Medical instrument state management system based on Internet of Things technology

Abstract

The invention relates to the technical field of medical apparatuses and instruments, in particular to a medical apparatus and instrument state management system based on the Internet of Things technology, which can remotely monitor and manage medical equipment and medical consumables in the whole period. Through the combination of the equipment sensor, the Internet of Things platform and the mobile terminal application, medical equipment management personnel can know information such as the operation state, the energy consumption condition, the maintenance period and the operation time of the medical equipment in real time, meanwhile, preventive maintenance can be carried out, related faults can be handled in time, and the quality and efficiency of medical services are improved. By means of intelligent remote monitoring and management, information islands are eliminated, efficiency is improved, data unification and sharing among all systems and departments are achieved, and the purpose of conducting real-time remote monitoring and management on medical instruments in the whole period is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to a medical device status management system based on Internet of Things technology. Background Art

[0002] Medical device management refers to the monitoring and management of the entire cycle of medical equipment purchase, acceptance, storage, use, repair, preventive maintenance and scrapping, as well as the purchase, storage, outbound storage, inventory management and usage statistics analysis of medical consumables by medical institutions. The core of medical device management is equipment management. Reasonable equipment management of medical equipment includes equipment classification management, preparation of equipment management system, regular inspection and maintenance, regular inspection of equipment use, training and assessment of equipment users, etc. At the same time, medical institutions should establish equipment files, record and manage medical equipment in detail, and timely update information such as the use, maintenance and service life of medical equipment.

[0003] Medical device management also includes the management of medical consumables, including procurement management, inventory management and use management. Hospitals should establish a complete procurement process for medical consumables, set up a special procurement department, establish procurement plans, determine procurement standards, standardize procurement procedures, establish procurement files, etc. For inventory management, hospitals need to implement grading and classification, real-time inventory, and timely reporting of losses to ensure the safety and normal use of inventory. The use of medical consumables also needs to be supervised more strictly, and measures such as establishing usage procedures, prescribing usage methods, and standardizing disinfection operations should be taken to ensure the quality and use of medical equipment and medical consumables. Medical device management is a very important task in medical institutions, but traditional medical device management methods have the following shortcomings and deficiencies:

[0004] 1. Information islands: The traditional medical device management method has the problem that data cannot be shared in real time between various links, resulting in the emergence of information islands, making it difficult to achieve full-cycle monitoring and management.

[0005] 2. Inefficiency: Medical institutions have a large number of medical devices and medical consumables, and the management work is cumbersome. Manual data entry and transaction processing are inefficient and prone to loopholes and errors.

[0006] 3. Improper inventory management: The traditional medical device management method has the problem of improper inventory management and is unable to effectively control the inventory situation, resulting in inventory backlog and waste.

[0007] 4. Untimely repair and maintenance: Due to poor information communication, untimely repair and maintenance of medical equipment can easily affect the normal operation and service life of the equipment.

[0008] 5. Imperfect data statistics and analysis: The data statistics and analysis functions of traditional medical device management methods are imperfect, and cannot provide hospital managers with accurate, real-time, and comprehensive data analysis and reports, making it difficult to provide effective support for decision-making.

[0009] To sum up, the shortcomings and deficiencies of traditional medical device management methods have brought great difficulties to hospital management. It is necessary to introduce modern medical device status management devices to improve management efficiency and level. Summary of the invention

[0010] In view of the above problems, the present invention proposes a medical device status management system based on the Internet of Things technology, which can remotely monitor and manage the entire cycle of medical equipment and medical consumables, including the purchase, acceptance, warehousing, use, maintenance, preventive maintenance and scrapping of equipment, as well as the purchase, warehousing, outbound, inventory management and usage statistics analysis of medical consumables. At the same time, process processing and status monitoring can be carried out through mobile phone APP or WeChat applet, which improves work efficiency. Through intelligent remote monitoring and management, information islands can be eliminated, efficiency can be improved, and data unification and sharing between systems and departments can be achieved, thereby achieving the purpose of real-time remote monitoring and management of the entire cycle of medical devices.

[0011] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0012] A medical device status management system based on Internet of Things technology, including the following parts:

[0013] Equipment sensors: Each set of sensors is installed with the corresponding medical equipment to monitor the equipment's operating status, energy consumption, maintenance cycle, operating time and other information in real time. The sensors can be connected to the cloud server via a wireless network for data storage and analysis;

[0014] IoT platform: Develop an IoT-based medical device management platform that collects and processes data from sensors through cloud servers to manage and monitor the entire life cycle of the device;

[0015] Mobile applications: Provide mobile applications for the hospital's clinical departments and equipment management departments for process processing, status viewing and message reminders; department managers can remotely view the status, maintenance status and preventive maintenance reminders of equipment, and handle related processes in a timely manner.

[0016] Preferably, the device sensor specifically includes:

[0017] Operation status monitoring: Sensors can monitor the working status of equipment, including but not limited to whether the equipment is operating normally, whether it is in a faulty state, and whether it needs maintenance;

[0018] Energy consumption monitoring: Sensors can monitor the energy consumption of equipment, including but not limited to the power consumption and consumables usage of equipment, so that managers can monitor and manage the use of equipment;

[0019] Maintenance cycle monitoring: Sensors can monitor the maintenance cycle of equipment, including but not limited to the time when the equipment needs maintenance and the time of the next maintenance, so that management personnel can perform maintenance and upkeep on the equipment in a timely manner;

[0020] Uptime monitoring: Sensors can monitor the operating time of equipment so that managers can understand the usage and life of the equipment.

