WO2023234569A1

WO2023234569A1 - Message transmission and energy management system using indoor air quality measurer and method therefor

Info

Publication number: WO2023234569A1
Application number: PCT/KR2023/006024
Authority: WO
Inventors: 김유신; 박은주; 이충근; 신정훈; 장진민
Original assignee: 주식회사 에어딥
Priority date: 2022-06-02
Filing date: 2023-05-03
Publication date: 2023-12-07
Also published as: KR102496128B1

Abstract

The present invention relates to an air quality management system and a method therefor. The air quality management system according to an embodiment comprises: an air quality management server that provides an air quality management program; and an air quality management apparatus that generates air quality status information and remote control information regarding a preset indoor space by using the air quality management program, wherein the air quality management apparatus comprises: a program reception unit that receives the air quality management program; an air quality data collection unit that collects air quality data regarding an indoor space; and an air quality information processing unit that analyzes the collected air quality data by using the air quality management program, and generates the air quality status information and the remote control information on the basis of the result of the analysis of the collected air quality data, and the air quality management server generates an air quality diagnosis model and a ventilation apparatus control model via machine learning that is based on at least one piece of air quality big data from among indoor air quality big data, outdoor air quality big data, weather big data, and space use pattern big data, and generates the air quality management program in which the air quality diagnosis model and the ventilation apparatus control model have been reflected.

Description

Message transmission and energy management system and method using an indoor air quality measuring device

The present invention relates to an air quality management system and method, and more specifically, to the technical idea of monitoring and managing the air quality of an indoor space using an air quality management program based on machine learning.

According to the Ministry of Environment, the concentration of fine dust in domestic cities in 2017 was more than twice that of major cities in developed countries, with Seoul at 26μg/ ^m3 , New York at 10μg/ ^m3 , and Tokyo at 13μg/ ^m3 .

In particular, it was reported that the average concentration of ultrafine dust PM 2.5 continued to rise in spring and winter, and the number of fine dust advisories issued also increased.

The annual average concentration of ultrafine dust PM2.5 was also 24μg/m ³ , confirming that it was the second most polluted among OECD countries after Chile (24.9μg/m ³ ). As of 2018, the average annual ultrafine dust concentration in the domestic metropolitan area was decreased by about 12% compared to 2015, but the number of 'very bad' ultrafine dust days increased significantly from 0 to 5 days, and the number of 'bad' days increased significantly from 62 to 72 days.

As air quality has deteriorated rapidly in recent years, inconveniences are increasing not only in outdoor activities but also in daily life in indoor spaces, and health concerns and damage, such as disease and death due to fine dust, are also rapidly increasing.

In particular, compared to outdoor air quality, which can be naturally purified by weather and wind, indoor air quality can rapidly worsen if there is no artificial ventilation or air purification activities.

Fine dust and ultrafine dust introduced from outside, carbon dioxide emitted from people working indoors, and volatile organic compounds emitted from indoor building materials, adhesives, paints, and various industrial products worsen indoor air quality. Not only does it slow down activity, but it can also have fatal consequences on health.

Various pollutants in the air penetrate the body through the respiratory tract, causing respiratory diseases, asthma, and lung diseases.

A survey by the U.S. Environmental Protection Agency (EPA) revealed that the concentration of these indoor air pollutants is 2 to 5 times higher than that of outdoor air pollutants, and sometimes more than 100 times higher.

The Korea Centers for Disease Control and Prevention announced that the number of deaths worldwide due to ultrafine dust increased from approximately 3.5 million in 1990 to 3.8 million in 2000 and 4.2 million in 2015.

In particular, it was announced that the number of deaths due to indoor air pollution is estimated at 2.8 million.

Meanwhile, the deterioration of indoor air quality in educational environments such as daycare centers, kindergartens, elementary, middle and high schools may have a serious negative impact on the health and educational effectiveness of growing children and adolescents in inevitable situations where they have no choice but to stay indoors for long periods of time.

In order to reduce the rapidly growing threat of fine dust and maintain people's health, the Ministry of Environment strengthened the 'Indoor Air Quality Management Act' for multi-use facilities and newly built apartment buildings, lowering the daily average environmental standard for fine dust to 50 μg/m as of 2018. ³ to 35μg/m ³ , the same level as developed countries such as the United States and Japan, and the annual average environmental standard was raised from 25μg/m ³ to 15μg/m ³ .

In order to comply with these strengthened indoor air quality management laws and ensure more comfortable and safe air quality in the indoor environment in which we live, a real-time air quality monitoring system that can diagnose the level of air quality by measuring various air quality pollutants, including fine dust, is needed. It is being demanded.

