CN111651495A - Air conditioner data processing method, device and system, computer equipment and storage medium - Google Patents
Air conditioner data processing method, device and system, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to an air conditioner data analysis method, device and system, computer equipment and a storage medium. The method comprises the following steps: acquiring collected air conditioner full life cycle data and corresponding internet of things card information; determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card; dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas; and analyzing the air conditioner data class to be analyzed corresponding to each climate area respectively. The method can improve the accuracy.
Description
Technical Field
The present application relates to the field of air conditioning technologies, and in particular, to an air conditioning data processing method, apparatus, system, computer device, and storage medium.
Background
With the development of the internet of things and big data technology, the air conditioner industry gradually starts to improve and research air conditioners by combining the idea of big data. Conventionally, in order to make the developed air conditioner more comfortable and closer to the daily life of people, the data basis for improving and developing the air conditioner is the result of analyzing the data generated by the behavior of the user using the air conditioner.
However, most of the existing data analysis methods are to uniformly analyze all the collected data, so that the difference of air conditioner using behaviors of nationwide users is ignored, and the accuracy is reduced.
Disclosure of Invention
In view of the above, it is necessary to provide an air conditioning data analysis method, apparatus, system, computer device, and storage medium capable of improving accuracy.
An air conditioner data analysis method, the method comprising:
acquiring collected air conditioner full life cycle data and corresponding internet of things card information;
determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card;
dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas;
and analyzing the air conditioner data class to be analyzed corresponding to each climate area respectively.
In one embodiment, the determining, according to the internet of things card information, a climate zone to which the full life cycle data of each air conditioner belongs includes:
accessing a positioning interface of an operator, and requesting corresponding geographical position information from the operator according to the Internet of things card information;
and determining the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information according to the geographical position information of the Internet of things card information returned by the operator.
In one embodiment, the determining, according to the geographical location information of the internet of things card information returned by the operator, a climate area of air conditioner full life cycle data corresponding to the internet of things card information includes:
determining the provincial and urban areas to which the Internet of things card information belongs according to the geographical position information;
and determining the climate area to which the provincial region belongs to obtain the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information.
In one embodiment, after the dividing the full life cycle data of each air conditioner according to the climate zones to obtain the air conditioner data classes to be analyzed corresponding to the climate zones, the method further includes:
determining air conditioner parameters influenced by climate;
and screening and deleting data corresponding to the air conditioner parameters from the air conditioner data class to be analyzed to obtain the final air conditioner data class to be analyzed.
In one embodiment, before analyzing the air-conditioning data classes to be analyzed corresponding to the respective climate zones, the method further includes:
acquiring mode parameters corresponding to all data in the air conditioner data class to be analyzed;
and carrying out mode classification on the data in the air conditioner data class to be analyzed according to the mode parameters to obtain the final air conditioner data class to be analyzed.
In one embodiment, the analyzing the air conditioner data classes to be analyzed corresponding to the climate areas respectively includes:
respectively preprocessing the data in each air conditioner data class to be analyzed;
aggregating and clustering the preprocessed data in each air conditioner data class to be analyzed;
and respectively carrying out data visualization on the aggregated and clustered air conditioner data classes to be analyzed.
An air conditioning data analysis apparatus, the apparatus comprising:
the acquisition module is used for acquiring the acquired air conditioner full life cycle data and the corresponding internet of things card information;
the determining module is used for determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card;
the dividing module is used for dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas;
and the analysis module is used for analyzing the air conditioner data to be analyzed corresponding to each climate area respectively.
An air conditioning data analysis system, the system comprising: the system comprises an air conditioner, a data acquisition device, a cloud server, a terminal and a data processing server;
the data acquisition device is arranged on the air conditioner and is used for acquiring the air conditioner full life cycle data of the air conditioner and acquiring corresponding Internet of things card information;
the cloud server is used for receiving the air conditioner full life cycle data uploaded by the data acquisition device and corresponding internet of things card information;
the data processing server is used for acquiring the air conditioner full life cycle data and corresponding internet of things card information from the cloud server; determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card; dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas; analyzing the air conditioner data class to be analyzed corresponding to each climate area respectively;
and the data processing server is also used for carrying out data visualization processing on the analyzed result and then sending the result to the terminal for displaying.
A computer device comprising a memory storing a computer program and a processor implementing the steps of any of the air conditioning data analysis methods described above when the processor executes the computer program.
A computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of any of the air conditioning data analysis methods described above.
According to the air conditioner data analysis method, the air conditioner data analysis device, the air conditioner data analysis system, the computer equipment and the storage medium, when the collected air conditioner full life cycle data is obtained, the corresponding Internet of things network card information is obtained, the climate areas to which the air conditioner life cycle data belong are determined according to the Internet of things network card information, then the air conditioner life cycle data are divided according to the climate areas, the air conditioner data classes to be analyzed corresponding to different climate areas can be obtained, and the air conditioner data classes to be analyzed corresponding to the climate areas are analyzed. According to the method, the air conditioner data generated by using the air conditioner behaviors of different users across the country are distinguished through the climate areas, and the difference of the air conditioner behaviors of the users caused by the influence of different weather zone environments is fully considered, so that the analysis accuracy is improved. And moreover, the habit of using the air conditioner by the user due to the regional difference can be determined according to the analysis result, and the research and development accuracy is improved for the follow-up research and development of the air conditioner for different regions.
Drawings
FIG. 1 is a diagram of an exemplary environment in which a method for analyzing air conditioning data is implemented;
FIG. 2 is a schematic flow chart illustrating a method for analyzing air conditioning data according to an embodiment;
FIG. 3 is a schematic flowchart illustrating a step of determining a climate zone to which full lifecycle data of each air conditioner belongs according to information of an Internet of things card in one embodiment;
FIG. 4 is a schematic illustration of the distribution of climate zones across the country in one embodiment;
FIG. 5 is a schematic diagram of an embodiment of an air conditioning data analysis system;
FIG. 6 is a block diagram showing the structure of an air conditioner data analysis device according to an embodiment;
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The air conditioner data analysis method provided by the application can be applied to the application environment shown in fig. 1. The application environment relates to an air conditioner 102, a data acquisition device 104 and a data processing server 106. The data acquisition device 104 is installed on the air conditioner 102, and acquires the air conditioner full life cycle data generated by the air conditioner by establishing communication with the air conditioner communication bus. And the data acquisition device is provided with an internet of things card. The data acquisition device 104 communicates with the data processing server 106 via a network.
Specifically, the data processing server 106 acquires the air conditioner full life cycle data acquired by the data acquisition device 104 and the corresponding internet of things card information; the data processing server 106 determines the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card; the data processing server 106 divides the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas; the data processing server 106 analyzes the air conditioner data classes to be analyzed corresponding to the climate areas respectively. The data processing server 106 may be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, an air conditioner data analysis method is provided, which is described by taking the method as an example applied to the data processing server 106 in fig. 1, and includes the following steps:
and step S202, acquiring the acquired air conditioner full life cycle data and corresponding Internet of things card information.
The air conditioner full life cycle data is air conditioner operation data acquired by the data acquisition devices arranged on the air conditioner internal unit and the air conditioner external unit through establishing communication with the air conditioner communication bus. The information of the internet of things card refers to an identification code ICCID (integrated circuit card identification code) of the internet of things card. The internet of things card is arranged on the data acquisition device and can be understood as an internet of things mobile phone card of an operator. The ICCID of the internet of things card may be understood as the SIM (Subscriber Identity Module) card number of the mobile phone card. The information of the Internet of things card uniquely corresponds to the acquired data of the full life cycle of the air conditioner.
Specifically, the data acquisition devices are installed on the air conditioners in advance, and one air conditioner is provided with one corresponding data acquisition device. And the data acquisition device arranged on the air conditioner establishes communication with the air conditioner communication bus so as to acquire data on the air conditioner bus. And the data on the air conditioner bus comprises air conditioner full life cycle data. And then, the data acquisition device transmits the acquired air conditioner full life cycle data and the information of the Internet of things card installed on the data acquisition device to the data processing server through the network. Therefore, the data processing server acquires the air conditioner full life cycle data acquired by the data acquisition device and the corresponding Internet of things card information.
In this embodiment, the data acquisition device is internally provided with a GPRS module, so that the data acquisition device preferentially establishes communication with the air conditioner through the GPRS module to acquire data. And preferentially establishing communication connection with the data processing server through the GPRS module to send the acquired data and the information of the Internet of things card.
And step S204, determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card.
