Push management method of nasal atomizer and related equipment

Abstract

The invention relates to a push management method and related equipment for a nasal atomizer, and the method comprises the following steps: carrying out the type analysis of a read consumable identifier, and obtaining a consumable analysis type and normal work information corresponding to the consumable analysis type; state monitoring is conducted on consumables corresponding to the consumable analysis type, and consumable state information is obtained; based on the consumable state information and the normal working information, whether the corresponding consumable works normally or not is judged, if yes, the use intensity of the target nasal atomizer is predicted based on the consumable state information, and a prediction result is obtained; and if the prediction result is that the use intensity exceeds a preset use intensity threshold value, taking the consumables exceeding the preset use intensity as target consumables, starting a sterilization module to sterilize the target consumables, and sending information to notify a target user through a preset notification mechanism. The technical problem that the treatment effect is poor due to the fact that a user often is difficult to accurately master the actual use condition and replacement time of consumables is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of nasal atomizers, and in particular to a push management method for a nasal atomizer and related equipment. Background Art

[0002] With the accelerated pace of modern life, the decline in air quality and the intensification of environmental pollution, the incidence of respiratory diseases has increased year by year, especially among children, a susceptible population. Children are more susceptible to various nasal diseases, such as rhinitis and allergic rhinitis, because their immune systems are not yet fully developed. In order to effectively treat these diseases, nasal atomization therapy is widely used as a non-invasive drug delivery method. It can directly deliver drugs to the lesion site, improve the treatment effect and reduce systemic side effects. However, in actual applications, how to ensure the safety and effectiveness of nasal atomizers has become an urgent problem to be solved.

[0003] There are some shortcomings in the use of existing nasal nebulizers, which are mainly manifested in the management of consumables. On the one hand, consumables such as atomizer nozzles, filters, etc. are key components for the normal operation of nasal nebulizers, and their performance directly affects the effect of treatment. However, most nasal nebulizers on the market currently lack an effective consumable management mechanism, and users often find it difficult to accurately grasp the actual usage and replacement time of consumables, which may not only lead to poor treatment effects, but also may cause the risk of secondary infection due to contamination of consumables. On the other hand, for families whose children use nasal nebulizers, parents need to regularly monitor their children's usage to ensure the safety and hygiene of the treatment process, but traditional methods often rely on manual observation and memory, which is inefficient and prone to errors.

[0004] In order to solve the above problems, this study proposed a push management method for nasal nebulizers, which uses built-in radio frequency communication module technology to achieve intelligent management of consumables. By automatically reading the consumables identification and parsing its type, combined with the timestamp algorithm to monitor the status of the consumables, it is possible to detect abnormal working of the consumables in time and take corresponding measures, such as starting the UV sterilization function to prevent bacterial growth caused by excessive use. At the same time, this method can also automatically generate detailed consumables usage records to help parents better understand and manage their children's treatment process, thereby improving the safety and convenience of nasal nebulization treatment. Summary of the invention

[0005] The main purpose of the present invention is to provide a push management method and related equipment for a nasal nebulizer, which solves the technical problem that users often find it difficult to accurately grasp the actual usage and replacement time of consumables, resulting in poor treatment effects.

[0006] To achieve the above object, the present invention provides a push management method for a nasal atomizer, wherein a radio frequency communication module is provided in the nasal atomizer, comprising the following steps: The radio frequency communication module is used to read the identification of various consumables of the target nasal atomizer to obtain the read consumable identification; Performing type analysis on the read consumable identification to obtain the consumable analysis type and normal working information corresponding to the consumable analysis type; The consumables corresponding to the consumables analysis type are monitored by a preset timestamp algorithm to obtain consumables status information; Based on the consumable status information and the normal working information, determining whether the corresponding consumable is working normally, and if so, predicting the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result; If the predicted result is that the usage intensity exceeds the preset usage intensity threshold, the consumables that exceed the preset usage intensity are taken as target consumables, and the sterilization module is started to sterilize the target consumables, and information is sent to notify the target user through a preset notification mechanism.

[0007] Furthermore, the radio frequency communication module is provided with a high-frequency radio frequency transmitter and a signal demodulation module, and the radio frequency communication module is used to read the identification of various consumables of the target nasal atomizer to obtain the read consumable identification, including: The radio frequency identification tags on the various consumables in the target nasal atomizer are radio-frequency excited by the high-frequency radio frequency transmitter in the radio frequency communication module to obtain an activation radio frequency tag signal, wherein each consumable corresponds to one activation radio frequency tag signal; The signal demodulation module receives the activated radio frequency tag signal, and performs signal demodulation processing on the activated radio frequency tag signal to obtain an original identification data code stream; wherein the original identification data code stream is a series of digital code elements arranged according to a specific coding rule; Analyze whether the original identification data code stream contains abnormal difference information by using a preset Reed-Solomon error correction code algorithm, and if so, determine the abnormal position in the original identification data code stream containing the abnormal difference information; Based on the abnormal position, error correction is performed on the original identification data code stream with abnormal differences to obtain corrected identification data; The correction identification data is structurally parsed to obtain identification structure information, and the identification structure information is used as the reading consumable identification; wherein the identification structure information is the meaning and arrangement order of each field in the identification data.

[0008] Furthermore, the reading of the consumable identification is subjected to type parsing to obtain the consumable parsing type and normal working information corresponding to the consumable parsing type, including: Receive target user requirements, and extract corresponding information from the read consumable identification based on the target user requirements to obtain corresponding consumable identification data; wherein the consumable identification data includes production batch identification data and model identification data of the consumable; Parsing the information of each of the consumable identification data to obtain a consumable identification element; Performing a hash operation on the consumable identification element to obtain an identification hash value; Mapping the identification hash value to a preset identification classification index table to obtain an initial classification index; Based on the initial classification index, a search is performed in a pre-stored consumable type database to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type.

[0009] Furthermore, the consumables corresponding to the consumables analysis type are monitored by a preset timestamp algorithm to obtain consumables status information, including: Through a preset timestamp algorithm, the consumables corresponding to the consumables analysis type are monitored and time stamps are added to obtain a timestamp matrix; wherein the timestamp matrix includes rows, columns and elements, the rows represent the consumables analysis type, the columns represent the timestamps, and the elements represent the working parameters of the consumables under the timestamps; The timestamp matrix is ​​symbolized by a symbolic dynamics algorithm to obtain a symbol sequence; wherein the symbol sequence includes a symbolized state representation, and the symbolized state representation is a combination of consumable states within a specific time period for each symbol; Inputting the symbol sequence into a preset forward-backward module of a hidden Markov model to perform state probability calculation to obtain state probability vectors corresponding to each type of consumables; The state probability vector is analyzed to obtain consumable state information; wherein the consumable state information includes the working state, working mode and abnormal situation of the consumable.

[0010] Furthermore, the prediction of the usage of the target nasal atomizer based on the consumable status information to obtain a prediction result includes: Performing vector quantization on the consumables status information to obtain a consumables status vector; Performing entropy coding on the consumable state vector to obtain entropy coded consumable information; Performing prediction analysis on the entropy coded consumable information by a linear prediction analysis method to obtain prediction residual data; Performing Kalman filtering on the prediction residual data to obtain filtered residual information; Performing fractal dimension calculation on the residual information after filtering to obtain fractal dimension features; The usage of the target nasal atomizer is predicted based on the fractal dimension feature to obtain a prediction result.