The present invention is an air quality management system that collects multiple information for managing indoor air quality, checks changes in air quality in real time based on the collected multiple information, and automatically manages indoor air quality to a comfortable state according to the confirmed change in air quality. We would like to provide that method.

In addition, the present invention provides visualization information so that indoor air quality information collected through Internet of Things sensors, outdoor air quality information based on location information, weather information, and indoor air quality status according to the user's device use and lifestyle can be checked in real time. We aim to provide an air quality management system and method that

The air quality management system according to an embodiment of the present invention includes an air quality management server that provides an air quality management program and an air quality management device that generates air quality status information and remote control information for a preset indoor space using the air quality management program, , where the air quality management device includes a program receiver that receives the air quality management program, an air quality data collection unit that collects air quality data for indoor space, and an air quality management program that analyzes the collected air quality data and provides information on the collected air quality data. It includes an air quality information processing unit that generates air quality status information and remote control information based on the results of the analysis, and the air quality management server includes at least one of indoor air quality big data, outdoor air quality big data, weather big data, and space usage pattern big data. Through machine learning based on air quality big data, an air quality diagnosis model and ventilation device control model can be created, and an air quality management program that reflects the air quality diagnosis model and ventilation device control model can be created.

Air quality data is collected through indoor air quality data collected through at least one Internet of Things (IoT) sensor installed in the indoor space, outdoor air quality data collected based on location information of the indoor space, and through the Korea Meteorological Administration's air pollution information application. It may include at least one of collected weather data and space usage pattern data collected based on the operating state of a ventilation device provided in an indoor space.

The space usage pattern data may include data corresponding to at least one piece of information among the open/closed state of windows provided in the indoor space, the operating state of the air purifying ventilation device provided in the indoor space, and power usage.

The air quality information processing unit inputs the collected air quality data into an air quality diagnosis model to generate air quality status information, and inputs the generated air quality status information into a ventilation device control model to generate remote control information.

The air quality management server re-collects at least one air quality big data at preset intervals, re-learns the air quality diagnosis model and ventilation device control model through machine learning based on the re-collected air quality big data, and performs the re-learned air quality diagnosis. Program update information including update information of the model, relearned ventilation control model, and edge computing module can be generated.

The program receiving unit may receive program update information from the air quality management server, and the air quality information processing unit may update the air quality management program based on the received program update information.

At least one of the air quality management device and the air quality management server generates visualization information about monitoring data corresponding to air quality status information, and provides the visualization information to the user through at least one of a preset user terminal, mobile app, web service, and TV app service. It may further include an air quality data visualization unit provided to.

The air quality data visualization unit generates monitoring data that classifies data by air quality element according to air quality status information by time passage, and can support visualization of the monitoring data on the user terminal.

The air quality information processing unit may further include an air quality management device control unit that controls the operation of a ventilation device provided in the indoor space based on remote control information.

The air quality management device control unit can remotely control the operation of the ventilation device by providing remote control information to the ventilation device.

The air quality management device control unit provides remote control information to the air quality management server, and the air quality management server can remotely control the operation of the ventilation device based on the provided remote control information.

The air quality information processing unit can perform information processing based on edge computing in offline mode and information processing based on cloud computing in online mode.

The information processing process based on edge computing includes the process of processing information to perform at least one operation among searching, connecting, controlling, and operating status monitoring of a ventilator that can be connected in an offline state, and the information processing process based on cloud computing. may include a process of processing information for registering at least one of a ventilation device and an air quality management device provided in an indoor space to an air quality management server.

The air quality management method according to an embodiment of the present invention includes the steps of providing an air quality management program from an air quality management server to an air quality management device, and using the air quality management program provided by the air quality management device to provide air quality status information and remote information for a preset indoor space. A step of generating control information, wherein the step of generating air quality status information and remote control information includes receiving an air quality management program from a program receiver, and collecting air quality data about the indoor space from an air quality data collection unit. And analyzing the air quality data collected using the air quality management program in the air quality information processing unit, and generating air quality status information and remote control information based on the results of the analysis of the collected air quality data, and running the air quality management program. The step of providing is to create an air quality diagnosis model and ventilation device control model through machine learning based on at least one air quality big data of indoor air quality big data, outdoor air quality big data, meteorological big data, and space usage pattern big data from the air quality management server. You can create an air quality management program that reflects the air quality diagnosis model and ventilation control model.

The present invention can collect multiple information for managing indoor air quality, check changes in air quality in real time based on the collected multiple information, and automatically manage indoor air quality to a comfortable state according to the confirmed change in air quality.

