Dynamic data push and alarm response system for intelligent equipment

Abstract

The invention discloses a dynamic data pushing and alarm response system for intelligent equipment. The dynamic data pushing and alarm response system comprises a data acquisition and processing module, an Internet of Things equipment module and a user interface and report module, and the data acquisition and processing module periodically acquires core business data through a high-precision timing scheduling mechanism, and performs format conversion and standardization processing on multi-source heterogeneous data. Alarm messages are received in real time through WebSocket long connection, information is efficiently distributed through a RabbitMQ message queue, traditional polling / timed tasks and an HTTP protocol are replaced, and response delay is greatly shortened to avoid emergency alarm delay; and meanwhile, unified management and real-time interaction of multiple devices are realized by relying on an MQTT protocol, the problem that data transmission is not timely in device cooperation is solved, the system security, the data transmission efficiency and the device cooperation capability are finally improved, and the system adapts to scenes with high requirements on real-time performance and reliability, such as smart wards and the like.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) technology, and in particular to a dynamic data push and alarm response system for smart devices. Background Technology

[0002] With the rapid development of the Internet of Things (IoT) and smart devices, smart devices are being used more and more widely in various industries, especially in the fields of security monitoring, industrial automation, and remote control. Smart devices typically need to respond in real time to alarm information from different sources to ensure the stability and security of the system. However, existing alarm systems often face the following challenges: 1. Poor real-time performance: Traditional alarm systems usually rely on polling or timed tasks to obtain alarm information. This method has a long response delay, which may cause the device to fail to respond to emergency alarms in a timely manner, affecting the security of the system. 2. Low data transmission efficiency: In some complex application scenarios, alarm information needs to be transmitted from multiple sources to different devices. Traditional communication methods based on HTTP requests or other protocols may not be able to meet the requirements of high concurrency and high reliability, resulting in low transmission efficiency and long system response time. 3. Inter-device collaboration issues: Smart devices often need to work in collaboration with other devices, but existing systems often neglect efficient data transmission and real-time interaction between devices, resulting in untimely transmission of alarm information or even missing critical opportunities. Based on the above, this application proposes a dynamic data push and alarm response system for smart devices. Summary of the Invention

[0003] Based on the technical problems existing in the background technology, the present invention proposes a dynamic data push and alarm response system for smart devices.

[0004] This invention proposes a dynamic data push and alarm response system for smart devices, comprising a data acquisition and processing module, an Internet of Things (IoT) device module, and a user interface and reporting module. The data acquisition and processing module periodically collects core business data through a high-precision timed scheduling mechanism, performs format conversion and standardization processing on multi-source heterogeneous data, and uses a distributed caching mechanism to accelerate access to hot data and optimize database load. The IoT device module is used to execute IoT device management and alarm information distribution mechanisms; The user interface and reporting module includes a data visualization interface and an alarm system, which are used to present the processing results to the user.

[0005] Preferably, the data acquisition and processing module is divided into a data acquisition stage and a data processing stage during operation. The specific logical steps of the data acquisition stage are as follows: S1011: Identity Authentication Initialization: When the system starts up for the first time, MD5 encryption calculation is performed on the HTTP request header to generate unique identity authentication information, which is used to establish a security baseline for data interaction. All subsequent data retrieval operations must pass this authentication verification to ensure the legality of data access. S1012: Data Acquisition Scheduling: The background starts a high-precision timed scheduling mechanism to trigger core business data acquisition tasks according to a preset cycle. The core business data includes patient information and bed status. S1013: Data retrieval execution: Based on the standardized HTTP protocol, a data retrieval request is initiated to the data source. The request carries the identity authentication information generated in S1011. After verification, the latest business data is obtained to achieve real-time information synchronization. S1014: Data Acquisition Status Monitoring: The data acquisition execution status is displayed in real time on the client's visual management interface, including the number of successfully acquired items, the number of failed items, and the reasons for failure. If a data acquisition error or task interruption occurs, the user can trigger the task start / stop or restart operation through the interface to complete the data acquisition process control. S1015: Exception Capture and Log Recording: An asynchronous exception capture mechanism is enabled during the data collection process. When a single point of failure occurs, the exception is immediately intercepted to prevent process crashes. At the same time, the details of the exception event and the system operation log are persistently stored in the log database to provide a basis for subsequent problem localization.