[0011] Further, the starting sterilization module to sterilize the target consumables includes: Partitioning and locating the target consumables to obtain corresponding consumable positions; Performing a topological structure analysis on the target consumable based on the position of the consumable to obtain topological structure information; wherein the topological structure information refers to the spatial relationship and connection mode between the consumable and surrounding components; By using a preset ray tracing algorithm, the irradiation angle of the sterilization module is optimized and adjusted based on the topological structure information to obtain an adjusted angle and a sterilization module corresponding to the adjusted angle; Acquire the physical characteristic parameters of the target consumables; wherein the physical characteristic parameters include material and area; Pre-allocating power to the sterilization module corresponding to the adjusted angle based on the physical characteristic parameter and the position of the consumables to obtain allocated power; Based on the allocated power, a sterilization module is started to sterilize the consumables that exceed a preset usage intensity.

[0012] Further, performing topological structure analysis on the target consumable based on the consumable position to obtain topological structure information includes: Using a spatial geometry algorithm, based on the position of the consumables, a spatial layout of the consumables inside the atomizer is modeled to obtain a consumables spatial model; The consumable space model is hierarchically divided to obtain a consumable topology hierarchy diagram; wherein the consumable topology hierarchy diagram is used to display the hierarchy and priority of consumables inside the atomizer; Perform consumable mapping on the consumable topology hierarchy graph based on the target consumable, and determine the consumable node corresponding to the target consumable in the consumable space model; Performing connection analysis on the consumable nodes to obtain a consumable connection graph; wherein the consumable connection graph is used to display the direct connection relationship between the mapped consumable node and surrounding consumable nodes; Using an adjacency matrix algorithm, based on the consumable connection graph, the distance and connectivity between each of the mapped consumables and surrounding consumables are calculated to obtain a consumable node distance matrix; wherein the consumable node distance matrix is ​​used to quantify the closeness of the spatial relationship between consumables; Determine the core path based on the consumable node distance matrix to obtain the core topological path; The core topology path is annotated with topology structure information to obtain topology structure information.

[0013] The present invention also provides a push management device for a nasal atomizer, wherein a radio frequency communication module is provided in the nasal atomizer, comprising: A reading module, used to read the identification of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identification; A parsing module, used to perform type parsing on the read consumable identification to obtain the parsed consumable type and normal working information corresponding to the parsed consumable type; A monitoring module, used to monitor the status of the consumables corresponding to the consumable analysis type through a preset timestamp algorithm to obtain consumable status information; A judgment module, used for judging whether the corresponding consumable is working normally based on the consumable status information and the normal working information, and if so, predicting the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result; The sterilization module is used to, if the predicted result is that the usage intensity exceeds a preset usage intensity threshold, take the consumables that exceed the preset usage intensity as target consumables, start the sterilization module to sterilize the target consumables, and send information to notify the target user through a preset notification mechanism.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0015] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0016] The push management method for a nasal atomizer provided by the present invention comprises the following steps: reading the identification of various consumables of a target nasal atomizer through the radio frequency communication module to obtain the read consumable identification; performing type parsing on the read consumable identification to obtain the consumable parsing type and the normal working information corresponding to the consumable parsing type; performing status monitoring on the consumables corresponding to the consumable parsing type through a preset timestamp algorithm to obtain consumable status information; judging whether the corresponding consumables are working normally based on the consumable status information and the normal working information, and if so, predicting the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result; if the prediction result is that the usage intensity exceeds a preset usage intensity threshold, the consumables exceeding the preset usage intensity are used as target consumables, and a sterilization module is started to sterilize the target consumables, and information is sent to notify the target user through a preset notification mechanism. Through the above technical means, the technical problem that users often find it difficult to accurately grasp the actual usage and replacement time of consumables, resulting in poor treatment effects, is solved, and a detailed consumable usage record is formed by extracting features of the consumable status information, including data such as total usage time, atomization duration, and atomization frequency. These records not only provide users with a convenient tool for consumables management, but also provide a scientific basis for doctors to evaluate treatment effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the steps of a push management method of a nasal atomizer in one embodiment of the present invention; Figure 2 It is a structural block diagram of a push management device for a nasal atomizer in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] like Figure 1 As shown, Figure 1 It is a schematic diagram of the steps of a method for managing the push of a nasal atomizer in one embodiment of the present invention; In one embodiment of the present invention, a push management method for a nasal atomizer is provided, wherein a radio frequency communication module is provided in the nasal atomizer, and the method comprises the following steps: Step S1, reading the identification of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identification.

[0021] Specifically, the radio frequency communication module is used to read the identification of various consumables of the target nasal nebulizer to obtain the reading of the consumable identification. This process is the basic link of the entire push management method. Specifically, the radio frequency communication module is an intelligent device integrated inside the nasal nebulizer, which can interact with specific identification on the consumables. These identifications may be in the form of barcodes, QR codes, or RFID tags. When the consumables are installed in the nasal nebulizer, the radio frequency communication module will be automatically activated, and quickly scan and read the identification information on the consumables through short-range wireless communication technology or physical contact. For example, in a family environment, if a parent prepares a nebulization treatment for a child with rhinitis, the new nebulizer nozzle must first be installed in the device. At this time, the radio frequency communication module located inside the nasal nebulizer will immediately identify and read the unique identifier on the nebulizer nozzle. This identifier contains important information such as the production batch, expiration date, and applicable model of the consumables. In this way, the system can not only confirm whether the consumables are suitable for the currently used nasal nebulizer model, but also preliminarily determine whether the consumables are within the validity period, thereby avoiding the risks caused by improper use or expired consumables, and laying a solid foundation for subsequent consumable type analysis and status monitoring. In addition, the radio frequency communication module can be NFC technology or RFID technology.

[0022] Step S2, performing type analysis on the read consumable identification to obtain the consumable analysis type and normal working information corresponding to the consumable analysis type.

[0023] Specifically, the type of the read consumable identification is parsed to obtain the consumable parsing type and the normal working information corresponding to the consumable parsing type. This is a key step after completing the reading of the consumable identification. In this process, the radio frequency communication module not only reads the identification information on the consumables, but also further analyzes this information to determine the specific type of consumables and their related normal working parameters. For example, when the radio frequency communication module reads the identification of a newly installed atomizer nozzle, it will then pass this identification information to the internal parsing module. The parsing module will search for the type of consumables that matches the identification according to the pre-stored data comparison table, such as atomizer nozzles suitable for adults or children, or special consumables for specific types of drugs. At the same time, the parsing module will also obtain the normal working information corresponding to the consumable type, such as the recommended maximum number of uses, the recommended cleaning cycle, the optimal atomization temperature range, etc. This information is crucial to ensure the efficient operation of the nasal nebulizer. Taking the family use scenario as an example, suppose a parent replaces a new children's nebulizer for a child with rhinitis. After the RF communication module reads and parses the consumable identification, the system will know that this is a consumable designed for children, with a gentler atomization mode and a shorter single-use time limit. In this way, the system can automatically adjust the operating parameters of the nasal nebulizer based on this normal working information to ensure that the child is safe and comfortable during treatment. It also makes it easier for parents to supervise and manage the use of consumables, avoiding problems such as poor treatment effects or equipment damage caused by improper operation.