In addition, the present invention provides visualization information so that indoor air quality information collected through Internet of Things sensors, outdoor air quality information based on location information, weather information, and indoor air quality status according to the user's device use and lifestyle can be checked in real time. can do.

1 is a diagram illustrating an air quality management system according to an embodiment of the present invention.

Figure 2 is a diagram explaining an air quality management device according to an embodiment of the present invention.

Figure 3 is a diagram explaining an environment to which an air quality management device according to an embodiment of the present invention is applied.

4A to 4C are diagrams illustrating the results of application of an air quality management device according to an embodiment of the present invention.

Figure 5 is a diagram explaining an air quality management method according to an embodiment of the present invention.

Hereinafter, various embodiments of this document are described with reference to the attached drawings.

The embodiments and terms used herein are not intended to limit the technology described in this document to a specific embodiment, and should be understood to include various changes, equivalents, and/or substitutes for the embodiments.

In the following description of various embodiments, if a detailed description of a related known function or configuration is judged to unnecessarily obscure the gist of the invention, the detailed description will be omitted.

The terms described below are terms defined in consideration of functions in various embodiments, and may vary depending on the intention or custom of the user or operator. Therefore, the definition should be made based on the contents throughout this specification.

In connection with the description of the drawings, similar reference numbers may be used for similar components.

Singular expressions may include plural expressions, unless the context clearly indicates otherwise.

In this document, expressions such as “A or B” or “at least one of A and/or B” may include all possible combinations of the items listed together.

Expressions such as “first,” “second,” “first,” or “second,” can modify the corresponding components regardless of order or importance and are used to distinguish one component from another. It is only used and does not limit the corresponding components.

When a component (e.g., a first) component is said to be "connected (functionally or communicatively)" or "connected" to another (e.g., second) component, it means that the component is connected to the other component. It may be connected directly to an element or may be connected through another component (e.g., a third component).

In this specification, “configured to” means “suitable for,” “having the ability to,” or “changed to,” depending on the situation, for example, in terms of hardware or software. ," can be used interchangeably with "made to," "capable of," or "designed to."

In some contexts, the expression “a device configured to” may mean that the device is “capable of” working with other devices or components.

For example, the phrase "processor configured (or set) to perform A, B, and C" refers to a processor dedicated to performing the operations (e.g., an embedded processor), or by executing one or more software programs stored on a memory device. , may refer to a general-purpose processor (e.g., CPU or application processor) capable of performing the corresponding operations.

Additionally, the term 'or' means 'inclusive or' rather than 'exclusive or'.

That is, unless otherwise stated or clear from the context, the expression 'x uses a or b' means any of the natural inclusive permutations.

In the above-described specific embodiments, components included in the invention are expressed in singular or plural numbers depending on the specific embodiment presented.

However, the singular or plural expressions are selected to suit the presented situation for convenience of explanation, and the above-described embodiments are not limited to singular or plural components, and even if the components expressed in plural are composed of singular or , Even components expressed as singular may be composed of plural elements.

Meanwhile, in the description of the invention, specific embodiments have been described, but of course, various modifications are possible without departing from the scope of the technical idea implied by the various embodiments.

Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined by the claims described below as well as equivalents to these claims.

Referring to FIG. 1, the air quality management system 100 collects multiple information for managing indoor air quality, checks changes in air quality in real time based on the collected multiple information, and adjusts indoor air quality according to the confirmed change in air quality. It can be automatically managed in a comfortable state.

In addition, the air quality management system 100 allows you to check in real time the indoor air quality information collected through the Internet of Things sensor, outdoor air quality information based on location information, weather information, and the status of indoor air quality according to the user's device use and lifestyle patterns. Visualization information can be provided.

For this purpose, the air quality management system 100 includes an air quality management device 110 that generates air quality status information and remote control information for a preset indoor space using an air quality management program, and an air quality management server that provides an air quality management program ( 120) may be included. For example, the indoor space may be inside a building or inside a vehicle, but is not limited thereto.

Specifically, the air quality management server 120 controls an air quality diagnosis model and ventilation device through machine learning based on at least one air quality big data of indoor air quality big data, outdoor air quality big data, weather big data, and space usage pattern big data. You can create a model and create an air quality management program that reflects the air quality diagnosis model and ventilation control model.

Here, at least one big data may be air quality big data corresponding to a plurality of preset indoor spaces, and the indoor air quality big data and outdoor air quality big data are collected from the air quality management device 110 installed in each of the plurality of indoor spaces. It could be data.

