Push Management Method and Related Devices for Nasal Atomizer

Abstract

The present invention relates to a pushing management method and related devices for a nasal atomizer, including the following steps: performing type analysis on the read consumable identifier to obtain a consumable analysis type and normal working information corresponding to the consumable analysis type; monitoring the status of the consumable corresponding to the consumable analysis type to obtain consumable status information; judging whether the corresponding consumable is working normally based on the consumable status information and the normal working information. 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, taking the consumable with the usage intensity exceeding the preset as the target consumable, starting a sterilization module to perform sterilization treatment on the target consumable, and sending an information notification to the target user through a preset notification mechanism, solving the technical problem that users often have difficulty accurately grasping the actual usage situation and replacement time of the consumable, resulting in poor treatment effects.

Description

Technical Field

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

[0002] With the accelerating pace of modern life, the decline in air quality and the intensification of environmental pollution, the incidence of respiratory diseases has been increasing year by year, especially among children, who are a susceptible group. Due to the imperfect development of the immune system, children are more vulnerable to the influence of the external environment and are prone to various nasal diseases, such as rhinitis and allergic rhinitis. To effectively treat these diseases, nasal atomization therapy, as a non-invasive drug delivery method, has been widely adopted. It can directly deliver drugs to the diseased site, improving the treatment effect while reducing systemic side effects. However, in practical applications, how to ensure the safety and effectiveness of nasal atomizers has become an urgent problem to be solved.

[0003] Existing nasal atomizers have some deficiencies during use, mainly manifested in consumable management. On the one hand, consumables such as atomizing nozzles and filters are key components for the normal operation of nasal atomizers, and their performance directly affects the treatment effect. However, most nasal atomizers on the market currently lack an effective consumable management mechanism, and users often have difficulty accurately grasping the actual usage and replacement time of consumables. This not only may lead to poor treatment effects but also may pose a risk of secondary infection due to consumable contamination. On the other hand, for families with children using nasal atomizers, parents need to regularly monitor their children's usage to ensure the safety and hygiene of the treatment process. However, traditional methods often rely on manual observation and memory, which are inefficient and prone to errors.

[0004] To solve the above problems, this study proposes a push management method for nasal atomizers. This method uses the built-in radio frequency communication module technology to achieve intelligent management of consumables. By automatically reading the consumable identification and parsing its type, and combining with the timestamp algorithm to monitor the status of consumables, it can timely detect abnormal operation of consumables and take corresponding measures, such as activating the UV sterilization function to prevent bacterial growth caused by overuse. At the same time, this method can also automatically generate detailed consumable usage records to help parents better understand and manage their children's treatment process, thereby improving the safety and convenience of nasal atomization therapy. Summary of the Invention

[0005] The main object of the present invention is to provide a push management method for a nasal atomizer and related devices, which solves the technical problem that users often have difficulty accurately grasping the actual usage and replacement time of consumables, resulting in poor treatment effects.

[0006] To achieve the above object, the present invention provides a method for push management of a nasal atomizer. A radio frequency communication module is provided in the nasal atomizer, and the method includes the following steps:

[0007] Read the identification of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identification;

[0008] Analyze the type of the read consumable identification to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type;

[0009] Monitor the status of the consumables corresponding to the consumable analysis type through a preset timestamp algorithm to obtain the consumable status information;

[0010] Based on the consumable status information and the normal working information, judge whether the corresponding consumables are working properly. If so, predict the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result;

[0011] If the prediction result is that the usage intensity exceeds the preset usage intensity threshold, regard the consumables with usage intensity exceeding the preset value as target consumables, start the sterilization module to perform sterilization treatment on the target consumables, and send information to notify the target user through a preset notification mechanism.

[0012] Further, a high-frequency radio frequency transmitter and a signal demodulation module are provided on the radio frequency communication module. The step of reading the identification of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identification includes:

[0013] Perform radio frequency excitation on the radio frequency identification tags on various consumables in the target nasal atomizer through the high-frequency radio frequency transmitter in the radio frequency communication module to obtain an activated radio frequency tag signal, and each consumable corresponds to one activated radio frequency tag signal;

[0014] Receive the activated radio frequency tag signal through the signal demodulation module and perform signal demodulation processing on the activated radio frequency tag signal to obtain an original identification data stream; wherein, the original identification data stream is a series of digital code elements arranged according to a specific coding rule;

[0015] Analyze whether there is abnormal difference information in the original identification data stream through a preset Reed-Solomon error correction code algorithm. If so, determine the abnormal position in the original identification data stream with abnormal difference information;

[0016] Perform error correction on the original identification data stream with abnormal difference based on the abnormal position to obtain corrected identification data;

[0017] Perform a structural analysis on the corrected identification data to obtain identification structure information, and use the identification structure information as the read consumable identification; wherein, the identification structure information is the meaning and arrangement order of each field in the identification data.

[0018] Further, perform a type analysis on the read consumable identification to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type, including:

[0019] Receive the target user's requirements, and extract the corresponding information in the read consumable identification based on the target user's requirements to obtain the corresponding consumable identification data; wherein, the consumable identification data includes the production batch identification data and the model identification data of the consumable.

[0020] Perform an information analysis on each of the consumable identification data to obtain consumable identification elements.

[0021] Perform a hash operation on the consumable identification elements to obtain an identification hash value.

[0022] Map the identification hash value into a preset identification classification index table to obtain an initial classification index.

[0023] Based on the initial classification index, perform a retrieval in a pre-stored consumable type database to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type.

[0024] Further, perform a status monitoring on the consumable corresponding to the consumable analysis type through a preset timestamp algorithm to obtain consumable status information, including:

[0025] Perform a status monitoring and add a time mark to the consumable corresponding to the consumable analysis type through a preset timestamp algorithm to obtain a timestamp matrix; wherein, the timestamp matrix includes rows, columns and elements, the rows represent the consumable analysis type, the columns represent timestamps, and the elements represent the working parameters of the consumable at that timestamp.

[0026] Perform a symbolic processing on the timestamp matrix through a symbolic dynamics algorithm to obtain a symbol sequence; wherein, the symbol sequence includes symbolic state representations, and each symbolic state representation represents a combination of consumable states within a specific time period.

[0027] Input the symbol sequence into the forward-backward module of a preset hidden Markov model to perform state probability calculation to obtain the state probability vectors corresponding to various consumables.