[0021] In the medical device status management system based on the Internet of Things technology, equipment sensors are a very important part. Sensors can be installed on medical equipment to monitor the operating status and energy consumption of the equipment in real time, and upload relevant data to the cloud server for storage and analysis. There are many types of sensors, and medical device managers need to choose different types of sensors according to different equipment conditions and management needs. By collecting data uploaded by sensors, medical device managers can remotely monitor and manage through the Internet of Things platform, monitor and manage the use of equipment in real time, and perform preventive maintenance and handle related faults in a timely manner, thereby effectively improving the quality and efficiency of medical services.

[0022] Preferably, the Internet of Things platform specifically includes:

[0023] Remote monitoring: Through the IoT platform, hospital managers can remotely monitor medical devices anytime and anywhere to understand the equipment's operating status, fault conditions, maintenance cycles and other information;

[0024] Real-time alarm: When equipment fails or requires maintenance, the IoT platform can send alarm information in time; hospital managers can receive alarm information through mobile applications or emails, and take timely measures to solve the problem;

[0025] Energy consumption management: The IoT platform can also manage the energy consumption of medical devices, helping hospitals reduce energy costs and improve equipment utilization;

[0026] Maintenance management: Through the IoT platform, hospital managers can understand the maintenance status of equipment in real time, including but not limited to maintenance cycles and maintenance records. The IoT platform can also perform remote diagnosis and upgrades on equipment to improve the efficiency and quality of equipment maintenance.

[0027] Data analysis: The IoT platform can analyze the operating data of equipment to help hospital managers understand the use of equipment, develop optimized equipment use plans and predict the risk of equipment failure; data analysis can also provide decision-making support for hospital managers, helping them optimize the use and management of medical equipment.

[0028] The IoT platform is a cloud server-based software system that is mainly used to collect, store, process and analyze data obtained from device sensors. It can manage and monitor various types of medical devices throughout their life cycle;

[0029] The data analysis specifically includes:

[0030] Data collection: By collecting data through device sensors, the operating status of the device can be monitored in real time; the voltage, current, temperature, humidity and other parameters of the device can be measured in real time to determine whether the device is operating normally;

[0031] Data storage: The collected data needs to be stored in the cloud server to ensure the long-term preservation and reliability of the data; the cloud server can provide highly available data storage services and support data backup and recovery to ensure that the data will not be lost due to equipment failure or other reasons;

[0032] Data cleaning: The collected data may contain duplication, noise, outliers and other problems, which need to be processed through data cleaning operations; cleaned data can improve the accuracy and reliability of data analysis, thereby providing more accurate decision support;

[0033] Data processing: Data processing is the core of data analysis, which mainly includes data clustering, statistical analysis, predictive modeling and other methods. Through data processing, the usage trends and potential problems of equipment can be identified, and corresponding solutions can be provided.

[0034] Data visualization: Data visualization is to display the processed data in the form of charts, reports, etc., so that hospital managers can understand the use of equipment and analysis results. Through data visualization, hospital managers can quickly understand the use of equipment and make corresponding decisions.

[0035] Data mining: Data mining uses machine learning, deep learning and other technologies to conduct in-depth analysis and modeling of data to reveal the patterns and rules behind the data and provide more accurate support for decision-making. For example, data mining technology can be used to predict the probability of equipment failure, perform maintenance and repairs in advance, and improve equipment reliability and service quality.

[0036] Decision support: The results of data analysis and mining can provide decision support for hospital managers. According to the equipment maintenance status and energy consumption data, suggestions can be provided for equipment maintenance and updating, so as to improve the equipment utilization efficiency and life cycle management; improve the quality and efficiency of medical services; decision support can include the optimization of equipment maintenance plans, equipment replacement and upgrade, and other decisions; through data analysis and mining, the hospital's equipment management level and service quality can be improved, and the satisfaction and trust of medical services can be further improved.

[0037] Preferably, the data cleaning specifically includes:

[0038] Missing value processing: Check whether there are missing values ​​in the data. If so, methods can be adopted, including but not limited to one or more of replacement, deletion, and interpolation;

[0039] Outlier processing: detect whether there are outliers in the data. If so, they need to be identified and processed to avoid affecting the analysis results;

[0040] Duplicate value processing: Check whether there are duplicate values ​​in the data. If so, delete or merge them to save storage space and improve analysis efficiency;

[0041] Data format conversion: Convert the data format into a unified format to facilitate subsequent data processing and analysis.

[0042] Preferably, the data processing specifically includes:

[0043] Data preprocessing: normalize and standardize the data to improve the accuracy and reliability of data analysis;

[0044] Data clustering: divide the data into several categories according to certain rules and observe the similarities and differences between the data;

[0045] Statistical analysis: Analyze the overall characteristics of the data through indicators such as the mean, variance, and standard deviation of the data;

[0046] Predictive modeling: By analyzing the historical changes, trends, cycles and other patterns of data, we can predict future development trends and possible problems.

