A pathogenic aerosol monitoring and disinfection integrated intelligent management and control system

Abstract

This invention discloses an integrated intelligent control system for pathogen aerosol monitoring and disinfection, relating to the field of pathogen aerosol control technology. Based on a "front-end sensing—edge control—cloud management" architecture, the system collects pathogen aerosol and environmental parameters in real time through monitoring devices, while disinfection devices perform disinfection tasks. Relying on multi-network communication guarantees, closed-loop control logic, and multi-terminal collaborative management, it achieves functions such as real-time monitoring of pathogen aerosol concentration, adaptive adjustment of disinfection dosage, and remote intelligent control, realizing deep linkage between monitoring and disinfection devices. This system is suitable for public health prevention and control in densely populated places such as hospitals, airports, and shopping malls, and can significantly improve the accuracy, efficiency, and intelligence level of pathogen aerosol disinfection.

Description

Technical Field

[0001] This invention belongs to the field of environmental disinfection, and in particular relates to an integrated intelligent control system for pathogen aerosol monitoring and disinfection. Background Technology

[0002] In public spaces such as hospitals, schools, and shopping malls, airborne respiratory pathogens (viruses, bacteria, fungi, etc.) are a significant factor contributing to group transmission. To reduce the risk of airborne transmission, current technologies typically employ aerosol monitoring equipment in conjunction with air disinfection devices for prevention and control. However, current pathogen aerosol monitoring and disinfection often use a separate approach, consisting mainly of independent monitoring and disinfection equipment without a direct linkage mechanism. The monitoring equipment is only responsible for collecting data on air quality, environmental parameters, or the types and concentrations of pathogen aerosols, presenting the information to the user through a local display screen or a simple data upload module, and does not have the function of sending control commands to the disinfection equipment. Its core structure includes sensor components, a data acquisition module, and a local display or simple upload module. The working principle is that after the sensor senses environmental data, the data is processed by the acquisition module and output to the display or primary storage terminal. Patent CN119643798A discloses a continuous aerosol monitoring system. The control module is used to control the gas flow process during sampling and measurement. The data processing module is used to set the parameters involved in the continuous monitoring of gas aerosols, process the data, and display the monitoring data. Patent CN119334837A discloses an online monitoring and early warning method and system for bioaerosols. By analyzing the first real-time monitoring data and transmitting it to the monitoring and early warning center, the early warning display unit dynamically displays the predicted concentration and the first bioaerosol concentration, and generates a first risk warning based on the dynamic display information.

[0003] The disinfection equipment requires users to manually operate or preset fixed programs based on information from monitoring equipment feedback; parameters such as disinfection dosage and duration cannot be dynamically adjusted based on real-time monitoring data. Its core structure includes disinfection execution components (such as photocatalysts, UV lamps, and plasma) and a manual / fixed program control module. Its working principle is to receive user commands or start disinfection operations according to preset parameters, and automatically shut down upon completion, without any data feedback. Furthermore, existing solutions rely on a single communication method, primarily fixed WiFi networks, lacking network redundancy; management is fragmented, supporting only local operation or single-terminal management, lacking a unified cloud platform for collaboration; data processing is limited to local storage or simple uploading, failing to establish a linkage mechanism for analysis, decision-making, and feedback calibration. Publication number CN119393889A proposes an intelligent control system for a plasma air disinfection module, which incorporates real-time detection of various air quality indicators. The data analysis module is electrically connected to the air quality detection module and is used to receive, classify, organize, and analyze various air quality indicators. Based on the air quality development trend model, the system determines the appropriate wind speed, discharge power, and discharge time according to a real-time matching strategy to ensure safe use, and can output the maximum discharge power.

[0004] While existing separate monitoring and disinfection solutions can meet basic requirements for pathogen aerosol control, they have significant technical limitations. The core problem lies in the disconnect between monitoring and disinfection, hindering data-driven intelligent decision-making and dynamic control. This results in insufficient targeting of disinfection operations, wasted resources, or incomplete disinfection. Furthermore, the reliance on a single communication method makes the system susceptible to environmental factors leading to outages; the decentralized management model is ill-suited for large-scale deployments; and the lack of a closed-loop feedback mechanism prevents continuous optimization of disinfection accuracy. These shortcomings make it difficult to meet the demands of modern public health prevention and control for intelligence and precision.

