CN112413855A - Air conditioning method, device and system - Google Patents
Air conditioning method, device and system Download PDFInfo
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- CN112413855A CN112413855A CN202011288768.5A CN202011288768A CN112413855A CN 112413855 A CN112413855 A CN 112413855A CN 202011288768 A CN202011288768 A CN 202011288768A CN 112413855 A CN112413855 A CN 112413855A
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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
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
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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
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Abstract
The application provides an air conditioning method, device and system, which belong to the technical field of smart home, and the method comprises the following steps: performing gas molecule recognition on air in the current environment through gas detection equipment to obtain an air recognition result; generating synthetic gas for regulating air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result; releasing the generated synthesis gas into the current environment. The air conditioning system can efficiently and reliably condition air and better improve the air taste.
Description
Technical Field
The application belongs to the technical field of smart home, and particularly relates to an air conditioning method, device and system.
Background
With the increasing demand for quality of life of modern people, people have raised higher demands for the taste of air in rooms such as home environment, offices, and the like. However, the gas composition in the indoor environment is usually complex, and many times there is peculiar smell, for example, in a relatively closed space, there may be various peculiar smells such as perfume smell, food smell, smoke smell, smell emitted from pets, and the sensitivity and tolerance of different people to the peculiar smell are different. However, most of the prior art only adopts a fresh air purification mode to ventilate to remove the peculiar smell of air, which takes a long time, and the gas molecules adsorbed on the object are difficult to remove by the fresh air mode, so that the effect of removing the peculiar smell is not good.
Disclosure of Invention
To overcome, at least to some extent, the problems of the related art, the present application provides air conditioning methods, devices and systems that facilitate efficient and reliable air conditioning, preferably improving the taste of the air.
In order to achieve the purpose, the following technical scheme is adopted in the application:
in a first aspect, the present application provides an air conditioning method comprising: performing gas molecule recognition on air in the current environment through gas detection equipment to obtain an air recognition result; generating synthetic gas for regulating air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result; releasing the generated synthesis gas into the current environment.
Further, the gas detection device comprises a multi-sensor array and a gas molecular dynamics detector; wherein the multi-sensor array comprises a plurality of sensors for detecting different types of gases.
Further, after obtaining the air identification result, the method further comprises: judging whether the air identification result is stored in the established air database; the air database stores sample data corresponding to air composed of a plurality of different gas molecules; the air database is stored in a local and/or cloud server; and if not, storing the air identification result as new sample data in the air database.
Further, the step of generating synthetic gas for adjusting the air under the current environment by using a machine learning technology and/or a big data technology based on the air recognition result comprises: inquiring whether an air conditioning scheme corresponding to the air identification result exists in a server; the server stores corresponding relations between a plurality of pairs of air identification results and air conditioning schemes; if so, generating synthesis gas for regulating the air in the current environment according to the inquired air regulation scheme; and if not, inputting the air recognition result into a neural network model obtained by pre-training, and generating synthetic gas for regulating the air in the current environment based on an air regulation scheme output by the neural network model.
Further, the air conditioning scheme records target gas molecular species to be released in the gas storage unit and a release amount corresponding to each target gas molecular species to be released; different kinds of gas molecules have different corresponding smells; the step of generating a synthesis gas for regulating air in the current environment according to the queried air-conditioning scheme includes: releasing, by the gas storage unit, a target gas molecule based on the queried air-conditioning scheme; and synthesizing the target gas molecules released by the gas storage unit through a gas generator to obtain the synthetic gas for regulating the air in the current environment.
Further, the method further comprises: and uploading the air conditioning scheme output by the neural network model and the air recognition result to the server in a correlation mode.
In a second aspect, the present application provides an air conditioning device comprising: the gas identification module is used for identifying gas molecules of the air in the current environment through gas detection equipment to obtain an air identification result; a gas synthesis module for generating a synthesis gas for conditioning the air in the current environment using a machine learning technique and/or a big data technique based on the air recognition result; a gas release module for releasing the generated synthesis gas into the current environment.
