CN111536662A - Network type fresh air system and regulation and control method based on big data analysis - Google Patents
Network type fresh air system and regulation and control method based on big data analysis Download PDFInfo
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- CN111536662A CN111536662A CN202010334929.3A CN202010334929A CN111536662A CN 111536662 A CN111536662 A CN 111536662A CN 202010334929 A CN202010334929 A CN 202010334929A CN 111536662 A CN111536662 A CN 111536662A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/50—Air quality properties
- F24F2110/52—Air quality properties of the outside air
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2120/00—Control inputs relating to users or occupants
- F24F2120/10—Occupancy
- F24F2120/12—Position of occupants
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2130/00—Control inputs relating to environmental factors not covered by group F24F2110/00
- F24F2130/10—Weather information or forecasts
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
Abstract
A network type fresh air system and a regulation and control method based on big data analysis are characterized in that a big data analysis network platform and a dispersed user fresh air system jointly form an outdoor air quality monitoring network; the user fresh air system at least comprises an air quality monitoring module which is arranged in the air supply channel and used for monitoring the quality of outdoor air entering the air supply channel, namely a data acquisition terminal used as a monitoring network; a monitoring network is formed by widely dispersed user fresh air systems, the change data of outdoor air quality at each position is collected, big data analysis is carried out after the data are collected, accurate prediction of air quality change in the network is achieved, and operation of the user fresh air systems is optimized and adjusted according to the prediction data.
Description
Technical Field
The invention relates to a fresh air system technology, in particular to a network type fresh air system and a regulation and control method based on big data analysis.
Background
The fresh air system is an air processing system consisting of an air supply system and an air exhaust system, and is used for continuously introducing outdoor fresh air into the room and exchanging indoor air, and exhausting the indoor air out of the room through an air exhaust channel; and simultaneously, the outdoor air introduced into the room is purified, so that high-quality clean air is continuously obtained indoors. The principle of the existing fresh air system is mainly that a multi-stage filtration method is adopted, and a plurality of purification modules with different functions can be added to work cooperatively, so that harmful components and inhalable particles in the air are gradually filtered or eliminated. The normal operation mode of the fresh air system is 24-hour automatic operation, but according to the difference of application requirements and use habits of users, the intermittent operation of some fresh air systems is not excluded.
The problem of current new trend system lies in:
1. high energy consumption and low air exchange rate: compared with the windowing natural ventilation, the ventilation volume of the fresh air system is only a fraction or even a tenth of the windowing natural ventilation, and the air supply needs to consume electric energy; for example, in a time period when the climate conditions are appropriate and the outdoor air quality is excellent, the fresh air system has almost no advantage compared with the windowing natural ventilation;
2. the intelligent degree is low: the filter device in the fresh air system is designed according to the worst outdoor air quality, although the filter effect is good, the ventilation resistance is very large, and the frequency of replacing consumables is high when the fresh air system is used for a long time; because the fluctuation of the outdoor air quality is large, the data of the outdoor air quality are different and sometimes fluctuate very violently in different seasons and different dates in one year and different time periods in one day, if a fresh air system can avoid the time period with poor air quality and simultaneously utilize the time period with good air quality as much as possible, the consumption of filter consumables can be reduced, and more fresh air with higher quality can be provided for the indoor; however, the influence of this factor is not considered in the design of the existing fresh air system.
In addition, there are many artificial intelligence algorithms for predicting air quality based on big data analysis in the prior art, for example, chinese patent application No. 201510626776.9, "a regional air PM2.5 concentration prediction method", and there are many similar schemes in the prior art. Common to such artificial intelligence algorithms are: algorithm rules and models are established according to the air quality of the area to be measured, historical meteorological data and real-time data, calculation and optimization are carried out through a computer, and prediction and analysis of the air quality can be achieved.
It should be noted that all gridding prediction algorithms are based on data, and the number and density of monitoring points are key factors for determining the gridding fineness of prediction. The existing artificial intelligence algorithm depends on the monitoring data of public observation points, and because the number of the public observation points is small, the local outdoor air quality change data related to a certain building (longitude and latitude) and a certain floor (height) can not be provided accurately, and the local sudden outdoor air quality change condition in a small range of a related area can not be monitored; therefore, the existing air quality prediction system cannot play an accurate guiding role in the operation strategy of the fresh air system of each user.