Since the air conditioners to which the data acquisition devices are installed are distributed in regions across the country, the air conditioners are located in different climatic zones. Correspondingly, the climate zone to which the air conditioner full life cycle data generated by the air conditioner belongs is the climate of the climate zone in which the air conditioner is located.
Specifically, the internet of things card information is usually an important parameter for positioning of the operator. Therefore, after the data processing server acquires the air conditioner full life cycle data and the physical network card information corresponding to the air conditioner full life cycle data, the geographical position information of the Internet of things network card can be requested to be positioned from the operation line according to the information of the Internet of things network card, and the climate area where the Internet of things network card is located is determined according to the geographical position information. And because the geographical positions of the Internet of things card and the air conditioner are the same, the determined climate zone where the Internet of things card is located is the climate zone corresponding to the full life cycle data of the air conditioner.
And S206, dividing the full life cycle data of each air conditioner according to the climate areas to obtain the air conditioner data classes to be analyzed corresponding to the climate areas.
The air conditioner data to be analyzed is a data set obtained by dividing data according to climate areas, and the air conditioner full life cycle data included in the data set of one type all belong to the same climate area.
Specifically, after the data processing server determines the climate zone to which the full-life-cycle data of each air conditioner belongs, data classification is performed according to the climate zone to which the full-life-cycle data of the air conditioner belongs. And dividing the full life cycle data of the air conditioners belonging to the same climate area into a class, thereby obtaining a class of air conditioner data to be analyzed. The data in the air conditioner data class to be analyzed all belong to the same climate area. For example, it is assumed that the currently determined full-life cycle data of each air conditioner includes data a belonging to a severe cold region, data B belonging to a cold region, data C belonging to a mild region, data D belonging to a hot summer and cold winter region, and data E belonging to a cold region. Then, when the data A, B, C, D and E are classified according to the climate zones, the data can be classified into four main types of air conditioning data to be analyzed. And the air conditioner data classes to be analyzed in the severe cold areas respectively comprise data A. And the air conditioner data class to be analyzed in the cold region comprises data B and data E. And the air conditioner data class to be analyzed in the hot summer and cold winter areas comprises data D. And a class of mild zone air conditioner data to be analyzed, including data C.
And step S208, analyzing the air conditioner data classes to be analyzed corresponding to the climate areas respectively.
Specifically, after each air conditioner data class to be analyzed belonging to a certain climate zone is obtained, the data processing server analyzes each data class. For example, the data in the air-conditioning data class to be analyzed in the severe cold region is analyzed uniformly, and the data in the air-conditioning data class to be analyzed in the severe cold region is analyzed uniformly. So that the data belonging to one class can be analyzed uniformly, while the data of another class can be analyzed independently. The data analysis comprises data preprocessing, aggregation, clustering and other processing.
According to the air conditioner data analysis method, when the collected air conditioner full life cycle data is obtained, the corresponding Internet of things card information is obtained together, the climate areas to which the air conditioner life cycle data belong are determined according to the Internet of things card information, then the air conditioner life cycle data are divided according to the climate areas, the air conditioner data classes to be analyzed corresponding to different climate areas can be obtained, and then the air conditioner data classes to be analyzed corresponding to the climate areas are analyzed respectively. According to the method, the air conditioner data generated by using the air conditioner behaviors of different users across the country are distinguished through the climate areas, and the difference of the air conditioner behaviors of the users caused by the influence of different weather zone environments is fully considered, so that the analysis accuracy is improved. And moreover, the habit of using the air conditioner by the user due to the regional difference can be determined according to the analysis result, and the research and development accuracy is improved for the follow-up research and development of the air conditioner for different regions.
In one embodiment, as shown in fig. 3, step S204 includes:
step 302, accessing a positioning interface of an operator, and requesting corresponding geographical position information from the operator according to the internet of things card information.
Specifically, when the data processing server determines the climate zone where the air conditioner full life cycle data belongs according to the internet of things card, the operator can be accessed to open a positioning interface which is provided by the operator and takes the internet of things card ICCID as an interface parameter. And requesting the geographical position information of the Internet of things card from an operator corresponding to the Internet of things card through the positioning interface according to the ICCID of the Internet of things card.
And step 304, determining the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information according to the geographical position information of the Internet of things card information returned by the operator.
