IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials

Abstract

This invention discloses an IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials, belonging to the field of remote monitoring technology for pharmaceutical raw material drying. This IoT-based system includes a data monitoring module, a data transmission module, a remote monitoring module, and a drying evaluation module. The invention collects real-time data during the pharmaceutical raw material drying process and preprocesses it to obtain key data. Then, it uses this key data to obtain a comprehensive raw material loss compliance index and provides feedback. Finally, based on the comprehensive raw material loss compliance index and the energy consumption of the equipment, it obtains a comprehensive drying evaluation index and performs a comprehensive evaluation to obtain a comprehensive evaluation result. This achieves the effect of reducing the raw material loss rate in remotely monitored pharmaceutical raw material mixing and drying, solving the problem of high raw material loss rates in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of remote monitoring technology for pharmaceutical raw material drying, and more particularly to a pharmaceutical raw material remote monitoring and mixing drying system based on the Internet of Things. Background Technology

[0002] With the continuous development of IoT technology and the expansion of its application areas, various high-tech terminals have emerged. The pharmaceutical industry holds a pivotal position in my country, and the drying process for pharmaceutical raw materials is not only a crucial step in ensuring the quality and efficacy of medicinal materials, but also an important means of improving production efficiency, reducing costs, meeting the needs of large-scale production, and enhancing drug quality and safety. The IoT, by enabling remote monitoring and management of the mixing and drying of pharmaceutical raw materials, promotes the intelligentization and efficiency of the medical industry.

[0003] Existing remote monitoring and mixing drying methods for pharmaceutical raw materials use sensors to monitor key parameters inside and around the drying equipment. Based on the collected data, an intelligent control system automatically adjusts the operating parameters of the drying equipment. Operators can remotely monitor the drying process through a secure network connection, ensuring the continuity and safety of the production process.

[0004] For example, the invention patent announcement CN105974902B discloses an IoT-based smart shoe cabinet system and control method. Without manual control by the user, the system automatically detects whether shoes are placed on the shoe trees using linear Hall effect sensors installed on the shoe trees. When shoes are placed in, temperature and humidity sensors and semiconductor air quality sensors detect the temperature, humidity, and concentration of pollutants inside the shoes. Under the control of the main control processor, the system automatically completes the sterilization, deodorization, drying, and dehumidification of the shoes. The real-time working status is transmitted to an external cloud server and mobile client via a Wi-Fi module, allowing users to check and control the working status of the shoe cabinet at any time.

[0005] For example, the invention patent announcement CN104049623B discloses a remote real-time monitoring and management system for grain dryers based on the Internet of Things. The monitoring center is used to remotely monitor the working status and security status of all the dryers under its management. The central display screen is used to display and monitor information collected from all dryers on-site, including grain flow rate, drying speed, start / stop status, running time, drying temperature, and grain moisture content. The monitoring center sets warning lines for the operating parameters of the dryers based on the model of the grain dryer and the local climate. The warning line parameters are obtained from the optimal algorithm mathematical model. Once the operating parameters of the dryer exceed the warning line during operation, the computer will immediately alarm and the monitoring center will send a control command to the dryer located in another location to stop the equipment. The monitoring center provides a database to store historical data in order to provide trend data and print business data reports.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, excessively high temperatures during the drying process of pharmaceutical raw materials can lead to the loss of active ingredients, while excessively low temperatures may result in excessively long drying times, increasing the risk of raw material deterioration. Improper humidity control may also lead to condensation or over-drying of the raw material surface, resulting in a high raw material loss rate during remote monitoring of mixed drying of pharmaceutical raw materials. Summary of the Invention

[0008] This application provides an IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials, which solves the problem of high raw material loss rate in the remote monitoring and mixing drying of pharmaceutical raw materials in the prior art, and achieves a reduction in the raw material loss rate in the remote monitoring and mixing drying of pharmaceutical raw materials.

[0009] This application provides an IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials, comprising: a data monitoring module, a data transmission module, a remote monitoring module, and a drying evaluation module. The data monitoring module collects real-time data during the drying process of pharmaceutical raw materials, preprocesses the collected real-time data to obtain key data, and stores it. The data transmission module encapsulates the key data and transmits it to the pharmaceutical raw material remote monitoring and mixing drying supervision platform, where the platform restores the data. The remote monitoring module displays the real-time status and historical data of the drying process. It obtains a comprehensive raw material loss compliance index by monitoring temperature and humidity during the drying process, as well as the quality changes of the pharmaceutical raw materials before and after drying, and provides feedback on this index. The comprehensive raw material loss compliance index describes the degree of compliance between the actual raw material loss and the reference loss in the pharmaceutical raw material remote monitoring and mixing drying system. The drying evaluation module obtains a comprehensive drying evaluation index based on the comprehensive raw material loss compliance index and the energy consumption of the equipment. It then performs a comprehensive evaluation based on the comprehensive drying evaluation index to obtain a comprehensive evaluation result, which is visualized in a chart. The comprehensive drying evaluation index describes the comprehensive drying performance of the pharmaceutical raw material remote monitoring and mixing drying system, and the comprehensive evaluation result describes the equipment performance of the pharmaceutical raw material remote monitoring and mixing drying system.