For example, the air quality management device 110 may collect indoor air quality data through a plurality of Internet of Things (IoT) sensors installed in an indoor space, and provide the collected data to the air quality management server 120. , the air quality management server 120 can collect a plurality of indoor air quality data received from each air quality management device 110 as indoor air quality big data.

In addition, the air quality management device 110 collects outdoor air quality data based on the location information of a plurality of Internet of Things sensors installed in the external area corresponding to the indoor space and a plurality of Internet of Things sensors installed in the external area, and stores the collected data. It can be provided to the air quality management server 120, and the air quality management server 120 can collect a plurality of outdoor air quality data received from each air quality management device 110 as outdoor air quality big data.

In addition, the air quality management device 110 may collect space usage pattern data based on the operating state of the ventilation device provided in the indoor space, and provide the collected data to the air quality management server 120, and the air quality management server ( 120) may collect a plurality of space usage pattern data received from each air quality management device 110 as space usage pattern big data.

Additionally, the air quality management server 120 may receive a plurality of air pollution information corresponding to the location of each of the plurality of indoor areas from the Korea Meteorological Administration and collect the received plurality of air pollution information as meteorological big data.

Here, IoT technology is a hyper-connected Internet network technology that connects objects to the Internet and utilizes information creation, collection, and sharing functions. In order to collect, process, and control indoor air quality data in real time, it communicates with various types of IoT devices. And an IoT data integration gateway that connects data generated from devices to a cloud platform may be required.

Additionally, the operating state of the ventilation device provided in the indoor space may be at least one of the operating state of the air purifying ventilator and the open/closed state of the window, but is not limited thereto. The air quality management server 120 may preprocess at least one air quality big data, load the preprocessed air quality big data into a cloud database, and use the air quality big data loaded on the cloud database to create an air quality diagnosis model and a ventilation device control model. can be created.

Pre-processed air quality big data guarantees expansion and contraction based on scalability, data volume increase and data user traffic increase and decrease, productivity-based, flexible response to data user accessibility and convenience, and reliability-based multi-processing. It is possible to reduce service downtime using the availability zone and reduce the investment costs required for hardware introduction and operation based on economic feasibility.

Specifically, the air quality management server 120 performs a pre-processing process of validating at least one air quality big data, data analysis, and processing and refining to meet pre-set service standards. However, during the pre-processing process, data omission and data Data consistency related to at least one of the occurrence of error data due to construction and integration and inconsistencies due to data movement and restructuring related to data extraction, conversion, loading and integration can be verified and processed.

Meanwhile, each air quality management device 100 generates air quality status information using an air quality diagnosis model provided in the air quality management program received from the air quality management server 120, and provides remote control information using a ventilation device control model. can be created.

In addition, each air quality management device 100 can generate visualization information about monitoring data corresponding to air quality status information, provide the generated visualization information to a preset user terminal, and send remote control information to the corresponding indoor space. You can remotely control the ventilation device by providing it to the ventilation device located in.

The air quality management device 100 according to an embodiment of the present invention will be described in more detail later with reference to FIG. 2.

Referring to FIG. 2 , the air quality management device 200 may include a program receiver 210, an air quality data collection unit 220, an air quality information processing unit 230, and an air quality data visualization unit 240. In FIG. 2 , the air quality data visualization unit 240 is described as being provided in the air quality management device 200, but the air quality data visualization unit 240 may also be provided in the air quality management server.

According to one embodiment of the present invention, the program receiver 210 may receive an air quality management program from an air quality management server, where the air quality management server includes indoor air quality big data, outdoor air quality big data, meteorological big data, and space usage pattern big data. An air quality diagnosis model and a ventilator control model can be created through machine learning based on at least one air quality big data among the data, and an air quality management program that reflects the air quality diagnosis model and the ventilator control model can be created.

For example, the air quality management program includes not only an air quality diagnosis model and a ventilator control model, but also an edge computing module that analyzes air quality data using an air quality diagnosis model and a ventilator control model, a ventilator control module, and an energy optimization module for the ventilator. It may include at least one module.

Specifically, at least one of the air quality diagnosis model and the ventilator control model may be a time-series forecasting model. That is, at least one model may be a model that predicts the future by analyzing data sequentially recorded over time.

Additionally, at least one model may be a long short-term memory model (LSTM). In RNN, a vanishing gradient problem occurs during backpropagation if the distance between the relevant information and the point where that information is used is long. LSTM is an algorithm created to solve this problem. It consists of a cell state, a forget gate, and an input gate, so that previous data is This can prevent it from completely disappearing.