[0047] Preferably, the data visualization specifically includes:

[0048] Select visualization target: determine the analysis object and target, and select the appropriate visualization chart type;

[0049] Data presentation: presenting data processing results in charts or reports;

[0050] Interactive analysis: Provides interactive data analysis and exploration functions, and supports user-defined filtering and analysis.

[0051] Preferably, the data mining specifically includes:

[0052] Feature selection: Select appropriate data features to facilitate analysis and modeling;

[0053] Model selection: Select the appropriate machine learning or deep learning model based on the analysis objectives and data characteristics;

[0054] Parameter adjustment: Adjust the parameters of a machine learning or deep learning model to optimize the model’s predictive performance;

[0055] Data validation: Validate and evaluate the model to test its predictive ability and accuracy.

[0056] Preferably, the decision support specifically includes:

[0057] Define the decision problem: clarify the nature, objectives and constraints of the problem in order to determine the direction and objectives of data analysis and mining;

[0058] Data collection: Collect data related to the problem through various channels, including but not limited to patients' medical records, equipment usage records and hospital economic data;

[0059] Data exploration: Perform preliminary exploration and visualization of data to understand its characteristics and distribution, identify outliers and missing values, and prepare for further analysis;

[0060] Feature selection: Perform feature selection on the collected data and retain features relevant to the problem to reduce noise and redundancy and improve the generalization ability of the model;

[0061] Data preprocessing: Process the data, including but not limited to missing value processing, outlier processing and normalization, to ensure the quality and availability of the data;

[0062] Model building: Select appropriate data mining methods and algorithms to build corresponding models, including but not limited to classification models, clustering models and regression models;

[0063] Model evaluation: Evaluate and validate the established model, including but not limited to cross-validation, ROC curve and confusion matrix to evaluate the accuracy and reliability of the model;

[0064] Model optimization: Optimize and adjust the established model, including but not limited to changing algorithm parameters and improving feature selection capabilities to improve the performance and generalization ability of the model;

[0065] Decision making: Based on the model results and analysis reports, formulate corresponding decision plans, including but not limited to equipment replacement and adjustment of maintenance plans;

[0066] Decision implementation: put the formulated decision plan into practice to optimize equipment management and improve efficiency;

[0067] Monitoring and feedback: Monitor and provide feedback on the implementation of decision-making plans to evaluate the effectiveness and sustainability of decisions, and continuously improve and refine decision-making plans.

[0068] Preferably, the mobile terminal application specifically includes:

[0069] Login and permission management: The mobile application needs to provide a login interface where users need to enter their username and password as well as their department information to log in. Permission management is also required to ensure that only authorized users can use the application;

[0070] Device status check: The mobile application needs to provide an interface that allows users to view the real-time status of the device, including the device's operating status, energy consumption, maintenance cycle, operating time and other information. It also needs to provide a historical data query function for the device to facilitate user comparison and analysis;

[0071] Maintenance management: The mobile application needs to provide a maintenance management interface so that users can view the maintenance status of the equipment, including maintenance personnel, maintenance time, maintenance costs and other information; it also needs to provide a maintenance application function so that users can submit maintenance applications in a timely manner;

[0072] Preventive maintenance reminder: The mobile application needs to provide a preventive maintenance reminder function, so that users can view the preventive maintenance reminder information of the equipment in a timely manner, and can be reminded and processed;

[0073] Message reminder: The mobile application needs to provide a message reminder function so that users can receive device-related notifications and messages in a timely manner, including device maintenance notifications, maintenance completion notifications, etc. It also needs to provide a message management function to facilitate users to view and process messages;

[0074] Process processing: The mobile application needs to provide a process processing function so that users can promptly handle equipment-related processes within the department, including equipment allocation, equipment maintenance, equipment scrapping and other processes; it also needs to provide a process query function to facilitate users to view the process and track progress.

[0075] Beneficial effects of the present invention:

[0076] The present invention proposes a medical device status management system based on the Internet of Things technology, which can realize remote monitoring and management of the entire cycle of medical equipment and medical consumables. Through the combination of equipment sensors, Internet of Things platforms and mobile applications, medical equipment managers can understand the operating status, energy consumption, maintenance cycle, operating time and other information of medical equipment in real time, and can also perform preventive maintenance and timely handle related faults to improve the quality and efficiency of medical services. Specifically, equipment sensors can monitor the operating status, energy consumption, maintenance cycle and operating time of medical equipment, and upload relevant data to the cloud server for storage and analysis; the Internet of Things platform can remotely monitor, real-time alarm, energy consumption management, maintenance management and data analysis of medical equipment; mobile applications can realize functions such as login and permission management, equipment status viewing, maintenance management, preventive maintenance prompts, message reminders and process processing. Through intelligent remote monitoring and management, the present invention eliminates information islands, improves efficiency, realizes the unification and sharing of data between various systems and departments, and achieves the purpose of real-time remote monitoring and management of medical equipment throughout the entire cycle.

[0077] The present invention realizes the full life cycle status management of medical devices, realizes the organic integration of hospital device management information, solves the information island problem between medical equipment and medical consumables management systems, and thus improves work efficiency. The full life cycle status management of medical devices includes two major parts: the management of medical equipment and medical consumables. Through the intelligent management system, the basic information, asset information, warranty information, maintenance information and other information of the equipment can be collected, stored and updated in real time, thereby realizing the full cycle management of medical device information and improving the data-based and standardized level of management. At the same time, the system can organically integrate medical device equipment information and medical consumables information, solve the information island problem, and improve work efficiency.