In a third aspect, the present application provides an air conditioning system comprising: the system comprises gas detection equipment, gas generation equipment and a fresh air system; the gas detection equipment is used for carrying out gas molecule identification on the air in the current environment to obtain an air identification result; the gas generation device is used for generating synthetic gas for adjusting the air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result; the fresh air system is used for releasing the generated synthesis gas to the current environment.
Further, the gas detection device comprises a multi-sensor array and a gas molecular dynamics detector; wherein the multi-sensor array comprises a plurality of sensors for detecting different kinds of gases.
Further, the gas generation device includes an information processing unit, a gas storage unit, and a gas generator; the information processing unit is used for obtaining an air conditioning scheme based on the air identification result; the gas storage unit is used for releasing target gas molecules based on the air conditioning scheme; the gas generator is used for synthesizing the target gas molecules released by the gas storage unit to obtain synthetic gas for regulating the air in the current environment.
According to the air conditioning method, the air conditioning device and the air conditioning system, the air detection equipment is used for identifying the gas molecules of the air in the current environment to obtain an air identification result; generating synthetic gas for regulating air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result; releasing the generated synthesis gas into the current environment. The mode can identify gas molecules in the air under the current environment, and generate and release synthetic gas based on the identification result, thereby efficiently and reliably conditioning the air and better improving the air taste.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart illustrating a method of air conditioning according to an exemplary embodiment;
FIG. 2 is a schematic diagram of an air conditioning system according to an exemplary embodiment;
FIG. 3 is a schematic illustration of a particular principle of an air conditioning system according to an exemplary embodiment;
FIG. 4 is a schematic diagram of an information processing unit shown in accordance with an exemplary embodiment;
fig. 5 is a block diagram illustrating a structure of an air conditioning device according to an exemplary embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail below. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without making any creative effort, shall fall within the protection scope of the present application.
In view of the poor effect and low efficiency of the prior art for removing the air odor, the embodiment of the application provides an air conditioning method, device and system, which can efficiently and reliably condition air and remove the air odor. For ease of understanding, the detailed description is as follows:
referring first to a flowchart of an air conditioning method shown in fig. 1, the method mainly includes the following steps S102 to S106:
and S102, performing gas molecule identification on the air in the current environment through gas detection equipment to obtain an air identification result.
The gas detection device may be used to identify the composition of air, and in order to be able to accurately identify the various components in air, in one embodiment, the gas detection device comprises a multi-sensor array and a gas molecular dynamics detector; wherein the multi-sensor array comprises a plurality of sensors for detecting different types of gases. The multi-sensor array can identify gas molecules with high concentration and peculiar smell in the gas, such as ammonia, hydrogen sulfide, disulfide, trimethylamine, methyl mercaptan, methyl sulfide, dimethyl disulfide, phenethyl ether and the like, and the gas molecule dynamics detector mainly identifies gas molecules with low concentration and complexity. Through the mode that combines together of this kind of sensor array and gas molecule dynamics detection, can discern the air composition comparatively comprehensively, effectively improve the identification accuracy degree of air composition, only adopt single sensor to detect and the following problem that probably appears among the prior art has been avoided: because the composition of air is complex, if the concentration of gas molecules corresponding to a certain smell is not high, the sensor cannot detect the gas molecules, and the complex peculiar smell in the air is difficult to tolerate because a plurality of gas molecules with low concentration are combined together.
And step S104, generating synthetic gas for regulating the air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result.
For example, an air conditioning scheme (i.e., a synthetic gas generation scheme) corresponding to the air recognition result may be directly generated through a neural network model in the machine learning technology, then synthetic gas for adjusting air in the current environment is generated based on the air conditioning scheme, and odor molecules in the air and adsorbed on the object are removed through the synthetic gas, so that odor in the air is removed to the maximum extent. As another example, the recorded air identification results similar to the current air composition and the corresponding air conditioning scheme may also be queried through the cloud (server) through big data technology. The server can collect air identification results uploaded by different devices (air conditioning systems) and corresponding air conditioning schemes based on a big data technology, each device is deployed at different positions, the server performs statistical analysis and recording based on the big data technology, and meanwhile data sharing is achieved. For example, the air conditioning system of zhang san jia binds and associates the air recognition results and the corresponding air conditioning schemes together, shares the air recognition results and the corresponding air conditioning schemes together to the server, adds the air recognition results to the database of the server, and if the air recognition results of zhang xia jia are consistent with the air recognition results of zhang san jia, the recorded air conditioning schemes are directly adopted, and if the air recognition results of zhang xia jia through comparison and zhang san jia are not consistent but are close, and only part of the gas molecular species or the concentration are different, the air conditioning schemes of zhang san jia can be obtained by performing partial adjustment based on the recorded air conditioning schemes of zhang san jia.