[0028] Perform an information analysis on the state probability vectors to obtain consumable status information; wherein, the consumable status information includes the working status, working mode and abnormal conditions of the consumable.

[0029] Further, predicting the usage condition of the target nasal atomizer based on the consumable status information to obtain a prediction result includes:

[0030] Performing vector quantization on the consumable status information to obtain a consumable status vector;

[0031] Performing entropy coding on the consumable status vector to obtain entropy-coded consumable information;

[0032] Performing prediction analysis on the entropy-coded consumable information through a linear prediction analysis method to obtain prediction residual data;

[0033] Performing Kalman filtering on the prediction residual data to obtain filtered residual information;

[0034] Calculating the fractal dimension of the filtered residual information to obtain a fractal dimension feature;

[0035] Predicting the usage condition of the target nasal atomizer based on the fractal dimension feature to obtain a prediction result.

[0036] Further, starting the sterilization module to perform sterilization treatment on the target consumable includes:

[0037] Performing partition positioning on the target consumable to obtain the corresponding consumable position;

[0038] Performing topological structure analysis on the target consumable based on the consumable position to obtain topological structure information; wherein, the topological structure information refers to the spatial relationship and connection method between the consumable and surrounding components;

[0039] Through a preset ray tracing algorithm, optimizing and adjusting the irradiation angle of the sterilization module based on the topological structure information to obtain an adjusted angle and the sterilization module corresponding to the adjusted angle;

[0040] Obtaining the physical property parameters of the target consumable; wherein, the physical property parameters include material and area;

[0041] Performing power pre-distribution on the sterilization module corresponding to the adjusted angle based on the physical property parameters and the consumable position to obtain a distributed power;

[0042] Starting the sterilization module based on the distributed power to perform sterilization treatment on the consumable with a usage intensity exceeding a preset value.

[0043] Further, performing topological structure analysis on the target consumable based on the consumable position to obtain topological structure information includes:

[0044] Using a spatial geometry algorithm, a spatial layout of the consumables inside the atomizer is modeled based on the positions of the consumables to obtain a consumable spatial model;

[0045] The consumable spatial model is hierarchically divided to obtain a consumable topological hierarchy graph; wherein, the consumable topological hierarchy graph is used to display the hierarchical structure and priority of the consumables inside the atomizer;

[0046] Based on the target consumables, a consumable mapping is performed on the consumable topological hierarchy graph to determine the consumable nodes corresponding to the target consumables in the consumable spatial model;

[0047] A connection analysis is performed on the consumable nodes to obtain a consumable connection graph; wherein, the consumable connection graph is used to display the direct connection relationships between the mapped consumable nodes and the surrounding consumable nodes;

[0048] Using an adjacency matrix algorithm, based on the consumable connection graph, the distances and connectivity between each of the mapped consumables and the surrounding consumables are calculated to obtain a consumable node distance matrix; wherein, the consumable node distance matrix is used to quantify the tightness of the spatial relationships between the consumables;

[0049] Based on the consumable node distance matrix, a core path is determined to obtain a core topological path;

[0050] Topological structure information annotation is performed on the core topological path to obtain topological structure information.

[0051] The present invention also provides a push management device for a nasal atomizer, wherein a radio frequency communication module is provided inside the nasal atomizer, including:

[0052] A reading module, configured to read the identifications of various consumables of a target nasal atomizer through the radio frequency communication module to obtain read consumable identifications;

[0053] An analysis module, configured to perform type analysis on the read consumable identifications to obtain a consumable analysis type and normal working information corresponding to the consumable analysis type;

[0054] A monitoring module, configured to monitor the status of the consumables corresponding to the consumable analysis type through a preset timestamp algorithm to obtain consumable status information;

[0055] A judgment module, configured to judge whether the corresponding consumables are working properly based on the consumable status information and the normal working information, and if so, perform a usage intensity prediction on the target nasal atomizer based on the consumable status information to obtain a prediction result;

[0056] A sterilization module, which is configured to, if the prediction result indicates that the usage intensity exceeds a preset usage intensity threshold, regard the consumables with usage intensity exceeding the preset value as target consumables, activate the sterilization module to perform sterilization treatment on the target consumables, and send information notifications to the target user through a preset notification mechanism.

[0057] The present invention also provides a computer device, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0058] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0059] The push management method for a nasal atomizer provided by the present invention includes the following steps: reading the identifiers of various consumables of a target nasal atomizer through the radio frequency communication module to obtain the read consumable identifiers; performing type parsing on the read consumable identifiers to obtain the consumable parsing types and the normal working information corresponding to the consumable parsing types; monitoring the status of the consumables corresponding to the consumable parsing types through a preset timestamp algorithm to obtain consumable status information; determining whether the corresponding consumables are working properly based on the consumable status information and the normal working information. 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 indicates that the usage intensity exceeds a preset usage intensity threshold, regarding the consumables with usage intensity exceeding the preset value as target consumables, activating the sterilization module to perform sterilization treatment on the target consumables, and sending information notifications to the target user through a preset notification mechanism. By the above technical means, the technical problem that users often have difficulty accurately grasping the actual usage situation and replacement time of consumables, resulting in poor treatment effects, is solved. It is realized to form detailed consumable usage records, including data such as total usage time, atomization duration, and atomization frequency, through feature extraction of the consumable status information. These records not only provide a convenient consumable management tool for users, but also provide a scientific basis for doctors to evaluate treatment effects. Description of the Drawings

[0060] Figure 1 is a schematic diagram of the steps of the push management method for a nasal atomizer in an embodiment of the present invention;

[0061] Figure 2 is a structural block diagram of the push management device for a nasal atomizer in an embodiment of the present invention;

[0062] Figure 3 is a schematic structural block diagram of a computer device in an embodiment of the present invention.

[0063] The realization, functional features, and advantages of the present invention will be further described in conjunction with embodiments and with reference to the accompanying drawings. Detailed implementation manners

[0064] In order to make the objectives, technical solutions, and advantages of the present invention more clearly understood, the present invention will be 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 used to limit the present invention.

[0065] As Figure 1 shown, Figure 1 is a schematic diagram of the steps of a pushing management method for a nasal atomizer in an embodiment of the present invention;

[0066] An embodiment of the present invention provides a pushing management method for a nasal atomizer. A radio frequency communication module is provided inside the nasal atomizer, and the method includes the following steps:

[0067] Step S1, reading the identifiers of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identifiers.

