Indoor air purification network control system

Abstract

We provide an indoor air purification network control system. [Solution] The system comprises multiple gas detectors, an indoor air pollution treatment device, and a network-connected cloud computing service device. The multiple gas detectors detect air pollution, and the network-connected cloud computing service device comprises a wireless network cloud computing service module, a cloud control service unit, a device management unit, an application unit, and an artificial intelligence-generated content model. It receives air quality data from the gas detectors via the Internet of Things (IoT) communication, analyzes it using artificial intelligence-generated content model technology, intelligently sends control commands based on the analysis results, automatically adjusts the operating mode of the indoor air pollution treatment device, and performs complete circulating air pollution purification and cleanroom treatment in the indoor space, bringing the indoor space to a cleanroom-class level of cleanliness.

Description

[Technical Field]

[0001] The present invention relates to an indoor air purification network control system, and more particularly to a system that performs real-time detection, purification treatment, and intelligent control of indoor air quality. This system utilizes Internet of Things (IoT) technology and artificial intelligence (AIGC) technology, and combines multiple types of indoor air pollution treatment devices and advanced control technologies to provide cleanroom-class high-quality indoor air. [Background technology]

[0002] Suspended particulate matter refers to solid particles or droplets contained in a gas. Its particle size is extremely small, easily passing through nasal hairs and entering the lungs, causing lung inflammation, asthma, and cardiovascular disease. When other pollutants attach to suspended particulate matter, the respiratory system becomes even more severe. In recent years, air pollution has become a serious problem, particularly with the frequent high concentrations of fine particulate matter (e.g., PM2.5), making monitoring the concentration of suspended particulate matter in the air crucial. However, air flows unpredictably depending on wind direction and speed, and most current air quality monitoring stations for detecting suspended particulate matter are fixed in place, making it impossible to determine the concentration of suspended particulate matter in the immediate vicinity.

[0003] Furthermore, modern people are increasingly concerned about air quality in their living environment. For example, gases such as carbon monoxide, carbon dioxide, volatile organic compounds (VOCs), PM2.5, nitric oxide, and sulfur monoxide, as well as particulate matter contained within these gases, can all affect human health when exposed to the environment, and in serious cases, can even threaten life. Therefore, the quality of ambient air is considered important in every country, and how to detect air quality and avoid or leave areas with poor air quality has become a crucial issue today.

[0004] One way to check the quality of air is to use gas sensors to detect ambient gases. If the detection information can be provided in real time, warning people in the environment and prompting immediate prevention or evacuation, thereby avoiding health effects and harm caused by gases in the environment, then using gas sensors to detect the surrounding environment would be an excellent application.

[0005] Furthermore, with the increasing severity of environmental pollution, indoor air quality is becoming increasingly important. Understanding indoor air quality is difficult, as factors other than outdoor air quality, such as indoor air conditioning conditions and pollution sources, are all major influences. While conventional air purification devices can provide some degree of filtration, they typically cannot adjust in real time according to environmental changes, lack the ability to efficiently respond to different pollution sources, and struggle to meet high air purification requirements. Considering these factors, the present invention aims to provide an indoor air purification network control system that can intelligently and rapidly detect indoor air pollution sources at various locations within a room, effectively remove indoor air pollution to create a clean gaseous state that allows for safe breathing, and monitor indoor air quality in real time, anytime, anywhere. However, these systems have high maintenance requirements during long-term operation, reducing their actual operational efficiency. Therefore, there is a need for an indoor air purification network control system that can handle complex indoor environmental requirements, meet cleanroom requirements for indoor spaces, avoid health impacts and harm from gases in the environment, is capable of automatic adjustment and intelligent control, and possesses highly efficient maintenance functions. This is the main objective of the present invention. [Overview of the project] [Problems that the invention aims to solve]

[0006] The main objective of the present invention is to provide an indoor air purification network control system that achieves highly efficient purification and precise control of indoor air, reaching cleanroom-class cleanliness standards, by monitoring indoor and outdoor air quality data in real time using multiple types of gas detectors and automatically adjusting multiple types of indoor air pollution devices using cloud computing and artificial intelligence technology. [Means for solving the problem]

[0007] To achieve the above objective, one embodiment of the present invention is an indoor air purification network control system comprising a plurality of gas detectors, at least one indoor air pollution treatment device, a network-connected cloud computing service device, a storage center, and at least one central control computer intelligent control device. The plurality of gas detectors are installed in indoor and outdoor spaces and detect air quality data such as PM1, PM2.5, CO2, VOCs, temperature, and humidity. The at least one indoor air pollution treatment device includes devices such as ventilation devices, air purifiers, fan filter units (FFUs), heating and cooling systems, range hoods, exhaust devices, humidity control devices, and mobile vacuum cleaners. The indoor air pollution treatment device can automatically perform air filtration, ventilation, temperature and humidity adjustment, and sterilization operations based on commands from the network-connected cloud computing service device. The network-connected cloud computing service device includes an artificial intelligence generated content (AIGC) model, receives and analyzes data from gas detectors via Internet of Things technology, generates control commands based on the analysis results, and realizes automated control and optimization of the indoor air pollution treatment device, thereby automatically adjusting the operating mode of the indoor air pollution treatment device, performing complete purification and cleanroom treatment of circulating air pollution in the indoor space, and ensuring that the indoor space achieves a cleanroom-class level of cleanliness. The storage center collects and stores information data of the system to form a big data database of professionally generated data and user-generated data, and generates automatically generated data by calculating, comparing, and identifying using the artificial intelligence generated content (AIGC) model. The at least one central control computer intelligent control device receives control commands from the network-connected cloud computing service device via Internet of Things communication, transmits the received control commands to the gas detection module of the indoor air pollution treatment device via Internet of Things communication, and controls the operation of the induction fan.

[0008] According to the proposed concept, the artificial intelligence generated content (AIGC) model technology includes an intelligent energy control system that achieves energy savings and emission reductions by automatically adjusting the operating mode of a device based on real-time monitoring data.

[0009] According to the concept of this proposal, the artificial intelligence generated content (AIGC) model technology includes monitoring the operating status of the device, predicting potential failures, and system maintenance diagnostics that include self-cleaning technology (particularly self-cleaning of filter units and ventilation passages) to maintain the long-term and efficient operation of the device and reduce the requirements for daily maintenance.

[0010] According to the concept of this proposal, the artificial intelligence generated content (AIGC) model technology includes an air quality prediction model to prevent sudden changes in air quality by predicting future changes in air quality and adjusting the operating status of devices in advance.

[0011] According to the concept of this proposal, the artificial intelligence generated content (AIGC) model technology includes an intelligent environmental sensing system that integrates multiple types of sensors and intelligently adjusts system operation according to different environmental parameters to improve the operational efficiency and accuracy of the system. [Brief explanation of the drawing]

