calculate the target dining time point of the waiting phase in each preset dining cycle when the actual dining time point and the initial dining time point in the waiting phase of the preset dining cycle updated the previous day are within a preset difference range, based on the actual dining time point and the initial dining time point within the preset difference range. The update module is used to determine the target time period of the waiting phase in each of the preset dining cycles based on each of the target dining time points, so as to update each of the preset dining cycles used on that day.

16. A disinfection device, characterized in that, The disinfection equipment includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the disinfection device control method based on blood glucose monitoring as described in any one of claims 1-14.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the disinfection device control method based on blood glucose monitoring as described in any one of claims 1-14.

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