[0068] Specifically, reading the identifiers of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identifiers is the basic link of the entire pushing management method. Specifically, the radio frequency communication module is an intelligent device integrated inside the nasal atomizer. It can interact with specific identifiers on the consumables, which may be in the form of barcodes, QR codes, or RFID tags, etc. When the consumable is installed in the nasal atomizer, the radio frequency communication module will be automatically activated and quickly scan and read the identifier information on the consumable 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, first, a new nebulizer mouthpiece needs to be installed in the device. At this time, the radio frequency communication module inside the nasal atomizer will immediately identify and read the unique identifier on the nebulizer mouthpiece. This identifier contains important information such as the production batch, expiration date, and applicable model of the consumable. In this way, the system can not only confirm whether the consumable is suitable for the current model of the nasal atomizer but also preliminarily determine whether the consumable is within the expiration date, thus avoiding risks caused by improper use or expired consumables and laying a solid foundation for subsequent consumable type analysis and status monitoring. Additionally, the radio frequency communication module can be NFC technology or RFID technology.

[0069] Step S2, performing type analysis on the read consumable identifiers to obtain the consumable analysis types and the normal working information corresponding to the consumable analysis types.

[0070] Specifically, type analysis is performed on the read consumable identifier to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type, which is a key step after the consumable identifier is read. In this process, the radio frequency communication module not only reads the identifier information on the consumable, but also further analyzes this information to determine the specific type of the consumable and its related normal working parameters. For example, when the radio frequency communication module reads the identifier of a newly installed atomizing nozzle, it will then transfer this identifier information to the internal analysis module. The analysis module will look up the consumable type that matches this identifier according to the pre-stored data comparison table, such as whether it is an atomizing nozzle suitable for adults or children, or a special consumable for a specific drug type, etc. At the same time, the analysis module will also obtain the normal working information corresponding to this consumable type, such as the recommended maximum number of uses, the recommended cleaning cycle, the optimal atomizing temperature range, etc. These information are crucial for ensuring the efficient operation of the nasal atomizer. Taking the home use scenario as an example, assume that a parent replaces a new atomizing nozzle specifically for children for a child with rhinitis. After the radio frequency communication module reads and analyzes the consumable identifier, the system can know that this is a consumable designed specifically for children, with a milder atomizing mode and a shorter single-use time limit. In this way, the system can automatically adjust the operating parameters of the nasal atomizer according to these normal working information, ensuring that the child is both safe and comfortable during treatment, and at the same time facilitating the parents to supervise and manage the use of the consumable, avoiding problems such as poor treatment effect or equipment damage caused by improper operation.

[0071] Step S3, through a preset timestamp algorithm, monitor the status of the consumable corresponding to the consumable analysis type to obtain consumable status information.

[0072] Specifically, through a preset timestamp algorithm, the status of the consumables corresponding to the consumable analysis type is monitored to obtain consumable status information, which is one of the important steps to ensure the efficient and safe operation of the nasal atomizer. After the radio frequency communication module has completed the reading and type analysis 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 the time of each use of the consumables, so that key data such as the cumulative usage time and usage frequency of the consumables can be accurately calculated. For example, in a home environment, when a parent uses a nasal atomizer for a child with rhinitis, each time the atomization treatment is started, the radio frequency communication module will record the start and end time points, and integrate and analyze this timestamp information with the previous data. 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 timely detect whether the consumables have reached the replacement standard recommended by the manufacturer, or whether there is an abnormal frequent usage situation, prompt the parent to replace the consumables in time, and avoid affecting the treatment effect due to consumable aging or pollution, or even causing health risks. In addition, the application of the timestamp algorithm also helps to establish a complete historical record of the consumable usage, providing data support for subsequent consumable management and services.

[0073] Step S4: Based on the consumable status information and the normal working information, determine whether the corresponding consumables are working properly. If so, predict the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result.

[0074] Specifically, based on the consumable status information and the normal working information, it is determined whether the corresponding consumable is working properly. 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 carried out after the system completes the monitoring and analysis of the consumable status, further ensuring that the consumable is within the normal usage range and predicting the future usage intensity to take necessary management measures in advance. Specifically, the system first continuously monitors the usage of the consumable using a preset timestamp algorithm and symbolic dynamics algorithm to generate detailed consumable status information. These status information include the working status, working mode, and abnormal conditions of the consumable. The system compares these status information with the pre-stored normal working information to determine whether the consumable is in a normal working state. The normal working information usually includes parameters such as the maximum usage times of the consumable and the recommended cleaning cycle, which are set by the manufacturer according to the characteristics and usage requirements of the consumable. For example, in a home environment, assume that a parent replaces a new atomizing nozzle for a child with rhinitis. The system monitors that the working status of the atomizing nozzle is normal, the working mode is the conventional mode, and no abnormal conditions are found through the timestamp algorithm and symbolic dynamics algorithm. The system compares these status information with the pre-stored normal working information and confirms that the usage times and cleaning cycle of the atomizing nozzle are within the normal range. If the system determines that the consumable is in a normal working state, next, the usage intensity of the target nasal atomizer is predicted based on the consumable status information to obtain a prediction result. The usage intensity prediction refers to predicting the usage intensity of the consumable in the future period by analyzing the historical usage data of the consumable, so as to take necessary management measures in advance. The system uses machine learning algorithms, such as time series analysis or regression analysis, to model the historical usage data of the consumable and predict the future usage intensity. For example, the system collects the usage data of the atomizing nozzle 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 atomizing nozzle in the next week. Assume that the system prediction result shows that the usage frequency of the atomizing nozzle will increase and the usage duration will also extend in the next week. The system will generate the corresponding prediction result and send a message notification to the parent through a preset notification mechanism. Through this series of steps, the system can not only monitor the usage of the consumable in real time to ensure that the consumable is always in a normal working state, but also predict the future usage intensity in advance to help the parent better manage the usage and maintenance of the consumable. For example, the parent can prepare new consumables in advance according to the system prediction result to avoid affecting the treatment effect of the child 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 atomizer according to the prediction result to provide a more personalized treatment experience.