[0024] Step S3, using a preset timestamp algorithm, monitoring the status of the consumables corresponding to the consumable analysis type to obtain consumable status information.

[0025] Specifically, through a preset timestamp algorithm, the status of the consumables corresponding to the consumable parsing type is monitored to obtain the consumable status information, which is one of the important steps to ensure the efficient and safe operation of the nasal nebulizer. After the RF communication module completes the reading and type parsing of the consumable identification, the system will use the built-in timestamp algorithm to continuously track and record the usage of the consumables. The role of the timestamp algorithm is to accurately mark each use of the consumables with a precise time mark, so that the key data such as the cumulative usage time and frequency of use of the consumables can be accurately calculated. For example, in a family environment, when a parent uses a nasal nebulizer for a child with rhinitis, each time the nebulization treatment is started, the RF communication module will record the start and end time points, and integrate these timestamp information with previous data for analysis. Over time, the system can generate a status report of the consumables based on these timestamp data, which will include information such as the total usage time of the consumables, the average duration of each use, and the usage interval. Through such status monitoring, the system can promptly detect whether the consumables have reached the replacement standards recommended by the manufacturer, or whether there are abnormally frequent uses, and remind parents to replace the consumables in time to avoid the effects of treatment being affected by aging or contamination of the consumables, or even causing health risks. In addition, the application of the timestamp algorithm also helps to establish a complete historical record of the use of consumables, providing data support for subsequent consumables management and services.

[0026] Step S4, judging whether the corresponding consumable is working normally based on the consumable status information and the normal working information, and if so, predicting the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result.

[0027] Specifically, based on the consumable status information and the normal working information, it is determined whether the corresponding consumable is working normally. If so, the usage intensity of the target nasal atomizer is predicted based on the consumable status information to obtain a prediction result. This process is to further ensure that the consumable is within the normal use range after the system completes the monitoring and analysis of the consumable status, and predict the future usage intensity, so as to take necessary management measures in advance. Specifically, the system will first use the preset timestamp algorithm and symbolic dynamics algorithm to continuously monitor the usage of consumables and generate detailed consumable status information. These status information include the working status, working mode and abnormal conditions of the consumables. The system will compare these status information with the pre-stored normal working information to determine whether the consumable is in a normal working state. Normal working information usually includes parameters such as the maximum number of consumable uses and the recommended cleaning cycle, which are set by the manufacturer according to the characteristics and usage requirements of the consumables. For example, in a family environment, suppose that the parents replace a new atomizer nozzle for a child with rhinitis. The system monitors the working status of the atomizer nozzle through the timestamp algorithm and the symbolic dynamics algorithm to be normal, the working mode is the normal mode, and no abnormal conditions are found. The system will compare these status information with the pre-stored normal working information to confirm that the number of times the atomizer is used and the cleaning cycle are within the normal range. If the system determines that the consumables are in normal working condition, it will then predict the usage intensity of the target nasal atomizer based on the consumable status information to obtain the prediction result. Usage intensity prediction refers to predicting the usage intensity of consumables in the future by analyzing the historical usage data of consumables so as to take necessary management measures in advance. The system will use machine learning algorithms, such as time series analysis or regression analysis, to model the historical usage data of consumables and predict future usage intensity. For example, the system will collect usage data of the atomizer in the past month, including information such as the duration, frequency and working mode of each use. Through time series analysis, the system can identify the periodicity and trend of the usage pattern and predict the usage intensity of the atomizer in the next week. Assuming that the system prediction results show that the frequency of use of the atomizer will increase and the usage time will be extended in the next week, the system will generate the corresponding prediction results and send information to notify parents through the preset notification mechanism. Through this series of steps, the system can not only monitor the use of consumables in real time to ensure that the consumables are always in normal working condition, but also predict the future usage intensity in advance to help parents better manage the use and maintenance of consumables. For example, parents can prepare new consumables in advance based on the system's prediction results to avoid affecting the child's treatment effect due to consumable problems and ensure the safety and effectiveness of the treatment process. At the same time, the system can also automatically adjust the operating parameters of the nasal nebulizer based on the prediction results to provide a more personalized treatment experience.

[0028] Step S5, if the predicted result is that the usage intensity exceeds the preset usage intensity threshold, the consumables that exceed the preset usage intensity are taken as target consumables, and the sterilization module is started to sterilize the target consumables, and information is sent to notify the target user through the preset notification mechanism.

[0029] Specifically, if the prediction result is that the usage intensity exceeds the preset usage intensity threshold, the consumables that exceed the preset usage intensity are taken as target consumables, and the sterilization module is started to sterilize the target consumables, and the information is sent to the target user through the preset notification mechanism. This process is a series of automated processing steps taken by the system to ensure the sanitary state and safety of the consumables after the system completes the prediction of the usage intensity of the consumables. Specifically, when the system predicts the usage intensity based on the consumable status information, and the result shows that the future usage intensity of the consumables will exceed the preset usage intensity threshold, the system will immediately mark the consumable as a target consumable. The preset usage intensity threshold is set based on factors such as the material properties, hygiene standards and usage frequency of the consumables. Exceeding this threshold means that the consumables may have a high risk of bacterial growth and require additional cleaning or sterilization. For example, in a home environment, suppose the system predicts through time series analysis that the frequency of use of the atomizer nozzle used by children will increase significantly in the next week, and the usage time will also be extended, resulting in the usage intensity exceeding the preset usage intensity threshold. The system will mark this atomizer nozzle as a target consumable and start a series of automated processing steps. First, the system will start the sterilization module to sterilize the target consumables. The sterilization module is a highly efficient disinfection device that emits ultraviolet light to irradiate the surface of the consumables to kill bacteria and viruses attached to them. The system will adjust the irradiation angle and power of the UV lamp according to the physical properties (such as material and area) and location information of the consumables to ensure that the ultraviolet light can evenly cover all parts of the consumables to achieve the best sterilization effect. For example, the system will adjust the angle of the UV lamp to 45 degrees, the power to 10 watts, and irradiate for 10 minutes. After the sterilization process is completed, the system will automatically turn off the UV lamp. Secondly, the system will send information to notify the target user through a preset notification mechanism. The preset notification mechanism can be a mobile phone APP push message, SMS or email, etc. These notification methods can promptly remind parents to pay attention to the use of consumables and the sterilization status. For example, the system will send a notification message to parents through a mobile phone APP: "The intensity of use of the atomizer used by your child will exceed the preset threshold in the next week. The system has automatically completed the UV sterilization process. Please pay attention to the use of consumables. If necessary, please replace new consumables in time." Through this series of steps, the system can not only automatically detect and predict the intensity of consumable use, but also start the sterilization module for sterilization when necessary to ensure that the consumables are always in a good sanitary state, thereby protecting the health and safety of users. For example, in a home environment, parents can use the notification information provided by the system to keep abreast of the use and sterilization status of consumables, prepare new consumables in advance, avoid affecting the child's treatment effect due to consumable problems, and ensure the safety and effectiveness of the treatment process. At the same time, the system can also automatically adjust the operating parameters of the nasal nebulizer according to the prediction results to provide a more personalized treatment experience. In addition, the sterilization module can be a UV sterilization module.