[0078] The present invention provides remote management and monitoring functions. Clinical departments, equipment management departments and relevant supervisors can view the status of medical equipment in real time, and deal with abnormal conditions of equipment in time through intelligent reminder functions to avoid downtime and delays caused by failures or other reasons. The intelligent management system provides remote management and monitoring functions. Clinical departments, equipment management departments and relevant supervisors can view the status of equipment remotely in real time and manage and control the equipment. At the same time, the system can provide intelligent prompts and reminders based on the use and maintenance of medical equipment, so that managers can deal with abnormal conditions of equipment in time to avoid downtime and delays caused by failures or other reasons.

[0079] The present invention realizes the periodic time expiration reminder of preventive maintenance, quality control and measurement of medical devices through the intelligent prompt function, thereby improving the service life and safety of medical devices. The intelligent management system provides functions such as preventive maintenance, quality control and measurement of medical devices. The system can automatically identify the operating status of medical equipment, provide prompts and reminders of periodic time expiration, and remind managers to perform preventive maintenance, quality control and measurement operations in a timely manner, thereby improving the service life and safety of medical devices.

[0080] The present invention realizes the full-cycle remote management and monitoring of medical consumables through functions such as process processing and status monitoring. In emergency situations such as beds and surgeries, departments can quickly obtain the required consumables, thereby improving work efficiency and production benefits. The intelligent management system provides full-cycle remote management and monitoring functions for medical consumables, including key links such as application submission by departments, approval by hospital leaders and the equipment department, procurement progress, acceptance into the warehouse, and delivery of materials from the department. The system can track the use of consumables in real time, and provide functions such as real-time monitoring and status reminders, thereby ensuring that in emergency situations such as beds and surgeries, departments can quickly obtain the required consumables, thereby improving work efficiency and production benefits.

[0081] The present invention can realize the unification and sharing of data, and the intercommunication of data between various systems and departments can be realized, avoiding the errors caused by repeated data entry and management information, thereby improving work efficiency and data accuracy. The intelligent management system can realize the unification and sharing of data, and the intercommunication of data between various systems and departments can be realized, avoiding the errors caused by repeated data entry and management information, thereby improving work efficiency and data accuracy.

[0082] The present invention realizes the traditional hospital warehouse management through intelligent management, reduces the time and energy consumed by the department to count the inventory every day, and improves the management efficiency of the warehouse. The intelligent management system provides a traditional hospital warehouse management method, which can replace manual inventory counting and management. Managers can query and count the inventory through intelligent terminals, understand the inventory status and consumption in real time, reduce the time and energy consumed by the department to count the inventory every day, and improve the management efficiency and accuracy of the warehouse.

[0083] To sum up, the intelligent management system realizes the status management of medical devices throughout their life cycle, remote management and monitoring, realizes data unification and sharing, improves work efficiency and data accuracy, and is a major improvement in the information management of medical institutions.

[0084] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. DETAILED DESCRIPTION

[0085] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0086] Example 1

[0087] The medical device status management system based on the Internet of Things technology described in this embodiment includes the following parts:

[0088] Equipment sensors: Each set of sensors is installed on the corresponding medical equipment to monitor the operating status, energy consumption, maintenance cycle, operating time and other information of the medical equipment in real time. The sensors can be connected to the cloud server through the wireless network for data storage and analysis;

[0089] IoT platform: Develop an IoT-based medical device management platform that collects and processes data from sensors through cloud servers to manage and monitor the entire life cycle of the device;

[0090] Mobile applications: Provide mobile applications for the hospital's clinical departments and equipment management departments for process processing, status viewing and message reminders; department managers can remotely view the status, maintenance status and preventive maintenance reminders of medical equipment, and handle related processes in a timely manner.

[0091] In this embodiment, the device sensor specifically includes:

[0092] Operation status monitoring: Sensors can monitor the working status of medical equipment, including but not limited to whether the medical equipment is operating normally, whether it is in a faulty state, and whether it needs maintenance;

[0093] Energy consumption monitoring: Sensors can monitor the energy consumption of medical equipment, including but not limited to the power consumption and consumables usage of medical equipment, so that managers can monitor and manage the use of medical equipment;

[0094] Maintenance cycle monitoring: Sensors can monitor the maintenance cycle of medical equipment, including but not limited to the time when the medical equipment needs maintenance and the time of the next maintenance, so that management personnel can perform maintenance and upkeep on the medical equipment in a timely manner;

[0095] Uptime monitoring: Sensors can monitor the uptime of medical equipment so that managers can understand the usage and life of medical equipment.

[0096] In the medical device status management system based on the Internet of Things technology, equipment sensors are a very important part. Sensors can be installed on medical equipment to monitor the operating status and energy consumption of medical equipment in real time, and upload relevant data to the cloud server for storage and analysis. There are many types of sensors, and medical device managers need to choose different types of sensors according to different medical equipment conditions and management needs. By collecting data uploaded by sensors, medical device managers can remotely monitor and manage through the Internet of Things platform, monitor and manage the use of medical equipment in real time, and perform preventive maintenance and handle related faults in a timely manner, thereby effectively improving the quality and efficiency of medical services.