[0075] Step S5, if the predicted result is that the usage intensity exceeds a preset usage intensity threshold, then use the consumables with usage intensity exceeding the preset value as target consumables, activate the sterilization module to perform sterilization treatment on the target consumables, and send a message notification to the target user through a preset notification mechanism.

[0076] Specifically, if the predicted result indicates that the usage intensity exceeds a preset usage intensity threshold, the consumable with a usage intensity exceeding the preset threshold is regarded as the target consumable, and the sterilization module is activated to perform sterilization treatment on the target consumable, and information is sent to notify the target user through a preset notification mechanism. This process is a series of automated processing steps taken after the system completes the prediction of the consumable usage intensity to ensure the hygienic status and usage safety of the consumable. Specifically, when the system predicts the usage intensity based on the consumable status information and the obtained result shows that the future usage intensity of the consumable will exceed the preset usage intensity threshold, the system immediately marks this consumable as the target consumable. The preset usage intensity threshold is set according to factors such as the material characteristics, hygienic standards, and usage frequency of the consumable. Exceeding this threshold means that the consumable may have a high risk of bacterial growth and requires additional cleaning or sterilization treatment. For example, in a home environment, assume that the system predicts through time series analysis that the usage frequency of the atomizer used by the child will increase significantly in the next week, and the usage duration will also be extended, resulting in the usage intensity exceeding the preset usage intensity threshold. The system will mark this atomizer as the target consumable and initiate a series of automated processing steps. First, the system activates the sterilization module to perform sterilization treatment on the target consumable. The sterilization module is an efficient disinfection device that emits ultraviolet light to irradiate the surface of the consumable to kill bacteria and viruses attached to it. The system adjusts the irradiation angle and power of the UV lamp according to the physical characteristic parameters (such as material and area) and location information of the consumable to ensure that the ultraviolet light can evenly cover all parts of the consumable and achieve the best sterilization effect. For example, the system adjusts the angle of the UV lamp to 45 degrees, the power to 10 watts, and irradiates for 10 minutes. After the sterilization treatment is completed, the system automatically turns off the UV lamp. Second, the system sends information to notify the target user through a preset notification mechanism. The preset notification mechanism can be in the form of mobile APP push messages, text messages, or emails. These notification methods can timely remind parents to pay attention to the usage situation and sterilization treatment status of the consumable. For example, the system sends a notification message to the parent through the mobile APP: "The usage intensity of the atomizer used by your child will exceed the preset threshold in the next week. The system has automatically completed the UV sterilization treatment. Please pay attention to the usage situation of the consumable and replace it with a new one in time if necessary." Through this series of steps, the system can not only automatically detect and predict the usage intensity of the consumable, but also activate the sterilization module to perform sterilization treatment when necessary to ensure that the consumable is always in a good hygienic state, thus protecting the health and safety of the user. For example, in a home environment, parents can timely understand the usage situation and sterilization treatment status of the consumable through the notification information provided by the system, prepare new consumables in advance, avoid affecting the treatment effect of the child 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 atomizer according to the prediction result to provide a more personalized treatment experience. Additionally, the sterilization module can be a UV sterilization module.

[0077] In a specific embodiment, a high-frequency radio frequency transmitter and a signal demodulation module are provided on the radio frequency communication module. The radio frequency communication module is used to read the identification of various consumables of the target nasal atomizer, and the obtained read consumable identification includes:

[0078] The radio frequency identification tags on 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 activated radio frequency tag signal, and each consumable corresponds to one activated radio frequency tag signal;

[0079] 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 bit stream; wherein, the original identification data bit stream is a series of digital code elements arranged according to a specific coding rule;

[0080] By using a preset Reed-Solomon error correction code algorithm, analyze whether there is abnormal difference information in the original identification data bit stream. If so, determine the abnormal position in the original identification data bit stream with abnormal difference information;

[0081] Based on the abnormal position, perform error correction on the original identification data bit stream with abnormal difference to obtain corrected identification data;

[0082] Perform structure analysis on the corrected identification data to obtain identification structure information, and use the identification structure information as the read consumable identification; wherein, the identification structure information is the meaning and arrangement order of each field in the identification data.

[0083] Specifically, in the nasal nebulizer, the RF communication module undertakes the core task of reading the consumable identification. When a parent replaces the new atomizing nozzle for a child 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, and these signals can penetrate the nebulizer housing and reach the RF identification tag installed on the consumable. After receiving the RF signal, the RF identification tag will be activated and reflect back the RF tag signal containing the consumable identification information. Each RF identification tag on the consumable corresponds to unique identification information, so the reflected RF tag signal is also unique. Next, the signal demodulation module in the RF communication module will receive these activated RF tag signals and demodulate them. The demodulation process is to convert the RF signal into a digital signal, that is, the original identification data bit stream. This original identification data bit stream is actually composed of a series of digital code elements arranged according to specific coding rules, and these code elements carry various information of the consumable, such as production date, batch number, model, etc. 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 bit stream. The Reed-Solomon error correction code is an efficient error detection and correction algorithm that can identify the errors that may occur during data transmission and determine the specific positions of the errors. If the system finds abnormal difference information in the original identification data bit stream during the analysis process, that is, some code elements do not match the expected values, then the system will locate these abnormal positions and correct the data at these positions to finally obtain the corrected identification data. Finally, the system will perform a structural analysis on the corrected identification data, extract the meanings and arrangement orders of each field therein, and form the complete identification structure information. The identification structure information contains all the key information of the consumable, such as consumable type, production date, expiration date, etc., and this information will be used in the subsequent type analysis and status monitoring steps. For example, in the home use scenario, when a parent replaces a new atomizing nozzle for children, the RF communication module will read and analyze the identification information of the atomizing nozzle through the above process, confirm that it is a consumable for children, and obtain information such as the recommended maximum number of uses and cleaning cycle. In this way, the system can automatically adjust the operating parameters of the nasal nebulizer according to this information to ensure the safety and comfort of the child during treatment, and at the same time facilitate the parents to supervise and manage the use of the consumable, avoiding problems such as poor treatment effect or equipment damage caused by improper operation. Through this series of fine steps, the nasal nebulizer can not only ensure the correct use of the consumable, but also provide a more personalized and efficient treatment experience.

[0084] In a specific embodiment, the type analysis of the read consumable identification to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type includes:

[0085] Receive the target user's requirements, and extract the corresponding information in the read consumable identifier based on the target user's requirements to obtain the corresponding consumable identifier data; wherein, the consumable identifier data includes the production batch number identifier data and the model identifier data of the consumable.