The energy optimization module analyzes the energy consumption pattern of the ventilation device based on an air quality diagnosis model and a previously stored real-time energy efficiency analysis model, and can optimize indoor air quality and energy efficiency based on the analysis results of the energy consumption pattern.

According to one embodiment of the present invention, the air quality data collection unit 220 may collect air quality data for an indoor space where the air quality management device 200 is installed.

For example, air quality data may include indoor air quality data collected through at least one Internet of Things sensor provided in an indoor space, at least one Internet of Things sensor provided in an external area corresponding to an indoor space, and/or a location corresponding to an indoor space. Based on the information, it includes at least one of outdoor air quality data collected from the Korea Meteorological Administration server, weather data collected through the Korea Meteorological Administration air pollution information application, and space usage pattern data collected based on the operating status of ventilation devices installed in indoor spaces. can do.

Here, the space usage pattern data may include data corresponding to at least one of the open and closed states of windows provided in the indoor space, the operating state and power usage of the air purifying ventilation device provided in the indoor space.

According to one embodiment of the present invention, the air quality information processing unit 230 analyzes air quality data collected using an air quality management program, and generates air quality status information and remote control information based on the results of the analysis of the collected air quality data. can do.

The air quality information processing unit 230 inputs the collected air quality data into an air quality diagnosis model to generate air quality status information, and inputs the generated air quality status information into a ventilation device control model to generate remote control information.

Additionally, the air quality information processing unit 230 may input collected air quality data and generated air quality status information into a ventilation device control model to generate remote control information.

For example, the air quality information processing unit 230 records at least one of indoor air quality data, outdoor air quality data, weather based on meteorological data, and the operating state of an air purifying ventilation device based on weather and space usage pattern data, window open/closed state, and power usage. Analysis results can be derived from the collected air quality data by entering it into an air quality management program.

The air quality information processing unit 230 may further include an air quality management device control unit that controls the operation of a ventilation device provided in the indoor space based on remote control information.

Here, the air quality management device control unit can remotely control the operation of the ventilator by providing remote control information to the ventilator.

Additionally, the air quality management device control unit provides remote control information to the air quality management server, and the air quality management server may remotely control the operation of the ventilation device based on the provided remote control information.

Specifically, the air quality management device control unit may remotely control the operation of a ventilation device linked to the air quality management device 200 using at least one of radio frequency (RF) communication and bluetooth low energy (BLE) communication.

Additionally, the air quality management device control unit may remotely control the operation of a ventilation device linked to the air quality management server through the air quality management server by providing remote control information to the air quality management server.

In other words, the air quality information processing unit 230 may optimally control the operating state of the air purifying ventilation device and/or the window opening/closing state based on the remote control information.

According to one side, the air quality information processing unit 230 derives the user's location information in the indoor space more precisely through indoor positioning based on the user terminal provided by the user entering the indoor space from the outdoors, and the derived location information Considering this, remote control information can be generated to optimally control the operation of the ventilation device provided in the indoor space.

Specifically, when a user enters an indoor space while carrying a user terminal, the user terminal can be linked to a door lock provided in the indoor space through short-distance wireless communication and control the door lock to be in an open state.

Next, the air quality data information processing unit 230 may receive a motion and direction signal from the user terminal at a preset period after receiving a notification signal according to the open state from the door lock, and the movement and direction received at a preset period. Based on the signal, the user's location information can be calculated by calculating the movement of the user terminal moving relative to the position of the door lock.

In other words, the air quality data information processing unit 230 sets the x and y coordinates to (0,0) based on the location of the user terminal (i.e., the location of the door lock) at the time of receiving the notification signal according to the open state. After initialization, the amount of change (△x, △y) in x-coordinates and y-coordinates can be calculated based on the motion and direction signals received at preset intervals, and the user's position in the indoor space is calculated based on the calculated amount of change. Information can be tracked more precisely.

In other words, the air quality data information processing unit 230 can perform more precise indoor positioning at minimal cost using only the user terminal without placing a separate camera device or position detection sensor in the indoor space, and through this, the ventilation device Operation can be optimally controlled.

For example, the air quality data information processing unit 230 increases the operation intensity of the air purifying ventilation device provided in the sub space (e.g., master bedroom, small room, etc.) where the user is located based on the user's location information in the indoor space. Alternatively, remote control information that controls the windows provided in the sub space to be opened can be generated.

According to one side, the air quality data collection unit 120 divides the indoor space into at least one sub-space and generates human body detection result data using a human body detection sensor disposed in at least one sub-space among the Internet of Things sensors. .