[0030] In a specific embodiment, the radio frequency communication module is provided with a high-frequency radio frequency transmitter and a signal demodulation module, and the radio frequency communication module is used to read the identification of various consumables of the target nasal atomizer to obtain the read consumable identification, including: The radio frequency identification tags on the various consumables in the target nasal atomizer are radio-frequency excited by the high-frequency radio frequency transmitter in the radio frequency communication module to obtain an activation radio frequency tag signal, wherein each consumable corresponds to one activation radio frequency tag signal; The signal demodulation module receives the activated radio frequency tag signal, and performs signal demodulation processing on the activated radio frequency tag signal to obtain an original identification data code stream; wherein the original identification data code stream is a series of digital code elements arranged according to a specific coding rule; Analyze whether the original identification data code stream contains abnormal difference information by using a preset Reed-Solomon error correction code algorithm, and if so, determine the abnormal position in the original identification data code stream containing the abnormal difference information; Based on the abnormal position, error correction is performed on the original identification data code stream with abnormal differences to obtain corrected identification data; The correction identification data is structurally parsed to obtain identification structure information, and the identification structure information is used as the reading consumable identification; wherein the identification structure information is the meaning and arrangement order of each field in the identification data.

[0031] Specifically, in the nasal atomizer, the RF communication module undertakes the core task of reading the consumables identification. When parents replace the atomizer mouthpiece for their children with rhinitis, the RF communication module will be automatically activated, and the high-frequency RF transmitter inside it will start working. The high-frequency RF transmitter will emit RF signals of a specific frequency, which can penetrate the nebulizer shell and reach the RFID tag installed on the consumables. After receiving the RF signal, the RFID tag will be activated and reflect back the RFID tag signal containing the consumables identification information. Each RFID tag on the consumable corresponds to unique identification information, so the reflected RFID tag signal is also unique. Next, the signal demodulation module in the RF communication module will receive these activated RFID tag signals and demodulate them. The demodulation process is to convert the RF signal into a digital signal, that is, the original identification data code stream. This original identification data code stream is actually composed of a series of digital code elements arranged according to specific coding rules. These code elements carry various information about the consumables, such as production date, batch number, model, etc. In order to ensure the accuracy of the data, the system will use the preset Reed-Solomon error correction code algorithm to analyze the original identification data code stream. Reed-Solomon error correction code is an efficient error detection and correction algorithm that can identify errors that may occur during data transmission and determine the specific location of the error. If the system finds abnormal difference information in the original identification data code stream during the analysis process, that is, some code elements do not match the expected value, then the system will locate these abnormal positions and perform error correction on the data at these positions to obtain the corrected identification data. Finally, the system will perform structural analysis on the corrected identification data, extract the meaning and arrangement order of each field, and form a complete identification structure information. The identification structure information contains all the key information of the consumables, such as the type of consumables, production date, expiration date, etc., which will be used in subsequent type analysis and status monitoring steps. For example, in a home use scenario, when the parent replaces a new child-specific atomizer nozzle, the RF communication module will read and parse the identification information of the atomizer nozzle through the above process, confirm that it is a child-specific consumable, and obtain information such as its recommended maximum number of uses and cleaning cycle. In this way, the system can automatically adjust the operating parameters of the nasal nebulizer based on this information, ensuring that the child is safe and comfortable during treatment. It also makes it easier for parents to supervise and manage the use of consumables to avoid problems such as poor treatment effects or equipment damage caused by improper operation. Through this series of meticulous steps, the nasal nebulizer can not only ensure the correct use of consumables, but also provide a more personalized and efficient treatment experience.

[0032] In a specific embodiment, the type parsing of the read consumable identification to obtain the consumable parsing type and the normal working information corresponding to the consumable parsing type includes: Receive target user requirements, and extract corresponding information from the read consumable identification based on the target user requirements to obtain corresponding consumable identification data; wherein the consumable identification data includes production batch identification data and model identification data of the consumable; Parsing the information of each of the consumable identification data to obtain a consumable identification element; Performing a hash operation on the consumable identification element to obtain an identification hash value; Mapping the identification hash value to a preset identification classification index table to obtain an initial classification index; Based on the initial classification index, a search is performed in a pre-stored consumable type database to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type.

[0033] Specifically, first, the system receives the target user's needs, and based on the received target user's needs, extracts the corresponding information from the read consumable identification to form consumable identification data. These consumable identification data include the production batch identification data and model identification data of the consumables. The production batch identification data can help the system trace the production batch of the consumables to ensure the quality and source of the consumables; while the model identification data is used to determine the specific model of the consumables, which is crucial for matching the correct consumable type. For example, in a family environment, parents replace a new atomizer nozzle for a child with rhinitis. After the radio frequency communication module reads the radio frequency identification tag information on the atomizer nozzle, the system extracts the production batch number and model identification data from this information. Assuming that the extracted production batch number identification data is "202305A" and the model identification data is "CHD-01", these two data are combined to form the consumable identification data. Next, the system will perform information analysis on these consumable identification data and decompose them into more fine-grained consumable identification elements. These consumable identification elements are the basic units that constitute the consumable identification data, and each element represents a specific attribute of the consumable. For example, the production batch identification data "202305A" can be parsed into the year "2023", the month "05" and the batch "A", and the model identification data "CHD-01" can be parsed into the product line code "CHD" and the serial number "01". The system then performs a hash operation on these consumable identification elements to generate a unique identification hash value. Hashing is the process of converting input data into a fixed-length output value, which is usually called a hash value. The characteristic of a hash value is that even a slight change in the input data will cause a significant change in the output value, so the hash value can be used to quickly compare the integrity of the data. In this example, the system combines the parsed consumable identification elements into a string, such as "202305ACHD01", and then performs a hash operation on the string to generate an identification hash value, such as "abc123def456". After the identification hash value is generated, the system maps the hash value to the preset identification classification index table to obtain the initial classification index. The identification classification index table is a pre-built database that contains the identification hash values ​​of all known consumables and their corresponding classification indexes. By comparing the generated identification hash value with the data in the index table, the system can quickly find the matching initial classification index. For example, suppose the identification hash value "abc123def456" corresponds to the classification index "001" in the index table. Finally, based on the obtained initial classification index, the system will search the pre-stored consumable type database to find the consumable parsing type that matches the classification index and its corresponding normal working information. The consumable type database stores detailed information on various consumables, including the name of the consumable, applicable models, maximum number of uses, recommended cleaning cycles, etc.In this example, the system will search for information corresponding to the classification index "001" in the consumable type database. Suppose the information found shows that the consumable is a nebulizer nozzle for children, with a maximum use of 100 times and a recommended cleaning cycle of once a week. Through this series of steps, the system can not only accurately identify the specific type of consumables, but also obtain the normal working parameters of this type of consumables, thereby providing reliable data support for subsequent status monitoring and usage management. For example, parents can use the information provided by the system to understand whether the nebulizer nozzle their child is using is suitable for the current nasal nebulizer model, as well as the remaining number of uses of the consumables and the time for the next cleaning, so as to better manage the use of consumables and ensure the safety and effectiveness of the treatment process.