[0086] Perform information parsing on each of the consumable identifier data to obtain consumable identifier elements.

[0087] Perform a hash operation on the consumable identifier elements to obtain an identifier hash value.

[0088] Map the identifier hash value to a preset identifier classification index table to obtain an initial classification index.

[0089] Based on the initial classification index, retrieve in a pre-stored consumable type database to obtain the consumable parsing type and the normal working information corresponding to the consumable parsing type.

[0090] Specifically, first, the system receives the target user's requirements and extracts corresponding information from the read consumable identifiers based on the received target user's requirements to form consumable identifier data. This consumable identifier data includes the production batch number identifier data and model identifier data of the consumables. The production batch number identifier data can help the system trace the production batch of the consumables to ensure the quality and source of the consumables; while the model identifier data is used to determine the specific model of the consumables, which is crucial for matching the correct consumable type. For example, in a home environment, when a parent replaces a new atomizing nozzle for a child with rhinitis, after the radio frequency communication module reads the radio frequency identification tag information on the atomizing nozzle, the system extracts the production batch number and model identifier data from this information. Suppose the extracted production batch number identifier data is "202305A" and the model identifier data is "CHD-01", and these two data combine to form the consumable identifier data. Next, the system parses this consumable identifier data and decomposes it into finer-grained consumable identifier elements. These consumable identifier elements are the basic units that make up the consumable identifier data, and each element represents a specific attribute of the consumables. For example, the production batch number identifier data "202305A" can be parsed into the year "2023", month "05", and batch "A", and the model identifier data "CHD-01" can be parsed into the product line code "CHD" and serial number "01". Then, the system performs a hash operation on these consumable identifier elements to generate a unique identifier hash value. The hash operation is a process of converting the input data into a fixed-length output value, and this output value is usually called the hash value. The characteristic of the 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 identifier elements into a string, such as "202305ACHD01", and then performs a hash operation on this string to generate an identifier hash value, such as "abc123def456". After generating the identifier hash value, the system maps this hash value into a preset identifier classification index table to obtain the initial classification index. The identifier classification index table is a pre-constructed database that contains the identifier hash values of all known consumables and their corresponding classification indexes. By comparing the generated identifier hash value with the data in the index table, the system can quickly find the matching initial classification index. For example, suppose the identifier hash value "abc123def456" corresponds to the classification index "001" in the index table. Finally, the system retrieves in the pre-stored consumable type database based on the obtained initial classification index to find the consumable parsing type that matches this classification index and its corresponding normal working information. The consumable type database stores detailed information about various consumables, including the name of the consumables, applicable models, maximum usage times, recommended cleaning cycles, etc.In this example, the system looks up the information corresponding to the classification index "001" in the consumable type database. Suppose the information found shows that the consumable is a nebulizer nozzle specifically for children, with a maximum usage times 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 the consumable, but also obtain the normal working parameters of this type of consumable, thus providing reliable data support for subsequent status monitoring and usage management. For example, parents can, through the information provided by the system, know whether the nebulizer nozzle their child is using is suitable for the current nasal nebulizer model, as well as the remaining usage times of the consumable and the time for the next cleaning, so as to better manage the usage of the consumable and ensure the safety and effectiveness of the treatment process.

[0091] In a specific embodiment, through a preset timestamp algorithm, the status of the consumable corresponding to the parsed type of the consumable is monitored to obtain consumable status information, including:

[0092] Through a preset timestamp algorithm, the status of the consumable corresponding to the parsed type of the consumable is monitored and a time mark is added to obtain a timestamp matrix; wherein, the timestamp matrix includes rows, columns and elements, the rows represent the parsed types of the consumables, the columns represent timestamps, and the elements represent the working parameters of the consumable at that timestamp;

[0093] Through a symbolic dynamics algorithm, the timestamp matrix is symbolically processed to obtain a symbol sequence; wherein, the symbol sequence includes symbolic state representations, and each symbolic state representation is that each symbol represents a combination of consumable states within a specific time period;

[0094] The symbol sequence is input into the forward-backward module of a preset hidden Markov model for state probability calculation to obtain state probability vectors corresponding to various consumables;

[0095] The state probability vectors are information-analyzed to obtain consumable status information; wherein, the consumable status information includes the working state, working mode and abnormal conditions of the consumable.

[0096] Specifically, this process is a key step in further monitoring and analyzing the usage of consumables in detail after the identification reading and type parsing of consumables are completed. First, the system continuously monitors the usage of consumables using a preset timestamp algorithm, adds a time mark each time a consumable is used, and generates a timestamp matrix. The timestamp matrix is a multi-dimensional array, where each row represents a type of consumable parsing, each column represents a timestamp, and each element represents the specific working parameters of the consumable at that timestamp, such as atomization duration, atomization frequency, working temperature, etc. For example, in a home environment, assume that a parent replaces a new atomization nozzle for a child with rhinitis. The system records the start and end times of each atomization treatment and collects various working parameters during this period. The system internally generates a timestamp matrix to record the time of each use and the corresponding parameters. Assume that the child starts a 10-minute atomization treatment every night at 7 pm. The system will record the following information in the timestamp matrix: the consumable parsing type is "child-specific atomization nozzle", the timestamp is "2023-10-01 19:00:00", the atomization duration is 600 seconds, the atomization frequency is 10 times per minute, and the working temperature is 37°C. Similarly, the records for the next day will also be saved in the same format. Next, the system symbolizes the timestamp matrix through a symbolic dynamics algorithm to generate a symbol sequence. The symbolic dynamics algorithm is a method of converting continuous time series data into discrete symbols, and through this method, complex consumable state combinations can be simplified into symbols that are easy to process. Specifically, the system maps each working parameter interval in the timestamp matrix to a symbol. For example, the state where the atomization duration is between 500 - 600 seconds is mapped to symbol "A", the state where the atomization frequency is between 8 - 10 times per minute is mapped to symbol "B", and the state where the working temperature is between 36 - 38°C is mapped to symbol "C". In this way, the consumable state combination at each timestamp can be represented as a symbol sequence, such as "ABC", "ABC", etc. After generating the symbol sequence, the system inputs these symbol sequences into the forward-backward module of a preset hidden Markov model (HMM) to calculate the state probability, obtaining the state probability vectors corresponding to various consumables. The hidden Markov model is a statistical model commonly used to process sequence data, especially widely used in fields such as speech recognition and bioinformatics. In this example, the forward-backward module of the HMM calculates the state probability vectors of various consumables in different time periods according to the symbol sequence. The state probability vector represents the possibility that the consumable is in a certain state during a certain time period. For example, the probability that the consumable is in a normal working state during a certain time period is 0.9, and the probability of being in an abnormal state is 0.1. Finally, the system parses the obtained state probability vector to extract the state information of the consumable.These status information include the working status of the consumables (such as normal working, abnormal working), working modes (such as regular mode, high-intensity mode), and abnormal situations (such as too high temperature, abnormal frequency, etc.). For example, the system may parse the following information: - The consumables were in a normal working state from 19:00:00 on October 1, 2023 to 19:10:00 on October 1, 2023, with the working mode being the regular mode and no abnormal situations found. - The consumables were also in a normal working state from 19:00:00 on October 2, 2023 to 19:10:00 on October 2, 2023, with the working mode being the regular mode and no abnormal situations found. Through this series of steps, the system can not only monitor the usage of the consumables in real time, but also detect and warn of potential abnormal states in a timely manner, helping parents better manage their children's treatment process and ensuring the safety and effectiveness of the treatment. For example, if the system detects that the working temperature of the consumables continuously exceeds the normal range, it will immediately send a warning message through a preset notification mechanism to remind the parents to check the device or replace the consumables, thus avoiding poor treatment effects or health risks caused by device failures or consumable problems. In addition, the system can also automatically adjust the operating parameters of the nasal nebulizer according to these status information to provide a more personalized treatment experience. For example, if the system detects that the atomization frequency of the child is relatively high during a certain period, it can automatically increase the atomization duration or adjust the atomization 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 guardianship burden of the parents, enabling the parents to be more at ease in performing atomization treatment for their children.