[0005] The existing technology has the following drawbacks:

[0006] Monitoring and disinfection are disconnected, as they are independent devices without an automatic linkage mechanism. Manual intervention is required to start the disinfection operation, resulting in a delayed response and an inability to dynamically adjust the disinfection parameters based on the real-time pathogen concentration.

[0007] The communication method is limited to WiFi network. When the network coverage is insufficient or interrupted on site, the system cannot transmit data and instructions normally, resulting in operation interruption.

[0008] The management model is fragmented and lacks a unified multi-terminal collaborative management platform. Users need to operate monitoring equipment and disinfection equipment separately, which makes it impossible to achieve remote overall control, centralized data analysis and multi-terminal synchronous management.

[0009] Without a closed-loop feedback mechanism, there is a lack of real-time effect monitoring and data feedback after the disinfection operation is completed, making it impossible to calibrate and optimize the subsequent disinfection dosage, resulting in low disinfection accuracy. Summary of the Invention

[0010] This invention achieves integrated monitoring and disinfection of pathogenic aerosols, automatically initiating and adjusting disinfection operations based on real-time monitoring data without manual intervention, thus improving response speed and targeting. This invention constructs a multi-network redundant communication mechanism to ensure continuous system operation even when the on-site WiFi network is interrupted, avoiding interruptions in data transmission and command execution. This invention establishes a multi-terminal collaborative management system of "local + cloud + mobile terminal," realizing centralized storage, intelligent analysis, remote control, and synchronization of monitoring data across multiple terminals. Ultimately, it forms a closed-loop control of "monitoring—decision-execution—feedback," calibrating disinfection dosage through real-time feedback data to improve the accuracy and effectiveness of pathogenic aerosol disinfection. The specific technical solution is as follows:

[0011] An integrated intelligent control system for pathogen aerosol monitoring and disinfection includes:

[0012] The front-end sensing layer consists of a monitoring device and a disinfection device. The monitoring device is an integrated pathogen aerosol monitoring device, used to collect pathogen aerosol concentration data and environmental parameters in real time. The disinfection device is based on a composite disinfection method of filtration, deep ultraviolet light irradiation, corona plasma discharge and photocatalysis, and is used to perform disinfection tasks. The monitoring device and the disinfection device communicate with each other through a router.

[0013] The edge control layer includes an Android tablet connected to the router and establishing a communication connection with the front-end perception layer. It is used to display the real-time status, monitoring data and alarm information of the monitoring device and the disinfection device, execute local policy configuration, and receive rule instructions from the cloud and forward them to the front-end perception layer. At the same time, it uploads local data to the cloud.

[0014] The cloud management layer includes a cloud server and a cloud platform. The cloud server is communicatively connected to the Android tablet and is used to receive data uploaded by the edge control layer or the front-end perception layer, perform storage, cleaning, and model analysis, calculate the optimal disinfection dosage based on monitoring data, generate control rules, and distribute them to the disinfection device in the edge control layer or directly to the front-end perception layer. The cloud platform is communicatively connected to the cloud server and provides data visualization analysis, batch device management, unified policy configuration, and alarm information aggregation functions.

[0015] The user interaction layer includes an APP terminal, which communicates bidirectionally with the Android tablet and the cloud platform, enabling users to remotely view monitoring data, device status, alarm information, remotely trigger disinfection tasks, adjust disinfection parameters, and receive alarm notifications pushed by the system.

[0016] The present invention has the following beneficial technical effects:

[0017] Integrated monitoring and disinfection architecture: The monitoring devices and disinfection devices at the front-end perception layer are directly linked through routers, edge control terminals, and the cloud, enabling automatic triggering of "data collection - intelligent decision-making - disinfection execution" without human intervention.

[0018] Multi-network redundancy communication mechanism: The edge control terminal (Android tablet) supports dual-mode switching between WiFi and 4G / 5G. When the WiFi network is interrupted, it automatically switches to the mobile network to ensure the continuity of system data transmission and command execution.

[0019] The "monitoring-decision-execution-feedback" closed-loop control logic calibrates the disinfection dosage model through post-disinfection data feedback, achieving adaptive matching of disinfection factor dosages and improving disinfection accuracy.