Disclosure of Invention
The design idea of the invention is as follows: a monitoring network is formed by widely dispersed user fresh air systems, the change data of outdoor air quality at each position is collected, big data analysis is carried out after the data are collected, accurate prediction of air quality change in the network is achieved, and operation of the user fresh air systems is optimized and adjusted according to the prediction data.
The technical scheme of the invention is as follows: a big data analysis network platform and a dispersed user fresh air system jointly form an outdoor air quality monitoring network;
the user fresh air system at least comprises an air quality monitoring module which is arranged in the air supply channel and used for monitoring the quality of outdoor air entering the air supply channel, namely a data acquisition terminal used as a monitoring network;
the user fresh air system has the functions of operation planning and operation regulation according to the change of the outdoor air quality;
in the operation process of the user fresh air system, outdoor air quality monitoring data monitored by the air quality monitoring module is sent to a big data analysis network platform through a network; the big data analysis network platform collects the position coordinates and monitoring data of the fresh air systems of all users and carries out data analysis processing, and then the prediction of the change trend of the outdoor air quality of all the position coordinates in the monitoring network is completed; the big data analysis network platform sends outdoor air quality prediction data related to the position coordinates of each user fresh air system to each corresponding user fresh air system; and then, planning the operation plan of the user fresh air system by each user fresh air system according to the received prediction data.
The invention relates to a regulation and control method of a network type fresh air system based on big data analysis, which comprises the following steps:
s101, registering the position coordinates of the fresh air systems of all users in a big data analysis network platform;
it should be noted that the position coordinates are based on the position where the air quality monitoring module is installed, and the coordinates include longitude, latitude and height; when the user fresh air system comprises a plurality of scattered air supply channels and scattered air quality monitoring modules, the position coordinates can be set respectively;
s102, when a user fresh air system runs, the air quality monitoring module monitors the air quality entering an air supply channel in real time and sends monitoring data to a big data analysis network platform through a network;
s103, the user fresh air systems adjust the operation modes of the respective systems in real time according to respective monitoring data; the regulation principle is that on the premise of meeting the requirements of users, the operation of introducing fresh air ventilation is enhanced when the outdoor air quality is good, and the operation of introducing fresh air ventilation is weakened or stopped when the outdoor air quality is poor;
it should be noted that, the user fresh air system can be adjusted beneficially through the step S103, but certain defects exist, namely lack of "foresight"; the air quality monitoring module can monitor the current outdoor air quality in real time in the operation process of the fresh air system, but cannot judge whether the outdoor air quality is better or worse than the outdoor air quality after a period of time; for example, when current outdoor PM2.5 concentration is 100 μ g/m, perhaps an hour later a shift to 200 μ g/m or an hour later a shift to 50 μ g/m flowering; for the trend of the change, the user fresh air system is difficult to make independent judgment, and an accurate control strategy cannot be realized;
s104, acquiring air quality monitoring data of fresh air systems of all users by a big data analysis network platform, summarizing the data, and performing predictive analysis on the change trend of outdoor air quality of all positions in the monitoring network through an artificial intelligence algorithm;
s105, the big data analysis network platform sends outdoor air quality prediction data related to the position coordinates of each user fresh air system to each corresponding user fresh air system through a network, and the user fresh air system makes a system operation plan based on user requirements and in combination with the outdoor air quality prediction data and operates according to the plan; the principle of making the operation plan is that on the premise of meeting the requirements of users, the operation of introducing fresh air ventilation is enhanced by fully utilizing the time period with better outdoor air quality, so that the operation of introducing fresh air ventilation is properly weakened or stopped in the time period with poorer outdoor air quality;
in addition, S105 is an adjustment means based on predictive analysis, and S103 is an adjustment means based on real-time data; in general, the air quality data predicted by the system is consistent with or has a small difference with the air quality data monitored in real time, and the execution of the operation plan set in the step S105 can be performed; if some special conditions occur, S103 is used as a backup measure to maintain normal operation, for example, when a network failure occurs, data cannot be updated in time or local burst air pollution causes prediction misalignment;
and S106, if the latest outdoor air quality prediction data sent by the big data analysis network platform is different from the outdoor air quality prediction data in a previous period of time, the user fresh air system updates the system operation plan based on the user requirements and in combination with the latest outdoor air quality prediction data, and operates according to the updated plan.