[0097] In a specific embodiment, the predicting the usage situation of the target nasal nebulizer based on the consumable status information to obtain a prediction result includes:

[0098] Performing vector quantization on the consumable status information to obtain a consumable status vector;

[0099] Performing entropy coding on the consumable status vector to obtain entropy-coded consumable information;

[0100] Performing prediction analysis on the entropy-coded consumable information through a linear prediction analysis method to obtain prediction residual data;

[0101] Performing Kalman filtering on the prediction residual data to obtain filtered residual information;

[0102] Calculating the fractal dimension of the filtered residual information to obtain fractal dimension features;

[0103] Predicting the usage situation of the target nasal nebulizer based on the fractal dimension features to obtain a prediction result.

[0104] Specifically, this process is a crucial step in further predicting the future usage of consumables after the consumable status monitoring is completed. First, the system performs vector quantization on the consumable status information to generate a consumable status vector. Vector quantization is a method of mapping continuous data values into discrete vector representations. Through this method, complex consumable status information can be simplified into a set of vectors that are easy to process. For example, in a home environment, assume that the system has obtained the consumable status information through the timestamp algorithm and the 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 the normal working status, 0 represents the conventional mode, and the other 0 represents no abnormal conditions. Next, the system performs entropy coding on the generated consumable status vector to obtain the entropy-coded consumable information. Entropy coding is a data compression technique that reduces the storage space of data by removing redundant information. In this example, the system will use the entropy coding algorithm to compress the consumable status vector and generate the entropy-coded consumable information. For example, assume that the consumable status vector is [1, 0, 0], and 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 performs predictive analysis on the entropy-coded consumable information through linear predictive analysis to obtain the prediction residual data. Linear predictive analysis is a commonly used time series analysis method that 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, predict the consumable status information within a certain future time period, and calculate the residual between the predicted value and the actual value. For example, assume that the system predicts the status information of a future atomization treatment to be "100", and the actual entropy-coded consumable information is "101", then the prediction residual is "001". Next, the system performs 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 reduces the influence of noise by continuously updating the estimated value. In this example, the system will use the Kalman filter to process the prediction residual data, filter out the noise caused by measurement errors or external disturbances, and obtain more accurate filtered residual information. For example, assume that the prediction residual is "001", and the result after Kalman filtering may be "000.8", which means that the system smooths the prediction residual and reduces the influence 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 index that measures the complexity and self-similarity of data. By calculating the fractal dimension, the internal structure and law of the data can be revealed. In this example, the system will use the fractal dimension calculation method to analyze the filtered residual information and obtain a characteristic value that reflects the complexity of the consumable usage situation.For example, assume that the filtered residual information is "000.8", and the fractal dimension feature calculated by the system may be 1.2, which indicates that the usage of the consumable is relatively stable without obvious abnormal fluctuations. Finally, the system will predict the usage of the target nasal atomizer based on the fractal dimension feature and obtain the prediction result. The fractal dimension feature can be used to predict the usage intensity of the consumable and possible abnormal conditions in the future. For example, assume that the fractal dimension feature is 1.2. The system will predict whether the usage intensity of the consumable will exceed the preset usage intensity threshold within the next week according to the preset model and threshold. If the prediction result shows that the usage intensity will exceed the threshold, the system will generate the corresponding prediction result and send a message notification to the parent through the preset notification mechanism. For example, the system will send a notification message to the parent through the mobile APP: "The usage intensity of the atomizing nozzle used by your child will exceed the preset threshold within the next week. It is recommended that you prepare new consumables in advance." Through this series of steps, the system can not only extract detailed features of the usage of the consumable, but also generate intuitive prediction results to help parents better manage their children's treatment process and ensure the safety and effectiveness of the treatment. For example, parents can understand the usage of the consumable and possible abnormal conditions in advance through the prediction results provided by the system, and take timely measures, such as replacing new consumables or adjusting the treatment plan, to avoid affecting the treatment effect due to consumable problems. At the same time, the system can also automatically adjust the operating parameters of the nasal atomizer according to these prediction results 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 guardianship burden of parents, enabling parents to be more at ease in performing atomization treatment for their children.