[0097] In this embodiment, the Internet of Things platform specifically includes:

[0098] Remote monitoring: Through the IoT platform, hospital managers can remotely monitor medical equipment anytime and anywhere to understand the operating status, fault conditions, maintenance cycle and other information of medical equipment;

[0099] Real-time alarm: When medical equipment fails or needs maintenance, the IoT platform can send alarm information in time; hospital managers can receive alarm information through mobile applications or emails, and take timely measures to solve the problem;

[0100] Energy consumption management: The IoT platform can also manage the energy consumption of medical devices, helping hospitals reduce energy costs and improve the utilization rate of medical equipment;

[0101] Maintenance management: Through the IoT platform, hospital managers can understand the maintenance status of medical equipment in real time, including but not limited to maintenance cycles and maintenance records. The IoT platform can also perform remote diagnosis and upgrades on medical equipment to improve the efficiency and quality of medical equipment maintenance.

[0102] Data analysis: The IoT platform can analyze the operating data of medical equipment to help hospital managers understand the use of medical equipment, develop optimized medical equipment use plans and predict the risk of medical equipment failure; data analysis can also provide decision-making support for hospital managers, helping them optimize the use and management of medical equipment.

[0103] The IoT platform is a cloud server-based software system that is mainly used to collect, store, process and analyze data obtained from device sensors. It can manage and monitor various types of medical devices throughout their life cycle;

[0104] In this embodiment, the data analysis specifically includes:

[0105] Data collection: By collecting data through device sensors, the operating status of medical equipment can be monitored in real time; the voltage, current, temperature, humidity and other parameters of medical equipment can be measured in real time to determine whether the medical equipment is operating normally;

[0106] Data storage: The collected data needs to be stored in the cloud server to ensure the long-term preservation and reliability of the data; the cloud server can provide highly available data storage services and support data backup and recovery to ensure that the data will not be lost due to medical equipment failure or other reasons;

[0107] Data cleaning: The collected data may contain duplication, noise, outliers and other problems, which need to be processed through data cleaning operations; cleaned data can improve the accuracy and reliability of data analysis, thereby providing more accurate decision support;

[0108] Data processing: Data processing is the core of data analysis, which mainly includes data clustering, statistical analysis, predictive modeling and other methods. Through data processing, the use trends and potential problems of medical equipment can be identified, and corresponding solutions can be provided;

[0109] Data visualization: Data visualization is to display the processed data in the form of charts, reports, etc., so that hospital managers can understand the use of medical equipment and analysis results. Through data visualization, hospital managers can quickly understand the use of medical equipment and make corresponding decisions.

[0110] Data mining: Data mining uses machine learning, deep learning and other technologies to conduct in-depth analysis and modeling of data to reveal the patterns and rules behind the data and provide more accurate support for decision-making. For example, data mining technology can be used to predict the failure probability of medical equipment, perform maintenance and repairs in advance, and improve the reliability and service quality of medical equipment.

[0111] Decision support: The results of data analysis and mining can provide decision support for hospital managers. According to the maintenance status and energy consumption data of medical equipment, suggestions can be provided for the maintenance and update of medical equipment, so as to improve the utilization efficiency and life cycle management of medical equipment and improve the quality and efficiency of medical services. Decision support can include the optimization of medical equipment maintenance plans, replacement and upgrade of medical equipment and other decisions. Through data analysis and mining, the hospital's medical equipment management level and service quality can be improved, and the satisfaction and trust of medical services can be further improved.

[0112] In this embodiment, the data cleaning specifically includes:

[0113] Missing value processing: Check whether there are missing values ​​in the data. If so, methods can be adopted, including but not limited to one or more of replacement, deletion, and interpolation;

[0114] Outlier processing: detect whether there are outliers in the data. If so, they need to be identified and processed to avoid affecting the analysis results;

[0115] Duplicate value processing: Check whether there are duplicate values ​​in the data. If so, delete or merge them to save storage space and improve analysis efficiency;

[0116] Data format conversion: Convert the data format into a unified format to facilitate subsequent data processing and analysis.

[0117] In this embodiment, the data processing specifically includes:

[0118] Data preprocessing: normalize and standardize the data to improve the accuracy and reliability of data analysis;

[0119] Data clustering: divide the data into several categories according to certain rules and observe the similarities and differences between the data;

[0120] Statistical analysis: Analyze the overall characteristics of the data through indicators such as the mean, variance, and standard deviation of the data;

[0121] Predictive modeling: By analyzing the historical changes, trends, cycles and other patterns of data, we can predict future development trends and possible problems.

[0122] In this embodiment, the data visualization specifically includes:

[0123] Select visualization target: determine the analysis object and target, and select the appropriate visualization chart type;

[0124] Data presentation: presenting data processing results in charts or reports;

[0125] Interactive analysis: Provides interactive data analysis and exploration functions, and supports user-defined filtering and analysis.

[0126] In this embodiment, the data mining specifically includes:

[0127] Feature selection: Select appropriate data features to facilitate analysis and modeling;

[0128] Model selection: Select the appropriate machine learning or deep learning model based on the analysis objectives and data characteristics;

[0129] Parameter adjustment: Adjust the parameters of a machine learning or deep learning model to optimize the model’s predictive performance;

[0130] Data validation: Validate and evaluate the model to test its predictive ability and accuracy.