[0006] Preferably, the specific logical steps of the data processing stage are as follows: S1021: Multi-source heterogeneous data standardization: Receive the collected multi-source heterogeneous data, complete the format conversion and structure processing according to the preset data parsing and conversion rules, and generate a standardized data set; S1022: Hot Data Caching Optimization: Identify frequently accessed key data and store it in a distributed caching system; at the same time, configure a cache expiration policy to reduce the number of direct database accesses, reduce database load, and shorten data access latency; S1023: Persistent Data Storage: The standardized and complete data is persistently stored using a high-availability storage strategy; index optimization is performed on the stored data to improve the efficiency of subsequent data retrieval; at the same time, a multi-replica storage mechanism is started to back up data on different nodes to ensure data security; S1024: Data and Configuration Backup: Start scheduled task scheduling to perform snapshot backups on persistent data according to preset cycles, generate backup files and store them on off-site disaster recovery nodes; for critical business configurations and rules, the system provides visualized backup and recovery management functions to ensure that core configurations can be quickly restored during version iterations, parameter adjustments or emergency recovery, and ensure that core configurations can be quickly restored during version iterations or anomalies.

[0007] Preferably, the IoT device module operates in two phases: an IoT device management phase and an IoT device alarm information dissemination phase. In the IoT device management phase, the system achieves unified access and intelligent control of various sensors and terminal devices through deep integration of smart gateways with multi-source heterogeneous IoT devices. The system is built on the MQTT protocol to construct an efficient message middleware, providing a lightweight communication mechanism with low bandwidth consumption, high reliability, and excellent scalability. It meets the device management and data interaction needs in large-scale IoT scenarios. At the functional level, it supports both fine-grained control of single-point devices and centralized management capabilities at the regional level, forming a multi-level control system from local to global. In terms of reliability, the system utilizes the message queue characteristics of MQTT to achieve message persistence. Even when devices are offline or the network is interrupted, messages can be securely stored on the server and automatically resent when the device is reconnected, thereby ensuring the stable transmission of critical instructions and alarm information and business continuity.

[0008] Preferably, the specific logical steps of the IoT device alarm information dissemination stage are as follows: S201: Alarm message monitoring started: The system background starts the WebSocket long connection service to establish continuous communication with the third-party alarm source, configures the specified communication address and message format parsing rules for monitoring, and realizes real-time capture of alarm information; S202: Alarm Message Reception and Parsing: When an alarm source detects an abnormal state, it pushes an alarm message to the system via a WebSocket long connection; after receiving the message, the system extracts key fields according to preset parsing rules, verifies the integrity of the message, and generates standardized alarm data; S203: Alarm Message Queue Distribution: The system encapsulates standardized alarm data into RabbitMQ messages and routes them to the corresponding topic message queue based on the device identifier and region information in the message. The RabbitMQ message queue pushes alarm messages asynchronously to the user interface and reporting module that subscribe to the queue according to the "first-in, first-out" principle to avoid message congestion and ensure push efficiency. S204: Alarm Information Closed-Loop Confirmation: After receiving the alarm message, the user interface and reporting module can accurately analyze the area and bed to which the alarm belongs, realizing closed-loop processing of the entire link from the device end to the platform end, so that medical staff can receive accurately located abnormal alarm information in the first time.

[0009] Preferably, the page design of the data visualization interface is based on the Vue modern framework for page construction, making full use of its componentization and responsive features to achieve efficient rendering and flexible expansion of the interface. Through modular layout and dynamic loading mechanism, the page not only has good maintainability and scalability, but also can adapt to the access needs of multiple terminals, providing medical staff with a simple, intuitive and high-performance operating environment. The charts are designed using ECharts professional front-end visualization technology to present multi-dimensional medical data graphically. Through various visualization methods such as line charts, bar charts, and heatmaps, the charts can intuitively display the trends of patients' vital signs, equipment usage, and regional monitoring status, forming a panoramic data display capability, thereby providing data support for clinical decision-making and management scheduling. In the interaction design, a user-centric design concept is introduced at the interaction level. By combining dynamic interaction and visual operation feedback, the smoothness of interaction for medical staff in data query, alarm confirmation and task operation is significantly improved. Through humanized interaction logic and intelligent prompt mechanism, medical staff can complete the operation in the shortest path, reduce learning cost and error rate, thereby comprehensively improving the system's usability and work efficiency.