[0020] Multi-terminal collaborative management system: Construct a multi-terminal management model of "cloud platform + edge tablet + APP" to achieve coordinated and unified data storage, global scheduling, local control and remote operation. Attached Figure Description

[0021] Figure 1 Architecture diagram of an intelligent system for aerosol detection and eradication;

[0022] Figure 2 A schematic diagram illustrating the content of the multi-terminal monitoring device;

[0023] Figure 3 A schematic diagram illustrating the multi-terminal disinfection device.

[0024] Figure 4 Here is a detailed structural diagram of the monitoring device;

[0025] Figure 5 Detailed diagram of the disinfection device. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other. To achieve the above objectives, this invention adopts the following technical solution.

[0027] The integrated intelligent control system for pathogen aerosol monitoring and disinfection of this invention consists of a "front-end sensing - edge control - cloud management - user interaction layer." Each layer is linked through specific communication methods to achieve deep integration of monitoring, disinfection, and management. The overall system architecture is as follows: Figure 1 As shown, it specifically includes the following core components:

[0028] Front-end sensing layer: Composed of monitoring devices and disinfection devices, serving as the system's data acquisition and execution end;

[0029] Edge control layer: Centered on the Android tablet, serving as a local management and communication hub;

[0030] Cloud management layer: including cloud servers and cloud platforms, responsible for data storage, model analysis and overall management;

[0031] User interaction layer: including APP terminal, providing users with access to remote operation and status viewing.

[0032] Monitoring devices, such as Figure 2 As shown: This integrated pathogen aerosol monitoring device achieves efficient capture, enrichment, and rapid nucleic acid extraction, amplification, and detection of eight pathogenic microorganisms, reaching a detection sensitivity of 20 copies / mL and a total process time of 45 minutes. It can operate continuously for 96 hours, ultimately achieving highly sensitive and rapid monitoring and alarm for pathogen aerosols. The monitoring device includes a sampling module, a purification module, a detection module, an automatic pipetting module, and a chip storage module. Figure 4 As shown, the system includes: ① a support frame; ② a reagent storage and waste disposal area containing adsorption solution (approximately 3.5L), cleaning solution (approximately 4.5L), waste liquid (8~10L), and a waste cartridge slot (capable of holding 300 purification cartridges); ③ a sampling module containing a magnetic bead mixing and automatic liquid dispensing device; ④ a purification cartridge storage tank for automatic cartridge replacement; ⑤ a purification cartridge conveyor belt for automatic cartridge transfer; ⑥ a magnetic sleeve; ⑦ a puncture needle; ⑧ a filter cartridge tip; ⑨ a clamp; and ⑩ a 3D moving platform for automated sample transfer. Magnetic rod, pipetting apparatus Chip storage slot, Fluorescence signal acquisition module, Heating and cooling module, Reagent bottles and waste liquid bottles Discarded card slot.

[0033] The instrument's working area is the core functional area of ​​the integrated aerosol sampling and detection machine, enabling automated sample processing and detection. It highly integrates key functional units such as a sampling module, purification module, detection module, automated pipetting module, and chip storage module. The sampling module, equipped with a magnetic bead mixing and automated liquid dispensing device, efficiently collects and enriches aerosol samples. The purification module, through the synergistic action of the purification cartridge storage tank, conveyor belt, magnetic sleeve, and magnetic rods, achieves automated transfer of the purification cartridge and magnetic bead-based separation and purification of target substances such as nucleic acids. The detection module integrates a fluorescence signal acquisition module and a temperature control module, providing precise temperature control for nucleic acid amplification reactions and completing fluorescence signal acquisition and analysis, thereby achieving qualitative or quantitative detection of pathogenic microorganisms. The automated pipetting module, utilizing a 3D moving platform and pipetting device, accurately completes liquid aspiration and release between modules, ensuring the continuity of sample processing. The chip storage tank stores the chips required for detection, providing hardware support for the detection process. The close cooperation of these modules makes this area the core hub from sample collection to result output, significantly improving the automation and efficiency of aerosol pathogen detection.