Furthermore, not only historical and real-time air quality data but also meteorological factors are important factors which must be considered when performing predictive analysis on air quality.
Therefore, the artificial intelligence algorithm of the big data analysis network platform also needs to quote meteorological data as original data, and obtains related data through the connection with a meteorological observation station or a meteorological satellite; the prediction results include predictions of weather conditions at various locations in the monitoring network and the effects of the weather conditions on the outdoor air quality. The artificial intelligence algorithm can adopt the prior art, or is expanded on the basis of the prior artificial intelligence algorithm model, and is not described in detail here.
Furthermore, when a user fresh air system makes an operation plan, user requirements and outdoor air quality factors are considered firstly; also considering the influence of meteorological conditions such as weather conditions, temperature, humidity, wind direction, wind speed, etc.; this makes the algorithm for making the operation plan more complex, especially for large-scale public building fresh air system. Therefore, when the user fresh air system cannot make an operation plan by itself, the user demand data of the system is sent to the big data analysis network platform through the network, the big data analysis network platform carries out calculation analysis and makes the operation plan, and the operation plan is sent to the user fresh air system. And the big data analysis network platform can also carry out big data analysis on historical operating data of the fresh air system of the user, so that the accuracy of the operating plan is improved.
Furthermore, when a certain user fresh air system is in a non-running state for a long time and the data collection of the big data analysis network platform is adversely affected by the loss of outdoor air quality monitoring data of the position of the user fresh air system, the big data analysis network platform sends an instruction through a network to activate the user fresh air system to run for a short time, so that the real-time data collection and the report are completed. If other user fresh air systems which are connected to the network and are in an operating state exist near the position of the user fresh air system, whether the user fresh air system operates or not does not cause adverse effects on data collection of the big data analysis network platform, and the user fresh air system does not need to be activated forcibly.
Furthermore, when the user fresh air system operates according to an operation plan designated by the outdoor air quality prediction data, if the difference between the outdoor air quality monitoring data collected by the air quality monitoring module in real time and the air quality prediction data is large, the user fresh air system preferably adopts the outdoor air quality monitoring data collected in real time to correct the operation plan of the system, and performs problem feedback on the big data analysis network platform. In the above situation, a local or sudden air pollution source may be generated around the user fresh air system, which may cause the outdoor environment of the local area to change.
Further, the big data analysis network platform collects the raw data and the forecast result data of the stored air quality, and provides related data information service for research institutions or application systems needing to utilize the data. For example, a person's outdoor activity plan may be prompted; the device can be used for tracing unconventional local pollution sources and giving an alarm; and so on.
The invention has the beneficial effects that:
1. the invention is not focused on the improvement of the intelligent analysis algorithm, but solves the problem of data source of the intelligent analysis algorithm; by installing monitoring modules in a large number of scattered user fresh air systems, the basic data sources of analysis are greatly enriched, and therefore the analysis capability and the predicted grid fineness of a big data analysis network platform are improved; when the number of the scattered user fresh air systems accessing the prediction network is larger, the scale effect can be reflected more, and the whole network system hardly generates extra cost; for example, the grid accuracy of the existing air quality monitoring system is in the order of thousands of meters, and when the cardinality of a user fresh air system accessed in the monitoring network of the invention is enough, the accuracy of the system can reach ten meters or even meters; moreover, the dimension is also expanded from two dimensions (longitude + latitude) to three dimensions (longitude + latitude + horizontal height); by means of big data analysis, a more refined user fresh air system operation strategy can be formulated;
2. the fresh air system is operated under the condition of serious outdoor air pollution, so that the service life of the filtering consumables is seriously influenced; if the filter material can be reasonably avoided, the service life of the filter material is multiplied;
3. the air quality monitoring module of the user fresh air system can play a role in correcting deviation in real time, and when the predicted data has errors with the actual situation, the operation of the user fresh air system can be adjusted on the basis of the actual data;
4. the air quality prediction analysis data with high grid precision obtained by the invention has wide application prospect and is not limited to the operation of an optimized fresh air system.