[0131] In this embodiment, the decision support specifically includes:

[0132] Define the decision problem: clarify the nature, objectives and constraints of the problem in order to determine the direction and objectives of data analysis and mining;

[0133] Data collection: Collect data related to the problem through various channels, including but not limited to patients' medical records, medical equipment usage records and hospital economic data;

[0134] Data exploration: Perform preliminary exploration and visualization of data to understand its characteristics and distribution, identify outliers and missing values, and prepare for further analysis;

[0135] Feature selection: Perform feature selection on the collected data and retain features relevant to the problem to reduce noise and redundancy and improve the generalization ability of the model;

[0136] Data preprocessing: Process the data, including but not limited to missing value processing, outlier processing and normalization, to ensure the quality and availability of the data;

[0137] Model building: Select appropriate data mining methods and algorithms to build corresponding models, including but not limited to classification models, clustering models and regression models;

[0138] Model evaluation: Evaluate and validate the established model, including but not limited to cross-validation, ROC curve and confusion matrix to evaluate the accuracy and reliability of the model;

[0139] Model optimization: Optimize and adjust the established model, including but not limited to changing algorithm parameters and improving feature selection capabilities to improve the performance and generalization ability of the model;

[0140] Decision making: Based on the model results and analysis reports, formulate corresponding decision plans, including but not limited to the replacement of medical equipment and adjustment of maintenance plans;

[0141] Decision implementation: put the formulated decision plan into practice to optimize medical equipment management and improve efficiency;

[0142] Monitoring and feedback: Monitor and provide feedback on the implementation of decision-making plans to evaluate the effectiveness and sustainability of decisions, and continuously improve and refine decision-making plans.

[0143] In this embodiment, the mobile terminal application specifically includes:

[0144] Login and permission management: The mobile application needs to provide a login interface where users need to enter their username and password as well as their department information to log in. Permission management is also required to ensure that only authorized users can use the application;

[0145] Device status check: The mobile application needs to provide an interface that allows users to view the real-time status of medical equipment, including the operating status, energy consumption, maintenance cycle, operating time and other information of the medical equipment. It also needs to provide a historical data query function for medical equipment to facilitate user comparison and analysis;

[0146] Maintenance management: The mobile application needs to provide a maintenance management interface so that users can view the maintenance status of medical equipment, including maintenance personnel, maintenance time, maintenance costs and other information; it also needs to provide a maintenance application function so that users can submit maintenance applications in a timely manner;

[0147] Preventive maintenance reminder: The mobile application needs to provide a preventive maintenance reminder function, so that users can view the preventive maintenance reminder information of medical equipment in a timely manner, and can remind and handle it;

[0148] Message reminder: The mobile application needs to provide a message reminder function so that users can receive timely notifications and messages related to medical equipment, including medical equipment maintenance notifications, maintenance completion notifications, etc.; it also needs to provide a message management function to facilitate users to view and process messages;

[0149] Process processing: The mobile application needs to provide a process processing function so that users can promptly handle medical equipment-related processes within the department, including equipment allocation, equipment maintenance, equipment scrapping and other processes; it also needs to provide a process query function to facilitate users to view the process and track progress.

[0150] Example 2

[0151] The medical device status management system based on the Internet of Things technology described in this embodiment includes the following parts:

[0152] Equipment sensors: Medical equipment can be equipped with sensors to monitor the operating status, energy consumption, maintenance cycle, operating time and other information of medical equipment in real time. Sensors can be connected to cloud servers via wireless networks for data storage and analysis. In this step, we need to install sensors for each medical device and use the sensors to collect data when the medical equipment is running. This data can include various status information such as temperature, current, power consumption, vibration, etc. of the medical equipment. Sensors can be connected to pre-configured Wi-Fi, Bluetooth or other wireless networks to send data to the cloud central storage. This data can help us understand the status and operation of medical equipment more clearly. At the same time, we can also add artificial intelligence algorithms to predict the status of medical equipment and detect medical equipment failures in advance, thereby improving the service life and efficiency of medical equipment.

[0153] IoT platform: Develop an IoT-based medical device management platform, collect and process data from sensors through cloud servers, and manage and monitor the entire life cycle of the device. In the second step, we need to use cloud servers to manage and monitor medical devices. In the IoT platform, various types of medical devices are connected together through IoT technology, and the status and operation of these devices are monitored and managed through cloud services. The IoT platform can analyze sensor data to discover problems such as abnormal operation of medical equipment and the life of medical equipment. At the same time, the IoT platform can also be integrated with other key systems, such as electronic medical records, bed management systems, etc., to better achieve data sharing and collaboration.

[0154] Mobile applications: Provide mobile applications for the hospital's clinical departments and equipment management departments for process processing, status viewing, and message reminders. Department managers can remotely view the status, maintenance status, and preventive maintenance reminders of medical equipment, and handle related processes in a timely manner. In the third step, we need to provide mobile applications for the hospital's clinical departments and equipment management departments so that they can manage the status of equipment anytime and anywhere. The mobile application can help clinical department managers initiate medical equipment requests and view the status and usage of medical equipment in a timely manner. In addition, the application can also help the equipment management department process maintenance requests and manage equipment status. Through the mobile application, department managers can easily track the maintenance status of medical equipment, manage the periodic maintenance dates of medical equipment, and receive real-time alarm notifications about medical equipment.