[0012] [Figure 1A] This is a schematic diagram of the indoor air purification network control system of the present invention. [Figure 1B] This is a schematic diagram showing the structure of the network-connected cloud computing service device of the present invention. [Figure 1C] This is a schematic diagram showing the structure of the indoor air pollution treatment device of the present invention. [Figure 1D] This is a schematic diagram showing the structure of the artificial intelligence generated content (AIGC) model for the network-connected cloud computing service device of the present invention. [Figure 1E]It is a diagram of an embodiment showing the usage state in the indoor space of the indoor air purification network control system of the present invention. [Figure 1F] It is a schematic diagram showing the ventilation device of the indoor air pollution treatment device of the present invention. [Figure 1G] It is a schematic diagram showing the air purifier of the indoor air pollution treatment device of the present invention. [Figure 1H] It is a cross-sectional schematic diagram of the air purifier of the indoor air pollution treatment device in FIGS. 1E and 1G of the present invention. [Figure 1I] It is a schematic diagram showing the fan filter unit (FFU) of the indoor air pollution treatment device of the present invention. [Figure 1J] It is a cross-sectional schematic diagram of the humidity control device of the indoor air pollution treatment device in FIG. 1E of the present invention. [Figure 1K] It is a cross-sectional schematic diagram of the mobile cleaner of the indoor air pollution treatment device in FIG. 1E of the present invention. [Figure 1L] It is a schematic diagram showing the flow of the ventilation device of the present invention comparing the pressure difference of carbon dioxide (CO2) between the indoor space and the outdoor space through a network-connected cloud computing service device and controlling the introduction of positive pressure air. [Figure 2] It is a schematic diagram showing the assembly relationship of the filter unit of the indoor air pollution treatment device of the present invention. [Figure 3A] It is a three-dimensional external appearance schematic diagram of the gas detector of the present invention. [Figure 3B] It is a three-dimensional external appearance schematic diagram of the gas detector of the present invention viewed from another angle. [Figure 3C] It is an external appearance schematic diagram of the gas detector of the present invention in which a gas detection module is installed inside. [Figure 4A] It is a three-dimensional assembly schematic diagram (one) of the gas detection body of the present invention. [Figure 4B] It is a three-dimensional assembly schematic diagram (two) of the gas detection body of the present invention. [Figure 4C] It is a three-dimensional exploded schematic diagram of the gas detector of the present invention. [Figure 5A] It is a three-dimensional schematic diagram (one) of the base of the present invention. [Figure 5B] This is a schematic three-dimensional diagram (2) of the base of the present invention. [Figure 6] This is a schematic three-dimensional diagram (3) of the base of the present invention. [Figure 7A] This is a schematic three-dimensional diagram showing the disassembled state of the piezoelectric actuator and base of the present invention. [Figure 7B] This is a schematic three-dimensional diagram showing the assembled state of the piezoelectric actuator and base of the present invention. [Figure 8A] This is a schematic diagram (1) of the piezoelectric actuator of the present invention. [Figure 8B] This is a schematic diagram (2) of the piezoelectric actuator of the present invention in three dimensions. [Figure 9A] This is a cross-sectional view (1) of the operation of the piezoelectric actuator of the present invention. [Figure 9B] This is a cross-sectional view (2) of the operation of the piezoelectric actuator of the present invention. [Figure 9C] This is a cross-sectional view (3) of the operation of the piezoelectric actuator of the present invention. [Figure 10A] This is an assembly cross-sectional view (1) of the gas detection unit. [Figure 10B] This is a cross-sectional view (2) of the assembled gas detection unit. [Figure 10C] This is a cross-sectional view (3) of the assembled gas detection unit. [Figure 11] This is a schematic diagram of the signal transmission of the gas detector of the present invention. [Figure 12] This is a structural diagram of the artificial intelligence generated content (AIGC) model for the network-connected cloud computing service device of the present invention. [Figure 13] This is a reference table of the equivalent amount of clean air supply rate (CADR) required per cubic meter for the cleanroom classes ZAPClean room 1 to 12 of the present invention. [Modes for carrying out the invention]

[0013] Embodiments that embody the features and advantages of the present invention will be described in detail in the following description. The present invention can be modified in various ways in different embodiments, none of which will depart from the scope of the invention, and the description and drawings are used for illustrative purposes only and are not intended to limit the invention.

[0014] The present invention relates to an indoor air purification network control system comprising a plurality of gas detectors, at least one indoor air pollution treatment device, a network-connected cloud computing service device, a storage center, and at least one central control computer intelligent control device. The plurality of gas detectors are installed in indoor and outdoor spaces and detect air quality data such as PM1, PM2.5, CO2, VOCs, temperature, and humidity. The at least one indoor air pollution treatment device includes devices such as ventilation devices, air purifiers, fan filter units (FFUs), heating and cooling systems, range hoods, exhaust devices, humidity control devices, and mobile vacuum cleaners. The indoor air pollution treatment device can automatically perform air filtration, ventilation, temperature and humidity adjustment, and sterilization operations based on commands from the network-connected cloud computing service device. The network-connected cloud computing service device includes an artificial intelligence generated content (AIGC) model, receives and analyzes data from gas detectors via Internet of Things technology, generates control commands based on the analysis results, and achieves automated control and optimization of the indoor air pollution treatment device. This automatically adjusts the operating mode of the indoor air pollution treatment device, performs complete purification and cleanroom treatment of circulating air pollution in the indoor space, and ensures that the indoor space achieves a cleanroom-class level of cleanliness. The storage center collects and stores information data from the system to form a big data database of professionally generated data and user-generated data, which is then calculated, compared, and identified by the artificial intelligence generated content (AIGC) model to generate automatically generated data. The at least one central control computer intelligent control device receives control commands from the network-connected cloud computing service device via Internet of Things communication, transmits the received control commands to the gas detection module of the indoor air pollution treatment device via Internet of Things communication, and controls the operation of the induction fan. The artificial intelligence generated content (AIGC) model technology includes an intelligent energy control system that achieves energy saving and emission reduction by automatically adjusting the operating mode of the device based on real-time monitoring data.Artificial Intelligence Generated Content (AIGC) model technology includes system maintenance diagnostics that monitor the operating status of a device, predict potential failures, and include self-cleaning technologies (particularly self-cleaning of filter units and ventilation passages) to maintain long-term and efficient operation of the device and reduce daily maintenance requirements. Artificial Intelligence Generated Content (AIGC) model technology includes air quality prediction models to prevent sudden changes in air quality by predicting future changes in air quality and adjusting the operating status of the device in advance. Artificial Intelligence Generated Content (AIGC) model technology includes intelligent environmental sensing systems that integrate multiple types of sensors and intelligently adjust system operation according to different environmental parameters to improve the operational efficiency and accuracy of the system.

[0015] As shown in Figures 1A and 1E, the multiple gas detectors 1 are placed in indoor space A and outdoor space B to detect air pollution and output air quality data via the Internet of Things (IoT) communication. In particular, the air quality data includes suspended particulate matter (PM1, PM2.5, PM10), CO2, VOCs, temperature, humidity, etc.

[0016] The indoor air pollution treatment device 2 is installed in an indoor space A and contains at least one gas detector 1, at least one induction fan 21, at least one filter unit 22, and at least one drive controller 23. The gas detector 1 is electrically connected to the drive controller 23 and operates the induction fan 21 by receiving control commands via the Internet of Things communication and providing them to the drive controller 23, thereby performing complete purification and cleanroom treatment of circulating air pollution in the indoor space A. In particular, as shown in Figure 1C, the indoor air pollution treatment device 2 includes a ventilation device 2a, an air purifier 2b, a fan filter unit (FFU) 2c, an exhaust device 2d, a heating and cooling device 2e, a range hood 2f, a humidity control device 2g, and a mobile vacuum cleaner 2h. The ventilation device 2a ventilates the indoor space A and introduces air under positive pressure to prevent air pollution from entering the indoor space. The air purifier 2b, fan filter unit (FFU) 2c, exhaust device 2d, range hood 2f, and mobile vacuum cleaner 2h perform complete air pollution purification and cleanroom treatment of the indoor space A. The heating and cooling device 2e and humidity control device 2g adjust the temperature and humidity of the indoor space A.