Specifically, the data processing server receives geographical location information returned by the operator according to the request, wherein the geographical location information generally includes the province to which the internet of things card belongs, latitude and longitude information and the like. And the data processing server acquires the provincial and urban areas to which the Internet of things card belongs from the geographical position information and determines the climate areas according to the provincial and urban areas.
In one embodiment, step S304 includes: determining a provincial and urban area to which the Internet of things card information belongs according to the geographical position information; and determining the climate area to which the provincial and urban areas belong to obtain the climate area of the air conditioner full life cycle data corresponding to the Internet of things information.
Specifically, since the climate regions to which the regions across the country belong are known, the climate regions to which the provincial regions belong can be determined according to the geographical locations of the provincial regions. And the climate area of the air conditioner full life cycle data corresponding to the internet of things card in the province and city is the climate area to which the province and city belong. As shown in fig. 4, a schematic diagram of the climate zones of provinces across the country is provided.
In this embodiment, the air conditioner is positioned by the internet of things card provided by the operator to determine the climate zone to which the corresponding air conditioner full life cycle data belongs, so that the accuracy of determining the climate zone can be improved.
In one embodiment, after step S206, the method further includes: determining air conditioner parameters influenced by climate; and screening and deleting data corresponding to the air conditioner parameters from the air conditioner data class to be analyzed to obtain the final air conditioner data class to be analyzed.
In particular, since the amount of data included in the air conditioner full life cycle data is enormous, and most of the data is not affected by the climate zone. Therefore, the data processing server acquires the preset climate-influenced air conditioning parameters. And screening the air conditioner data affected by the climate from the data class to be analyzed comprising the air conditioner full life cycle data according to the air conditioner parameters to obtain the updated data class of the air conditioner to be analyzed. The climate-influenced air conditioning parameters include, but are not limited to, the parameters shown in table 1 below.
TABLE 1 climate-influenced air-conditioning parameters
| Outdoor ambient temperature |
| Indoor ambient temperature |
| Set temperature |
| Difference between set temperature and indoor ambient temperature |
| Operating load |
| Length of use |
| Frequency of temperature point pause machine |
| Time length of stopping machine at temperature point |
For example, according to the climate-influenced air conditioning parameters shown in table 1, the data of each air conditioning parameter shown in table 1 is screened from the data in the air conditioning data class to be analyzed corresponding to the severe cold region, so as to form a new air conditioning data class to be analyzed in the severe cold region. Namely, the data included in the new air conditioner data class to be analyzed in the severe cold region are outdoor environment temperature data, indoor environment temperature data, set temperature and indoor environment temperature difference data, operation load data, use duration data, temperature point shutdown frequency data and temperature point shutdown duration data.
In this embodiment, data quantity of data to be analyzed can be reduced by screening data affected by climate, analysis resources are saved, and analysis efficiency is improved.
In one embodiment, before step S208, the method further includes: acquiring mode parameters corresponding to each data in the air conditioner data class to be analyzed; and carrying out mode classification on the data in the air conditioner data class to be analyzed according to the mode parameters to obtain the final air conditioner data class to be analyzed.
The mode parameter is used for identifying whether the data is generated in a cooling mode or a heating mode. That is, it can be determined whether the data generated by the air conditioner is generated in the cooling mode or the heating mode according to the mode parameter.
Specifically, the mode parameters are also operation data generated by the operation of the air conditioner and acquired by a data acquisition device installed on the air conditioner. When the data acquisition device is communicated with the air conditioner bus to acquire the operation data, not only the full life cycle data of the air conditioner can be acquired, but also the mode parameters corresponding to the full life cycle data of the air conditioner can be acquired. The air conditioner mode to which the air conditioner full life cycle data belongs can be determined through the mode parameters. Therefore, when the air conditioner full life cycle data is divided into the air conditioner data class to be analyzed, the data in the air conditioner data class to be analyzed can be subjected to mode classification according to the mode parameters through the mode parameters, and the air conditioner data class to be analyzed in the cooling mode and the air conditioner data class to be analyzed in the heating mode are obtained respectively. It can be understood that the air conditioner data class to be analyzed corresponding to each climate can obtain two new air conditioner data classes to be analyzed through mode classification. For example, the air conditioning data class to be analyzed in the cooling mode corresponding to the severe cold region and the air conditioning data class to be analyzed in the heating mode corresponding to the severe cold region.