Drawings
FIG. 1: the invention is a network structure diagram;
FIG. 2 is a drawing: the invention has a network structure schematic diagram (comprising a control mode amplification schematic diagram of a user fresh air system);
in fig. 2, two user fresh air systems 2a and 2b are displayed in an enlarged manner, wherein 2a corresponds to a state with good outdoor air quality, and 2b corresponds to a state with poor outdoor air quality; the arrow direction indicates the process that fresh air enters the room through the air supply channel and indoor air is discharged out of the room through the air exhaust channel.
Detailed Description
Example 1:
in summary, the system and method of the present invention have been described in detail, and the adjustment strategy and adjustment means of the user fresh air system are explained in detail with the actual case emphasis. For convenience of understanding and explanation, in the present embodiment, the technical solution of the present invention is explained in detail by taking the outdoor air quality parameter as the adjusting basis.
The existing fresh air system is designed according to the worst outdoor air quality and cannot be properly adjusted according to the change of the outdoor air quality. The user fresh air system provided by the invention has the functions of operation planning and operation regulation according to the change of the outdoor air quality. The specific principles and measures are as follows:
as the demands of users are various, the fresh air system mainly serves people; therefore, as an intelligent fresh air system, the basic principle that the operation is strengthened in the time period of human activities and the operation is weakened in the time period of no human activities is followed, so that people can be better served, and meanwhile, the energy consumption and the consumable material loss of the system are reduced as much as possible. For example:
for an office area, the personnel are dense in the working time period in the daytime and have higher fresh air demand, and the operation intensity of a fresh air system can be reduced when no one works at night;
for a meeting room area, the requirement of fresh air is higher in a time period when people gather for meeting, and the operation intensity of a fresh air system can be reduced in other time periods;
for double-worker families, if no person is at home in the daytime during working days, the operation intensity of the fresh air system can be reduced; when a person is in the house, the fresh air system is enabled to normally operate or be started in advance;
for the situation that old people and children are at home for a long time, the normal operation of the fresh air system is required to be kept for 24 hours;
the demand data of the user can be input into the control module of the fresh air system through methods such as user autonomous setting, system intelligent perception or user behavior analysis and the like.
It should be noted that for flexibly changing customer demands, it is not possible to completely synchronize the change in demand with the change in outdoor air quality, and the following control strategy can be followed:
firstly, when the time period of large fresh air demand and the time period of good outdoor air quality of a user are basically overlapped, the operation of introducing fresh air and exchanging air can be enhanced in the time period of large fresh air demand and good outdoor air quality according to the demand of the user;
secondly, when the time period with large fresh air demand by the user basically coincides with the time period with poor outdoor air quality, the time period before the time period with large fresh air demand and with relatively good outdoor air quality is selected to enhance the operation of introducing fresh air ventilation according to the prediction data of outdoor air quality change, so that the indoor environment is improved in advance; then, the operation of introducing fresh air ventilation is weakened in the time period when the fresh air demand is large and the outdoor air quality is poor; thereby, the indoor environment is not excessively deteriorated;
thirdly, when the prediction of outdoor air quality change is severe pollution in a time period when the user demands a large amount of fresh air and a long time in the early period, an operation mode of 'internal circulation' can be adopted.
Based on the principle and the case, the dynamic adjustment of the running state of the fresh air system is very necessary; of course, the adjustment process needs to be combined with outdoor air quality data to achieve the best adjustment effect with a good target. In the following, measures of how the fresh air system achieves regulation are exemplified.