In practical application, the air identification method can be realized by using a machine learning technology alone or a big data technology alone, or the machine learning technology and the big data technology are used in combination, and specifically, which technology is used can be determined according to the air identification result, or which technology is used can be set manually in advance, and is not limited herein.
Step S106, releasing the generated synthesis gas into the current environment. For example, a fresh air system can be adopted to release the synthetic gas to the current environment, so that the odor molecules in the air and adsorbed on the object are removed through the synthetic gas, and the effect of removing the odor in the air to the maximum extent is achieved.
The method can identify the gas molecules in the air under the current environment, and generate and release the synthesis gas based on the identification result, thereby efficiently and reliably conditioning the air and better improving the air taste.
In order to facilitate subsequent air conditioning based on the air recognition result, the detected air recognition result may be stored in an air database, so that the subsequent equipment or other equipment may also retrieve the same or similar air recognition result and corresponding air conditioning scheme through the air database. The air database can record a plurality of air recognition results with different tastes, and it can be understood that the air with different tastes indicates different types and/or different concentrations of air molecules, and the air database can record a plurality of air recognition results collected by one or more air conditioning systems at different times and/or different positions and corresponding air conditioning schemes, so as to facilitate subsequent direct application. Based on this, after obtaining the air identification result, the method further includes: judging whether an air identification result is stored in an established air database; the air database stores sample data corresponding to air composed of various different gas molecules; the air database is stored in a local and/or cloud server; if not, the air identification result is stored in the air database as new sample data to enrich the air database, so that the air identification result can be directly applied based on the data recorded in the air database.
Further, the present embodiment provides an embodiment of generating synthesis gas for regulating air in the current environment by using machine learning technology and/or big data technology based on the air recognition result: firstly, inquiring whether an air conditioning scheme corresponding to an air identification result exists in a server; the server stores the corresponding relationship between the air identification results and the air conditioning schemes, and specifically, the corresponding relationship between the air identification results and the air conditioning schemes may be recorded in an air database of the server. If the query result is yes, generating synthetic gas for adjusting the air in the current environment according to the queried air-conditioning scheme; if not, the fact that the air in the current environment is not recorded before is shown, so that the air recognition result can be input into a neural network model obtained through pre-training, and the synthesis gas for regulating the air in the current environment is generated based on an air regulation scheme output by the neural network model. That is, the air conditioning scheme may be determined by using a big data technology, if the air conditioning scheme is not queried, the air conditioning scheme may be generated by using a machine learning technology, and then the air conditioning scheme output by the neural network model is further associated with the air recognition result and uploaded to the server, so that the server can share data, and the linkage between multiple sets of air conditioning systems is increased.
In practical application, a plurality of groups of training data can be adopted to train the neural network model in advance, each group of data comprises information (type, concentration and the like) of gas molecules to be regulated and information of corresponding regulated gas molecules, and the neural network model obtained through training can directly generate a corresponding air regulation scheme based on an air recognition result.