[0017] As shown in Figure 1B, the network-connected cloud computing service device 3 comprises a wireless network cloud computing service module 31, a cloud control service unit 32, a device management unit 33, an application unit 34, and an artificial intelligence generated content (AIGC) model 35. The wireless network cloud computing service module 31 receives air quality data for the outdoor space B, the indoor space A, and communication information for the indoor air pollution treatment device 2, and transmits control commands. The wireless network cloud computing service module 31 transmits and stores received air quality data for indoor space A and outdoor space B to the cloud control service unit 32 to form an air pollution big data database. It performs intelligent calculations and comparisons using the air pollution big data database, transmits control commands to the wireless network cloud computing service module 31, and transmits them to the indoor air pollution processing devices 2 via the wireless network cloud computing service module 31 to operate them. The device management unit 33 receives communication information from the indoor air pollution processing devices 2 via the wireless network cloud computing service module 31 to manage user registration and device binding. It provides management information to the application unit, such as maintenance management of the indoor air pollution processing devices 2, automatic inspection, analysis, processing and improvement of abnormal areas, control and inspection measurement of whether the cleanliness requirements of cleanroom class are met, customer request feedback, and correction mechanisms for improving software and hardware technology, in order to control and manage the system. The application unit 34 also acquires and displays air quality data information via the cloud control service unit 32, allowing users to understand the air pollution removal status in real time using their mobile phones or communication devices. Furthermore, users can control the indoor air purification network control system through the application unit 34 on their mobile phones or communication devices. The artificial intelligence generated content (AIGC) model 35 generates automatically generated data through calculation, comparison, and identification when professionally generated data and user-generated data are input.As shown in Figure 12, professionally generated data includes outdoor and indoor air pollution data for the building (air pollution characteristics, concentration safety values, etc.), indoor space data for the building (building size and proportions, intended use and function, environmental ventilation, comfort parameters for temperature control, etc.), cleanroom class data (e.g., a comparison table of ZAPClean room 1-12 classes as shown in Figure 13), and hardware / software specifications for the air purification system (e.g., clean air delivery rate (CADR) of the fan, filter specifications, etc.). User-generated information includes air pollution data for the indoor space of the user's building (e.g., air quality data detected in real time by gas detector 1), experimentally measured air pollution data for the indoor space of the user's building (actual air pollution data for the user's indoor space inspected by the inspection unit), and air exchange rate data for the HVAC system in the indoor space of the user's building (e.g., comparative data of indoor and outdoor carbon dioxide in the user's environment space detected in real time by gas detector 1). The automatically generated data includes the number of optimized air purification hardware units, performance control of the optimized air purification hardware, noise reduction control of the optimized air purification hardware, initial setup cost information for the minimized air purification system, and operating cost information for the minimized air purification system. The Artificial Intelligence Generated Content (AIGC) Model 35 features an autoregressive correction analysis mechanism that provides integrated efficiency correction. By performing a final integrated evaluation on the automatically generated data produced by the Artificial Intelligence Generated Content (AIGC) Model 35, it predicts and generates the latest and most accurate deep learning processing data and corrects it toward optimization. By comparing the credibility of the automatically generated data, it guides the Artificial Intelligence Generated Content (AIGC) Model 35 to quickly converge toward the "correct" application direction, and obtains the most accurate automatically generated data through regression analysis.

[0018] In particular, the network-connected cloud computing service device 3 receives and stores air quality data from indoor space A and outdoor space B via the Internet of Things (IoT) to form an air pollution big data database. Based on the detected air quality data, it intelligently compares and selectively issues control commands to the gas detector 1 of the indoor air pollution treatment device 2, which then controls and drives the drive controller 23 to operate the induction fan 21. The network-connected cloud computing service device 3 receives air quality data from the gas detector 1 via the Internet of Things (IoT), analyzes it using artificial intelligence generated content (AIGC) model 35 technology, and intelligently sends control commands based on the analysis results to automatically adjust the operating mode of the indoor air pollution treatment device 2, thereby performing complete circulating air pollution purification and cleanroom treatment in indoor space A, and ensuring that indoor space A achieves a cleanroom-class level of cleanliness.

[0019] In particular, the gas detector 1 has a built-in gas detection module. The gas detector 1 may have an external power terminal, as shown in Figures 3A and 3B, and by plugging the external power terminal directly into the power interface of the indoor space A, it may start detecting air pollution, carbon dioxide (CO2) pressure, and air temperature and humidity information. Alternatively, as shown in Figure 3C, it may not have an external power terminal, but may be directly connected to the indoor air pollution treatment device 2 and electrically connected, and start operating by receiving a control command and controlling the power supply of the indoor air pollution treatment device 2.

[0020] In particular, the aforementioned air pollution refers to any or a combination thereof of suspended particulate matter, carbon monoxide, carbon dioxide, ozone, sulfur dioxide, nitrogen dioxide, lead, total volatile organic compounds, formaldehyde, bacteria, fungi, viruses.

[0021] In particular, the aforementioned Internet of Things communication refers to a collective network to which various devices are connected, and the technology that supports communication between devices and the cloud, and between devices. This Internet of Things communication may be wired communication connecting to the network-connected cloud computing service device 3 via a wired connection. The Internet of Things communication may also be wireless communication connecting to the network-connected cloud computing service device 3 wirelessly. This wireless communication may be any one of the following: a Wi-Fi module, a Bluetooth® module, a radio frequency identification module, or a short-range communication module.

[0022] In particular, as shown in Figures 1A and 1E, the indoor air pollution treatment device 2 is installed in indoor space A, and indoor space A is provided with at least one intake port C1 and at least one exhaust port C2. As shown in Figures 1E and 1F, the ventilation device 2a is equipped with an air guide passage 24, which has an intake port 24a corresponding to the intake port C1 of indoor space A, a circulation return port 24b communicating with indoor space A, and a filtration air passage 24c communicating with indoor space A. A ventilation fan 25 is provided in the circulation return port 24b, and an induction fan 21 and a filter unit 22 are provided in the filtration air passage 24c. The network-connected cloud computing service device 3 intelligently calculates and compares carbon dioxide (CO2) pressure detection information in indoor space A and outdoor space B, and the safe value of the carbon dioxide (CO2) pressure detection information in indoor space A must be maintained at 400 to 600 PPM. As shown in Figure 1L, the network-connected cloud computing service device 3 receives detection information from the ventilation device 2a via the Internet of Things communication and compares the carbon dioxide (CO2) pressure in indoor space A and outdoor space B to determine whether the difference is zero (i.e., whether the carbon dioxide (CO2) pressure detection information in indoor space A and outdoor space B matches). If it is not zero, it selectively sends a control command to the gas detector 1 of the ventilation device 2a, controlling the drive controller 23 to operate the induction fan 21, introducing air from outdoor space B into the filtration air passage 24c from the intake port C1, filtering it with the filter unit 22, and then entering indoor space A. At the same time, the air from indoor space A also enters the filtration air passage 24c again from the circulation return port 24b, where it is circulated and filtered, and the temperature is adjusted to perform ventilation. Through ventilation, the difference in the carbon dioxide (CO2) pressure detection values ​​between indoor space A and outdoor space B becomes zero. In particular, when the ventilation system 2a is activated to perform ventilation, the indoor space A is always maintained at a positive pressure of 0 Pa or higher, so that air pollution from the outdoor space B does not enter the indoor space A.Here, the dust detector 1 inside the indoor air pollution treatment device 2 continuously receives control commands from the network-connected cloud computing service device 3 and drives the drive controller 23 to operate the induction fan 21, thereby continuously performing complete circulating air pollution purification, cleanroom treatment, and temperature and humidity adjustment in indoor space A for air pollution inside indoor space A. When the network-connected cloud computing service device 3 determines that the pressure difference of carbon dioxide (CO2) between indoor space A and outdoor space B is zero, the network-connected cloud computing service device 3 sends a control command to the dust detector 1 inside the indoor air pollution treatment device 2 and drives the drive controller 23 to reduce the rotation speed of the induction fan 21 and adjust the airflow, effectively controlling the energy-saving efficiency of the device operation, effectively suppressing the generation of induction airflow noise, realizing real-time detection of air pollution, complete purification, and cleanroom treatment, and achieving cleanroom-class cleanliness. In particular, as shown in Figure 1C, the ventilation device 2a is a ventilator, a total heat exchanger, or an air conditioning control system (HVAC), but is not limited to these.

[0023] As shown in Figures 1E, 1G, and 1H, the air purifier 2b is plugged into the indoor space A. A control command transmitted by the network-connected cloud computing service device 3 is sent via the Internet of Things to the dust detector 1 inside the air purifier 2b, which drives the drive controller 23 to operate the induction fan 21. This induces air pollution in indoor space A, which is then filtered and purified by the filter unit 22. The purified air is then reintroduced into indoor space A, and the air pollution in indoor space A is passed through the filter unit 22 multiple times, resulting in complete air pollution purification and cleanroom treatment.