[0155] Data analysis and decision support: Provide decision support for hospital managers by analyzing the collected data. For example, based on the maintenance status and energy consumption data of medical equipment, provide suggestions for the maintenance and update of medical equipment to improve the efficiency of medical equipment use and life cycle management. In the fourth step, we can use data analysis technology to analyze the data collected from sensors. Through the analysis of data, we can better understand the use, maintenance and life of medical equipment, and provide better decision support. For example, for some medical equipment that often fails or has a high number of repairs, the system can generate a medical equipment maintenance report and make suggestions for updating or replacing medical equipment. By analyzing energy consumption data, hospitals can understand which medical equipment consumes a lot of electricity, and then formulate energy-saving measures to reduce costs. Through data analysis, we can improve the efficiency of medical equipment management throughout the life cycle.

[0156] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A medical device status management system based on Internet of Things technology, characterized in that: Includes the following sections: Equipment sensors: Each set of sensors is installed with the corresponding medical equipment to monitor the equipment's operating status, energy consumption, maintenance cycle, operating time and other information in real time. The sensors can be connected to the cloud server via a wireless network for data storage and analysis; IoT platform: Develop an IoT-based medical device management platform that collects and processes data from sensors through cloud servers to manage and monitor the entire life cycle of the device; Mobile applications: Provide mobile applications for the hospital's clinical departments and equipment management departments for process processing, status checking, and message reminders; Department managers can remotely view the status, maintenance status and preventive maintenance reminders of equipment, and handle related processes in a timely manner.

2. A medical device status management system based on Internet of Things technology as claimed in claim 1, characterized in that: The device sensors specifically include: Operation status monitoring: Sensors can monitor the working status of equipment, including but not limited to whether the equipment is operating normally, whether it is in a faulty state, and whether it needs maintenance; Energy consumption monitoring: Sensors can monitor the energy consumption of equipment, including but not limited to the power consumption and consumables usage of equipment, so that managers can monitor and manage the use of equipment; Maintenance cycle monitoring: Sensors can monitor the maintenance cycle of equipment, including but not limited to the time when the equipment needs maintenance and the time of the next maintenance, so that management personnel can perform maintenance and upkeep on the equipment in a timely manner; Uptime monitoring: Sensors can monitor the operating time of equipment so that managers can understand the usage and life of the equipment.

3. The medical device status management system based on Internet of Things technology as claimed in claim 1, characterized in that: The Internet of Things platform specifically includes: Remote monitoring: Through the IoT platform, hospital managers can remotely monitor medical devices anytime and anywhere to understand the equipment's operating status, fault conditions, maintenance cycles and other information; Real-time alarm: When equipment fails or requires maintenance, the IoT platform can send alarm information in time; hospital managers can receive alarm information through mobile applications or emails, and take timely measures to solve the problem; Energy consumption management: The IoT platform can also manage the energy consumption of medical devices, helping hospitals reduce energy costs and improve equipment utilization; Maintenance management: Through the IoT platform, hospital managers can understand the maintenance status of equipment in real time, including but not limited to maintenance cycles and maintenance records. The IoT platform can also perform remote diagnosis and upgrades on equipment to improve the efficiency and quality of equipment maintenance. Data analysis: The IoT platform can analyze the operating data of equipment to help hospital managers understand the use of equipment, develop optimized equipment use plans and predict the risk of equipment failure; data analysis can also provide decision-making support for hospital managers, helping them optimize the use and management of medical equipment.

4. A medical device status management system based on Internet of Things technology as claimed in claim 3, characterized in that: The data analysis specifically includes: Data collection: By collecting data through device sensors, the operating status of the device can be monitored in real time; the voltage, current, temperature, humidity and other parameters of the device can be measured in real time to determine whether the device is operating normally; Data storage: The collected data needs to be stored in the cloud server to ensure the long-term preservation and reliability of the data; the cloud server can provide highly available data storage services and support data backup and recovery to ensure that the data will not be lost due to equipment failure or other reasons; Data cleaning: The collected data may contain duplication, noise, outliers and other problems, which need to be processed through data cleaning operations; cleaned data can improve the accuracy and reliability of data analysis, thereby providing more accurate decision support; Data processing: Data processing is the core of data analysis, which mainly includes data clustering, statistical analysis, predictive modeling and other methods. Through data processing, the usage trends and potential problems of equipment can be identified, and corresponding solutions can be provided. Data visualization: Data visualization is to display the processed data in the form of charts, reports, etc., so that hospital managers can understand the use of equipment and analysis results. Through data visualization, hospital managers can quickly understand the use of equipment and make corresponding decisions. Data mining: Data mining uses machine learning, deep learning and other technologies to conduct in-depth analysis and modeling of data to reveal the patterns and rules behind the data and provide more accurate support for decision-making. For example, data mining technology can be used to predict the probability of equipment failure, perform maintenance and repairs in advance, and improve equipment reliability and service quality. Decision support: The results of data analysis and mining can provide decision support for hospital managers. According to the equipment maintenance status and energy consumption data, suggestions can be provided for equipment maintenance and updating, so as to improve the equipment utilization efficiency and life cycle management; improve the quality and efficiency of medical services; decision support can include the optimization of equipment maintenance plans, equipment replacement and upgrade, and other decisions; through data analysis and mining, the hospital's equipment management level and service quality can be improved, and the satisfaction and trust of medical services can be further improved.