In addition, it should be understood that after the air conditioner data class to be analyzed is subjected to mode classification according to the mode parameters, the number of classes is increased. When the subsequent analysis is carried out, the analysis is carried out according to the category. That is, the data of the cooling mode and the data of the heating mode in the same climate zone are not analyzed in a unified manner, but are analyzed separately. For example, the data in the air-conditioning data class to be analyzed in the cooling mode corresponding to the severe cold region is analyzed in a unified manner, and the data in the air-conditioning data class to be analyzed in the heating mode corresponding to the severe cold region is analyzed in a unified manner.
In the embodiment, the classification is further performed according to the air conditioner operation mode, and the difference of different modes used in different climate areas can be analyzed subsequently, so that the analysis accuracy is improved. Meanwhile, accurate research and development reference data can be provided for subsequent research and development of the air conditioner.
In one embodiment, step S208 includes: respectively preprocessing data in each air conditioner data class to be analyzed; respectively aggregating and clustering the preprocessed data in each air conditioner data class to be analyzed; and respectively carrying out data visualization on the aggregated and clustered air conditioner data classes to be analyzed.
Specifically, in order to ensure the quality of the data to be analyzed, the data in the air conditioner data class to be analyzed is preprocessed. The preprocessing includes, but is not limited to, data cleaning, data integration, data fusion, data transformation, and data reduction. Then, the preprocessed data in the air conditioner data class to be analyzed can be analyzed in a mode of aggregation, clustering and the like, and the analyzed data is subjected to data visualization processing through a software tool and visually displayed on a terminal. For example, the aggregated and clustered data is displayed on the terminal in a data visualization manner by using software tools such as excel, python, MATLAB and the like. And the terminal user determines the difference of the data in different climate areas through the analyzed data displayed by the terminal to obtain a relevant conclusion.
In addition, because the data in the air conditioner data class to be analyzed comprise different air conditioner parameters, different analysis processing can be carried out on different data in the class according to actual analysis requirements when the air conditioner data class to be analyzed is analyzed. For example, the outdoor environment temperature data, the indoor environment temperature data, and the like are compared to determine the distribution of the outdoor environment and the indoor environment of different climate areas, i.e., the indoor environment temperature data and the outdoor environment temperature data can be aggregated. The set temperature data and the like relate to specific temperature values, namely after normalization processing is carried out on the set temperature data, clustering statistics is carried out on the set temperature data by using a clustering algorithm (for example, a K value clustering algorithm), and the difference of the set temperature in different climate areas can be determined according to the result of the clustering statistics.
In one embodiment, the data processing server periodically displays the data in a mail mode according to set timing. For example, with months as a statistical time limit, the data processing server generates a month report mail for pushing the relevant data information analyzed by the air conditioning data to relevant air conditioning designers and developers every month. The research and development personnel can know the relevant information conveniently.
In one embodiment, as shown in FIG. 5, an air conditioning data analysis system is provided. Referring to fig. 5, the air conditioner data analysis system includes an air conditioner 102, a data acquisition device 104, a cloud server 105, a data processing server 106, and a terminal 107. The Data acquisition device 104 includes a GPRS module and a DTU (Data Transfer unit) module. The present embodiment describes the air conditioning data analysis method in detail according to the air conditioning data analysis system shown in fig. 5.
The method comprises the following steps: the data acquisition device 104 communicates with the bus of the air conditioner 102 through the GPRS module, and acquires the air conditioner full life cycle data of the air conditioner 102 by using the DTU module. And then, the collected full life cycle data of the air conditioner and the information of the internet of things card installed on the air conditioner are returned to the cloud server 105 of the big data center in real time through the GPRS module. The cloud server 105 transmits the received air conditioner full life cycle data and the corresponding internet of things card information to the data processing server 106 for processing the data.
Step two: and after the data processing server 106 receives the air conditioner full life cycle data and the corresponding internet of things card information, accessing a positioning interface of an operator. And acquiring the geographical position information of the air conditioner from an operator through internet of things card information (ICCID). And then, determining the climate area where the air conditioner is located through the provincial region in the geographical position information, so as to obtain the climate area where the corresponding air conditioner full life cycle data belongs.
Step three: the data processing server 106 divides all the air conditioner full life cycle data according to the climate zones to which the air conditioner full life cycle data belongs, divides the air conditioner full life cycle data belonging to the same climate zone into a class, and obtains the air conditioner data class to be analyzed corresponding to each climate zone.