[0034] (2) Reagent Storage and Waste Disposal Area: The reagent storage and waste disposal area serves as the "logistics support center" for the aerosol sampling and testing machine, primarily responsible for centralized reagent management and standardized disposal of experimental waste. Regarding reagent storage, this area is equipped with large-capacity containers that can store approximately 3.5L of adsorption liquid for preliminary sample enrichment and approximately 4.5L of washing liquid for eluting impurities during purification, providing a stable reagent supply for the entire testing process. For waste disposal, it is equipped with 8-10L waste liquid bottles to centrally collect various waste liquids generated during the testing process, preventing contamination; simultaneously, a waste card slot can accommodate 300 purification boxes for unified collection of used purification boxes, facilitating subsequent centralized processing and disposal. Through the orderly storage of reagents and standardized management of waste, this area ensures both the reagent needs of the testing process and the compliant disposal of experimental waste, providing strong support for the stable operation of the entire equipment and the safety of the operating environment.

[0035] The pathogen detection software achieves closed-loop management of the entire detection process through the collaboration of multiple functional modules:

[0036] (1) Parameter setting module: This module provides flexible and accurate parameter configuration capabilities for the detection process, and supports personalized configuration of key parameters such as number of runs (single or multiple cycle detections can be set according to experimental needs), nucleic acid collection time (precisely control the duration of sample collection to ensure the consistency of sample volume), sampling volume (adapt to the sample collection volume requirements under different detection scenarios), pipetting volume (ensure the accuracy of reagent transfer to ensure the accuracy of experimental results), and PCR temperature (temperature values ​​and maintenance time can be set in stages to meet the temperature conditions for nucleic acid amplification).

[0037] (2) Equipment control module: mainly responsible for the connection of equipment hardware and the status management of the testing process. In terms of serial port connection, it can automatically identify and adapt to various serial port devices to achieve rapid access of the device; for the testing process, it can accurately execute status control commands such as start, pause, and termination. When starting, it starts the full process testing; when pausing, it retains the current testing status for subsequent recovery; when terminating, it safely shuts down the device and saves the testing data, ensuring the flexibility and controllability of the testing process.

[0038] (3) Data storage module: It is responsible for data storage throughout the entire detection cycle. It not only stores the configuration data before detection (such as various parameters set in the parameter setting module), but also stores the dynamic data generated during the detection process in real time (such as robotic arm action data, equipment operation status data, etc.). At the same time, it persistently stores the final detection results (such as the qualitative or quantitative results of nucleic acid detection) to provide data support for subsequent data analysis and result traceability.

[0039] (4) Data analysis and processing module: It has powerful data analysis and processing capabilities, and can monitor the detection data in real time (such as monitoring the operating status of the robotic arm, the temperature change of the detection equipment, etc.), perform calculations on the collected data (such as concentration calculation based on sample data, statistical analysis based on multiple sets of data, etc.), draw relevant images required for detection (such as nucleic acid amplification curves, data trend charts, etc.), and finally generate a professional detection report containing detection parameters, process data, and result analysis, providing a basis for the interpretation of detection results and decision-making.

[0040] (5) Communication module: As an information bridge between the software and external systems, it realizes efficient information interaction with the back-end program. It can upload local detection configuration, process data, etc. to the back-end system, and at the same time receive instructions or update information issued by the back-end program, ensuring data synchronization and business collaboration between the software and the back-end system, and helping to build a complete information system for pathogen detection.

[0041] Disinfection devices, such as Figure 3 , 5 As shown, (a) is a schematic diagram of the disinfection device, (b) is a physical image, and (c) is an all-in-one gas sensor and controller. The disinfection device is based on a composite disinfection technology of filtration, deep ultraviolet irradiation, corona plasma discharge, and photocatalysis. The filter is a combination of electrostatic fiber, steel wire mesh, and aluminum alloy frame, with a filtration level of F5 (medium efficiency) and fire resistance; there are 2 ultraviolet lamps, 2 ultraviolet lamp drivers, 8W power, and 24V voltage; there are 4 plasma electrode pins, 6 modules, and 1 driver; the photocatalyst is titanium dioxide.