[0010] Preferably, after receiving an alarm message about an abnormal patient status sent by an IoT device, the alarm system can achieve immediate alarm through multi-channel linkage, ensuring that alarm data is transmitted to the alarm device within milliseconds. After receiving the alarm, the alarm device immediately activates the response mechanism to ensure that the alarm is transmitted in a timely manner and to perform necessary response actions, including triggering an alarm sound and changing the device status. At the same time, the data visualization interface can present abnormal information intuitively through highlighting prompts, pop-up warnings, and real-time data refresh, thereby ensuring that medical staff are informed of the alarm content as soon as they operate the terminal. The alarm system supports a multimodal alarm mechanism. When medical staff fail to pay attention to the terminal interface in a timely manner, it will proactively push the patient's abnormal condition to the medical staff's work environment through voice broadcast enhanced notification, so as to avoid the risk from escalating due to information omission or delayed confirmation.

[0011] Preferably, the patient abnormal status alarm message includes the abnormality type, the patient's region and bed information, and the abnormality type includes excessively fast heart rate, excessively slow heart rate, and abnormal drip rate.

[0012] Compared with existing technologies, the beneficial effects of this invention are: 1. Ensuring the real-time and accuracy of medical data: Through multi-source data acquisition and intelligent processing, efficient integration and millisecond-level synchronization of third-party heterogeneous data are achieved, ensuring that patients' physiological indicators can be accurately and timely transmitted to the back-end system, enabling medical staff to make decisions and interventions based on global and real-time data trends; 2. Efficient real-time monitoring and low-latency alarm mechanism: The system adopts an advanced real-time monitoring terminal to continuously track and intelligently analyze the patient's key vital signs. Thanks to the millisecond-level low-latency communication mechanism, once a patient shows an abnormality, the system can trigger an early warning and push it to the medical terminal immediately, realizing a high-speed closed loop from abnormality identification to alarm response, which greatly improves the efficiency and agility of clinical nursing. 3. Visualized intelligent interaction and multimodal reminders: When a patient experiences an abnormal condition, the system can provide real-time pop-up reminders on the nurse station equipment through a data visualization interface. Combined with multimodal interaction methods such as voice broadcasting, it forms an intuitive and efficient information transmission link, helping medical staff to quickly locate the problem and take immediate action, thereby significantly optimizing the nursing experience. 4. Comprehensive improvement in patient safety and nursing quality: Through continuous monitoring and intelligent early warning of patient vital signs data, the system not only strengthens the patient safety protection mechanism, but also provides medical staff with scientific and accurate auxiliary decision support, further improving the reliability of medical services and the quality of nursing care. This invention uses a WebSocket long connection to receive alarm messages in real time and a RabbitMQ message queue to efficiently distribute information, replacing traditional polling / scheduled tasks and the HTTP protocol, significantly reducing response latency to avoid delays in emergency alarms. At the same time, it relies on the MQTT protocol to achieve unified management and real-time interaction of multiple devices, solving the problem of untimely data transmission in device collaboration, and ultimately improving system security, data transmission efficiency and device collaboration capabilities, making it suitable for scenarios with high requirements for real-time performance and reliability, such as smart wards. Attached Figure Description

[0013] Figure 1 This is a block diagram of a dynamic data push and alarm response system for smart devices proposed in this invention; Figure 2 This is a flowchart of a data acquisition and processing module in a dynamic data push and alarm response system for smart devices proposed in this invention; Figure 3 This is a flowchart of an IoT device module in a dynamic data push and alarm response system for smart devices proposed in this invention. Detailed Implementation

[0014] The present invention will be further explained below with reference to specific embodiments. Example