[0034] In a specific embodiment, the status of the consumables corresponding to the consumables parsing type is monitored by a preset timestamp algorithm to obtain the consumables status information, including: Through a preset timestamp algorithm, the consumables corresponding to the consumables analysis type are monitored and time stamps are added to obtain a timestamp matrix; wherein the timestamp matrix includes rows, columns and elements, the rows represent the consumables analysis type, the columns represent the timestamps, and the elements represent the working parameters of the consumables under the timestamps; The timestamp matrix is ​​symbolized by a symbolic dynamics algorithm to obtain a symbol sequence; wherein the symbol sequence includes a symbolized state representation, and the symbolized state representation is a combination of consumable states within a specific time period for each symbol; Inputting the symbol sequence into a preset forward-backward module of a hidden Markov model to perform state probability calculation to obtain state probability vectors corresponding to each type of consumables; The state probability vector is analyzed to obtain consumable state information; wherein the consumable state information includes the working state, working mode and abnormal situation of the consumable.

[0035] Specifically, this process is a key step to further monitor and analyze the use of consumables in detail after completing the reading of consumable identification and type parsing. First, the system will use the preset timestamp algorithm to continuously monitor the use of consumables, and add a time stamp each time the consumables are used to generate a timestamp matrix. The timestamp matrix is ​​a multidimensional array, in which each row represents a consumable parsing type, each column represents a timestamp, and each element represents the specific working parameters of the consumables at the timestamp, such as atomization duration, atomization frequency, working temperature, etc. For example, in a home environment, suppose that the parents replace a new atomizer mouthpiece for a child with rhinitis. The system will record the start and end time of each atomization treatment and collect various working parameters during this period. The system will generate a timestamp matrix internally to record the time and corresponding parameters of each use. Assuming that the child starts a 10-minute nebulization treatment at 7 pm every day, the system will record the following information in the timestamp matrix: the consumable analysis type is "nebulizer nozzle for children", the timestamp is "2023-10-01 19:00:00", the nebulization time is 600 seconds, the nebulization frequency is 10 times / minute, and the working temperature is 37°C. Similarly, the records of the second day will be saved in the same format. Next, the system will symbolize the timestamp matrix through the symbolic dynamics algorithm to generate a symbol sequence. The symbolic dynamics algorithm is a method of converting continuous time series data into discrete symbols, which can simplify complex consumable state combinations into easy-to-handle symbols. Specifically, the system will map each working parameter interval in the timestamp matrix to a symbol, for example, the state between 500-600 seconds of nebulization is mapped to the symbol "A", the state between 8-10 times / minute is mapped to the symbol "B", and the state between 36-38°C of working temperature is mapped to the symbol "C". In this way, the combination of consumable states at each timestamp can be represented as a symbol sequence, such as "ABC", "ABC", etc. After generating the symbol sequence, the system will input these symbol sequences into the forward-backward module of the preset hidden Markov model (HMM) to calculate the state probability and obtain the state probability vectors corresponding to each type of consumable. Hidden Markov model is a statistical model that is often used to process sequence data, especially in fields such as speech recognition and bioinformatics. In this example, the forward-backward module of HMM will calculate the state probability vectors of various types of consumables in different time periods based on the symbol sequence. The state probability vector represents the possibility that the consumable is in a certain state in a certain time period. For example, the probability that the consumable is in a normal working state in a certain time period is 0.9, and the probability that it is in an abnormal state is 0.1. Finally, the system will perform information analysis on the obtained state probability vector to extract the state information of the consumable.This status information includes the working status of the consumables (such as normal working, abnormal working), working mode (such as regular mode, high-intensity mode) and abnormal conditions (such as overtemperature, abnormal frequency, etc.). For example, the system may parse the following information: - The consumables were in normal working condition from 2023-10-01 19:00:00 to 2023-10-01 19:10:00, the working mode was regular mode, and no abnormal conditions were found. - The consumables were also in normal working condition from 2023-10-02 19:00:00 to 2023-10-02 19:10:00, the working mode was regular mode, and no abnormal conditions were found. Through this series of steps, the system can not only monitor the use of consumables in real time, but also detect and warn of potential abnormal conditions in a timely manner, helping parents better manage their children's treatment process and ensure the safety and effectiveness of the treatment. For example, if the system detects that the operating temperature of the consumables is continuously higher than the normal range, it will immediately send a warning message through the preset notification mechanism to remind parents to check the equipment or replace the consumables, thereby avoiding poor treatment effects or health risks caused by equipment failure or consumable problems. In addition, the system can also automatically adjust the operating parameters of the nasal nebulizer based on this status information to provide a more personalized treatment experience. For example, if the system detects that the child's nebulization frequency is high within a certain period of time, it can automatically increase the nebulization time or adjust the nebulization mode to ensure the treatment effect. In this way, the system not only improves the safety and effectiveness of the treatment, but also reduces the burden of supervision on parents, allowing parents to more confidently perform nebulization treatment for their children.

[0036] In a specific embodiment, the prediction of the usage of the target nasal atomizer based on the consumable status information to obtain the prediction result includes: Performing vector quantization on the consumables status information to obtain a consumables status vector; Performing entropy coding on the consumable state vector to obtain entropy coded consumable information; Performing prediction analysis on the entropy coded consumable information by a linear prediction analysis method to obtain prediction residual data; Performing Kalman filtering on the prediction residual data to obtain filtered residual information; Performing fractal dimension calculation on the residual information after filtering to obtain fractal dimension features; The usage of the target nasal atomizer is predicted based on the fractal dimension feature to obtain a prediction result.