[0024] As shown in Figures 1E and 1I, the fan filter unit (FFU) 2c is built into the indoor space A, and the fan filter unit (FFU) 2c is equipped with an air guide passage 24, which has a circulation return port 24b communicating with the indoor space A and a filtration air passage 24c communicating with the indoor space A, and an induction fan 21 and a filter unit 22 are provided in the filtration air passage 24c, and control commands transmitted by the network-connected cloud computing service device 3 are transmitted via the Internet of Things The signal is transmitted via a signal to the dust detector 1 inside the fan filter unit (FFU) 2c, which drives the drive controller 23 to operate the induction fan 21. This induces the air pollution from indoor space A to enter the air guide passage 24 from the circulation return port 24b, pass through the filtered air passage 24c, and after being filtered and purified by the filter unit 22, is reintroduced into indoor space A. The air pollution from indoor space A enters the air guide passage 24 multiple times, effectively suppressing the gas backflow effect of circulation filtration and achieving complete air pollution purification and cleanroom treatment.

[0025] As shown in Figure 1E, the exhaust device 2d is built into the indoor space A and communicates with the outdoor space B corresponding to the exhaust port C2. A control command transmitted by the network-connected cloud computing service device 3 is sent via the Internet of Things to the dust detector 1 inside the exhaust device 2d, which drives the drive controller 23 to operate the induction fan 21. This induces the air pollution in indoor space A to be introduced into the filter unit 22 for filtration and purification before being discharged to the outdoor space B, thereby completely purifying the air pollution in indoor space A and performing cleanroom treatment.

[0026] As shown in Figure 1E, the heating and cooling system 2e is installed in the indoor space A, and includes a temperature-controlled heat exchanger 26. Control commands transmitted by the network-connected cloud computing service device 3 are sent to a waste detector 1 inside the heating and cooling system 2e via the Internet of Things communication, which drives a drive controller 23 to operate an induction fan 21, thereby inducing air to pass through the temperature-controlled heat exchanger 26, and adjusting the temperature and humidity of the air in the indoor space A. The waste detector 1 transmits the temperature and humidity information of the air in the indoor space A to the outside. In particular, the heating and cooling system 2e adjusts the temperature of the indoor space A to be maintained at 25°C ± 3°C and the humidity at 50% ± 10%. In particular, as shown in Figure 1C, the heating and cooling system 2e is a cooling heat exchanger, a heating heat exchanger, or a cooling / heating heat exchanger, but is not limited to these.

[0027] Furthermore, as shown in Figure 1E, when cooking in the kitchen area of ​​indoor space A, serious air pollution occurs relatively rapidly. To avoid the impact and harm to human health from the air pollution generated in indoor space A, a range hood 2f can be installed in the kitchen area of ​​indoor space A as an indoor air pollution treatment device 2 of the indoor air purification network control system. The range hood 2f includes an exhaust passage 2fa and an oil exhaust smoke body 2fb. The exhaust passage 2fa communicates with the outdoor space B corresponding to the exhaust port C2 and is installed above the cooking appliance H. The exhaust passage 2fa is equipped with an induction fan 21, a filter unit 22, and a drive controller 23. The oil exhaust smoke body 2fb communicates with the outdoor space B corresponding to the exhaust port C2 and is installed in front of the cooking appliance H. The oil exhaust smoke body 2fb is equipped with an induction fan 21, a filter unit 22, and a drive controller 23. Furthermore, inside the exhaust passage 2fa and the oil smoke exhaust body 2fb, there are sludge detectors 1 that are electrically connected to the drive controller 23. Control commands transmitted by the network-connected cloud computing service device 3 are sent via the Internet of Things to the sludge detectors 1 inside the exhaust passage 2fa and the oil smoke exhaust body 2fb, which drive the drive controller 23 to operate the induction fan 21. This allows the air pollutants from the kitchen area of ​​indoor space A to enter the exhaust passage 2fa and the oil smoke exhaust body 2fb, where they are filtered and purified by the filter unit 22 before being discharged to the outdoor space B, thus performing complete air pollution purification and cleanroom treatment.

[0028] As shown in Figures 1E and 1J, the humidity control device 2g is plugged into the indoor space A. A control command transmitted by the network-connected cloud computing service device 3 is sent via the Internet of Things to the dust detector 1 inside the humidity control device 2g, which drives the drive controller 23 to operate the induction fan 21, thereby inducing air pollution in indoor space A. The filter unit 22 then performs complete air pollution purification and cleanroom treatment, adjusting the temperature and humidity of the air in indoor space A. In particular, when the humidity control device 2g adjusts the temperature and humidity, safety values ​​are set to maintain a temperature of 25°C ± 3°C and a humidity of 50% ± 10%. In particular, as shown in Figure 1C, the humidity control device 2g is a dehumidifier, a humidifier, or a dehumidifier / humidifier, but is not limited to these.

[0029] As shown in Figures 1E and 1K, the mobile vacuum cleaner 2h is plugged into the indoor space A. A control command transmitted by the network-connected cloud computing service device 3 is sent via the Internet of Things to the dust detector 1 inside the mobile vacuum cleaner 2h, which drives the drive controller 23 to operate the induction fan 21, thereby inducing air pollution in the indoor space A, and the filter unit 22 performs complete air pollution purification and cleanroom treatment. In particular, the mobile vacuum cleaner 2h is a cleaning robot.

[0030] As shown in Figure 1A, the storage center 4 collects and stores system information data to form a big data database of professionally generated data and user-generated data, and generates automatically generated data by performing calculations, comparisons, and identification using the artificial intelligence generated content (AIGC) model 35.

[0031] In particular, as shown in Figures 1D and 1E, the artificial intelligence generated content (AIGC) model 35 includes an intelligent energy control system that achieves energy saving and emission reduction by automatically adjusting the operating mode of the device based on real-time monitoring data. In other words, the smart interconnected system formed by the indoor air purification network control system immediately operates the induction fan 21 in conjunction with other systems, monitors the air quality and temperature / humidity in the indoor space anytime, anywhere, and intelligently compares and sends control commands based on the monitoring status to control the operation of the induction fan 21 and adjust the airflow rate, thereby efficiently controlling the energy-saving effect in the operation of the air conditioning system.

[0032] In particular, as shown in Figure 1D, the artificial intelligence generated content (AIGC) model 35 includes system maintenance diagnostics that monitor the operating status of the device, predict potential failures, include self-cleaning technologies (especially self-cleaning of filter units and ventilation passages), maintain long-term and efficient operation of the device, and reduce the requirements for daily maintenance.

[0033] In particular, as shown in Figure 1D, the artificial intelligence generated content (AIGC) model 35 includes an air quality prediction model to prevent sudden changes in air quality by predicting future changes in air quality and adjusting the operating state of the device in advance.

[0034] In particular, as shown in Figure 1D, the artificial intelligence generated content (AIGC) model 35 includes an intelligent environmental sensing system that integrates multiple types of sensors (e.g., noise sensors) and intelligently adjusts system operation according to different environmental parameters to improve the operational efficiency and accuracy of the system.

[0035] As shown in Figures 1A and 1C, the central control computer intelligent control device 5 receives control commands transmitted from the network-connected cloud computing service device 3 via the Internet of Things (IoT) communication, transmits the received control commands to the gas detector 1 of the indoor air pollution treatment device 2 via the IoT communication communication, and operates the induction fan 21.

[0036] As can be seen from the above, the present invention provides an indoor air purification network control system that achieves highly efficient purification and precise control of indoor air by monitoring indoor and outdoor air quality data in real time using multiple types of gas detectors and automatically adjusting multiple types of indoor air pollution devices 2 using cloud computing and artificial intelligence technology, thereby reaching cleanroom-class cleanliness standards.

[0037] The present invention's indoor air purification network control system specifically achieves real-time detection of air pollution, complete purification, and cleanroom treatment, thereby achieving a cleanroom-class level of cleanliness. Through the artificial intelligence-generated content (AIGC) model 35 of the network-connected cloud computing service device 3, the system intelligently calculates and determines the equivalent amount of clean air supply rate (CADR) required in indoor space A. Based on the required equivalent amount of clean air supply rate (CADR), it determines the number of indoor air pollution treatment devices 2 and the optimal clean air supply rate (CADR) of the induction fan 21, thereby achieving real-time detection of air pollution, complete purification, and cleanroom treatment, and optimizing the cost and operation of complete purification and cleanroom treatment.