Specifically, the operation state of the fresh air system can be divided into high-gear external circulation, low-gear external circulation, internal circulation and stop operation;
firstly, when the outdoor air quality data is good, the fresh air system is set to be in high-gear external circulation, and more fresh air with high quality can be introduced from the outdoor;
secondly, when the quality data of the outdoor air is poor, the fresh air system is set to be in low-gear external circulation, namely, the quantity of fresh air introduced from the outdoor is reduced;
furthermore, the adjustment of high gear/low gear can be realized by increasing the power of the blower/reducing the power of the blower;
alternatively, as shown in fig. 2, a fresh air system with a dynamic combined air purification module is adopted, and the fresh air system at least comprises an air supply channel 101, an air blower 102, an air purification module 103, an air exhaust channel 104 and a control module, wherein an air quality monitoring module 105 for monitoring the quality of air entering the air supply channel is arranged in the air supply channel 101. The air purification module 103 is a dynamic combined air purification module, taking fig. 2 as an example, and includes four layers of air purification components 106 with air purification functions, namely a primary filter screen, a secondary filter screen, and a high-efficiency filter screen, wherein the purification capacity of the air purification components is sequentially enhanced, and the resistance to air circulation is also sequentially increased. The dynamic combined air purification module is divided into two areas, namely a working area 107 and a standby area 108, the working area 107 is communicated with the air supply channel 101, and the air purification component 106 positioned in the working area 107 purifies air flowing in the air supply channel 101; the standby area 108 is not communicated with the air supply passage 101, and the air cleaning component 106 in the standby area 108 is kept in a standby state; the position of each air cleaning component 106 can be switched between the working area 107 and the standby area 108, respectively, to form a filtering combination of different functions. As shown in fig. 2a, corresponding to the case of better outdoor air quality, two layers of the air purification components 106 with four layers in total in the air purification module 103 are arranged in the working area 107, and the other two layers are arranged in the standby area 108, so that the ventilation resistance is smaller, and the ventilation capacity can be enhanced without changing the power of the blower 102; as shown in fig. 2b, corresponding to the case of poor outdoor air quality, all four layers of air purification components 106 in the air purification module 103 are arranged in the working area 107, and at this time, the ventilation resistance is large, the ventilation volume is small, but the poor outdoor air can be purified;
thirdly, when the outdoor air quality data is heavily polluted, setting the fresh air system into an internal circulation or stopping operation, wherein the internal circulation means that the air inlet and the air outlet are closed and the air outlet channel is connected to the air inlet channel, namely, the fresh air system is adopted to circularly purify the indoor air without introducing fresh air from the outdoor; this measure makes it possible to reduce the meaningless consumption of filter consumables, especially for situations of short-term heavy contamination or no current user demand. If the measure of stopping operation is taken, the indoor air purifier can be started in a linkage mode to temporarily replace a fresh air system to purify indoor air.
By adopting the above regulation and control measures and other similar technical means of the disclosed regulation and control measures, the technical scheme of 'performing operation regulation or making an operation plan according to real-time data or prediction data of outdoor air quality and combining with application requirements of users' of the invention can be realized.
The invention is not limited to the above embodiments, and those skilled in the art can make equivalent modifications or substitutions without departing from the spirit of the invention, and such equivalent modifications or substitutions are included in the scope defined by the claims of the present application.
Claims (7)
1. Big data analysis based network formula new trend system its characterized in that: a big data analysis network platform (1) and a dispersed user fresh air system (2) jointly form an outdoor air quality monitoring network;
the user fresh air system (2) at least comprises an air quality monitoring module (105) which is arranged in the air supply channel (101) and used for monitoring the quality of outdoor air entering the air supply channel (101), namely, the air quality monitoring module is used as a data acquisition terminal of a monitoring network;
the user fresh air system (2) has the functions of operation planning and operation regulation according to the change of outdoor air quality;
in the operation process of the user fresh air system (2), outdoor air quality monitoring data monitored by the air quality monitoring module (105) are sent to the big data analysis network platform (1) through a network; the big data analysis network platform (1) collects the position coordinates and monitoring data of each user fresh air system (2) and carries out data analysis processing, and then the prediction of the change trend of the outdoor air quality of each position coordinate in the monitoring network is completed; the big data analysis network platform (1) sends outdoor air quality prediction data related to the position coordinates of each user fresh air system (2) to each corresponding user fresh air system (2); and then, planning the operation plan of the user fresh air system (2) by each user fresh air system (2) according to the received prediction data.