[0010] Furthermore, the data monitoring module includes a real-time data acquisition unit and a data processing unit; the real-time data acquisition unit is used to collect real-time data during the drying process of pharmaceutical raw materials and transmit it to the data processing unit, the real-time data including temperature, humidity, airflow speed and the quality of the pharmaceutical raw materials to be dried; the data processing unit is used to preprocess the real-time data to obtain key data and perform storage management, the preprocessing includes data cleaning, data verification and data compression.

[0011] Furthermore, the specific preprocessing process is as follows: the collected real-time data is cleaned to obtain first real-time data, the data cleaning including outlier removal and missing value filling; parity check is performed on the first real-time data to obtain second real-time data; and Gzip compression is performed on the second real-time data to obtain key data.

[0012] Furthermore, the data transmission module includes a key data encapsulation unit, a key data communication unit, and a key data restoration unit; the key data encapsulation unit is used to encapsulate the acquired key data and transmit it to the key data communication unit; the key data communication unit is used to transmit the encapsulated key data to the pharmaceutical raw material remote monitoring and mixing drying supervision platform via optical fiber; the key data restoration unit is used to decompress and restore the received encapsulated key data and automatically back it up before restoration.

[0013] Furthermore, the remote monitoring module includes a data display unit, a monitoring and alarm unit, and a data storage unit. The data display unit is used to display key data and historical data restored by the pharmaceutical raw material remote monitoring and mixing drying supervision platform in real time. The monitoring and alarm unit obtains the comprehensive raw material loss compliance index based on the key data from the data display unit and determines whether the comprehensive raw material loss compliance index is within a preset threshold range. If it exceeds the preset threshold range, an audible and visual alarm is triggered; otherwise, the comprehensive raw material loss compliance index is transmitted to the data management database. The data storage unit is used to store and back up the key data, historical data, and comprehensive raw material loss compliance index.

[0014] Furthermore, the specific method for obtaining the comprehensive raw material loss compliance index is as follows: The pharmaceutical raw materials to be dried are numbered according to their type, and the mass of the corresponding numbered pharmaceutical raw material is obtained. This mass is used to describe the initial mass of the pharmaceutical raw material. The mass of the pharmaceutical raw material during the drying process is obtained within a preset time interval, and it is determined whether the obtained mass of the pharmaceutical raw material has at least two consecutive identical values. If so, the mass of the pharmaceutical raw material at this time is recorded as the final mass; otherwise, the mass of the pharmaceutical raw material continues to be obtained until the final mass is obtained. The comprehensive raw material loss compliance index is obtained through the change in the mass of the pharmaceutical raw material, based on the comprehensive raw material loss reference deviation and a preset weight.

[0015] Furthermore, the comprehensive raw material loss compliance index is calculated using the following formula:

[0016] ;

[0017] In the formula, This indicates that the overall raw material loss conforms to the index. Indicates the type code of pharmaceutical raw materials. , This indicates the total number of pharmaceutical raw materials. Indicates the quality of the i-th pharmaceutical raw material. This represents the final quality of the i-th pharmaceutical raw material. This represents the preset weight of the i-th pharmaceutical raw material. This represents the reference deviation for the quality loss of the i-th pharmaceutical raw material.

[0018] Furthermore, the specific method for obtaining the comprehensive drying evaluation index is as follows: During the drying process of pharmaceutical raw materials, the temperature of the raw materials within a preset time interval is obtained using an infrared thermometer. The average temperature during the drying process is statistically analyzed, and corresponding preset thresholds and reference deviations are also obtained. The humidity of the pharmaceutical raw materials during the drying process is obtained using a humidity sensor deployed in the drying system within a preset time interval. The average humidity during the drying process is statistically analyzed, and corresponding preset thresholds and reference deviations are also obtained. The comprehensive raw material loss compliance index of the pharmaceutical raw materials is obtained, along with corresponding preset thresholds and reference deviations. The comprehensive drying evaluation index is obtained by combining the evaluation weights obtained from a preset database. These evaluation weights include temperature weight, humidity weight, and comprehensive raw material loss compliance index weight.

[0019] Furthermore, the comprehensive drying evaluation index is calculated using the following formula:

[0020] ;

[0021] In the formula, Indicates the type code of pharmaceutical raw materials. , R represents the total number of pharmaceutical raw materials, and R represents the comprehensive drying evaluation index of pharmaceutical raw materials. Let represent the average temperature change during the drying process of the i-th pharmaceutical raw material. This indicates the preset temperature threshold during the drying process of pharmaceutical raw materials. Indicates the reference deviation for temperature accuracy. This represents the average change in humidity during the drying process of the i-th pharmaceutical raw material. This indicates the preset threshold for humidity during the drying process of pharmaceutical raw materials. Indicates the reference deviation for humidity accuracy. This indicates that the overall raw material loss of pharmaceutical raw materials conforms to the index. This indicates that the overall raw material loss conforms to the index accuracy reference deviation. Indicates temperature weighting. Indicates humidity weight. This indicates that the overall raw material loss conforms to the index weighting.