[0042] The disinfection device includes a sensor module employing a laser particulate sensor, an infrared non-dispersive carbon dioxide sensor, an electrochemical formaldehyde sensor, and a VOC sensor, respectively for acquiring particulate matter concentration (PM2.5), carbon dioxide and formaldehyde concentration, and TVOC concentration. The sensor module also incorporates a temperature and humidity sensor chip. Multiple parameters are output uniformly via an RS485 digital interface. Under identical conditions, data from the all-in-one gas sensor module was compared with data from an indoor environmental testing instrument (within its calibration validity period), and the two sets of data showed near-identical agreement. The data collected by the all-in-one gas sensor module is accurate. The all-in-one gas sensor is integrated with the disinfection and purification module and installed in the central air conditioning system of the controlled area. Airflow passes through the disinfection and purification module, and the sensor collects air quality parameters. This air quality data is uploaded to the cloud via the controller, and the air quality of the controlled area can be viewed on a computer or mobile phone in the background.

[0043] The data communication and module controller receives environmental data collected by sensors and uploads it to the cloud server in real time via Wi-Fi / 4G modules. It also supports remote command issuance for precise control of the execution modules. The controller uses an industrial-grade MCU, possessing excellent anti-interference capabilities and stability, and operates within a temperature range of -10℃ to 60℃, adapting to complex field environments. The communication protocol employs a dual-mode design of MQTT (Message Queuing Telemetry) and HTTP (Hypertext Transfer Protocol) to ensure reliable data transmission and low latency, meeting the needs of various application scenarios.

[0044] In the edge control layer,

[0045] Core device: Android tablet, which connects to the on-site router via WiFi to enable local management of the front-end sensing layer devices.

[0046] Core functions: Display the real-time status, monitoring data, and alarm information of front-end devices; execute local policy configurations (such as disinfection threshold settings and delay parameter settings); automatically switch to 4G / 5G networks to communicate directly with the cloud server when the WiFi network is interrupted, ensuring continuous system operation; receive rule instructions from the cloud and forward them to the front-end devices, while uploading local data to the cloud.

[0047] In the cloud management layer,

[0048] Cloud server: Responsible for receiving data uploaded from the edge control layer or front-end devices, storing, cleaning and model analyzing it; calculating the optimal disinfection dose based on preset algorithms and monitoring data, generating control rules and sending them to the edge control layer or directly to the front-end disinfection device; supporting multi-terminal collaborative management to achieve data synchronization and unified command scheduling.

[0049] Cloud platform: As the global management hub, it provides functions such as data visualization and analysis, batch device management, unified policy configuration, and alarm information aggregation, and supports centralized management and control after large-scale device deployment.

[0050] In the user interaction layer,

[0051] APP terminal: It can communicate bidirectionally with Android tablets and cloud platforms, allowing users to remotely view monitoring data (environmental parameters, pathogen concentration), device status (connection status, running status), and alarm information; remotely trigger disinfection tasks and adjust disinfection parameters; receive alarm notifications pushed by the system, and realize remote management and scheduling of the entire system.

[0052] System workflow (closed-loop control logic):

[0053] Monitoring phase: The monitoring device collects environmental parameters and pathogen aerosol concentration data in real time, uploads them to the router via WiFi, the router aggregates the data and forwards it to the Android tablet, and the tablet simultaneously uploads it to the cloud server.

[0054] Decision-making stage: The cloud server analyzes data using cloud-based models to calculate the optimal disinfection dosage; in local management mode, Android tablets can directly generate decision commands based on preset strategies and real-time data.

[0055] Execution phase: The cloud server sends decision instructions to the Android tablet, which forwards them to the disinfection device via the router, or the cloud server sends instructions directly to the disinfection device via the network. The disinfection device adjusts the spray volume, duration and concentration according to the instructions to carry out the disinfection operation.

[0056] Feedback Phase: After the disinfection operation is completed, the monitoring device collects environmental data and pathogen concentration data again, repeats the upload process, and compares the data before and after disinfection on the cloud server / Android tablet to calibrate the optimal disinfection dosage model, providing parameter basis for the next disinfection operation and forming a closed-loop control of "monitoring-decision-execution-feedback". Specific Implementation

[0058] Taking the prevention and control of pathogenic aerosols in the hospital outpatient hall as an example, the specific implementation process is as follows:

[0059] System Deployment: One monitoring device and one disinfection device are evenly distributed in the outpatient hall. All devices are connected to the on-site router via WiFi. Android tablets are deployed at the nurses' station as edge control terminals and are connected to the router. The cloud server is linked with the hospital's public health management cloud platform, and medical staff and management personnel install APP terminals respectively.