[0037] Specifically, this process is a key step to further predict the future use of consumables after completing the monitoring of the consumable status. First, the system will vector quantize the consumable status information to generate a consumable status vector. Vector quantization is a method of mapping continuous data values ​​into discrete vector representations. This method can simplify complex consumable status information into a set of easy-to-process vectors. For example, in a home environment, assume that the system has obtained the status information of consumables through a timestamp algorithm and a symbolic dynamics algorithm. This information includes the working status, working mode, and abnormal conditions of the consumables. The system will quantize this status information into a vector, such as [1, 0, 0], where 1 represents a normal working state, 0 represents a normal mode, and another 0 represents no abnormal conditions. Next, the system will entropy encode the generated consumable status vector to obtain entropy-encoded consumable information. Entropy coding is a data compression technology that reduces the storage space of data by removing redundant information. In this example, the system will use an entropy coding algorithm to compress the consumable status vector to generate entropy-encoded consumable information. For example, assuming that the consumable state vector is [1, 0, 0], the result after entropy coding may be "100". This coding method not only saves storage space, but also improves the efficiency of data processing. Then, the system will use the linear prediction analysis method to predict the entropy coded consumable information and obtain the prediction residual data. Linear prediction analysis is a commonly used time series analysis method. It predicts future data points by establishing a linear model and calculates the difference between the predicted value and the actual value, that is, the prediction residual. In this example, the system will establish a linear prediction model based on the historical data of the entropy coded consumable information to predict the consumable state information in a certain period of time in the future and calculate the residual between the predicted value and the actual value. For example, assuming that the system predicts that the state information of a future atomization treatment is "100", and the actual entropy coded consumable information is "101", then the prediction residual is "001". Next, the system will perform Kalman filtering on the prediction residual data to obtain the filtered residual information. Kalman filtering is a recursive filter used to estimate the state of the system and reduce the impact of noise by continuously updating the estimated value. In this example, the system uses a Kalman filter to process the prediction residual data, filter out the noise caused by measurement errors or external interference, and obtain more accurate filtered residual information. For example, assuming that the prediction residual is "001", the result after Kalman filtering may be "000.8", which means that the system has smoothed the prediction residual and reduced the impact of noise. Then, the system calculates the fractal dimension of the filtered residual information to obtain the fractal dimension feature. The fractal dimension is an indicator to measure the complexity and self-similarity of data. By calculating the fractal dimension, the internal structure and rules of the data can be revealed. In this example, the system uses the fractal dimension calculation method to analyze the filtered residual information and obtain a characteristic value that reflects the complexity of consumables usage.For example, assuming that the residual information after filtering is "000.8", the fractal dimension feature calculated by the system may be 1.2, which means that the use of consumables is relatively stable and there is no obvious abnormal fluctuation. Finally, the system predicts the use of the target nasal atomizer based on the fractal dimension feature and obtains the prediction result. The fractal dimension feature can be used to predict the use intensity and possible abnormalities of consumables in the future. For example, assuming that the fractal dimension feature is 1.2, the system will predict whether the use intensity of consumables in the next week will exceed the preset use intensity threshold based on the preset model and threshold. If the prediction result shows that the use intensity will exceed the threshold, the system will generate the corresponding prediction result and send information to notify the parents through the preset notification mechanism. For example, the system will send a notification message to the parents through the mobile phone APP: "The use intensity of the atomizer used by your child will exceed the preset threshold in the next week. It is recommended that you prepare new consumables in advance." Through this series of steps, the system can not only perform detailed feature extraction on the use of consumables, but also generate intuitive prediction results to help parents better manage their children's treatment process and ensure the safety and effectiveness of treatment. For example, parents can use the prediction results provided by the system to understand the usage of consumables and possible abnormalities in advance, and take timely measures, such as replacing new consumables or adjusting treatment plans, to avoid the treatment effect being affected by consumable problems. At the same time, the system can also automatically adjust the operating parameters of the nasal nebulizer based on these prediction results to provide a more personalized treatment experience. In this way, the system not only improves the safety and effectiveness of treatment, but also reduces the burden of supervision on parents, allowing parents to more confidently perform nebulization treatment for their children.

[0038] In a specific embodiment, the starting sterilization module to sterilize the target consumables includes: Partitioning and locating the target consumables to obtain corresponding consumable positions; Performing a topological structure analysis on the target consumable based on the position of the consumable to obtain topological structure information; wherein the topological structure information refers to the spatial relationship and connection mode between the consumable and surrounding components; By using a preset ray tracing algorithm, the irradiation angle of the sterilization module is optimized and adjusted based on the topological structure information to obtain an adjusted angle and a sterilization module corresponding to the adjusted angle; Acquire the physical characteristic parameters of the target consumables; wherein the physical characteristic parameters include material and area; Pre-allocating power to the sterilization module corresponding to the adjusted angle based on the physical characteristic parameter and the position of the consumables to obtain allocated power; Based on the allocated power, a sterilization module is started to sterilize the consumables that exceed a preset usage intensity.

[0039] Specifically, this process is a series of automated sterilization steps taken to ensure the hygienic state of the consumables and prevent bacterial growth after the system detects that the usage intensity of the consumables exceeds the preset threshold. First, the system will partition and locate the target consumables that exceed the preset usage intensity to determine the specific location of the consumables in the nasal atomizer. Partition positioning is achieved through sensors and position detection modules inside the RF communication module, which can accurately identify the location information of the consumables. For example, in a home environment, assuming that the system detects that the usage intensity of an atomizer nozzle exceeds the preset threshold, the RF communication module will immediately partition and locate the atomizer nozzle to determine its specific location inside the atomizer. Next, the system will perform topological structure analysis on the target consumables based on the location of the consumables to obtain topological structure information. Topological structure analysis refers to the analysis of the spatial relationship and connection method between the consumables and their surrounding components, which is very important for subsequent sterilization processing. For example, the system will analyze the relative position and connection method between the atomizer nozzle and other components (such as atomization chamber, air pump, etc.) to ensure that the sterilization module will not be blocked or interfered by other components during irradiation. Assuming that the atomizer nozzle is located in the center of the atomizer chamber and there are no other parts around it to block it, the system will record this topological structure information to provide basic data for the subsequent optimization of the irradiation angle. Then, the system will optimize the irradiation angle of the sterilization module based on the topological structure information through the preset ray tracing algorithm to obtain the adjusted angle and the sterilization module corresponding to the adjusted angle. The ray tracing algorithm is an algorithm that simulates the propagation path of light. Through this algorithm, the optimal irradiation angle of the UV lamp can be calculated to ensure that the light can evenly cover the surface of the consumables and achieve the best sterilization effect. For example, assuming that the system knows through topological structure analysis that the atomizer nozzle is located in the center of the atomizer chamber and there are no obstructions around it, the ray tracing algorithm will calculate that the optimal irradiation angle of the UV lamp is 45 degrees and apply this angle to the sterilization module. The system will adjust the position and angle of the UV lamp to ensure that the light can evenly irradiate all parts of the atomizer nozzle. Next, the system will obtain the physical property parameters of the target consumables, which include the material and area of ​​the consumables. The physical property parameters are crucial to determining the power distribution of the sterilization module. Different materials and areas require different irradiation times and powers to achieve the ideal sterilization effect. For example, assuming that the atomizer nozzle detected by the system is made of medical-grade silicone with an area of ​​10 square centimeters, the system will search for the corresponding sterilization parameters, such as the required irradiation time and power, from the preset database based on these physical characteristic parameters. Based on these physical characteristic parameters and the position of the consumables, the system will pre-allocate the power of the sterilization module corresponding to the adjusted angle to obtain the allocated power. Power pre-allocation means calculating the power value that the sterilization module needs to output based on the specific situation of the consumables to ensure the safety and effectiveness of the sterilization process.For example, based on the material and area of ​​the atomizer nozzle and its position in the atomizer, the system calculates that the power value that the UV lamp needs to output is 10 watts, and allocates this power value to the sterilization module. Finally, the system starts the sterilization module based on the allocated power to sterilize the target consumables that exceed the preset usage intensity. The sterilization module will work at the preset power for a period of time, irradiating the surface of the consumables with ultraviolet light to kill bacteria and viruses attached to it, ensuring that the sanitary conditions of the consumables meet safety standards. For example, the system will start the UV lamp and irradiate the atomizer nozzle with a power of 10 watts for 10 minutes. After the sterilization treatment is completed, the system will automatically turn off the UV lamp and send a message through the preset notification mechanism to notify the parents that the consumables have been sterilized, ensuring that the parents can continue to use the nasal atomizer to treat their children with peace of mind. Through this series of steps, the system can not only automatically detect the usage intensity of the consumables, but also start the sterilization module for sterilization when necessary, ensuring that the consumables are always in a good sanitary state, thereby protecting the health and safety of users. For example, in a home environment, parents can use the information provided by the system to understand the usage and sterilization status of consumables, replace consumables in a timely manner, avoid affecting the treatment effect due to consumable problems, and ensure that their children are safe and comfortable during treatment. At the same time, the system can also automatically adjust the operating parameters of the nasal nebulizer based on this information to provide a more personalized treatment experience. In this way, the system not only improves the safety and effectiveness of treatment, but also reduces the burden of supervision on parents, allowing parents to more confidently perform nebulization treatment for their children.