[0038] As shown in Figure 13, the required cleanroom class for indoor space A in this invention is ZAPClean room 1 to 12. Therefore, once the artificial intelligence generated content (AIGC) model 35 intelligently calculates and determines the required equivalent of clean air supply rate (CADR) in indoor space A, the indoor air purification network control system can determine the number of indoor air pollution treatment devices 2 and the optimal clean air supply rate (CADR) for the induction fan 21 based on the required equivalent of clean air supply rate (CADR). This allows for monitoring of the air quality in indoor space A anytime, anywhere, and optimizes the cost and operation of complete purification and cleanroom treatment. In particular, the required equivalent of clean air supply rate (CADR) refers to the clean air supply rate (CADR) required by the induction fan 21 to completely purify the air pollution in indoor space A in this area at this time.

[0039] The following are examples of preferred embodiments of the required equivalent amount of clean air supply rate (CADR) in indoor space A according to the present invention.

[0040] Here, the indoor air purification network control system can obtain the required equivalent amount of Clean Air Delivery Rate (CADR) for indoor space A by inputting the region of this indoor space A. For example, if the indoor space is located in the Taipei area, and the cleanliness level of ZAPClean room 9 is required for a 3-ping (approximately 10.5 square meters) indoor space, the system can determine the required equivalent amount of Clean Air Delivery Rate (CADR).

[0041] The indoor air purification network control system of the present invention can intelligently perform calculations and analyses based on a big data database of air pollution prevention systems, for example, a comparison table of the equivalent amount of clean air supply rate (CADR) required per cubic meter for ZAPClean rooms 1 to 12 in Figure 13.

[0042] The equivalent amount of clean air supply rate (CADR) required per cubic meter for ZAPClean rooms 1 to 12 of the present invention is as follows:

[0043] For ZAPClean room 1, the required equivalent of Clean Air Delivery Rate (CADR) per cubic meter is 195,000 to 370,000 m³. 3 The range is / h, and for ZAPClean room2, the equivalent amount of clean air supply rate (CADR) required per cubic meter is 58,000 to 115,000 m³. 3 The range is / h, and in the case of ZAPClean room 3, the equivalent amount of clean air supply rate (CADR) required per cubic meter is 17,500 to 35,000 m³. 3 The range is / h, and in the case of ZAPClean room 4, the equivalent amount of clean air supply rate (CADR) required per cubic meter is 5200~10000m 3It is in the range of / h. For ZAP Clean room 5, the equivalent clean air supply rate (CADR) required per cubic meter is 1500 - 3000 m 3 / h. For ZAP Clean room 6, the equivalent clean air supply rate (CADR) required per cubic meter is 450 - 1000 m 3 / h. For ZAP Clean room 7, the equivalent clean air supply rate (CADR) required per cubic meter is 135 - 300 m 3 / h. For ZAP Clean room 8, the equivalent clean air supply rate (CADR) required per cubic meter is 60 - 135 m 3 / h. For ZAP Clean room 9, the equivalent clean air supply rate (CADR) required per cubic meter is 35 - 80 m 3 / h. For ZAP Clean room 10, the equivalent clean air supply rate (CADR) required per cubic meter is 15 - 40 m 3 / h. For ZAP Clean room 11, the equivalent clean air supply rate (CADR) required per cubic meter is 10 - 30 m 3 / h. For ZAP Clean room 12, the equivalent clean air supply rate (CADR) required per cubic meter is 3 - 10 m 3 It is in the range of / h.

[0044] As can be seen from the above, if the location of indoor space A is in Taipei and the required spatial volume is input, the artificial intelligence generated content (AIGC) model 35 of the network-connected cloud computing service device 3 intelligently calculates and determines the required equivalent of Clean Air Delivery Rate (CADR) to execute complete air pollution purification and cleanroom treatment. Through calculation, it is found that the maximum value of PM2.5 in the Taipei area over five years is 37 and the average value is 11.9. At this time, the average value of 11.9 falls within the average value range of 10-15 in the reference table, the ratio of the maximum value 37 / average value 11.9 is 3.1, which falls within the maximum value / average value range of 3-4 in the average value range of 10-15 in the reference table, and the cleanliness of ZAPClean room 9 is required, so the equivalent of Clean Air Delivery Rate (CADR) required per cubic meter for the cleanliness of ZAPClean room 9 in the area of ​​this indoor space is 56.26 m³. 3 This means the interior space is 30 tsubo (268 m²). 3 ) requires 56.26m 3 Multiplying by / h gives an equivalent of 15078 m³ of clean air supply rate (CADR) required by the indoor space. 3 This results in a value of / h. Therefore, the required equivalent amount of clean air supply rate (CADR) for the indoor air pollution treatment device 2 that performs complete air pollution purification and cleanroom treatment is 15,000 m³. 3 It takes / h. Therefore, the indoor air pollution treatment device 2 of the present invention achieves an optimal clean air supply rate (CADR) of 1000m by arranging the induction fans 21 of three ventilation devices 2a. 3 By setting the rate of operation to / h and arranging 15 fan filter units (FFUs) 2c with induction fans 21, the optimal clean air delivery rate (CADR) is 800m / h. 3 The required equivalent of the Clean Air Delivery Rate (CADR) of the indoor air pollution treatment device 2, which performs complete air pollution purification and cleanroom treatment, is set to 15,000 m³ / h. 3Let / h. However, this is not the only option. Based on the required equivalent of the clean air supply rate (CADR) for indoor space A, the number of indoor air pollution treatment devices 2 and the optimal clean air supply rate (CADR) of the induction fan 21 of the indoor air pollution treatment device 2 can be determined, enabling real-time detection of air pollution, complete purification, and cleanroom treatment, and optimizing the cleanliness level of a cleanroom and the cost of complete purification and cleanroom treatment.

[0045] To understand the indoor air purification network control system provided by the present invention, the structure of the gas detection module of the gas detector 1 of the present invention will be described in detail below. Refer to Figures 3A to 11. The gas detection module comprises a control circuit board 11, a gas detection unit 12, a microprocessor 13, and a communication device 14. The gas detection unit 12, microprocessor 13, and communication device 14 are integrally packaged on the control circuit board 11 and are electrically connected to each other. The microprocessor 13 and communication device 14 are provided on the control circuit board 11, and the microprocessor 13 controls the drive signal of the gas detection unit 12 to start the detection operation. In this way, the gas detection unit 12 detects air pollution and outputs detection information, the microprocessor 13 receives the detection information, processes it, and provides it to the communication device 14, which transmits it to an external network-connected cloud computing service device 3 via the Internet of Things (IoT) communication.

[0046] Refer to Figures 4A to 9A. The gas detection unit 12 comprises a base 121, a piezoelectric actuator 122, a drive circuit board 123, a laser member 124, a particulate sensor 125, and an outer cover 126. The base 121 comprises a first surface 1211, a second surface 1212, a laser installation area 1213, a gas inlet groove 1214, a gas induction assembly mounting area 1215, and a gas discharge groove 1216. The first surface 1211 and the second surface 1212 are two surfaces facing each other. The laser installation area 1213 is formed by cutting out from the first surface 1211 toward the second surface 1212. The outer cover 126 covers the base 121 and has side plates 1261. The side plates 1261 have an intake frame opening 1261a and an exhaust frame opening 1261b. The gas inlet groove 1214 is formed with a recessed second surface 1212 and is adjacent to the laser installation area 1213. The gas inlet groove 1214 is provided with an intake port 1214a that communicates with the outside of the base 121 and corresponds to the intake frame port 1261a of the outer cover 126. The gas inlet groove 1214 has light-transmitting windows 1214b on both side walls that penetrate the piezoelectric actuator 122 and communicate with the laser installation area 1213. Therefore, the first surface 1211 of the base 121 is covered by the outer cover 126 and the second surface 1212 is covered by the drive circuit board 123, thereby defining the intake path with the gas inlet groove 1214. Here, the gas induction assembly mounting area 1215 is formed with a recessed second surface 1212 that communicates with the gas inlet groove 1214, and the bottom surface penetrates to form a ventilation hole 1215a. Positioning protrusions 1215b are provided at each of the four corners of the gas induction assembly mounting area 1215. The gas discharge groove 1216 is provided with an exhaust port 1216a, which is positioned to correspond to the exhaust frame port 1261b of the outer cover 126.The gas discharge groove 1216 comprises a first section 1216b formed by recessing the portion of the first surface 1211 corresponding to the vertical projection area of ​​the gas induction assembly mounting area 1215, and a second section 1216c formed by hollowing out the area from the first surface 1211 to the second surface 1212 in a region offset from the vertical projection area of ​​the gas induction assembly mounting area 1215. The first section 1216b and the second section 1216c are connected, forming a step, and the first section 1216b of the gas discharge groove 1216 communicates with the ventilation hole 1215a of the gas induction assembly mounting area 1215, while the second section 1216c of the gas discharge groove 1216 communicates with the exhaust port 1216a. Therefore, when the first surface 1211 of the base 121 is covered by the outer cover 126 and the second surface 1212 is covered by the drive circuit board 123, both the gas discharge groove 1216 and the drive circuit board 123 define an exhaust path.