[0060] Parameter configuration: Preset disinfection thresholds (such as starting disinfection when the concentration of a pathogen aerosol is ≥200 copies / mL) and basic disinfection duration (default 30 minutes) through the cloud platform, and synchronize them to Android tablets and disinfection devices.

[0061] Monitoring Operation: The monitoring device collects real-time data on the temperature (25℃), humidity (60%), and PM2.5 (35μg / m³) in the hall. 3 Data on carbon dioxide concentration (450 ppm) and concentrations of eight pathogenic aerosols were collected, with one respiratory pathogen reaching a concentration of 50 copies / mL. The data were uploaded to a tablet and a cloud server via a router.

[0062] Intelligent decision-making: After analyzing the data, the cloud server determines that the disinfection threshold has been reached, calculates the optimal power (50W) and duration (30 minutes), generates a disinfection command and sends it to the Android tablet. The tablet simultaneously pushes alarm information to the management personnel's APP.

[0063] Disinfection execution: The Android tablet forwards instructions to the disinfection device through the router. The disinfection device starts automatically and performs disinfection work according to the set spray volume and duration.

[0064] Feedback calibration: After the disinfection is completed, the monitoring device collects data showing that the concentration of the pathogen aerosol has dropped to 20 copies / mL. The data is uploaded to the cloud, and the cloud server compares the data before and after the disinfection to determine the optimal disinfection dose and duration of 30 minutes for this scenario, and completes the model calibration.

[0065] Network redundancy test: If the WiFi network is interrupted during the disinfection process, the Android tablet will automatically switch to the 4G network to maintain communication with the cloud server and disinfection device, ensuring the continuous execution of the disinfection operation. After the network is restored, it will automatically switch back to WiFi.

[0066] More specifically, the alternative communication method is as follows:

[0067] LoRa wireless communication replaces WiFi as the communication method between the front-end sensing layer and the router: the monitoring and disinfection devices have built-in LoRa modules, and the router is replaced by a LoRa gateway, enabling long-distance, low-power communication between the front-end devices and the gateway; Android tablets connect to the front-end devices through the LoRa gateway, while retaining the 4G / 5G dual-mode switching function. This solution is suitable for scenarios with poor WiFi signal coverage and dispersed device deployment (such as large logistics warehouses), reducing communication power consumption, extending device battery life, and ensuring multi-network redundancy capabilities, while still achieving integrated closed-loop management of monitoring and disinfection.

[0068] More specifically, the alternative to edge control terminals is as follows:

[0069] Replacing Android tablets with industrial-grade IoT gateways as edge control terminals: Industrial-grade IoT gateways support multi-protocol access (compatible with the communication protocols of front-end devices), possess stronger environmental adaptability (high temperature resistance, anti-interference), and communicate with cloud servers via WiFi / 4G / 5G to achieve functions such as data aggregation, local decision-making, and command forwarding. The gateway is equipped with a local display screen to show device status and key data, and supports local button operation to adjust strategies. This solution is suitable for harsh environments such as industrial workshops and outdoor locations, while still meeting the local management and communication hub requirements of the edge control layer, ensuring closed-loop system operation.

[0070] More specifically, the alternative decision-making model is as follows:

[0071] The original cloud-based disinfection dosage calculation model is replaced with a machine learning algorithm: The cloud server has a built-in machine learning model based on random forest. The model is optimized by training a dataset (historical monitoring data, disinfection parameters, and disinfection effect data). After inputting real-time monitoring data, it outputs the optimal disinfection parameters (power and duration). The model supports online updates, continuously improving decision accuracy. This solution only replaces the decision-making algorithm without changing the system architecture and workflow, and can still achieve adaptive matching of disinfection dosage, thus achieving the core objective of this invention.