[0015] Reference Figure 1-3 This embodiment proposes a dynamic data push and alarm response system for smart devices, including a data acquisition and processing module, an Internet of Things (IoT) device module, and a user interface and reporting module. The data acquisition and processing module periodically collects core business data through a high-precision timed scheduling mechanism, performs format conversion and standardization processing on multi-source heterogeneous data, and uses a distributed caching mechanism to accelerate access to hot data and optimize database load. The data acquisition and processing module operates in two phases: data acquisition and data processing. The specific logical steps of the data acquisition phase are as follows: S1011: Identity Authentication Initialization: When the system starts up for the first time, MD5 encryption calculation is performed on the HTTP request header to generate unique identity authentication information, which is used to establish a security baseline for data interaction. All subsequent data retrieval operations must pass this authentication verification to ensure the legality of data access. S1012: Data Acquisition Scheduling: The background starts a high-precision timed scheduling mechanism to trigger core business data acquisition tasks according to a preset cycle. The core business data includes patient information and bed status. S1013: Data retrieval execution: Based on the standardized HTTP protocol, a data retrieval request is initiated to the data source. The request carries the identity authentication information generated in S1011. After verification, the latest business data is obtained to achieve real-time information synchronization. S1014: Data Acquisition Status Monitoring: The data acquisition execution status is displayed in real time on the client's visual management interface, including the number of successfully acquired items, the number of failed items, and the reasons for failure. If a data acquisition error or task interruption occurs, the user can trigger the task start / stop or restart operation through the interface to complete the data acquisition process control. S1015: Anomaly Capture and Logging: An asynchronous anomaly capture mechanism is enabled during the data collection process. When a single point of failure occurs, the anomaly is immediately intercepted to prevent process crashes. At the same time, the details of the anomaly event and the system operation log are persistently stored in the log database to provide a basis for subsequent problem localization. The specific logical steps in the data processing stage are as follows: S1021: Multi-source heterogeneous data standardization: Receive the collected multi-source heterogeneous data, complete the format conversion and structure processing according to the preset data parsing and conversion rules, and generate a standardized data set; S1022: Hot Data Caching Optimization: Identify frequently accessed key data and store it in a distributed caching system; at the same time, configure a cache expiration policy to reduce the number of direct database accesses, reduce database load, and shorten data access latency; S1023: Persistent Data Storage: The standardized and complete data is persistently stored using a high-availability storage strategy; index optimization is performed on the stored data to improve the efficiency of subsequent data retrieval; at the same time, a multi-replica storage mechanism is started to back up data on different nodes to ensure data security; S1024: Data and Configuration Backup: Start scheduled task scheduling to perform snapshot backups on persistent data according to a preset cycle, generate backup files and store them on off-site disaster recovery nodes; for critical business configurations and rules, the system provides visual backup and recovery management functions to ensure that core configurations can be quickly restored during version iterations, parameter adjustments or emergency recovery, and ensure that core configurations can be quickly restored during version iterations or anomalies. The IoT device module is used to implement IoT device management and alarm information distribution mechanisms; The operation of the IoT device module is divided into two phases: IoT device management and IoT device alarm information dissemination. In the IoT device management phase, the system achieves unified access and intelligent control of various sensors and terminal devices through deep integration of smart gateways and multi-source heterogeneous IoT devices. The system is built on the MQTT protocol to build an efficient message middleware, providing a lightweight communication mechanism with low bandwidth consumption, high reliability and excellent scalability, meeting the device management and data interaction needs in large-scale IoT scenarios. At the functional level, it supports both fine-grained control of single-point devices and centralized management capabilities at the regional level, forming a multi-level control system from local to global. In terms of reliability, the system uses the message queue characteristics of MQTT to achieve message persistence. Even when the device is offline or the network is interrupted, the message can be securely stored on the server and automatically resent when the device is reconnected, thereby ensuring the stable transmission of critical instructions and alarm information and business continuity. The specific logical steps for issuing alarm information from IoT devices are as follows: S201: Alarm message monitoring started: The system background starts the WebSocket long connection service to establish continuous communication with the third-party alarm source, configures the specified communication address and message format parsing rules for monitoring, and realizes real-time capture of alarm information; S202: Alarm Message Reception and Parsing: When an alarm source detects an abnormal state, it pushes an alarm message to the system via a WebSocket long connection; after receiving the message, the system extracts key fields according to preset parsing rules, verifies the integrity of the message, and generates standardized alarm data; S203: Alarm Message Queue Distribution: The system encapsulates standardized alarm data into RabbitMQ messages and routes them to the corresponding topic message queue based on the device identifier and region information in the message. The RabbitMQ message queue pushes alarm messages asynchronously to the user interface and reporting module that subscribe to the queue according to the "first-in, first-out" principle to avoid message congestion and ensure push efficiency. S204: Alarm Information Closed-Loop Confirmation: After receiving the alarm message, the user interface and reporting module can accurately analyze the area and bed to which the alarm belongs, realizing the closed-loop processing of the entire link from the device end to the platform end, so that medical staff can receive the accurately located abnormal alarm information in the first time. The user interface and reporting module includes a data visualization interface and an alarm system, which are used to present the processing results to the user. The data visualization interface is designed based on the modern Vue framework, which fully utilizes its componentization and responsive features to achieve efficient rendering and flexible expansion of the interface. Through modular layout and dynamic loading mechanism, the page not only has good maintainability and scalability, but also can adapt to the access needs of multiple terminals, providing medical staff with a simple, intuitive and high-performance operating environment. The charts are designed using ECharts professional front-end visualization technology to present multi-dimensional medical data graphically. Through various visualization methods such as line charts, bar charts, and heatmaps, the charts can intuitively display the trends of patients' vital signs, equipment usage, and regional monitoring status, forming a panoramic data display capability, thereby providing data support for clinical decision-making and management scheduling. In the interaction design, a user-centric design concept is introduced at the interaction level. By combining dynamic interaction and visual operation feedback, the smoothness of interaction for medical staff in data query, alarm confirmation and task operation is significantly improved. Through humanized interaction logic and intelligent prompt mechanism, medical staff can complete the operation in the shortest path, reduce learning cost and error rate, thereby comprehensively improving the system's usability and work efficiency. After receiving an alarm message about an abnormal patient status from an IoT device, the alarm system can provide immediate alerts through multi-channel linkage, ensuring that alarm data is transmitted to the alarm device within milliseconds. Upon receiving the alarm, the alarm device immediately activates the response mechanism to ensure timely alarm transmission and execute necessary response actions, including triggering alarm sounds and changing device status. At the same time, the data visualization interface can present abnormal information intuitively through highlighting prompts, pop-up warnings, and real-time data updates, thereby ensuring that medical staff are informed of the alarm content as soon as they operate the terminal. The patient abnormal status alarm message includes the abnormality type, the patient's area and bed information, and the abnormality types include too fast heart rate, too slow heart rate and abnormal drip rate. The alarm system supports a multimodal alarm mechanism. When medical staff fail to pay attention to the terminal interface in time, the system will proactively push the patient's abnormal condition to the medical staff's work environment through voice broadcast enhanced notification, so as to avoid the risk from escalating due to information omission or delayed confirmation. This embodiment uses a WebSocket long connection to receive alarm messages in real time and a RabbitMQ message queue to efficiently distribute information, replacing traditional polling / scheduled tasks and the HTTP protocol, significantly reducing response latency to avoid delays in emergency alarms; at the same time, it relies on the MQTT protocol to achieve unified management and real-time interaction of multiple devices, solving the problem of untimely data transmission in device collaboration, and ultimately improving system security, data transmission efficiency and device collaboration capabilities, making it suitable for scenarios with high requirements for real-time performance and reliability, such as smart wards.