Additionally, the air quality data information processing unit 230 may consider the generated human body detection result data and generate remote control information that limits the operation of the ventilation device provided in at least one sub-space.

For example, the human body detection sensor may be at least one of an image sensor and an infrared sensor, and the human body detection result data may include at least one of the number of people located in at least one subspace and activity pattern information, but is limited thereto. That is not the case.

Specifically, based on the human body detection result data, the air quality data information processing unit 230 determines that the number of people located in one of the at least one sub-space is less than a preset threshold number of people, and determines that fine dust is present in one of the sub-spaces. Operate the ventilation device more efficiently by generating remote control information that includes control commands to restrict operation to remove fine dust even if the concentration is high and to restrict operation to improve air quality with the windows open. can do.

The air quality information processing unit 230 may perform an information processing process based on edge computing in offline mode and an information processing process based on cloud computing in online mode.

Here, the offline mode may be a mode performed when the communication connection with the air quality management server is disconnected or the communication state is below a preset threshold sensitivity. To this end, the air quality information processing unit 230 monitors the communication status with the air quality management server in real time. It can be monitored.

For example, an information processing process based on edge computing includes processing information to perform at least one operation among searching, connecting, controlling, and operating status monitoring of a ventilator that can be connected in an offline state, and an information processing process based on cloud computing. The information processing process may include processing information for registering at least one of a ventilation device and an air quality management device provided in an indoor space to an air quality management server.

Specifically, in offline mode, the air quality information processing unit 230 has a function of searching for a connectable ventilation device using at least one of RF (radio frequency) communication and BLE (bluetooth low energy) communication even when offline, and linking the ventilation device. It can perform the processing of information necessary to perform the function of monitoring the operating status of the ventilation device, and provide notification of ventilation device errors or filter replacement based on the monitoring results of the operating status of the ventilation device. can be provided.

Additionally, in online mode, the air quality information processing unit 230 can control the program receiving unit 210 to receive an air quality management program from an air quality management server, and at least one ventilation device and air quality control device among ventilation devices located in a preset indoor space. In order to register (i.e., link) the management device 200 with the air quality management server, related information may be transmitted and received with the air quality management server.

Meanwhile, the air quality information processing unit 230 may generate air quality status information and remote control information in at least one of offline mode and online mode.

According to one embodiment of the present invention, the air quality data visualization unit 240 generates visualization information about monitoring data corresponding to air quality status information, and displays the visualization information among preset user terminals, mobile apps, web services, and TV app services. It can be provided to the user through at least one.

In other words, the air quality data visualization unit 240 may provide visualization information to the user by linking with the user terminal through at least one of RF communication and BLE communication and providing visualization information to the user terminal.

Additionally, the air quality data visualization unit 240 can provide visualization information to the user through a mobile app and/or web service through the air quality management server by providing visualization information to the air quality management server.

In addition, the air quality data visualization unit 240 can be linked directly with a TV set-top box among the user terminals or through an air quality management server to provide visualization information to the user through a TV app service, preferably by Visualization information can be provided in the form of warning notifications on the TV screen.

For example, the air quality data visualization unit 240 may generate monitoring data that classifies data for each air quality element according to air quality status information by time elapse, and may support visualization of the monitoring data in the user terminal.

Specifically, the air quality data visualization unit 240 can reprocess, aggregate, and classify according to indoor air quality analysis standards and provide the user with real-time status information and statistical analysis information of past data, which allows the user to easily adjust the indoor air quality level. It can be visualized with various graphs and time series charts so that you can understand it, and it can also be provided in the form of a dashboard so that you can see the overall status at a glance.

These certified classification standards are guidelines for weather information or air quality monitoring, and indoor air quality can be measured in real time and the air quality can be more explicitly expressed as good or bad according to the classification criteria.

Meanwhile, the air quality management server re-collects at least one air quality big data at preset intervals, re-learns the air quality diagnosis model and ventilation device control model through machine learning based on the re-collected air quality big data, and re-learns the re-learned air quality big data. Program update information including update information of the air quality diagnosis model, relearned ventilation control model, and edge computing module can be generated.

Additionally, the program receiving unit 210 may receive program update information from the air quality management server, and the air quality information processing unit 230 may update the air quality management program based on the received program update information. For example, the air quality information processing unit 230 may control the program receiving unit 210 to receive program update information from the air quality management server in online mode.

In other words, the air quality information processing unit 230 may receive program update information and update the air quality diagnosis model, ventilation device control model, and edge computing module.