Claims

1. An integrated intelligent control system for pathogen aerosol monitoring and disinfection, characterized in that, include: The front-end sensing layer consists of a monitoring device and a disinfection device. The monitoring device is an integrated pathogen aerosol monitoring device, used to collect pathogen aerosol concentration data and environmental parameters in real time. The disinfection device is based on a composite disinfection method of filtration, deep ultraviolet light irradiation, corona plasma discharge and photocatalysis, and is used to perform disinfection tasks. The monitoring device and the disinfection device communicate with each other through a router. The edge control layer includes an Android tablet connected to the router and establishing a communication connection with the front-end perception layer. It is used to display the real-time status, monitoring data and alarm information of the monitoring device and the disinfection device, execute local policy configuration, and receive rule instructions from the cloud and forward them to the front-end perception layer. At the same time, it uploads local data to the cloud. The cloud management layer includes a cloud server and a cloud platform. The cloud server is communicatively connected to the Android tablet and is used to receive data uploaded by the edge control layer or the front-end perception layer, store, clean and analyze the data, calculate the optimal disinfection dose based on the monitoring data, generate control rules and send them to the disinfection device of the edge control layer or directly to the front-end perception layer. The cloud platform communicates with the cloud server and provides functions such as data visualization analysis, batch device management, unified policy configuration, and alarm information aggregation. The user interaction layer includes an APP terminal, which communicates bidirectionally with the Android tablet and the cloud platform, enabling users to remotely view monitoring data, device status, alarm information, remotely trigger disinfection tasks, adjust disinfection parameters, and receive alarm notifications pushed by the system.

2. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The monitoring device includes a sampling module, a purification module, a detection module, an automatic pipetting module, and a chip storage module. The sampling module is equipped with a magnetic bead mixing and automatic liquid feeding device. The purification module realizes the automatic transfer of purification boxes and the separation and purification of nucleic acids by magnetic beads through a purification box storage tank, a conveyor belt, a magnetic sleeve, and a magnetic rod assembly. The detection module integrates a fluorescence signal acquisition module and a temperature rise and fall module. The automatic pipetting module accurately completes the aspiration and release of liquid between the modules with the help of a three-dimensional moving platform and a pipetting device.

3. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 2, characterized in that, The monitoring device also includes a reagent storage and waste treatment area. The reagent storage and waste treatment area is equipped with large-capacity containers to store adsorption liquid and cleaning liquid, waste liquid bottles to collect test waste liquid, and waste card slots to accommodate used purification boxes, so as to realize the orderly storage of reagents and the standardized management of waste.

4. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The monitoring device operates pathogen detection software, which includes a parameter setting module, an equipment control module, a data storage module, a data analysis and processing module, and a communication module, to achieve closed-loop management of the entire detection process.

5. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The disinfection device includes a filter, an ultraviolet lamp, a plasma electrode, a photocatalyst, and a sensor module. The sensor module uses a laser particulate matter sensor, an infrared non-dispersive carbon dioxide sensor, an electrochemical formaldehyde sensor, and a VOC sensor to obtain particulate matter concentration, carbon dioxide concentration, formaldehyde concentration, and TVOC concentration, respectively. The sensor module has a built-in temperature and humidity sensor chip, and multiple parameters are output uniformly in the form of an RS485 digital interface.

6. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The disinfection device also includes a data communication and module controller. The data communication and module controller adopts an industrial-grade MCU and uploads data to the cloud server in real time through a Wi-Fi / 4G module. It also supports remote command issuance to achieve precise control of the execution module. The communication protocol adopts a dual-mode design of MQTT and HTTP.

7. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The filter is a combination of electrostatic fiber, steel wire mesh, and aluminum alloy frame, with a filtration level of F5 medium efficiency and fire resistance; the ultraviolet lamp is equipped with 2 lamps, with a power of 8W and a voltage of 24V; the plasma electrode is equipped with 4 pins and 6 modules; the photocatalyst is titanium dioxide.

8. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The communication method between the monitoring device and the disinfection device and the router can also be LoRa wireless communication. The monitoring device and the disinfection device have built-in LoRa modules, and the router uses a LoRa gateway to realize long-distance, low-power communication between the front-end device and the gateway. The Android tablet accesses the front-end sensing layer through the LoRa gateway.

9. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The Android tablet in the edge control layer is replaced by an industrial-grade IoT gateway. The industrial-grade IoT gateway supports multi-protocol access and communicates with the cloud server via WiFi / 4G / 5G to achieve data aggregation, local decision-making, and command forwarding functions. It is equipped with a local display screen to show device status and key data and supports local button operation to adjust strategies.

10. The integrated intelligent control system for pathogen aerosol monitoring and disinfection according to claim 1, characterized in that, The cloud server in the cloud management layer has a built-in machine learning model based on random forest. It optimizes the model by training a dataset and outputs the optimal disinfection parameters after inputting real-time monitoring data.

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