[0040] In a specific embodiment, performing topological structure analysis on the target consumable based on the consumable position to obtain topological structure information includes: Using a spatial geometry algorithm, based on the position of the consumables, a spatial layout of the consumables inside the atomizer is modeled to obtain a consumables spatial model; The consumable space model is hierarchically divided to obtain a consumable topology hierarchy diagram; wherein the consumable topology hierarchy diagram is used to display the hierarchy and priority of consumables inside the atomizer; Perform consumable mapping on the consumable topology hierarchy graph based on the target consumable, and determine the consumable node corresponding to the target consumable in the consumable space model; Performing connection analysis on the consumable nodes to obtain a consumable connection graph; wherein the consumable connection graph is used to display the direct connection relationship between the mapped consumable node and surrounding consumable nodes; Using an adjacency matrix algorithm, based on the consumable connection graph, the distance and connectivity between each of the mapped consumables and surrounding consumables are calculated to obtain a consumable node distance matrix; wherein the consumable node distance matrix is ​​used to quantify the closeness of the spatial relationship between consumables; Determine the core path based on the consumable node distance matrix to obtain the core topological path; The core topology path is annotated with topology structure information to obtain topology structure information.

[0041] Specifically, this process is a key step to conduct a detailed analysis of the topological structure of the consumables inside the atomizer in order to ensure that the sterilization module can effectively sterilize the consumables after the system detects that the usage intensity of the consumables exceeds the preset threshold. First, the system will use the spatial geometry algorithm to model the spatial layout of the consumables inside the atomizer based on the position of the consumables and generate a consumable space model. The spatial geometry algorithm is a mathematical method that can accurately describe the position and shape of consumables in three-dimensional space. For example, in a home environment, assuming that the system detects that the usage intensity of an atomizer nozzle exceeds the preset threshold, the radio frequency communication module will use the spatial geometry algorithm to construct a three-dimensional consumable space model based on the position information of the atomizer nozzle inside the atomizer. Next, the system will hierarchically divide the generated consumable space model to obtain a consumable topology hierarchy diagram. Hierarchical division refers to dividing the consumable space model into multiple levels, each level representing different parts or components of the consumables, as well as their relative position relationship and priority. For example, the system divides the space inside the atomizer into multiple levels. The first level may include the atomizer nozzle and the atomizer chamber, and the second level may include the air pump and the control circuit board, etc. This hierarchical information is helpful for subsequent consumables mapping and node connection analysis. Assume that the consumables topology hierarchy diagram generated by the system shows that the atomizer nozzle is located in the first level, surrounded by the atomizer chamber and other related components. Then, the system will perform consumable mapping on the consumables topology hierarchy diagram based on the target consumables, and determine the consumable nodes corresponding to the target consumables in the consumables space model. Consumables mapping refers to accurately locating the target consumables in the topology hierarchy diagram and generating mapped consumables nodes. For example, the system will mark the atomizer nozzle that exceeds the usage intensity in the topology hierarchy diagram and generate a mapped consumable node so that the location and hierarchical information of the consumable can be accurately identified in subsequent analysis. Next, the system will perform connection analysis on the mapped consumable nodes and generate a consumables connection diagram. Connection analysis refers to analyzing the direct connection relationship between the mapped consumable nodes and the surrounding consumable nodes, and generating a diagram showing these connection relationships. For example, the system will analyze the connection relationship between the mapped consumables (atomizer nozzle) and the surrounding atomizer chamber, air pump and other components to generate a consumable connection graph. Assume that the consumable connection graph shows that the atomizer nozzle is directly connected to the atomizer chamber, and the atomizer chamber is connected to the air pump. Then, the system will use the adjacency matrix algorithm to calculate the distance and connectivity between each mapped consumable and the surrounding consumables based on the consumable connection graph, and generate a consumable node distance matrix. The adjacency matrix algorithm is a graph theory method that can be used to calculate the distance and connectivity between each node in the graph. For example, the system will generate an adjacency matrix, and each element in the matrix represents the distance and connectivity between two consumable nodes. Assume that the generated consumable node distance matrix shows that the distance between the atomizer nozzle and the atomizer chamber is 1, the connectivity is 1, and the distance between the atomizer chamber and the air pump is 2, and the connectivity is 1. Next, the system will determine the core path based on the consumable node distance matrix and generate a core topological path.Core path determination refers to finding one or more key paths from the consumable node distance matrix, which reflect the main connection relationship between consumable nodes. For example, the system will determine a core path from the atomizer nozzle to the air pump from the consumable node distance matrix, which shows the main connection relationship from the atomizer nozzle to the air pump. Finally, the system will annotate the core topology path with topological structure information and generate topological structure information. Topological structure information annotation refers to adding detailed annotations and marks on the core topological path, which includes the name, location, connection method, etc. of each node. For example, the system will annotate the name and location of the atomizer nozzle, atomization chamber and air pump on the core topological path to generate detailed topological structure information. Assume that the generated topological structure information shows that the atomizer nozzle is located at the front end of the atomizer and is directly connected to the atomization chamber, the atomization chamber is located in the middle position and is connected to the air pump, and the air pump is located at the back end. Through this series of steps, the system can not only perform accurate topological structure analysis on consumables that exceed the preset usage intensity, but also generate detailed topological structure information, providing important reference data for the subsequent optimization of the irradiation angle and power distribution of the sterilization module. For example, in a home environment, when the system detects that the intensity of use of the atomizer nozzle exceeds the preset threshold, it will generate detailed topological structure information through the above steps to ensure that the sterilization module can accurately irradiate all parts of the atomizer nozzle to achieve the best sterilization effect. Parents can understand the usage and sterilization status of consumables through the information provided by the system, replace consumables in time, avoid affecting the treatment effect due to consumable problems, and ensure that the child is safe and comfortable during treatment. At the same time, the system can also automatically adjust the operating parameters of the nasal nebulizer based on this information to provide a more personalized treatment experience. In this way, the system not only improves the safety and effectiveness of the treatment, but also reduces the burden of supervision on parents, allowing parents to more confidently perform atomization treatment for their children.

[0042] The above describes the push management method of the nasal atomizer in the embodiment of the present invention. The following describes the push management device of the nasal atomizer in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a push management device for a nasal atomizer includes: The reading module 21 is used to read the identification of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identification; The parsing module 22 is used to perform type parsing on the read consumable identification to obtain the parsed consumable type and normal working information corresponding to the parsed consumable type; A monitoring module 23, configured to monitor the status of the consumables corresponding to the consumables analysis type by using a preset timestamp algorithm to obtain consumables status information; A judgment module 24 is used to judge whether the corresponding consumable is working normally based on the consumable status information and the normal working information, and if so, to predict the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result; The sterilization module 25 is used to, if the predicted result is that the usage intensity exceeds the preset usage intensity threshold, take the consumables that exceed the preset usage intensity as target consumables, start the sterilization module to sterilize the target consumables, and send information to notify the target user through a preset notification mechanism.

[0043] In this embodiment, for the specific implementation of each unit in the above device embodiment, please refer to the above method embodiment, which will not be repeated here.