[0016] In this embodiment, after the system starts, the data acquisition and processing module first uses MD5 encryption to generate unique identity authentication information to build a security baseline. Then, it uses a high-precision timed scheduling mechanism combined with a standardized HTTP protocol to pull core business data such as patient information and bed status. During the process, asynchronous anomaly capture and log persistence functions are enabled simultaneously to ensure stability. Subsequently, the multi-source heterogeneous data is formatted and standardized. Distributed caching is used to optimize the access efficiency of hot data. Finally, data security persistence and efficient retrieval are achieved through multi-copy storage, timed backup, and index optimization. The IoT device module completes unified registration, status monitoring, and configuration updates for all connected smart devices based on the MQTT protocol, supporting single-point fine-grained control and regional centralized management. At the same time, it listens in real time through a WebSocket long connection. Alarm information from sensors is asynchronously distributed to the target module via a RabbitMQ message queue after receiving abnormal data. The MQTT message persistence mechanism ensures that messages are not lost when the device is offline and are automatically resent when the device comes back online. The user interface and reporting module are built on the Vue framework to create a responsive interface that is compatible with multiple terminals. ECharts is used to visualize medical data in the form of line charts, bar charts, etc. After receiving alarm information, millisecond-level visual alarms are achieved through interface highlighting and pop-up warnings. Medical staff can clearly identify the type of abnormality and the patient's area and bed information. After the medical staff has completed the treatment, the alarm status can be updated by confirming in the system. This forms a closed loop from data collection to alarm response and treatment, ultimately ensuring real-time and accurate medical data, improving alarm response efficiency, and strengthening patient safety protection and nursing quality.