[0022] Furthermore, the specific process of obtaining the comprehensive evaluation result based on the comprehensive drying evaluation index is as follows: obtaining the comprehensive drying evaluation index, classifying the grades according to the comprehensive drying evaluation index to obtain the grade classification result, the grade classification result being used to visualize the comprehensive drying evaluation index; drawing a comprehensive drying evaluation comparison chart based on the grade classification result to obtain the comprehensive evaluation result, and drawing a drying evaluation comparison chart in combination with the comprehensive raw material loss compliance index and drying data, the drying data representing key data in the operation process of the pharmaceutical raw material remote monitoring mixing and drying system.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0024] 1. By collecting real-time data during the drying process of pharmaceutical raw materials and preprocessing it to obtain key data, which is then stored, the key data is encapsulated and transmitted to the pharmaceutical raw material remote monitoring and mixing drying supervision platform for data restoration. Then, by monitoring the data of the drying process, a comprehensive raw material loss compliance index is obtained and fed back. Finally, a comprehensive evaluation is conducted to obtain a comprehensive evaluation result. This achieves the timeliness of the operation of the pharmaceutical raw material remote monitoring and mixing drying system, thereby reducing the raw material loss rate in the remote monitoring and mixing drying of pharmaceutical raw materials and effectively solving the problem of high raw material loss rate in the existing technology for remote monitoring and mixing drying of pharmaceutical raw materials.

[0025] 2. By numbering the pharmaceutical raw materials to be dried according to their types, and obtaining the initial and final quality of the corresponding numbered pharmaceutical raw materials, and by obtaining the comprehensive raw material loss compliance index based on the changes in the quality of pharmaceutical raw materials, the comprehensive raw material loss reference deviation, and the preset weights, the raw material loss situation is quantified, thereby enabling a more accurate assessment of the raw material loss rate of the remote monitoring and mixing drying system for pharmaceutical raw materials.

[0026] 3. By obtaining the average temperature and humidity during the drying process of pharmaceutical raw materials, and based on the comprehensive raw material loss compliance index and evaluation weight, a comprehensive drying evaluation index is calculated. This enables the quantification of the comprehensive drying performance of the remote monitoring mixed drying system for pharmaceutical raw materials, thereby achieving a more accurate evaluation of the comprehensive drying performance of the remote monitoring mixed drying system for pharmaceutical raw materials. Attached Figure Description

[0027] Figure 1 A schematic diagram of the structure of a pharmaceutical raw material remote monitoring, mixing and drying system based on the Internet of Things provided in this application embodiment;

[0028] Figure 2 A schematic diagram of the data monitoring module in the IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials provided in this application embodiment;

[0029] Figure 3 A schematic diagram of the structure of the remote monitoring module in the IoT-based pharmaceutical raw material remote monitoring and mixing drying system provided in this application embodiment;

[0030] Figure 4 The graph shows the changes in the comprehensive drying evaluation index provided in the embodiments of this application. Detailed Implementation

[0031] This application provides an IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials, which solves the problem of high raw material loss rate in the remote monitoring and mixing drying of pharmaceutical raw materials in the prior art. It collects real-time data during the drying process, preprocesses the collected data to obtain key data, and stores it. Then, the key data is encapsulated and transmitted to the remote monitoring and mixing drying supervision platform for pharmaceutical raw materials. The platform restores the data, monitors temperature and humidity during the drying process, and calculates a comprehensive raw material loss compliance index based on the quality changes of the pharmaceutical raw materials before and after drying. This index is then fed back. Finally, a comprehensive drying evaluation index is obtained based on the comprehensive raw material loss compliance index and the energy consumption of the equipment, and a comprehensive evaluation result is obtained. This achieves a reduction in the raw material loss rate during the remote monitoring and mixing drying of pharmaceutical raw materials.

[0032] The technical solution in this application embodiment aims to address the problem of high raw material loss rate during remote monitoring and mixing drying of pharmaceutical raw materials. The overall approach is as follows:

[0033] By collecting real-time data during the drying process of pharmaceutical raw materials and preprocessing it to obtain key data, the key data is then packaged and transmitted to the regulatory platform for data restoration. Subsequently, a comprehensive raw material loss compliance index is obtained from the key data and feedback is provided. Finally, a comprehensive evaluation is conducted to obtain the comprehensive evaluation result, which achieves the effect of reducing the raw material loss rate in the remote monitoring of pharmaceutical raw material mixing and drying.