Recording target gas molecular species to be released in the gas storage unit and the release amount corresponding to each target gas molecular species to be released in the air conditioning scheme; the synthetic gas used for adjusting the air under the current environment is obtained by the gas generator through the gas storage unit releasing the target gas molecules based on the inquired air conditioning scheme and performing synthetic processing on the target gas molecules released by the gas storage unit. The gas storage unit may include a plurality of small containers, each of which stores one kind of gas molecule, such as one of compounds formed by pyralone, limonene, linalool, β -phenylethyl alcohol, and β -myrcene, nonadienal, ambroxan, amyl vinyl carbinol, esters, linear terpenes, cyclic terpenes, aromatic hydrocarbons, amines, alcohols, aldehydes, ketones, lactones, or thiols, and then determines a target container of the gas molecule to be released according to an air conditioning scheme, opens the target container and releases the target gas molecule according to the amount released in the air conditioning scheme, and the gas generator may release the target gas molecule after integrating the target gas molecule. Compared with the prepared aromatic substances such as the common essence and the essential oil in the prior art, the method can prepare thousands of new fragrances by combining different types of gas molecules and adjusting different release amounts, can generate the synthetic gas which can improve the current ambient air in a targeted manner based on the air recognition result, and has better air conditioning effect.
The present embodiment provides a system for implementing the air conditioning method, namely an air conditioning system, including: the system comprises gas detection equipment, gas generation equipment and a fresh air system; referring to the schematic diagram of the air conditioning system shown in fig. 2, air in the current environment (referred to as current air for short) is input to a gas detection device, and the gas detection device is configured to perform gas molecule recognition on the air in the current environment to obtain an air recognition result; the gas generation equipment is used for generating synthetic gas for regulating the air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result; the fresh air system is used for releasing the generated synthetic gas to the current environment, namely the fresh air system outputs fresh air. In practical applications, the gas detection apparatus may also be referred to as a scent recognition system, and the gas generation apparatus may also be referred to as a scent generation system.
On the basis of fig. 2, referring to a specific principle schematic diagram of an air conditioning system shown in fig. 3, it is illustrated that a gas detection device includes a multi-sensor array and a gas molecular dynamics detector, and further includes an information processing unit, both the multi-sensor array and the gas molecular dynamics detector are used for identifying the types and concentrations of gas molecules in the air, the multi-sensor array mainly can identify gas molecules with high concentration and peculiar smell in the gas, the gas molecular dynamics detector mainly identifies gas molecules with low concentration and complex molecules, the information processing unit is mainly used for analyzing the odor information in the current environment based on the detection results of the multi-sensor array and the gas molecular dynamics detector, and further can store the odor identification result obtained by analysis locally or upload the odor identification result to a server. The gas generation device in fig. 3 includes an information processing unit, a gas storage unit, and a gas generator; the information processing unit is used for obtaining an air conditioning scheme based on the air identification result, namely, the composition of the synthesis gas for conditioning the air of the current environment is prepared mainly through sample comparison and analysis; for example, the offensive odor remaining on the wall surface can be neutralized with a smell similar to that of grapefruit peel, so that a gas having a smell of grapefruit peel is added to the air conditioning scheme. The gas storage unit is used for releasing target gas molecules based on an air conditioning scheme; the gas generator is used for synthesizing the target gas molecules released by the gas storage unit to obtain synthetic gas for regulating the air in the current environment. It should be noted that the information processing units in the gas detection device and the gas generation device are independent from each other, and only names are the same in fig. 3, but specific information processing procedures are different, but in the specific implementation, the hardware adopted by the two information processing units may be the same or different, such as hardware with a data processing function, such as a processing chip, is adopted, but software programs set on the hardware are different, and finally, the data processing procedures that can be realized are different.
In addition, fig. 3 also illustrates that the gas detection device, the gas generation device, and the fresh air system are further connected to a local storage medium and a server, and may generate a corresponding air conditioning scheme based on the air recognition result locally, or search for an air conditioning scheme matching the current air recognition result locally, or share the air recognition result and the air conditioning scheme to the server, or retrieve an air conditioning scheme corresponding to the air recognition result from the server, where the local storage medium may be implemented by using, for example, a RAM (Random Access Memory) or a ROM (Read-Only Memory), and an air database (also referred to as an odor sample library) may be disposed in the server to implement data sharing. In addition, the data recorded locally can be called and updated from the server in an online upgrading mode.