[0017] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A dynamic data push and alert response system for smart devices, characterized in that, The system comprises a data acquisition and processing module, an Internet of Things device module, and a user interface and reporting module. The data acquisition and processing module periodically acquires core business data through a high-precision timing scheduling mechanism, and performs format conversion and standardization processing on multi-source heterogeneous data, and uses a distributed cache mechanism to accelerate access to hot data and optimize database load. The Internet of Things device module is used to perform Internet of Things device management and alarm information issuing mechanism. The user interface and reporting module comprises a data visualization interface and an alarm system, and is used to present the processing results to the user.

2. The dynamic data push and alert response system for smart devices according to claim 1, wherein, The data acquisition and processing module is divided into a data acquisition stage and a data processing stage during operation, and the specific logic steps of the data acquisition stage are as follows: S1011: identity authentication initialization: when the system is started for the first time, MD5 encryption calculation is performed on the HTTP request header to generate unique identity authentication information, which is used to establish a security baseline for data interaction, and all subsequent data pulling operations need to pass through the authentication verification to ensure the legality of data access; S1012: data acquisition scheduling: a high-precision timing scheduling mechanism is started in the background, and core business data acquisition tasks are triggered according to a preset period, and the core business data includes patient information and bed status; S1013: data pulling execution: based on the standardized HTTP protocol, a data pulling request is initiated to the data source, the request carries the identity authentication information generated in S1011, the latest business data is obtained after verification, and information real-time synchronization is realized; S1014: acquisition state monitoring: the acquisition execution state is displayed in real time on the client visual management interface, including the number of successfully acquired items, the number of failed items and the failure reason, if acquisition exception or task interruption occurs, the user can trigger task start-stop or restart operation through the interface to complete acquisition process control; S1015: exception capture and log recording: an asynchronous exception capture mechanism is enabled during the acquisition process, when a single-point exception occurs, the exception is immediately intercepted and process crash is avoided; at the same time, the exception event details and system running log are stored persistently in the log database to provide basis for subsequent problem positioning.

3. The dynamic data push and alert response system for smart devices of claim 2, wherein, The specific logic steps of the data processing stage are as follows: S1021: multi-source heterogeneous data standardization: the multi-source heterogeneous data collected is received, format conversion and structured processing are completed according to the preset data parsing and conversion rules, and a standardized data set is generated; S1022: hot data cache optimization: the key data with high access frequency is stored in the distributed cache system; at the same time, the cache expiration strategy is configured to reduce the number of direct database access times, reduce the database load, and shorten the data access delay; S1023: data persistent storage: the complete data after standardization processing is stored persistently through a high-availability storage strategy; index optimization is performed on the stored data to improve the subsequent data retrieval efficiency; at the same time, a multi-replica storage mechanism is started to backup data in different nodes to ensure data security; S1024: data and configuration backup: a timed task scheduling is started, and snapshot backup is performed on the persistent data according to a preset period to generate a backup file and store it in a remote disaster recovery node; For key business configuration and rules, the system provides visual backup and recovery management functions to ensure that the core configuration can be quickly restored during version iteration, parameter adjustment or emergency recovery, and to ensure that the core configuration can be quickly restored during version iteration or abnormality.