[0044] Reference Figure 3 The present invention also provides a computer device in an embodiment, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0045] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0046] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0047] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0048] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0049] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for managing the push of a nasal atomizer, characterized in that: The nasal atomizer is provided with a radio frequency communication module, comprising the following steps: The radio frequency communication module is used to read the identification of various consumables of the target nasal atomizer to obtain the read consumable identification; Performing type analysis on the read consumable identification to obtain the consumable analysis type and normal working information corresponding to the consumable analysis type; The consumables corresponding to the consumables analysis type are monitored by a preset timestamp algorithm to obtain consumables status information; Based on the consumable status information and the normal working information, determining whether the corresponding consumable is working normally, and if so, predicting the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result; If the predicted result is that the usage intensity exceeds the preset usage intensity threshold, the consumables that exceed the preset usage intensity are taken as target consumables, and the sterilization module is started to sterilize the target consumables, and information is sent to notify the target user through a preset notification mechanism.

2. The push management method of the nasal atomizer according to claim 1, characterized in that: The radio frequency communication module is provided with a high-frequency radio frequency transmitter and a signal demodulation module. The radio frequency communication module is used to read the identification of various consumables of the target nasal atomizer to obtain the read consumable identification, including: The radio frequency identification tags on the various consumables in the target nasal atomizer are radio-frequency excited by the high-frequency radio frequency transmitter in the radio frequency communication module to obtain an activation radio frequency tag signal, wherein each consumable corresponds to one activation radio frequency tag signal; The signal demodulation module receives the activated radio frequency tag signal, and performs signal demodulation processing on the activated radio frequency tag signal to obtain an original identification data code stream; wherein the original identification data code stream is a series of digital code elements arranged according to a specific coding rule; Analyze whether the original identification data code stream contains abnormal difference information by using a preset Reed-Solomon error correction code algorithm, and if so, determine the abnormal position in the original identification data code stream containing the abnormal difference information; Based on the abnormal position, error correction is performed on the original identification data code stream with abnormal differences to obtain corrected identification data; The correction identification data is structurally parsed to obtain identification structure information, and the identification structure information is used as the reading consumable identification; wherein the identification structure information is the meaning and arrangement order of each field in the identification data.

3. The push management method of the nasal atomizer according to claim 1, characterized in that: The reading of the consumable identification and performing type parsing to obtain the consumable parsing type and normal working information corresponding to the consumable parsing type include: Receive target user requirements, and extract corresponding information from the read consumable identification based on the target user requirements to obtain corresponding consumable identification data; wherein the consumable identification data includes production batch identification data and model identification data of the consumable; Parsing the information of each of the consumable identification data to obtain a consumable identification element; Performing a hash operation on the consumable identification element to obtain an identification hash value; Mapping the identification hash value to a preset identification classification index table to obtain an initial classification index; Based on the initial classification index, a search is performed in a pre-stored consumable type database to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type.

4. The push management method of the nasal atomizer according to claim 1, characterized in that: The consumables corresponding to the consumables analysis type are monitored by a preset timestamp algorithm to obtain consumables status information, including: Through a preset timestamp algorithm, the consumables corresponding to the consumables analysis type are monitored and time stamps are added to obtain a timestamp matrix; wherein the timestamp matrix includes rows, columns and elements, the rows represent the consumables analysis type, the columns represent the timestamps, and the elements represent the working parameters of the consumables under the timestamps; The timestamp matrix is ​​symbolized by a symbolic dynamics algorithm to obtain a symbol sequence; wherein the symbol sequence includes a symbolized state representation, and the symbolized state representation is a combination of consumable states within a specific time period for each symbol; Inputting the symbol sequence into a preset forward-backward module of a hidden Markov model to perform state probability calculation to obtain state probability vectors corresponding to each type of consumables; The state probability vector is analyzed to obtain consumable state information; wherein the consumable state information includes the working state, working mode and abnormal situation of the consumable.

5. The push management method of the nasal atomizer according to claim 1, characterized in that: The predicting the usage of the target nasal atomizer based on the consumable status information to obtain a prediction result includes: Performing vector quantization on the consumables status information to obtain a consumables status vector; Performing entropy coding on the consumable state vector to obtain entropy coded consumable information; Performing prediction analysis on the entropy coded consumable information by a linear prediction analysis method to obtain prediction residual data; Performing Kalman filtering on the prediction residual data to obtain filtered residual information; Performing fractal dimension calculation on the residual information after filtering to obtain fractal dimension features; The usage of the target nasal atomizer is predicted based on the fractal dimension feature to obtain a prediction result.

6. The method for managing the push of a nasal atomizer according to claim 1, characterized in that: The starting sterilization module to sterilize the target consumables includes: Partitioning and locating the target consumables to obtain corresponding consumable positions; Performing a topological structure analysis on the target consumable based on the position of the consumable to obtain topological structure information; wherein the topological structure information refers to the spatial relationship and connection mode between the consumable and surrounding components; By using a preset ray tracing algorithm, the irradiation angle of the sterilization module is optimized and adjusted based on the topological structure information to obtain an adjusted angle and a sterilization module corresponding to the adjusted angle; Acquire the physical characteristic parameters of the target consumables; wherein the physical characteristic parameters include material and area; Pre-allocating power to the sterilization module corresponding to the adjusted angle based on the physical characteristic parameter and the position of the consumables to obtain allocated power; Based on the allocated power, a sterilization module is started to sterilize the consumables that exceed a preset usage intensity.

7. The method for managing the push of a nasal atomizer according to claim 6, characterized in that: The performing topological structure analysis on the target consumable based on the consumable position to obtain topological structure information includes: Using a spatial geometry algorithm, based on the position of the consumables, a spatial layout of the consumables inside the atomizer is modeled to obtain a consumables spatial model; The consumable space model is hierarchically divided to obtain a consumable topology hierarchy diagram; wherein the consumable topology hierarchy diagram is used to display the hierarchy and priority of consumables inside the atomizer; Perform consumable mapping on the consumable topology hierarchy graph based on the target consumable, and determine the consumable node corresponding to the target consumable in the consumable space model; Performing connection analysis on the consumable nodes to obtain a consumable connection graph; wherein the consumable connection graph is used to display the direct connection relationship between the mapped consumable node and surrounding consumable nodes; Using an adjacency matrix algorithm, based on the consumable connection graph, the distance and connectivity between each of the mapped consumables and surrounding consumables are calculated to obtain a consumable node distance matrix; wherein the consumable node distance matrix is ​​used to quantify the closeness of the spatial relationship between consumables; Determine the core path based on the consumable node distance matrix to obtain the core topological path; The core topology path is annotated with topology structure information to obtain topology structure information.

8. A push management device for a nasal atomizer, characterized in that: The nasal atomizer is provided with a radio frequency communication module, including: A reading module, used to read the identification of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identification; A parsing module, used to perform type parsing on the read consumable identification to obtain the parsed consumable type and normal working information corresponding to the parsed consumable type; A monitoring module, used to monitor the status of the consumables corresponding to the consumable analysis type through a preset timestamp algorithm to obtain consumable status information; A judgment module, used for judging whether the corresponding consumable is working normally based on the consumable status information and the normal working information, and if so, predicting the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result; The sterilization module is used to, if the predicted result is that the usage intensity exceeds a preset usage intensity threshold, take the consumables that exceed the preset usage intensity as target consumables, start the sterilization module to sterilize the target consumables, and send information to notify the target user through a preset notification mechanism.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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