Referring to a schematic diagram of an information processing unit shown in fig. 4, which simply illustrates a basic principle of operation of the information processing unit, basic operation principles of the information processing units in the gas detection device and the gas generation device are similar, and both involve a neural network and a deep learning technique, and also involve memory storage and comparison storage, and the comparison storage is mainly used to distinguish whether current data is brand new or not, so as to determine whether to call data from a server or share data to the server, and the brand new data is not usually recorded locally or by the server. The neural network and the deep learning are used for processing the most original data, and the identification accuracy can be improved in an online upgrading mode. The information processing units in the gas detection equipment and the gas generation equipment can respectively adopt a deep learning comparison mode to perform smell identification processing and smell generation processing so as to improve the efficiency and reliability of data processing, and can also acquire data from a local storage medium or a server end so as to improve the data utilization rate, further improve the data processing rate and effectively save calculation resources. Among them, the information processing units in the gas detection apparatus and the gas generation apparatus are mainly different in that: the information processing unit of the gas detection equipment is mainly used for analyzing the odor in the current environment; the information unit in the gas generating apparatus is mainly used for dispensing new scents.
To sum up, this application embodiment can improve the precision of air identification through the combined use of multisensor array and gas molecular dynamics detector, has reduced the cost of labor and has improved the precision of air conditioning based on big data technology and machine learning technique again, moreover through data sharing to server, can make one set of data multiterminal use, has improved data utilization and can save computational resource betterly to a great extent, increases the linkage nature between the different equipment. In addition, the most appropriate adjusting gas component can be analyzed in a targeted manner through the peculiar smell component in the air recognition result of the current environment, so that the synthetic gas is released accurately, the air and peculiar smell molecules adsorbed on an object can be removed simultaneously, the peculiar smell in the air can be removed to the maximum extent, and a better air purification effect is realized. In addition, the air conditioning system provided by the embodiment of the application is not limited by the network connection condition in the use scene, can automatically and selectively call the server or local data according to the current network environment, is suitable for products such as a central air conditioner or a large household air conditioner in a household environment, and has better universality.
In correspondence to the foregoing air conditioning method, the present embodiment also provides an air conditioning apparatus, referring to a structural block diagram of an air conditioning apparatus shown in fig. 5, including:
the gas identification module 52 is configured to perform gas molecule identification on air in the current environment through a gas detection device to obtain an air identification result;
a gas synthesis module 54 for generating a synthesis gas for conditioning air in the current environment using a machine learning technique and/or a big data technique based on the air recognition result;
a gas release module 56 for releasing the generated synthesis gas into the current environment.
The device can identify gas molecules in the air under the current environment, and generate and release synthetic gas based on the identification result, thereby efficiently and reliably conditioning the air and better improving the air taste.
In one embodiment, after obtaining the air recognition result, the apparatus further includes: the judging module is used for judging whether an air identification result is stored in the established air database; the air database stores sample data corresponding to air composed of various different gas molecules; the air database is stored in a local and/or cloud server; and the database storage module is used for storing the air identification result as new sample data in the air database when the judgment result of the judgment module is negative.
In one embodiment, the gas synthesis module 54 is further configured to: inquiring whether an air conditioning scheme corresponding to the air identification result exists in the server; the server stores corresponding relations between a plurality of pairs of air identification results and air conditioning schemes; if so, generating synthesis gas for regulating the air under the current environment according to the inquired air regulation scheme; and if not, inputting the air recognition result into a neural network model obtained by pre-training, and generating the synthesis gas for regulating the air in the current environment based on an air regulation scheme output by the neural network model.
In one embodiment, the air conditioning scheme records the target gas molecular species to be released in the gas storage unit and the corresponding release amount for each target gas molecular species to be released; different kinds of gas molecules have different corresponding smells;
the gas synthesis module 54 is further configured to: releasing, by the gas storage unit, the target gas molecule based on the queried air-conditioning scheme; and synthesizing the target gas molecules released by the gas storage unit through the gas generator to obtain the synthetic gas for regulating the air in the current environment.
In one embodiment, the above apparatus further comprises: and the uploading module is used for associating and uploading the air conditioning scheme output by the neural network model and the air recognition result to the server.
The device provided by the embodiment has the same implementation principle and technical effect as the foregoing embodiment, and for the sake of brief description, reference may be made to the corresponding contents in the foregoing method embodiment for the portion of the embodiment of the device that is not mentioned.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present application, the meaning of "plurality" means at least two unless otherwise specified.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or intervening elements may also be present; when an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present, and further, as used herein, connected may include wirelessly connected; the term "and/or" is used to include any and all combinations of one or more of the associated listed items.