[0047] Both the laser member 124 and the particulate sensor 125 are mounted on the drive circuit board 123 and located within the base 121. The drive circuit board 123 has been omitted in order to clearly explain the positional relationship between the laser member 124, the particulate sensor 125 and the base 121. The laser member 124 is housed within the laser installation area 1213 of the base 121, and the particulate sensor 125 is housed within the gas inlet groove 1214 of the base 121 and is aligned with the laser member 124. The laser member 124 corresponds to the light transmission window 1214b, and the light transmission window 1214b transmits the laser light emitted from the laser member 124, so that the laser light is irradiated into the gas inlet groove 1214. The beam path emitted from the laser member 124 passes through the light transmission window 1214b and is perpendicular to the gas inlet groove 1214. The beam emitted from the laser member 124 passes through the light transmission window 1214b and enters the gas inlet groove 1214, irradiating the gas in the gas inlet groove 1214. When the beam comes into contact with the gas, it scatters and generates a projected light spot. Since the particulate sensor 125 is positioned perpendicular to this spot, it receives the scattered projected light spot and calculates the data to obtain gas detection data.

[0048] The piezoelectric actuator 122 is housed within a square-shaped gas induction assembly mounting area 1215 of the base 121. The gas induction assembly mounting area 1215 is in communication with a gas inlet groove 1214. When the piezoelectric actuator 122 is operated, it draws gas from the gas inlet groove 1214, drives it into the piezoelectric actuator 122, passes it through the vent hole 1215a of the gas induction assembly mounting area 1215, and discharges it into the gas discharge groove 1216. The drive circuit board 123 covers the second surface 1212 of the base 121. The laser member 124 is provided on the drive circuit board 123 and electrically connected. The particulate sensor 125 is also provided on the drive circuit board 123 and electrically connected. When the outer cover 126 covers the base 121, the intake frame opening 1261a corresponds to the intake port 1214a of the base 121, and the exhaust frame opening 1261b corresponds to the exhaust port 1216a of the base 121.

[0049] The piezoelectric actuator 122 comprises a nozzle plate 1221, a chamber frame 1222, an actuator element 1223, an insulating frame 1224, and a conductive frame 1225. Here, the nozzle plate 1221 is made of a flexible material and has a suspension plate 1221a and a hollow hole 1221b. The suspension plate 1221a is a sheet-like structure that vibrates in a curved manner, and its shape and size correspond to the inner edge of the gas induction assembly mounting area 1215. The hollow hole 1221b passes through the center of the suspension plate 1221a to allow gas to flow. In a preferred embodiment of the present invention, the shape of the suspension plate 1221a may be one of a square, a circle, an ellipse, a triangle, or a polygon.

[0050] The chamber frame 1222 is stacked on top of the vent plate 1221, and its appearance corresponds to that of the vent plate 1221. The actuator element 1223 is stacked on top of the chamber frame 1222, defining a resonant chamber 1226 between the chamber frame 1222 and the suspension plate 1221a. The insulating frame 1224 is stacked on top of the actuator element 1223, and its appearance is similar to that of the chamber frame 1222. The conductive frame 1225 is stacked on top of the insulating frame 1224, and its appearance is similar to that of the insulating frame 1224. The conductive frame 1225 has conductive pins 1225a and conductive electrodes 1225b, the conductive pins 1225a extending outward from the outer edge of the conductive frame 1225, and the conductive electrodes 1225b extending inward from the inner edge of the conductive frame 1225. Furthermore, the actuator element 1223 comprises a piezoelectric carrier plate 1223a, a resonance adjustment plate 1223b, and a piezoelectric plate 1223c. Here, the piezoelectric carrier plate 1223a is stacked on the chamber frame 1222. The resonance adjustment plate 1223b is stacked on the piezoelectric carrier plate 1223a. The piezoelectric plate 1223c is stacked on the resonance adjustment plate 1223b. The resonance adjustment plate 1223b and the piezoelectric plate 1223c are housed in an insulating frame 1224. The conductive electrode 1225b of the conductive frame 1225 and the piezoelectric plate 1223c are electrically connected. Here, in a preferred embodiment of the present invention, both the piezoelectric carrier plate 1223a and the resonance adjustment plate 1223b are made of conductive material. The piezoelectric carrier plate 1223a has piezoelectric pins 1223d, and the piezoelectric pins 1223d and conductive pins 1225a are connected to a drive circuit (not shown) on the drive circuit board 123 to receive a drive signal (which may be a drive frequency and drive voltage), and form a drive signal transmission path for the piezoelectric pins 1223d, piezoelectric carrier plate 1223a, resonance adjustment plate 1223b, piezoelectric plate 1223c, conductive electrode 1225b, conductive frame 1225, and conductive pins 1225a. The conductive frame 1225 and actuator element 1223 are insulated by an insulating frame 1224 to avoid short-circuit phenomena and to ensure that the drive signal is transmitted to the piezoelectric plate 1223c.When the piezoelectric plate 1223c receives a drive signal, it deforms due to the piezoelectric effect, further driving the piezoelectric carrier plate 1223a and the resonance adjustment plate 1223b to generate reciprocating bending vibrations.

[0051] To explain further, the resonance adjustment plate 1223b is located between the piezoelectric plate 1223c and the piezoelectric carrier plate 1223a, and functions as a buffer between them, thereby adjusting the vibration frequency of the piezoelectric carrier plate 1223a. Basically, the thickness of the resonance adjustment plate 1223b is greater than that of the piezoelectric carrier plate 1223a, and the vibration frequency of the actuator element 1223 is adjusted by changing the thickness of the resonance adjustment plate 1223b.

[0052] Refer to Figures 7A, 7B, 8A, 8B, and 9A. The nozzle plate 1221, chamber frame 1222, actuator element 1223, insulating frame 1224, and conductive frame 1225 are stacked in this order and positioned within the gas induction assembly mounting area 1215, thereby positioning the piezoelectric actuator 122 within the gas induction assembly mounting area 1215. The piezoelectric actuator 122 has a gap 1221c defined between the suspension plate 1221a and the inner edge of the gas induction assembly mounting area 1215 for gas to flow through. A fluid chamber 1227 is defined between the nozzle plate 1221 and the bottom surface of the gas induction assembly mounting area 1215. The fluid chamber 1227 communicates with the resonant chamber 1226 between the actuator element 1223, the chamber frame 1222, and the suspension plate 1221a via the hollow hole 1221b of the nozzle plate 1221. By bringing the vibration frequency of the gas in the resonant chamber 1226 closer to the vibration frequency of the suspension plate 1221a, a Helmholtz resonance effect is generated between the resonant chamber 1226 and the suspension plate 1221a, thereby improving the gas transport efficiency. As the piezoelectric plate 1223c moves away from the bottom surface of the gas induction assembly mounting area 1215, the suspension plate 1221a of the nozzle plate 1221 is moved away from the bottom surface of the gas induction assembly mounting area 1215 by the piezoelectric plate 1223c, causing the volume of the fluid chamber 1227 to rapidly expand, the internal pressure to decrease and become negative, the gas outside the piezoelectric actuator 122 to be drawn in through the gap 1221c and enter the resonant chamber 1226 through the hollow hole 1221b, the air pressure inside the resonant chamber 1226 to rise and a pressure gradient to be generated. When the suspension plate 1221a of the nozzle plate 1221 is moved toward the bottom surface of the gas induction assembly mounting area 1215 by the piezoelectric plate 1223c, the gas in the resonant chamber 1226 rapidly flows out through the hollow hole 1221b, pushing out the gas in the fluid chamber 1227. The combined gas is then rapidly and in large quantities ejected in a state close to the ideal gas according to Bernoulli's theorem, and introduced into the vent hole 1215a of the gas induction assembly mounting area 1215.