[0105] In a specific embodiment, the activation of the sterilization module to perform sterilization treatment on the target consumable includes:

[0106] Perform zoning and positioning on the target consumable to obtain the corresponding consumable position;

[0107] Based on the consumable position, perform topological structure analysis on the target consumable to obtain topological structure information; wherein, the topological structure information refers to the spatial relationship and connection method between the consumable and surrounding components;

[0108] Through a preset ray tracing algorithm, optimize and adjust the irradiation angle of the sterilization module based on the topological structure information to obtain the adjusted angle and the sterilization module corresponding to the adjusted angle;

[0109] Obtain the physical characteristic parameters of the target consumable; wherein, the physical characteristic parameters include material and area;

[0110] Based on the physical characteristic parameters and the consumable position, perform power pre-allocation on the sterilization module corresponding to the adjusted angle to obtain the allocated power;

[0111] Start the sterilization module based on the allocated power to sterilize the consumables that exceed the preset usage intensity.

[0112] Specifically, this process is a series of automated sterilization treatment steps taken after the system detects that the usage intensity of the consumable exceeds the preset threshold to ensure the hygienic state of the consumable and prevent bacterial growth. First, the system will perform zonal positioning on the target consumable with an usage intensity exceeding the preset threshold to determine the specific position of the consumable within the nasal nebulizer. The zonal positioning is achieved through sensors and position detection modules within the RF communication module, which can accurately identify the position information of the consumable. For example, in a home environment, assuming the system detects that the usage intensity of an atomizing nozzle exceeds the preset threshold, the RF communication module will immediately perform zonal positioning on the atomizing nozzle to determine its specific position within the nebulizer. Next, the system will conduct a topological structure analysis on the target consumable based on its position to obtain topological structure information. Topological structure analysis refers to analyzing the spatial relationship and connection method between the consumable and its surrounding components, and this information is very important for subsequent sterilization treatment. For example, the system will analyze the relative position and connection method between the atomizing nozzle and other components (such as the atomizing chamber, air pump, etc.) to ensure that the sterilization module is not blocked or interfered by other components during irradiation. Assuming the atomizing nozzle is located at the center of the atomizing chamber and there are no other components blocking it, the system will record this topological structure information to provide basic data for subsequent irradiation angle optimization. Then, the system will optimize and adjust the irradiation angle of the sterilization module based on the topological structure information through a 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 consumable and achieve the best sterilization effect. For example, assuming the system learns through topological structure analysis that the atomizing nozzle is located at the center of the atomizing chamber and there are no blockers 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 atomizing nozzle. Next, the system will obtain the physical property parameters of the target consumable, which include the material and area of the consumable. The physical property parameters are crucial for 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 the material of the atomizing nozzle detected by the system is medical-grade silicone and the area is 10 square centimeters, the system will look up the corresponding sterilization parameters (such as the required irradiation time and power) from the preset database based on these physical property parameters. Based on these physical property parameters and the position of the consumable, the system will perform power pre-distribution on the sterilization module corresponding to the adjusted angle to obtain the allocated power. Power pre-distribution refers to calculating the power value that the sterilization module needs to output according to the specific situation of the consumable to ensure the safety and effectiveness of the sterilization process.For example, the system calculates that the power value to be output by the UV lamp is 10 watts based on the material and area of the atomizing nozzle, as well as its position within the atomizer, and assigns this power value to the sterilization module. Finally, the system starts the sterilization module based on the allocated power to sterilize the target consumable that exceeds the preset usage intensity. The sterilization module operates at the preset power for a period of time, irradiating the surface of the consumable with ultraviolet light to kill the bacteria and viruses attached thereto, ensuring that the hygienic conditions of the consumable meet the safety standards. For example, the system starts the UV lamp to irradiate the atomizing nozzle at a power of 10 watts for 10 minutes. After the sterilization process is completed, the system automatically turns off the UV lamp and sends a message through a preset notification mechanism to inform the parent that the consumable has been sterilized, ensuring that the parent can continue to use the nasal atomizer for the child's treatment with confidence. Through this series of steps, the system can not only automatically detect the usage intensity of the consumable, but also start the sterilization module for sterilization when necessary, ensuring that the consumable is always in good hygienic condition, thereby protecting the health and safety of the user. For example, in a home environment, parents can, through the information provided by the system, understand the usage situation and sterilization status of the consumable, replace the consumable in a timely manner, 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 atomizer 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 guardianship burden of parents, enabling parents to be more at ease in performing atomization treatment for their children.

[0113] In a specific embodiment, the topology structure analysis of the target consumable based on the position of the consumable to obtain topology structure information includes:

[0114] Using a spatial geometry algorithm, a spatial layout model of the consumable within the atomizer is modeled based on the position of the consumable to obtain a consumable space model;

[0115] 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 hierarchical structure and priority of the consumable within the atomizer;

[0116] Based on the target consumable, a consumable mapping is performed on the consumable topology hierarchy diagram to determine the consumable node corresponding to the target consumable in the consumable space model;

[0117] Connection analysis is performed on the consumable node to obtain a consumable connection diagram; wherein, the consumable connection diagram is used to display the direct connection relationship between the mapped consumable node and the surrounding consumable nodes;

[0118] Using the adjacency matrix algorithm, based on the consumable connection graph, calculate the distances and connectivity between each of the mapped consumables and the surrounding consumables to obtain a consumable node distance matrix; wherein, the consumable node distance matrix is used to quantify the tightness of the spatial relationship between consumables;

[0119] Based on the consumable node distance matrix, determine the core path to obtain the core topological path;

[0120] Perform topological structure information annotation on the core topological path to obtain topological structure information.