Any process or method descriptions in flow charts or otherwise described herein may be understood as: represents modules, segments or portions of code which include one or more executable instructions for implementing specific logical functions or steps of a process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. An air conditioning method, characterized by comprising:
performing gas molecule recognition on air in the current environment through gas detection equipment to obtain an air recognition result;
generating synthetic gas for regulating air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result;
releasing the generated synthesis gas into the current environment.
2. The method of claim 1, wherein the gas detection device comprises a multi-sensor array and a gas molecular dynamics detector; wherein the multi-sensor array comprises a plurality of sensors for detecting different types of gases.
3. The method of claim 1, wherein after obtaining the air identification result, the method further comprises:
judging whether the air identification result is stored in the established air database; the air database stores sample data corresponding to air composed of a plurality of different gas molecules; the air database is stored in a local and/or cloud server;
and if not, storing the air identification result as new sample data in the air database.
4. The method of claim 1, wherein the step of generating a synthetic gas for conditioning the air in the current environment using a machine learning technique and/or a big data technique based on the air recognition result comprises:
inquiring whether an air conditioning scheme corresponding to the air identification result exists in a server; the server stores corresponding relations between a plurality of pairs of air identification results and air conditioning schemes;
if so, generating synthesis gas for regulating the air in the current environment according to the inquired air regulation scheme;
and if not, inputting the air recognition result into a neural network model obtained by pre-training, and generating synthetic gas for regulating the air in the current environment based on an air regulation scheme output by the neural network model.
5. The method according to claim 4, wherein the air conditioning protocol records the target gas molecular species to be released in the gas storage unit and the corresponding release amount for each target gas molecular species to be released; different kinds of gas molecules have different corresponding smells;
the step of generating a synthesis gas for regulating air in the current environment according to the queried air-conditioning scheme includes:
releasing, by the gas storage unit, a target gas molecule based on the queried air-conditioning scheme;
and synthesizing the target gas molecules released by the gas storage unit through a gas generator to obtain the synthetic gas for regulating the air in the current environment.
6. The method of claim 4, further comprising:
and uploading the air conditioning scheme output by the neural network model and the air recognition result to the server in a correlation mode.
7. An air conditioning device characterized by comprising:
the gas identification module is used for identifying gas molecules of the air in the current environment through gas detection equipment to obtain an air identification result;
a gas synthesis module for generating a synthesis gas for conditioning the air in the current environment using a machine learning technique and/or a big data technique based on the air recognition result;
a gas release module for releasing the generated synthesis gas into the current environment.
8. An air conditioning system, comprising: the system comprises gas detection equipment, gas generation equipment and a fresh air system;
the gas detection equipment is used for carrying out gas molecule identification on the air in the current environment to obtain an air identification result;
the gas generation device is used for generating synthetic gas for adjusting the air in the current environment by adopting a machine learning technology and/or a big data technology based on the air identification result;
the fresh air system is used for releasing the generated synthesis gas to the current environment.
9. The air conditioning system of claim 8, wherein the gas detection device comprises a multi-sensor array and a gas molecular dynamics detector; wherein the multi-sensor array comprises a plurality of sensors for detecting different kinds of gases.
10. The air conditioning system according to claim 8, wherein the gas generation device includes an information processing unit, a gas storage unit, and a gas generator;
the information processing unit is used for obtaining an air conditioning scheme based on the air identification result;
the gas storage unit is used for releasing target gas molecules based on the air conditioning scheme;
the gas generator is used for synthesizing the target gas molecules released by the gas storage unit to obtain synthetic gas for regulating the air in the current environment.
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| CN202011288768.5A CN112413855B (en) | 2020-11-17 | 2020-11-17 | Air conditioning method, device and system |
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| CN202011288768.5A CN112413855B (en) | 2020-11-17 | 2020-11-17 | Air conditioning method, device and system |
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| CN112413855B CN112413855B (en) | 2022-03-18 |
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