2. The big data analysis-based network type fresh air system regulation and control method is characterized by comprising the following steps of: the method comprises the following steps: a big data analysis network platform (1) and a dispersed user fresh air system (2); the user fresh air system (2) at least comprises an air quality monitoring module (105) which is arranged in the air supply channel (101) and is used for monitoring the quality of air entering the air supply channel (101); the method comprises the following steps:
s101, registering the position coordinates of each user fresh air system (2) in a big data analysis network platform (1);
s102, when a user fresh air system (2) runs, the air quality monitoring module (105) monitors the air quality entering an air supply channel (101) in real time, and sends monitoring data to a big data analysis network platform (1) through a network;
s103, the user fresh air system (2) adjusts the operation modes of the respective systems in real time according to respective monitoring data; the regulation principle is that on the premise of meeting the requirements of users, the operation of introducing fresh air ventilation is enhanced when the outdoor air quality is good, and the operation of introducing fresh air ventilation is weakened or stopped when the outdoor air quality is poor;
s104, acquiring air quality monitoring data of the fresh air systems (2) of all users by the big data analysis network platform (1), summarizing the data, and performing predictive analysis on the change trend of outdoor air quality of all positions in the monitoring network through an artificial intelligence algorithm;
s105, the big data analysis network platform (1) sends outdoor air quality prediction data related to the position coordinates of each user fresh air system (2) to each corresponding user fresh air system (2) through a network, and the user fresh air systems (2) make system operation plans on the basis of user requirements and in combination with the outdoor air quality prediction data and operate according to the plans; the principle of making the operation plan is that on the premise of meeting the requirements of users, the operation of introducing fresh air ventilation is enhanced by fully utilizing the time period with better outdoor air quality, so that the operation of introducing fresh air ventilation is properly weakened or stopped in the time period with poorer outdoor air quality;
and S106, if the latest outdoor air quality prediction data sent by the big data analysis network platform (1) is different from the outdoor air quality prediction data in a previous period of time, the user fresh air system (2) updates the system operation plan based on the user requirements and in combination with the latest outdoor air quality prediction data, and operates according to the updated plan.
3. The method for regulating and controlling the network type fresh air system based on big data analysis as claimed in claim 2, wherein: the artificial intelligence algorithm of the big data analysis network platform (1) also needs to quote meteorological data as original data, and obtains related data through the connection with a meteorological observation station or a meteorological satellite; the prediction results include predictions of weather conditions at various locations in the monitoring network and the effects of the weather conditions on the outdoor air quality.
4. The method for regulating and controlling the network type fresh air system based on big data analysis as claimed in claim 2, wherein: when the user fresh air system (2) can not make an operation plan by itself, user demand data of the system is sent to the big data analysis network platform (1) through a network, the big data analysis network platform (1) performs calculation analysis, makes the operation plan, and sends the operation plan to the user fresh air system (2).
5. The method for regulating and controlling the network type fresh air system based on big data analysis as claimed in claim 2, wherein: when a certain user fresh air system (2) is in a non-running state for a long time and the data collection of the big data analysis network platform (1) is adversely affected by the loss of outdoor air quality monitoring data of the position of the user fresh air system (2), the big data analysis network platform (1) sends an instruction through a network to activate the user fresh air system (2) to run for a short time, so that the real-time data collection and the report are completed.
6. The method for regulating and controlling the network type fresh air system based on big data analysis as claimed in claim 2, wherein: when the user fresh air system (2) operates according to an operation plan appointed by the outdoor air quality prediction data, if the difference between outdoor air quality monitoring data acquired by the air quality monitoring module (105) in real time and the air quality prediction data is large, the user fresh air system (2) preferably adopts the outdoor air quality monitoring data acquired in real time to correct the system operation plan, and performs problem feedback to the big data analysis network platform (1).
7. The method for regulating and controlling the network type fresh air system based on big data analysis as claimed in claim 2, wherein: the big data analysis network platform (1) collects the stored air quality raw data and prediction result data and provides related data information service for research institutions or application systems needing to utilize the data.
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| CN113719944A (en) * | 2021-09-09 | 2021-11-30 | 苏州行净环保科技有限公司 | Efficient filtering method for air pollution |
| CN114211940A (en) * | 2021-11-30 | 2022-03-22 | 北京汽车股份有限公司 | TSP service-based automobile air purification system and method |
| CN114383275A (en) * | 2021-12-10 | 2022-04-22 | 安徽新识智能科技有限公司 | Indoor air conditioning method and system of Internet of things |
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