[0121] Specifically, this process is a crucial step in the detailed analysis of the topological structure of the consumable inside the atomizer after the system detects that the usage intensity of the consumable exceeds a preset threshold, in order to ensure that the sterilization module can effectively sterilize the consumable. First, the system uses a spatial geometry algorithm to model the spatial layout of the consumable inside the atomizer based on the position of the consumable, generating a consumable space model. The spatial geometry algorithm is a mathematical method through which the position and shape of the consumable in three-dimensional space can be accurately described. For example, in a home environment, assuming the system detects that the usage intensity of an atomizing 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 atomizing nozzle inside the atomizer. Next, the system performs hierarchical partitioning on the generated consumable space model to obtain a consumable topology hierarchy diagram. Hierarchical partitioning means dividing the consumable space model into multiple levels, each level representing different parts or components of the consumable, as well as their relative positional relationships and priorities. For example, the system divides the space inside the atomizer into multiple levels. The first level may include the atomizing nozzle and the atomizing chamber, and the second level may include the air pump and the control circuit board, etc. This hierarchical structure information helps with subsequent consumable mapping and node connection analysis. Suppose the generated consumable topology hierarchy diagram shows that the atomizing nozzle is located in the first level, surrounded by the atomizing chamber and other related components. Then, the system performs consumable mapping on the consumable topology hierarchy diagram based on the target consumable to determine the consumable node corresponding to the target consumable in the consumable space model. Consumable mapping means accurately positioning the target consumable in the topology hierarchy diagram to generate a mapped consumable node. For example, the system marks the atomizing nozzle with an excessive usage intensity in the topology hierarchy diagram to generate a mapped consumable node so that the position and hierarchical information of the consumable can be accurately identified during subsequent analysis. Next, the system performs connection analysis on the mapped consumable node to generate a consumable connection diagram. Connection analysis means analyzing the direct connection relationships between the mapped consumable node and the surrounding consumable nodes to generate a diagram showing these connection relationships. For example, the system analyzes the connection relationships between the mapped consumable (atomizing nozzle) and the surrounding components such as the atomizing chamber and the air pump to generate a consumable connection diagram. Suppose the consumable connection diagram shows that the atomizing nozzle is directly connected to the atomizing chamber, and the atomizing chamber is in turn connected to the air pump. Then, the system uses the adjacency matrix algorithm based on the consumable connection diagram to calculate the distances and connectivity between each mapped consumable and the surrounding consumables, generating a consumable node distance matrix. The adjacency matrix algorithm is a graph theory method through which the distances and connectivity between nodes in a graph can be calculated. For example, the system generates an adjacency matrix, and each element in the matrix represents the distance and connectivity between two consumable nodes. Suppose the generated consumable node distance matrix shows that the distance between the atomizing nozzle and the atomizing chamber is 1 and the connectivity is 1, and the distance between the atomizing chamber and the air pump is 2 and the connectivity is 1. Next, the system determines the core path based on the consumable node distance matrix to generate a core topology path.Core path determination refers to finding one or more critical paths from the consumable node distance matrix, which reflect the main connection relationships between consumable nodes. For example, the system determines a core path from the atomizing nozzle to the air pump from the consumable node distance matrix, and this path shows the main connection relationship from the atomizing nozzle to the air pump. Finally, the system annotates the topological structure information on the core topological path to generate topological structure information. Topological structure information annotation means adding detailed annotations and marks on the core topological path, and this information includes the names, positions, connection methods, etc. of each node. For example, the system annotates the names and positions of the atomizing nozzle, atomizing chamber, and air pump on the core topological path to generate detailed topological structure information. Suppose the generated topological structure information shows that the atomizing nozzle is located at the front end of the atomizer, is directly connected to the atomizing chamber, the atomizing chamber is located in the middle position and is connected to the air pump, and the air pump is located at the rear end. Through this series of steps, the system can not only perform accurate topological structure analysis on consumables with usage intensity exceeding the preset value, 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 usage intensity of the atomizing 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 atomizing nozzle to achieve the best sterilization effect. Parents can understand the usage situation and sterilization treatment status of the consumables through the information provided by the system, replace the 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 atomizer according to 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 guardianship burden of parents, enabling parents to be more at ease in performing atomization treatment for their children.

[0122] The push management method of the nasal atomizer in the embodiment of the present invention has been described above. Next, the push management device of the nasal atomizer in the embodiment of the present invention will be described. Please refer to Figure 2 , an embodiment of the push management device of the nasal atomizer in the embodiment of the present invention includes:

[0123] A reading module 21, configured to read the identifiers of various consumables of the target nasal atomizer through the radio frequency communication module to obtain the read consumable identifiers;

[0124] An analysis module 22, configured to perform type analysis on the read consumable identifiers to obtain the consumable analysis type and the normal working information corresponding to the consumable analysis type;

[0125] A monitoring module 23, configured to monitor the status of the consumables corresponding to the consumable analysis type through a preset timestamp algorithm to obtain the consumable status information;

[0126] A judgment module 24, configured to judge whether the corresponding consumable is working properly based on the consumable status information and the normal working information. If so, predict the usage intensity of the target nasal atomizer based on the consumable status information to obtain a prediction result;

[0127] A sterilization module 25, configured to, if the prediction result is that the usage intensity exceeds a preset usage intensity threshold, use the consumable with the usage intensity exceeding the preset as the target consumable, start the sterilization module to perform sterilization treatment on the target consumable, and send an information notification to the target user through a preset notification mechanism.

[0128] In this embodiment, for the specific implementation of each unit in the above device embodiment, please refer to that described in the above method embodiment, and details are not described herein again.

[0129] Refer to Figure 3 , this embodiment of the present invention further provides a computer device, the internal structure of which can be as Figure 3 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 of the computer design 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. The computer program, when executed by the processor, implements the above method.

[0130] Those skilled in the art can understand that Figure 3 the structure shown in

[0131] is only a block diagram of a part 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.

[0132] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. 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 methods. Among them, any reference to a memory, storage, database, or other medium provided by the present invention and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0133] It should be noted that in this document, the terms "including", "comprising", or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "including one..." does not exclude the existence of additional identical elements in the process, apparatus, article, or method that includes such element.

[0134] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally 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; By using a preset timestamp algorithm, the status of the consumables corresponding to the consumables analysis type is monitored 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 exceeding the preset usage intensity threshold 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; 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; Performing information analysis on the state probability vector to obtain consumables state information; wherein the consumables state information includes the working state, working mode and abnormal situation of the consumables; 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 exceeding a preset usage intensity threshold; 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 the surrounding consumable nodes 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 the 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.

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 predicting of the usage intensity 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 intensity of the target nasal atomizer is predicted based on the fractal dimension feature to obtain a prediction result.

5. 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; A sterilization module, for, if the predicted result is that the usage intensity exceeds a preset usage intensity threshold, taking the consumables exceeding the preset usage intensity threshold as target consumables, starting the sterilization module to sterilize the target consumables, and sending information to notify the target user through a preset notification mechanism; 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; Performing information analysis on the state probability vector to obtain consumables state information; wherein the consumables state information includes the working state, working mode and abnormal situation of the consumables; 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 exceeding a preset usage intensity threshold; 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 the surrounding consumable nodes 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 the 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.

6. 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 4 are implemented.

7. 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 4 are implemented.

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