Referring to FIG. 3, the environment 300 to which the air quality management device is applied includes an outdoor air measurement unit 310, a first indoor air measurement unit 320, a power quantity measurement unit 330, and a second indoor air measurement unit 340. and a door open detection unit 350.

For example, the first indoor air measuring unit 320 may be an air measuring device attached to an air purifier among air purifying ventilators, and the second indoor air measuring unit 340 may be an air measuring device with a built-in air measuring function among air purifying ventilating devices. It could be an Internet of Things device. Here, an air purifier may be a mechanical device that sucks in outdoor air, removes fine dust and suspended matter through a filter, and then supplies it indoors.

The outdoor air measuring unit 310 is installed outside the external pipe through which the air purifying ventilation device intakes external air and can measure external air quality.

The first indoor air measuring unit 320 is a type 3 air quality measuring sensor that can measure the air quality before and after the filter and purified through the filter, and the second indoor air measuring unit 340 is an air purifying ventilation device. It is possible to check whether the air purified by the air purifying ventilation device is being circulated.

The power measurement unit 330 is a smart plug that can indicate the amount of power used by the air purifying ventilation device and can measure and collect the amount of power used by the air purifying ventilation device.

Additionally, the power measurement unit 330 may measure and collect the amount of power used by the air purifying ventilation device.

The door open detection unit 350 can check the open/closed state of the door and may be related to space usage pattern data.

Meanwhile, the environment 300 to which the air quality management device is applied may be replaced with the inside of a vehicle.

Referring to FIGS. 4A to 4C,

reference numerals

410 and 420 indicate the operating status of the ventilation device for the preset indoor space provided by the air quality management device and the air quality status indoors (410) and outdoors (420). As an example, reference numeral 430 illustrates a time series linear graph for individual air quality measurements provided by an air quality management device.

According to

reference numerals

410 and 420, on the real-time air quality monitoring service screen provided by the air quality management device, the air quality indicators for the small room and living room where the ventilation device is operating are all "good", while the master bedroom where the ventilation device is not operating is relatively low. You can see that it is showing “normal” and “poor”.

In addition, according to reference numeral 430, the air quality management device can provide a time series linear graph with detailed values so that individual air quality measurements such as ultrafine dust and carbon dioxide can be seen in real time. In reference number 430, the second Fine dust and carbon dioxide are examples, but atmospheric information related to fine dust, temperature, humidity, and volatile organic compounds can also be provided.

Here, the air quality status time series graph displays the risk recommendation standards for air quality items so that the level of the actual measured value can be easily seen, and whether the ventilation system is in operation can be distinguished by indicating the background color change of the linear graph.

In other words, the air quality management device provides visualization information so that indoor air quality information collected through IoT sensors, outdoor air quality information based on location information, weather information, and indoor air quality status according to the user's device use and lifestyle can be checked in real time. By providing this, user convenience can be improved.

In other words, Figure 5 is a diagram illustrating the operation method of the air quality management system according to an embodiment of the present invention described through Figures 1 to 4c. Among the contents described through Figure 5 below, Figures 1 to 4c are included. Explanations that overlap with what was explained above will be omitted.

Referring to FIG. 5, in step 510, the air quality management method may provide an air quality management program from an air quality management server to an air quality management device.

Specifically, in step 510, the air quality management method is machine learning based on at least one air quality big data among indoor air quality big data, outdoor air quality big data, meteorological big data, and space usage pattern big data in the air quality management server. Through this, you can create an air quality diagnosis model and a ventilation device control model, and create an air quality management program that reflects the air quality diagnosis model and ventilation device control model.

Additionally, in step 520, the air quality management method may generate air quality status information and remote control information for a preset indoor space using an air quality management program provided by the air quality management device.

Specifically, in step 521, the air quality management method may receive an air quality management program from a program receiving unit of the air quality management device.

Next, in step 522, the air quality management method may collect air quality data for the indoor space from the air quality data collection unit of the air quality management device.

Next, in step 523, the air quality management method analyzes the air quality data collected using the air quality management program in the air quality information processing unit of the air quality management device, and provides air quality status information and remote information based on the results of the analysis of the collected air quality data. Control information can be generated.

Ultimately, using the present invention, it is possible to collect multiple information for indoor air quality management, check changes in air quality in real time based on the collected multiple information, and automatically manage indoor air quality to a comfortable state according to the confirmed air quality changes. You can.

In addition, using the present invention, indoor air quality information collected through the Internet of Things sensor, outdoor air quality information based on location information, weather information, and indoor air quality according to the user's device use and lifestyle patterns can be visualized in real time. Information can be provided.