[0034] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0035] like Figure 1The diagram shown is a structural schematic of the IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials provided in this embodiment of the application. The IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials provided in this embodiment includes: a data monitoring module, a data transmission module, a remote monitoring module, and a drying evaluation module. The data monitoring module collects real-time data during the drying process of pharmaceutical raw materials, preprocesses the collected real-time data to obtain key data, and stores it. The data transmission module encapsulates the key data and transmits it to the pharmaceutical raw material remote monitoring and mixing drying supervision platform, where the platform performs data reconstruction. The remote monitoring module displays the real-time status and historical data of the drying process. By monitoring the temperature and humidity during the drying process, as well as the quality changes of pharmaceutical raw materials before and after drying, a comprehensive raw material loss compliance index is obtained and fed back. The comprehensive raw material loss compliance index is used to describe the degree of compliance between the actual raw material loss and the reference loss in the remote monitoring mixed drying system for pharmaceutical raw materials. The drying evaluation module is used to obtain a comprehensive drying evaluation index based on the comprehensive raw material loss compliance index and the energy consumption of the equipment. A comprehensive evaluation is then performed based on the comprehensive drying evaluation index to obtain a comprehensive evaluation result, which is visualized in the form of charts. The comprehensive drying evaluation index is used to describe the comprehensive drying performance of the remote monitoring mixed drying system for pharmaceutical raw materials, and the comprehensive evaluation result is used to describe the equipment performance of the remote monitoring mixed drying system for pharmaceutical raw materials.

[0036] In this embodiment, the raw material loss situation is judged by the comprehensive raw material loss compliance index. If the comprehensive raw material loss compliance index exceeds a preset threshold, it indicates that an abnormality has occurred in the drying process. The preset threshold is set by professionals according to industry standards or business objectives in the medical field. When the system detects an abnormality, it will issue a feedback alarm to prevent further loss of raw materials. Since factors such as temperature and humidity affect the drying process, the calculation of the comprehensive drying evaluation index can further comprehensively evaluate the drying process and assess the comprehensive drying performance of the pharmaceutical raw material remote monitoring mixed drying system. This achieves the accuracy of the raw material loss rate in the pharmaceutical raw material remote monitoring mixed drying system.

[0037] Furthermore, such as Figure 2 The diagram shown is a structural schematic of the data monitoring module in the IoT-based remote monitoring and mixing drying system for pharmaceutical raw materials provided in this application embodiment. The data monitoring module includes a real-time data acquisition unit and a data processing unit. The real-time data acquisition unit is used to collect real-time data during the drying process of pharmaceutical raw materials and transmit it to the data processing unit. The real-time data includes temperature, humidity, airflow speed, and the quality of the pharmaceutical raw materials to be dried. The data processing unit is used to preprocess the real-time data to obtain key data and perform storage management. The preprocessing includes data cleaning, data verification, and data compression.

[0038] In this embodiment, during the transmission of real-time data from the data acquisition unit to the data processing unit, data loss may occur due to various reasons such as sensor malfunction and data transmission problems. If these missing values ​​are not processed, they will lead to inaccurate calculations in the later stages. Outliers are usually caused by measurement errors, equipment malfunctions, or other unforeseen factors. These values ​​can seriously interfere with the accuracy of data analysis. Therefore, they need to be identified and removed using statistical methods or domain knowledge. Commonly used statistical methods include the quartile method and the normal distribution method. Outliers are initially identified using statistical methods. Outliers can be obtained by calculating the mean and standard deviation of the data. Outliers are defined as observations that differ from the mean by more than a certain number of standard deviations, generally twice. Then, a reasonable range is set according to the business rule logic, and the accuracy of the outliers is judged by professionals. The collected real-time data is stored and managed, which can include databases, file systems, and cloud storage, to ensure data security and reliability. This improves the accuracy of data acquisition in the pharmaceutical raw material remote monitoring and mixing drying system.

[0039] Furthermore, the specific preprocessing process is as follows: the collected real-time data is cleaned to obtain the first real-time data, including outlier removal and missing value filling; parity checking is performed on the first real-time data to obtain the second real-time data; and Gzip compression is performed on the second real-time data to obtain key data.

[0040] In this embodiment, outliers detected based on business rules are replaced with values ​​within a reasonable range, or these data points are directly deleted, and the missing data is filled in by interpolation to obtain the first real-time data; parity bits are added to the data to obtain the second real-time data, and methods such as format verification, range verification, consistency verification, and uniqueness verification can also be used; the second real-time data is losslessly compressed using the Gzip algorithm to reduce storage space and improve transmission efficiency, thereby obtaining key data; thus improving the data reliability of the pharmaceutical raw material remote monitoring and mixing drying system.

[0041] Furthermore, the data transmission module includes a key data encapsulation unit, a key data communication unit, and a key data restoration unit. The key data encapsulation unit encapsulates the acquired key data and transmits it to the key data communication unit. The key data communication unit transmits the encapsulated key data to the pharmaceutical raw material remote monitoring and mixing drying supervision platform via optical fiber. The key data restoration unit decompresses and restores the received encapsulated key data and automatically backs it up before restoration.