[0053] By repeating the operations shown in Figures 9B and 9C, the piezoelectric plate 1223c vibrates back and forth, and due to the principle of inertia, the air pressure inside the resonant chamber 1226 after exhaust becomes lower than the equilibrium pressure, causing the gas to re-enter the resonant chamber 1226. In this way, by controlling the vibration frequency of the gas inside the resonant chamber 1226 to approach the vibration frequency of the piezoelectric plate 1223c, Helmholtz resonance is generated, enabling high-speed and high-volume transport of gas. All the gas enters through the intake frame opening 1261a of the outer cover 126, passes through the intake opening 1214a, enters the gas inlet groove 1214 of the base 121, and flows to the position of the particulate sensor 125. Then, the piezoelectric actuator 122 is continuously driven to draw in the gas in the intake path, which is advantageous for the rapid introduction and stable flow of external gas, and the gas passes above the particulate sensor 125. At this time, the beam from the laser member 124 passes through the light transmission window 1214b and enters the gas inlet groove 1214, while also passing above the particulate sensor 125. When the beam from the laser member 124 irradiates the suspended particulate matter in the gas, scattering phenomena and projected light spots are generated. The particulate sensor 125 receives the projected light spots generated by scattering and performs calculations to obtain information such as the particle size and concentration of the suspended particulate matter contained in the gas. The gas above the particulate sensor 125 is also continuously introduced into the ventilation hole 1215a of the gas induction assembly mounting area 1215 by the driving of the piezoelectric actuator 122 and enters the gas discharge groove 1216. Finally, after the gas enters the gas discharge groove 1216, the piezoelectric actuator 122 continues to send gas into the gas discharge groove 1216, so that the gas in the gas discharge groove 1216 is pushed out and discharged to the outside through the exhaust port 1216a and the exhaust frame port 1261b.

[0054] The gas detector 1 of the present invention can not only detect suspended particulate matter in a gas, but can also detect the characteristics of introduced gases, such as formaldehyde, ammonia gas, carbon monoxide, carbon dioxide, oxygen, and ozone. Therefore, the gas detector 1 of the present invention further comprises a gas sensor 127 that is positioned on a drive circuit board 123, electrically connected, and housed in a gas discharge groove 1216 to detect the characteristics of introduced gases. Here, the gas sensor 127 may be a volatile organic compound sensor that detects information on carbon dioxide or total volatile organic compound gases. The gas sensor 127 may be a formaldehyde sensor that detects information on formaldehyde gas. The gas sensor 127 may be a bacterial sensor that detects information on bacteria or fungi. The gas sensor 127 may be a virus sensor that detects information on virus gases. The gas sensor 127 may be a temperature and humidity sensor that detects temperature and humidity information of the air.

[0055] Refer again to Figures 1E and 2. The ultra-high performance air filter (HEPA) is a ULPA14 filter, which further improves filtration efficiency and achieves even higher cleanliness requirements. As shown in the figure, when the induction fan 21 of the indoor air pollution treatment device 2 is driven and controlled, air pollution is guided to the filter unit 22 and filtered. The filter unit 22 may be a filter of the MREV (Minimum Efficiency Reporting Value) class of 8 or higher, or an ultra-high performance air filter (HEPA) class, and aims to filter and purify the introduced air pollution by adsorbing chemical fumes, bacteria, dust particles and pollen contained in the air pollution. In particular, the ultra-high performance air filter (HEPA) in this invention is an ultra-high performance air filter (HEPA) 10 or higher, with a dust collection capacity exceeding 12,000 mg, or a more efficient ULPA14 filter class, which further improves filtration efficiency and achieves even higher cleanliness requirements. The filter unit 22 can be further combined with physical or chemical materials to provide a sterilizing effect against passing air pollution. The airflow direction by the induction fan 21 is indicated by the arrow. By applying a decomposition layer to the filter unit 22, air pollution can be sterilized and removed by chemical means. The decomposition layer may be activated carbon 22a, which can remove organic and inorganic substances in the air pollution, as well as colored and odorous substances. In particular, in this invention, the formaldehyde absorption capacity of activated carbon 22a exceeds 1500 mg. The decomposition layer may also be a purifying element 22b containing chlorine dioxide, which can suppress viruses, bacteria, fungi, influenza A virus, influenza B virus, enterovirus, and norovirus in the air pollution, achieving a suppression rate of 99% or more, and helping to reduce cross-infection between viruses. The decomposition layer may also be a herbal protective layer 22c extracted from ginkgo and Japanese nasturtium, which can effectively suppress allergies and destroy the surface proteins of passing influenza viruses (e.g., H1N1). The decomposition layer may also consist of silver ions 22d, which can suppress viruses, bacteria, and fungi in the introduced air pollution.The decomposition layer may be zeolite 22e, and can remove ammonia nitrogen, heavy metals, organic pollutants, E. coli, phenol, chloroform, and anionic surfactants. In some embodiments, the filter unit 22 may also be combined with a light irradiation element that sterilizes and removes air pollutants by chemical means. The light irradiation element is a photocatalytic unit including a photocatalyst 22f and an ultraviolet lamp 22g, which further improves the efficiency of removing air pollutants and allergens. When the photocatalyst 22f is irradiated by the ultraviolet lamp 22g, it converts light energy into electrical energy, decomposing harmful substances in the air pollutant to disinfect and sterilize, achieving a filtration and sterilization effect. In particular, in this invention, the output of the ultraviolet lamp 22g is 120mW or more. The light irradiation element may be a photoplasma unit of the nanophototube 22h. When introduced air pollutants are irradiated by the nanophototube 22h, oxygen molecules and water molecules in the air pollutants are decomposed into a highly oxidizing photoplasma, forming an ion flow that destroys organic molecules. This decomposes gas molecules such as volatile formaldehyde, toluene, and volatile organic compounds (VOCs) contained in the air pollutants into water and carbon dioxide, further improving the efficiency of removing airborne pollutants and allergens and achieving a filtration and sterilization effect. In some embodiments, the filter unit 22 may be combined with a decomposition unit that sterilizes and removes air pollutants by chemical means. The decomposition unit may be a negative ion unit 22i. By giving positive charge to fine particles contained in the introduced air pollutants and causing them to adhere to negative charges, the efficiency of removing airborne pollutants and allergens is further improved, and a filtration and sterilization effect of the introduced air pollutants can be achieved. The decomposition unit may also be a plasma ion unit 22j. Plasma ions ionize oxygen molecules and water molecules contained in the air pollutants to form positive ions (H. + ) and anions (O 2-This process generates ions, and when water molecules attach to the surface of viruses and bacteria, the resulting substance is converted into highly oxidative reactive oxygen species (hydroxyl radicals, OH groups) through a chemical reaction. These radicals then strip hydrogen from the proteins on the surface of viruses and bacteria, and oxidatively decompose them, thereby decomposing and removing airborne pollutants, allergens, and microorganisms. This improves air purity and provides a filtration and sterilization effect on introduced air pollution.