4. The dynamic data push and alert response system for smart devices of claim 1, wherein, The Internet of Things device module is divided into an Internet of Things device management stage and an Internet of Things device alarm information issuing stage during operation; In the Internet of Things device management stage, through the deep integration of intelligent gateways and multi-source heterogeneous Internet of Things devices, unified access and intelligent control of various sensors and terminal devices are realized. The system is based on the MQTT protocol to build an efficient message middleware, providing a lightweight communication mechanism with low bandwidth occupation, high reliability and excellent expansion capability, meeting the device management and data interaction needs in large-scale Internet of Things scenarios. In terms of function, it not only supports fine-grained control of single-point devices, but also has regional-level centralized management capability, forming a multi-level control system from local to global. In terms of reliability, the system uses the message queue feature of MQTT to realize message persistence. Even in the case of device offline or network interruption, messages can be safely saved on the server side and automatically reissued when the device is reconnected, thereby ensuring the stable transmission of critical instructions and alarm information and business continuity.

5. The dynamic data push and alert response system for smart devices of claim 4, wherein, The specific logic steps of the Internet of Things device alarm information issuing stage are as follows: S201: Alarm message listening starts: the system background starts the WebSocket long connection service, establishes continuous communication with the third-party alarm source, configures the listening of the specified communication address and message format analysis rules, and realizes real-time capture of alarm information; S202: Alarm message receiving and parsing: when the alarm source detects an abnormal state, it pushes the alarm message to the system through the WebSocket long connection; after receiving the message, the system extracts the key fields according to the preset parsing rules, verifies the message integrity, and generates standardized alarm data; S203: Alarm message queue distribution: the system encapsulates the standardized alarm data into RabbitMQ messages, and routes them to the corresponding topic message queue according to the device identifier and region information in the message; the RabbitMQ message queue pushes the alarm message to the user interface and report module subscribed to the queue according to the "first-in, first-out" principle, avoiding message congestion and ensuring pushing efficiency; S204: Alarm information closed loop confirmation: the user interface and report module can accurately parse the region and bed to which the alarm belongs after receiving the alarm message, realizing full-link closed loop processing from the device end to the platform end, so that medical staff can receive accurate positioning of abnormal alarm information in the first time.

6. The dynamic data push and alert response system for smart devices of claim 1, wherein, The page design of the data visualization interface is based on the Vue modern framework for page construction, fully utilizing its componentization and responsiveness to realize efficient rendering and flexible expansion of the interface. Through modular layout and dynamic loading mechanism, the page not only has good maintainability and scalability, but also can adapt to multi-terminal access needs, providing a simple, intuitive and superior performance operating environment for medical staff; The ECharts professional front-end visualization technology is used in the design of the chart to realize graphical presentation of multidimensional medical data, and through various visualization means such as line charts, column charts and heat maps, the patient vital sign trend, the equipment usage and the regional monitoring state can be intuitively displayed, forming a panoramic data display capability, thereby providing data support for clinical decision-making and management scheduling. In the interactive design, the design concept with user experience as the core is introduced in the interaction layer, and the dynamic interaction and visual operation feedback are combined to significantly improve the interaction fluency of medical staff in the data query, alarm confirmation and task operation process. Through the humanized interaction logic and intelligent prompt mechanism, the medical staff can complete the operation in the shortest path, reduce the learning cost and the misoperation rate, thereby comprehensively improving the ease of use and the work efficiency of the system.

7. The dynamic data push and alert response system for smart devices of claim 1, wherein, After receiving the patient abnormal state alarm message sent by the Internet of Things device, the alarm system can realize instant alarm through the multi-channel linkage mode, ensure that the alarm data is transmitted to the alarm device within a millisecond delay, and after receiving the alarm, the alarm device starts the response mechanism immediately to ensure that the alarm is conveyed in time and the necessary response actions are executed, including triggering the alarm sound, changing the device state, and at the same time, the data visualization interface can intuitively present the abnormal information in the form of highlight prompt, pop-up warning and real-time data refresh, thereby ensuring that the medical staff can learn the alarm content in the first time when operating the terminal. The alarm system supports a multi-modal alarm mechanism, and in the case that the medical staff fails to timely focus on the terminal interface, the abnormal condition of the patient is actively pushed to the working environment of the medical staff through voice broadcast enhanced notification, thereby avoiding the risk of risk expansion due to information omission or delayed confirmation. 8.The smart device-oriented dynamic data push and alarm response system according to claim 7, wherein, The patient abnormal state alarm message includes the abnormal type, the area and bed information of the patient, and the abnormal type includes rapid heart rate, slow heart rate and abnormal drop speed.

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