[0042] In this embodiment, the process of encapsulating the acquired key data includes data encryption and verification. Symmetric or asymmetric encryption algorithms (such as Advanced Encryption Standard and Rivest-Shamir-Adleman) can be used to encrypt the data, and a checksum (such as Cyclic Redundancy Check) is generated to verify the integrity of the data. The encapsulated information is transmitted using a fiber optic network. When the transmission distance is long, relay equipment can be used to ensure the signal strength and stability. After receiving the key data after data encapsulation, the corresponding decompression algorithm is used to restore the data to its original size, and the decryption algorithm corresponding to the encryption is used to restore the data content. The integrity of the data is verified by the checksum. Finally, automatic backup is performed before data restoration to ensure the security of the data during the decapsulation process. This improves the data security of the pharmaceutical raw material remote monitoring and mixing drying system.

[0043] Furthermore, such as Figure 3 The diagram shows the structure of the remote monitoring module in the IoT-based pharmaceutical raw material remote monitoring and mixing drying system provided in this application embodiment. The remote monitoring module includes a data display unit, a monitoring and alarm unit, and a data storage unit. The data display unit is used to display key data and historical data restored by the pharmaceutical raw material remote monitoring and mixing drying supervision platform in real time. The real-time display means that dynamic and real-time updated charts and datasets are created using Power BI data visualization tools. The monitoring and alarm unit obtains the comprehensive raw material loss compliance index based on the key data from the data display unit and determines whether the comprehensive raw material loss compliance index is within a preset threshold range. If it exceeds the preset threshold range, an audible and visual alarm is triggered; otherwise, the comprehensive raw material loss compliance index is transmitted to the data management database. The data storage unit is used to store and back up the key data, historical data, and comprehensive raw material loss compliance index.

[0044] In this embodiment, the data display unit is responsible for displaying key and historical data in real time during the drying process. Using data visualization tools such as Power BI, it creates dynamic and real-time updated charts and datasets. Key and historical data are transmitted to Power BI via API interfaces or data pipelines for real-time graphical display. Based on the acquired key information, it monitors the comprehensive raw material loss compliance index in real time to determine if any anomalies exist. If an anomaly is detected, it triggers an audible and visual alarm. Simultaneously, it uploads the comprehensive raw material loss rate to the data management database and archives historical data, freeing up storage space and improving system performance. This achieves visualization of raw material loss in the pharmaceutical raw material remote monitoring and mixing drying platform.

[0045] Furthermore, the specific method for obtaining the comprehensive raw material loss compliance index is as follows: The raw materials to be dried are numbered according to their type, and the mass of the corresponding numbered raw material is obtained. This mass describes the initial mass of the raw material. During the drying process, the mass of the raw materials is obtained within a preset time interval. It is determined whether the obtained mass has at least two consecutive identical values. If so, the mass at that time is recorded as the final mass; otherwise, the mass is obtained until the final mass is obtained. The comprehensive raw material loss compliance index is obtained based on the changes in the raw material mass and according to the comprehensive raw material loss reference deviation and preset weights. The preset weights represent the degree of influence of each raw material on the comprehensive raw material loss compliance index.

[0046] In this embodiment, each pharmaceutical raw material is numbered before drying to ensure that each raw material has a unique identifier throughout the process. The quality of the pharmaceutical raw materials before drying is obtained, and the difference between the final quality and the initial quality is the loss of the raw materials. Professionals obtain a comprehensive raw material loss reference deviation by referring to industry standards and historical data. By having professionals preset the influence of each pharmaceutical raw material on the comprehensive raw material loss compliance index, the influence of each pharmaceutical raw material on the comprehensive raw material loss compliance index is preset, thus realizing the specification of the types of pharmaceutical raw material losses during the remote monitoring and mixing drying process.

[0047] Furthermore, the comprehensive raw material loss compliance index is calculated using the following formula:

[0048] ;

[0049] In the formula, This indicates that the overall raw material loss conforms to the index. Indicates the type code of pharmaceutical raw materials. , This indicates the total number of pharmaceutical raw materials. Indicates the quality of the i-th pharmaceutical raw material. This represents the final quality of the i-th pharmaceutical raw material. This represents the preset weight of the i-th pharmaceutical raw material. This represents the reference deviation for the quality loss of the i-th pharmaceutical raw material.

[0050] In this embodiment, assuming K=3, the comprehensive raw material loss compliance index can be calculated using the above method. The statistical table of changes in the comprehensive raw material loss compliance index is shown in Table 1.

[0051] Table 1. Statistical Table of Changes in the Comprehensive Raw Material Loss Consistency Index

[0052]

[0053] The Comprehensive Raw Material Loss Compliance Index (CRCI) can be used to measure the overall loss of raw materials. A CRCI within a preset threshold range indicates that the loss of raw materials is still within a controllable range. An abnormal CRCI outside the range indicates that the loss of raw materials differs significantly from the reference value, requiring further inspection or calibration. Since different raw materials contribute differently to the CRCI, raw materials with higher weights (such as the second raw material in the table) have a greater impact on the CRCI and therefore require more attention in loss management. The preset threshold range is set by professionals based on industry standards, thus enabling a numerical assessment of the CRCI.