[0056] Based on the above, the present invention provides an indoor air purification network control system. This indoor air purification network control system is a system that monitors, purifies, and intelligently controls the air quality of an indoor environment in real time. By utilizing Internet of Things (IoT) technology and artificial intelligence generated content (AIGC) technology, and combining multiple types of indoor air pollution treatment devices and advanced control technologies, it can not only monitor and adjust indoor air quality in real time, but also reduce operating costs and improve the long-term stability and efficiency of the system through intelligent predictive control and self-cleaning functions. It is suitable for cleanroom environments where high levels of cleanliness are required, can provide cleanroom-class high-quality indoor air, realizes real-time detection of air pollution, complete purification and cleanroom treatment, achieves cleanroom-class cleanliness, and has extremely high industrial value. [Explanation of Symbols]

[0057] A: Indoor space B: Outdoor space C1: Air intake C2: Exhaust port H:Cooking utensils 1: Gas detector 11: Control circuit board 12: Gas detection unit 121: Bass 1211: First surface 1212:Second surface 1213: Laser installation area 1214: Gas inlet channel 1214a: Air intake 1214b: Light-transmitting window 1215: Gas induction assembly mounting area 1215a: Ventilation holes 1215b: Positioning projection 1216: Gas discharge channel 1216a: Exhaust port 1216b: First section 1216c: Second section 122: Piezoelectric Actuator 1221: Vent plate 1221a: Suspension plate 1221b: Hollow hole 1221c: void 1222: Chamber Frame 1223: Actuator element 1223a: Piezoelectric carrier plate 1223b: Resonance adjustment plate 1223c: Piezoelectric plate 1223d: Piezoelectric pin 1224: Insulating frame 1225: Conductive frame 1225a: Conductive pin 1225b: Conductive electrode 1226:Resonance chamber 1227: Fluid Chamber 123: Drive circuit board 124: Laser components 125: Particulate Sensor 126: Outer cover 1261: Side panel 1261a: Intake frame 1261b: Exhaust vent 127: Gas sensor 13: Microprocessor 14: Communication device 2: Indoor air pollution treatment devices 2a: Ventilation system 2b: Air purifier 2c: Fan filter unit (FFU) 2d: Exhaust system 2e: Heating and cooling systems 2F: Range Hood 2fa: Exhaust passage 2fb: Exhaust oil smoke body 2g: Humidity control device 2h: Mobile vacuum cleaner 21: Induction fan 22: Filter Unit 22a:Activated carbon 22b: Cleaning element containing chlorine dioxide 22c: Ginkgo and sumac herb protective layer 22d: Silver ions 22e: Zeolite 22f: Photocatalyst 22g: UV lamp 22h: Nanophototube 22i: Negative Ion Unit 22j: Plasma Ion Unit 23: Drive controller 24: Air guide passage 24a: Intake port 24b: Circulation return port 24c: Filtration airflow path 25: Ventilation fan 26: Temperature control heat exchanger 3: Network-attached cloud computing service devices 31: Wireless Network Cloud Computing Service Module 32: Cloud Control Service Unit 33: Device Management Unit 34: Application Unit 35: Artificial Intelligence Generated Content (AIGC) Model 4: Storage Center 5: Central Control Computer Intelligent Control System

Claims

1. An indoor air purification network control system, It comprises multiple gas detectors, at least one indoor air pollution treatment device, and a network-connected cloud computing service device, The aforementioned multiple gas detectors are placed in indoor and outdoor spaces to detect air pollution and output air quality data via the Internet of Things (IoT) communication. The at least one indoor air pollution treatment device is installed in the indoor space and contains at least one gas detector, at least one induction fan, at least one filter unit, and at least one drive controller, the gas detector is electrically connected to the drive controller, and receives control commands via the Internet of Things communication to operate the induction fan and perform complete purification and cleanroom treatment of circulating air pollution in the indoor space. The network-connected cloud computing service device comprises a wireless network cloud computing service module, a cloud control service unit, a device management unit, an application unit, and an artificial intelligence generated content (AIGC) model. The network-connected cloud computing service device receives air quality data from the gas detector via the Internet of Things communication, analyzes it using the artificial intelligence generated content (AIGC) model technology, and intelligently transmits control commands based on the analysis results to automatically adjust the operating mode of the indoor air pollution treatment device, thereby performing complete circulating air pollution purification and cleanroom treatment in the indoor space, and ensuring that the indoor space achieves a cleanroom-class level of cleanliness. This is an indoor air purification network control system.

2. The aforementioned air quality data includes suspended particulate matter (PM1, PM2.5, PM10), CO2 ２ The indoor air purification network control system according to claim 1, wherein the components are VOCs, temperature, and humidity.

3. The indoor air purification network control system according to claim 1, comprising a storage center that collects and stores information data from the indoor air purification network control system to form a big data database of professionally generated data and user-generated data, and generates automatically generated data by performing calculations, comparisons, and identification using the artificial intelligence generated content (AIGC) model, wherein the artificial intelligence generated content (AIGC) model technology achieves energy saving effects by automatically adjusting the operating mode of the indoor air pollution treatment device based on air quality data output from the gas detector, and comprising an intelligent energy control system.

4. The indoor air purification network control system according to claim 1, wherein the artificial intelligence generated content (AIGC) model technology includes a system maintenance diagnosis and an air quality prediction model, the system maintenance diagnosis monitors the operating status of the indoor air pollution treatment device and includes a self-cleaning technology to maintain the long-term and efficient operation of the indoor air pollution treatment device, and the air quality prediction model predicts future changes in air quality and prevents sudden changes in air quality by adjusting the operating status of the indoor air pollution treatment device in advance.

5. The indoor air purification network control system according to claim 1, comprising a central control computer intelligent control device that receives control commands transmitted from the network-connected cloud computing service device via the Internet of Things communication, transmits the received control commands to the gas detector of the indoor air pollution treatment device via the Internet of Things communication, and controls the operation of the induction fan, wherein the artificial intelligence generated content (AIGC) model technology includes an intelligent environmental sensing system that integrates multiple types of sensors and intelligently adjusts the system operation according to different environmental parameters to improve the operational efficiency and accuracy of the system.

6. The indoor air pollution treatment device includes a ventilation device, an air purifier, a fan filter unit (FFU), an exhaust device, a heating and cooling device, a range hood, a humidity control device, and a mobile vacuum cleaner, wherein the ventilation device is a ventilator, a total heat exchanger, or an HVAC (high-voltage air conditioning control system), according to claim 1, an indoor air purification network control system.

7. The indoor air purification network control system according to claim 1, wherein the filter unit is a filter of class MREV (Minimum Efficiency Reporting Value) 8 or higher.

8. The indoor air purification network control system according to claim 1, wherein the filter unit is of the ultra-high performance air filter (HEPA) class or higher, and the ultra-high performance air filter (HEPA) is of the ultra-high performance air filter (HEPA) class 10 or higher, and the dust collection capacity exceeds 12,000 mg.

9. The indoor air purification network control system according to claim 1, wherein the filter unit is combined with a light irradiation element that sterilizes and removes the air pollutants by chemical means, the light irradiation element is a photocatalytic unit including a photocatalyst and an ultraviolet lamp, and the output of the ultraviolet lamp is 120 mW or more, or the filter unit is combined with a decomposition unit that sterilizes and removes the air pollutants by chemical means, the decomposition unit is a negative ion unit or a plasma ion unit.

10. The indoor air purification network control system according to claim 1, wherein the Internet of Things communication is wireless communication for wirelessly connecting and communicating with the network-connected cloud computing service device, or wired communication for wired connection and communication with the network-connected cloud computing service device, and the wireless communication is one of a Wi-Fi module, a Bluetooth® module, a radio frequency identification module, or a short-range communication module.

11. Each of the gas detectors comprises a control circuit board, a gas detection unit, a microprocessor, and a communication device, the control circuit board is electrically connected to the drive controller, the gas detection unit, the microprocessor, and the communication device are integrally packaged on the control circuit board and electrically connected to each other, the microprocessor controls the detection operation of the gas detection unit, the gas detection unit detects the air pollution, the microprocessor processes the detected air pollution, and provides the information of the air pollution to the communication device for external communication transmission, as described in claim 1.

12. The indoor air purification network control system according to claim 1, wherein the cleanroom class is the cleanliness level of ZAPClean rooms 1 to 12.

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