5. The medical device status management system based on Internet of Things technology as claimed in claim 4, characterized in that: The data cleaning specifically includes: Missing value processing: Check whether there are missing values ​​in the data. If so, methods can be adopted, including but not limited to one or more of replacement, deletion, and interpolation; Outlier processing: detect whether there are outliers in the data. If so, they need to be identified and processed to avoid affecting the analysis results; Duplicate value processing: Check whether there are duplicate values ​​in the data. If so, delete or merge them to save storage space and improve analysis efficiency; Data format conversion: Convert the data format into a unified format to facilitate subsequent data processing and analysis.

6. The medical device status management system based on Internet of Things technology as claimed in claim 4, characterized in that: The data processing specifically includes: Data preprocessing: normalize and standardize the data to improve the accuracy and reliability of data analysis; Data clustering: divide the data into several categories according to certain rules and observe the similarities and differences between the data; Statistical analysis: Analyze the overall characteristics of the data through indicators such as the mean, variance, and standard deviation of the data; Predictive modeling: By analyzing the historical changes, trends, cycles and other patterns of data, we can predict future development trends and possible problems.

7. The medical device status management system based on Internet of Things technology as claimed in claim 4, characterized in that: The data visualization specifically includes: Select visualization target: determine the analysis object and target, and select the appropriate visualization chart type; Data presentation: presenting data processing results in charts or reports; Interactive analysis: Provides interactive data analysis and exploration functions, and supports user-defined filtering and analysis.

8. The medical device status management system based on Internet of Things technology as claimed in claim 4, characterized in that: The data mining specifically includes: Feature selection: Select appropriate data features to facilitate analysis and modeling; Model selection: Select the appropriate machine learning or deep learning model based on the analysis objectives and data characteristics; Parameter tuning: Adjust the parameters of a machine learning or deep learning model to optimize the model’s predictive performance; Data validation: Validate and evaluate the model to test its predictive ability and accuracy.

9. The medical device status management system based on Internet of Things technology as claimed in claim 4, characterized in that: The decision support specifically includes: Define the decision problem: clarify the nature, objectives and constraints of the problem in order to determine the direction and objectives of data analysis and mining; Data collection: Collect data related to the problem through various channels, including but not limited to patients' medical records, equipment usage records and hospital economic data; Data exploration: Perform preliminary exploration and visualization of data to understand its characteristics and distribution, identify outliers and missing values, and prepare for further analysis; Feature selection: Perform feature selection on the collected data and retain features relevant to the problem to reduce noise and redundancy and improve the generalization ability of the model; Data preprocessing: Process the data, including but not limited to missing value processing, outlier processing and normalization, to ensure the quality and availability of the data; Model building: Select appropriate data mining methods and algorithms to build corresponding models, including but not limited to classification models, clustering models and regression models; Model evaluation: Evaluate and validate the established model, including but not limited to cross-validation, ROC curve and confusion matrix to evaluate the accuracy and reliability of the model; Model optimization: Optimize and adjust the established model, including but not limited to changing algorithm parameters and improving feature selection capabilities to improve the performance and generalization ability of the model; Decision making: Based on the model results and analysis reports, formulate corresponding decision plans, including but not limited to equipment replacement and adjustment of maintenance plans; Decision implementation: put the formulated decision plan into practice to optimize equipment management and improve efficiency; Monitoring and feedback: Monitor and provide feedback on the implementation of decision-making plans to evaluate the effectiveness and sustainability of decisions, and continuously improve and refine decision-making plans.

10. The medical device status management system based on Internet of Things technology as claimed in claim 1, characterized in that: The mobile terminal application specifically includes: Login and permission management: The mobile application needs to provide a login interface where users need to enter their username and password as well as their department information to log in. Permission management is also required to ensure that only authorized users can use the application; Device status check: The mobile application needs to provide an interface that allows users to view the real-time status of the device, including the device's operating status, energy consumption, maintenance cycle, operating time and other information. It also needs to provide a historical data query function for the device to facilitate user comparison and analysis; Maintenance management: The mobile application needs to provide a maintenance management interface so that users can view the maintenance status of the equipment, including maintenance personnel, maintenance time, maintenance costs and other information; it also needs to provide a maintenance application function so that users can submit maintenance applications in a timely manner; Preventive maintenance reminder: The mobile application needs to provide a preventive maintenance reminder function, so that users can view the preventive maintenance reminder information of the equipment in a timely manner, and can be reminded and processed; Message reminder: The mobile application needs to provide a message reminder function so that users can receive device-related notifications and messages in a timely manner, including device maintenance notifications, maintenance completion notifications, etc. It also needs to provide a message management function to facilitate users to view and process messages; Process processing: The mobile application needs to provide a process processing function so that users can promptly handle equipment-related processes within the department, including equipment allocation, equipment maintenance, equipment scrapping and other processes; it also needs to provide a process query function to facilitate users to view the process and track progress.