[0054] Furthermore, the specific method for obtaining the comprehensive drying assessment index is as follows: During the drying process of pharmaceutical raw materials, the temperature of the pharmaceutical raw materials within a preset time interval is obtained using an infrared thermometer. The average temperature during the drying process is statistically analyzed, and the corresponding preset threshold and reference deviation are also obtained. The humidity of the pharmaceutical raw materials during the drying process is obtained by collecting data from humidity sensors deployed in the drying system within a preset time interval. The average humidity during the drying process is statistically analyzed, and the corresponding preset threshold and reference deviation are also obtained. The comprehensive raw material loss compliance index of the pharmaceutical raw materials is obtained, along with the corresponding preset threshold and reference deviation. The comprehensive drying assessment index is obtained by combining the assessment weights obtained from the preset database. The assessment weights include temperature weight, humidity weight, and comprehensive raw material loss compliance index weight.

[0055] In this embodiment, temperature weight represents the degree of influence of temperature change on the comprehensive drying assessment index, humidity weight represents the degree of influence of humidity change on the comprehensive drying assessment index, and comprehensive raw material loss compliance index weight represents the degree of influence of the comprehensive raw material loss compliance index on the comprehensive drying assessment index. Specifically, temperature weight is obtained from a preset database. In a specific embodiment, the relationship between the energy consumed by the heating equipment during the drying process and the corresponding working time during a historical period is fitted to obtain a curve, and the corresponding temperature weight is determined based on the fitted curve. Humidity weight is obtained from a preset database. The relationship between the energy consumed by the drying equipment during the drying process and the corresponding working time during a historical period is fitted to obtain a curve, and the corresponding humidity weight is determined based on the fitted curve. The comprehensive raw material loss compliance index weight is set by professionals based on historical data and professional rules in the field.

[0056] Specifically, a comprehensive drying assessment index is obtained by combining temperature, humidity, and a comprehensive raw material loss compliance index. Temperature can be obtained through an infrared thermometer or a temperature sensor deployed on the drying equipment, along with corresponding preset thresholds and reference deviations. These values ​​are used to assess the stability and compliance of temperature during the drying process. Humidity changes are obtained through a humidity sensor, along with corresponding preset thresholds and reference deviations, to assess the control and rationality of humidity during the drying process. The comprehensive raw material loss compliance index is obtained by having professionals preset corresponding weights and obtain corresponding reference deviations based on historical data, thus calculating the comprehensive drying assessment index. This enables remote monitoring of the stability of the pharmaceutical raw material mixing and drying system.

[0057] Furthermore, the comprehensive drying assessment index is calculated using the following formula:

[0058] ;

[0059] In the formula, Indicates the type code of pharmaceutical raw materials. , R represents the total number of pharmaceutical raw materials, and R represents the comprehensive drying evaluation index of pharmaceutical raw materials. Let represent the average temperature change during the drying process of the i-th pharmaceutical raw material. This indicates the preset temperature threshold during the drying process of pharmaceutical raw materials. Indicates the reference deviation for temperature accuracy. This represents the average change in humidity during the drying process of the i-th pharmaceutical raw material. This indicates the preset threshold for humidity during the drying process of pharmaceutical raw materials. Indicates the reference deviation for humidity accuracy. This indicates that the overall raw material loss of pharmaceutical raw materials conforms to the index. This indicates that the overall raw material loss conforms to the index accuracy reference deviation. Indicates temperature weighting. Indicates humidity weight. This indicates that the overall raw material loss conforms to the index weighting.

[0060] In this embodiment, the main indicators during the drying process include temperature, humidity, and the comprehensive raw material loss compliance index. Therefore, taking the study of the changes in the comprehensive drying assessment index with the average changes in the comprehensive raw material loss compliance index and temperature as an example, the correlation and mutual influence between the main indicators are considered through quantitative methods. A mathematical formula is established through comprehensive analysis, which can accurately quantify the degree of comprehensive drying.

[0061] like Figure 4The diagram shows the change of the comprehensive drying evaluation index provided in this embodiment. When the total number of pharmaceutical raw materials is 3, the corresponding weights are: temperature 0.4, humidity 0.3, comprehensive raw material loss compliance index 0.3, preset temperature threshold 25°C, preset humidity threshold 50%, fixed average humidity change constant 45%, temperature accuracy reference deviation 5°C, humidity accuracy reference deviation 10%, and comprehensive raw material loss compliance index accuracy reference deviation 0.1. Taking the average temperature change as an example, the comprehensive drying evaluation index gradually increases as the average temperature change increases; thus, the comprehensive drying degree of the pharmaceutical raw material remote monitoring mixed drying system is effectively judged.