Although the embodiments have been described with limited drawings as described above, various modifications and variations can be made by those skilled in the art from the above description. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the claims described below.

Claims

An air quality management server that provides an air quality management program and

An air quality management device that generates air quality status information and remote control information for a preset indoor space using the air quality management program.

Including,

The air quality management device,

a program receiving unit that receives the air quality management program;

An air quality data collection unit that collects air quality data for the indoor space, and

An air quality information processing unit that analyzes the collected air quality data using the air quality management program and generates the air quality status information and the remote control information based on the results of the analysis of the collected air quality data.

Including,

The air quality management server,

An air quality diagnosis model and a ventilation device control model are generated through machine learning based on at least one air quality big data among indoor air quality big data, outdoor air quality big data, weather big data, and space usage pattern big data, and the air quality diagnosis model and Generating the air quality management program reflecting the ventilation device control model

Air quality management system.
According to paragraph 1,

The air quality data is,

Indoor air quality data collected through at least one Internet of Things (IoT) sensor provided in the indoor space, outdoor air quality data collected based on location information of the indoor space, and collected through the Korea Meteorological Administration air pollution information application. Containing at least one of weather data and space usage pattern data collected based on the operating state of the ventilation device provided in the indoor space

Air quality management system.
According to paragraph 2,

The space usage pattern data is,

Containing data corresponding to at least one of the open and closed status of the window provided in the indoor space, the operating state and power usage of the air purifying ventilation device provided in the indoor space

Air quality management system.
According to paragraph 1,

The air quality information processing unit,

Inputting the collected air quality data into the air quality diagnosis model to generate the air quality status information, and inputting the generated air quality status information into the ventilation device control model to generate the remote control information.

Air quality management system.
According to paragraph 1,

The air quality management server,

Re-collecting the at least one air quality big data at preset intervals, relearning the air quality diagnosis model and the ventilator control model through machine learning based on the re-collected air quality big data, and relearning the re-learned air quality Generating program update information including a diagnostic model, the re-learned ventilation control model, and update information of the edge computing module.

Air quality management system.
According to clause 5,

The program receiver,

Receiving the program update information from the air quality management server,

The air quality information processing unit,

Updating the air quality management program based on the received program update information.

Air quality management system.
According to paragraph 1,

At least one of the air quality management device and the air quality management server,

It further includes an air quality data visualization unit that generates visualization information about monitoring data corresponding to the air quality status information and provides the visualization information to the user through at least one of a preset user terminal, mobile app, web service, and TV app service. doing

Air quality management system.
In clause 7,

The air quality data visualization unit,

Generating the monitoring data that classifies data for each air quality element according to the air quality status information by time passage, and supporting visualization of the monitoring data in the user terminal

Air quality management system.
According to paragraph 1,

The air quality information processing unit,

Further comprising an air quality management device control unit that controls the operation of a ventilation device provided in the indoor space based on the remote control information.

Air quality management system.
According to clause 9,

The air quality management device control unit,

Remotely controlling the operation of the ventilator by providing the remote control information to the ventilator

Air quality management system.
According to clause 9,

The air quality management device control unit,

Providing the remote control information to the air quality management server,

The air quality management server,

Remotely controlling the operation of the ventilation device based on the provided remote control information

Air quality management system.
According to paragraph 1,

The air quality information processing unit,

Performs information processing based on edge computing in offline mode, and performs information processing based on cloud computing in online mode.

Air quality management system.
According to clause 12,

The information processing process based on edge computing is,

Including the process of processing information to perform at least one operation of searching, connecting, controlling, and operating status monitoring of a connectable ventilation device in an offline state,

The information processing process based on cloud computing is,

Including the process of processing information for registering at least one of a ventilation device provided in the indoor space and the air quality management device with the air quality management server.

Air quality management system.
In the air quality management server, providing an air quality management program to the air quality management device, and

In the air quality management device, generating air quality status information and remote control information for a preset indoor space using the provided air quality management program,

The step of generating the air quality status information and remote control information is,

Receiving the air quality management program at a program receiving unit;

In the air quality data collection unit, collecting air quality data for the indoor space, and

In an air quality information processing unit, analyzing the collected air quality data using the air quality management program and generating the air quality status information and the remote control information based on the results of the analysis of the collected air quality data.

Includes,

The step of providing the air quality management program is,

In the air quality management server, an air quality diagnosis model and a ventilation device control model are generated through machine learning based on at least one air quality big data of indoor air quality big data, outdoor air quality big data, weather big data, and space usage pattern big data, and , generating the air quality management program reflecting the air quality diagnosis model and the ventilation device control model.

How to manage air quality.