[0062] Furthermore, the specific process for obtaining the comprehensive evaluation result based on the comprehensive drying evaluation index is as follows: The comprehensive drying evaluation index is obtained; the index is used to classify the grades, and these grades are used to visualize the comprehensive drying evaluation index; a comprehensive drying evaluation comparison chart is drawn based on the grade classification results to obtain the comprehensive evaluation result; and a drying evaluation comparison chart is drawn by combining the comprehensive raw material loss compliance index and drying data. The drying evaluation comparison chart includes scatter plots, line graphs, time series dynamic graphs, and safety charts. The drying data represents key data during the operation of the pharmaceutical raw material remote monitoring mixing and drying system.

[0063] In this embodiment, the general grading methods include weighted average, worst-case performance, multi-factor analysis, fuzzy comprehensive evaluation, analytic hierarchy process (AHP), and principal component analysis. Each method has different applicability; for example, the weighted average is suitable for situations where there are clear priorities or differences in importance among indicators. Specifically, one or more methods can be selected for comprehensive grading based on the actual situation. The drying evaluation comparison charts include scatter plots, line graphs, time-series dynamic graphs, and safety charts, which can be drawn using various data visualization tools and libraries such as Matplotlib in Python. For example, a safety chart for temperature and humidity can be drawn to indicate the safe operating range and check if any data points exceed the safe range. This achieves improved accuracy and visualization of the comprehensive drying evaluation index.

[0064] In summary, this application embodiment collects real-time data during the drying process of pharmaceutical raw materials, preprocesses it to obtain key data, and stores it. Then, the key data is encapsulated and transmitted to the pharmaceutical raw material remote monitoring and mixing drying supervision platform for data restoration. Then, the comprehensive raw material loss compliance index is obtained by monitoring the data of the drying process and feedback is provided. Finally, a comprehensive evaluation is performed to obtain a comprehensive evaluation result. This achieves the timeliness of the operation of the pharmaceutical raw material remote monitoring mixing drying system, thereby reducing the raw material loss rate in the remote monitoring of pharmaceutical raw material mixing drying.

[0065] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0066] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 The device that provides the performance specified in one or more boxes.

[0067] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The performance specified in one or more boxes.

[0068] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The performance steps specified in one or more boxes.

[0069] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0070] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A mixed drying system for remote monitoring of pharmaceutical raw materials based on the Internet of Things, characterized in that, The data monitoring module, the data transmission module, the remote monitoring module and the drying evaluation module are comprised; The data monitoring module is used for collecting real-time data in the drying process of the pharmaceutical raw materials, and pre-processing the collected real-time data to obtain key data and store them; The data transmission module is used for data encapsulation and transmission of the key data to the pharmaceutical raw material remote monitoring mixed drying supervision platform, and data restoration by the pharmaceutical raw material remote monitoring mixed drying supervision platform; The remote monitoring module is used for displaying the real-time state and historical data of the drying process, and obtaining a comprehensive raw material loss compliance index through temperature monitoring and humidity monitoring of the drying process, and quality change of the pharmaceutical raw materials before and after drying, and feeding back the comprehensive raw material loss compliance index, which is used for describing the compliance degree of the actual raw material loss and the reference loss of the pharmaceutical raw material remote monitoring mixed drying system; The drying evaluation module is used for obtaining a comprehensive drying evaluation index according to the comprehensive raw material loss compliance index and the energy consumption of the equipment, and obtaining a comprehensive evaluation result according to the comprehensive drying evaluation index, and visualizing the comprehensive evaluation result in the form of a chart, the comprehensive drying evaluation index is used for describing the comprehensive drying performance of the pharmaceutical raw material remote monitoring mixed drying system, and the comprehensive evaluation result is used for describing the equipment performance of the pharmaceutical raw material remote monitoring mixed drying system; The remote monitoring module comprises a data display unit, a monitoring alarm unit and a data storage unit; The data display unit is used for real-time display of the key data and historical data restored by the pharmaceutical raw material remote monitoring mixed drying supervision platform; The monitoring alarm unit obtains the comprehensive raw material loss compliance index according to the key data of the data display unit, judges whether the comprehensive raw material loss compliance index is within a preset threshold range, if it is out of the preset threshold range, it will sound and light alarm, otherwise the comprehensive raw material loss compliance index will be transmitted to the data management library; The comprehensive raw material loss compliance index is calculated by the following formula: ； In the formula, denotes that the comprehensive raw material loss conforms to the index, denotes the medical raw material type number, , denotes the total number of medical raw materials, denotes the mass of the i-th medical raw material, denotes the final mass of the i-th medical raw material, denotes the preset weight of the i-th medical raw material, denotes the i-th medical raw material mass loss reference deviation; The data display unit uses the Power BI data visualization tool to create dynamic and real-time updated charts and datasets, and transmits the key data and historical data to Power BI through an API interface or a data stream pipeline for graphical display of real-time data; The specific acquisition method of the comprehensive raw material loss compliance index is as follows: According to the type of the pharmaceutical raw materials, the to-be-dried pharmaceutical raw materials are numbered, the quality of the corresponding numbered pharmaceutical raw materials is obtained, and the quality of the pharmaceutical raw materials is used to describe the initial quality of the pharmaceutical raw materials; In a preset time interval, the quality of the pharmaceutical raw materials in the drying process is obtained, and it is judged whether the obtained quality of the pharmaceutical raw materials has at least two consecutive same values, if it has, the quality of the pharmaceutical raw materials at this time is recorded as the final quality, otherwise the quality of the pharmaceutical raw materials is continuously obtained until the final quality is obtained; The change of the quality of the pharmaceutical raw materials is obtained, and the comprehensive raw material loss compliance index is obtained according to the comprehensive raw material loss reference deviation and the preset weight.

2. The system according to claim 1, wherein the system is characterized by: The data monitoring module comprises a real-time data acquisition unit and a data processing unit; The real-time data acquisition unit is used for acquiring real-time data in the drying process of the medical raw material and transmitting the real-time data to the data processing unit, wherein the real-time data includes temperature, humidity, air flow speed and mass of the medical raw material to be dried; The data processing unit is used for pre-processing the real-time data to obtain key data and performing storage management, wherein the pre-processing includes data cleaning, data verification and data compression.

3. The system according to claim 1, wherein the system further comprises a drying device. The specific process of the pre-processing is as follows: The collected real-time data is subjected to data cleaning to obtain first real-time data, wherein the data cleaning includes removing abnormal value processing and missing value filling processing; The first real-time data is subjected to odd-even verification to obtain second real-time data; The second real-time data is subjected to Gzip compression to obtain key data.

4. The system according to claim 1, wherein the system further comprises a drying device. The data transmission module includes a key data packaging unit, a key data communication unit and a key data restoration unit; The key data packaging unit is used for packaging the obtained key data and transmitting the packaged key data to the key data communication unit; The key data communication unit is used for transmitting the packaged key data to the medical raw material remote monitoring mixed drying supervision platform through optical fiber transmission; The key data restoration unit is used for decompressing and restoring the received packaged key data and automatically backing up the key data before the restoration.

5. The hybrid drying system for remote monitoring of pharmaceutical raw materials based on the Internet of Things according to claim 1, characterized in that, The remote monitoring module includes a data display unit, a monitoring alarm unit and a data storage unit; The data storage unit is used for storing and backing up the key data, historical data and comprehensive raw material loss compliance index.

6. The system according to claim 1, wherein the system further comprises a drying device. The specific acquisition method of the comprehensive drying evaluation index is as follows: In the drying process of the medical raw material, the temperature of the medical raw material in a preset time interval is obtained by an infrared thermometer, the mean value of the temperature in the drying process of the medical raw material is obtained by statistics, and a corresponding preset threshold and reference deviation are obtained; The humidity of the medical raw material in the drying process in a preset time interval is obtained by a humidity sensor arranged in the drying system, the mean value of the humidity in the drying process of the medical raw material is obtained by statistics, and a corresponding preset threshold and reference deviation are obtained; The comprehensive raw material loss compliance index of the medical raw material is obtained, and a corresponding preset threshold and reference deviation are obtained; The comprehensive drying evaluation index is obtained in combination with evaluation weights obtained from a preset database, wherein the evaluation weights include temperature weight, humidity weight and comprehensive raw material loss compliance index weight.

7. The system according to claim 6, wherein the system further comprises a drying device. The comprehensive drying evaluation index is calculated by the following formula: ； In the formula, denotes the total number of medical material types, , denotes the total number of medical materials, R denotes the comprehensive drying evaluation index of medical materials, denotes the average change of temperature in the drying process of the i-th medical material, denotes the preset threshold of temperature in the drying process of medical materials, denotes the temperature accuracy reference deviation, denotes the average change of humidity in the drying process of the i-th medical material, denotes the preset threshold of humidity in the drying process of medical materials, denotes the humidity accuracy reference deviation, denotes the comprehensive material loss compliance index of medical materials, denotes the comprehensive material loss compliance index accuracy reference deviation, denotes the temperature weight, denotes the humidity weight, denotes the comprehensive material loss compliance index weight. 8.The hybrid drying system for remote monitoring of pharmaceutical raw materials based on the Internet of Things according to claim 1, wherein, The specific process of obtaining a comprehensive evaluation result according to the comprehensive drying evaluation index is as follows: The comprehensive drying evaluation index is obtained, the comprehensive drying evaluation index is classified to obtain a classification result, and the classification result is used for visualizing the comprehensive drying evaluation index; A comprehensive drying evaluation comparison chart is drawn according to the classification result to obtain a comprehensive evaluation result, and a drying evaluation comparison chart is drawn in combination with the comprehensive raw material loss compliance index and drying data, wherein the drying data represent key data in the running process of the medical raw material remote monitoring mixed drying system.

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