Step four: and the data processing server 106 performs data screening and pattern classification on the air conditioner data classes to be analyzed corresponding to each climate area according to the air conditioner parameters influenced by the climate and the acquired pattern parameters to obtain the air conditioner data classes to be analyzed in different modes of different climate areas. And then, respectively carrying out analysis processing such as preprocessing, aggregation, clustering and the like on the air conditioner data classes to be analyzed in different modes in different climate areas.
Step five: the data processing server 106 performs data visualization processing on the analyzed data, and performs data visualization by using software tools such as excel, python, MATLAB and the like. The analyzed data is visually presented at the terminal 107. The user of the terminal 107 can directly obtain the obvious difference of using the air conditioner in different climate areas according to the displayed data.
It should be understood that although the various steps in the flow charts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
In one embodiment, as shown in fig. 6, there is provided an air conditioning data analyzing apparatus including: an obtaining module 602, a determining module 604, a dividing module 606, and an analyzing module 608, wherein:
the obtaining module 602 is configured to obtain the collected air conditioner full life cycle data and the corresponding internet of things card information.
And the determining module 604 is configured to determine, according to the information of the internet of things card, a climate area to which the full life cycle data of each air conditioner belongs.
And a dividing module 606, configured to divide the full life cycle data of each air conditioner according to the climate zones to obtain the air conditioner data classes to be analyzed corresponding to each climate zone.
The analysis module 608 is configured to analyze the air conditioner data classes to be analyzed corresponding to the respective climate areas.
In one embodiment, the determining module 604 is further configured to access a positioning interface of an operator, and request corresponding geographic location information from the operator according to the internet of things card information; and determining the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information according to the geographical position information of the Internet of things card information returned by the operator.
In one embodiment, the determining module 604 is further configured to determine, according to the geographic location information, a city area to which the internet of things card information belongs; and determining the climate area to which the provincial and urban areas belong to obtain the climate area of the air conditioner full life cycle data corresponding to the Internet of things information.
In one embodiment, the air conditioner data analysis device further comprises a screening module for determining air conditioner parameters affected by climate; and screening and deleting data corresponding to the air conditioner parameters from the air conditioner data class to be analyzed to obtain the final air conditioner data class to be analyzed.
In one embodiment, the dividing module 606 is further configured to obtain mode parameters corresponding to each data in the air conditioner data class to be analyzed; and carrying out mode classification on the data in the air conditioner data class to be analyzed according to the mode parameters to obtain the final air conditioner data class to be analyzed.
In one embodiment, the analysis module 608 is further configured to perform preprocessing on the data in each air conditioner data class to be analyzed; respectively aggregating and clustering the preprocessed data in each air conditioner data class to be analyzed; and respectively carrying out data visualization on the aggregated and clustered air conditioner data classes to be analyzed.
For specific limitations of the air conditioning data analysis device, reference may be made to the above limitations of the air conditioning data analysis method, which are not described herein again. All or part of each module in the air conditioner data analysis device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data generated by the operation of the air conditioner. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an air conditioning data analysis method.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring collected air conditioner full life cycle data and corresponding internet of things card information;
determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card;
dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas;
and analyzing the air conditioner data classes to be analyzed corresponding to the climate areas respectively.
In one embodiment, the processor, when executing the computer program, further performs the steps of: accessing a positioning interface of an operator, and requesting corresponding geographical position information from the operator according to the Internet of things card information; and determining the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information according to the geographical position information of the Internet of things card information returned by the operator.
In one embodiment, the processor, when executing the computer program, further performs the steps of: determining a provincial and urban area to which the Internet of things card information belongs according to the geographical position information; and determining the climate area to which the provincial and urban areas belong to obtain the climate area of the air conditioner full life cycle data corresponding to the Internet of things information.
In one embodiment, the processor, when executing the computer program, further performs the steps of: determining air conditioner parameters influenced by climate; and screening and deleting data corresponding to the air conditioner parameters from the air conditioner data class to be analyzed to obtain the final air conditioner data class to be analyzed.
In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring mode parameters corresponding to each data in the air conditioner data class to be analyzed; and carrying out mode classification on the data in the air conditioner data class to be analyzed according to the mode parameters to obtain the final air conditioner data class to be analyzed.
In one embodiment, the processor, when executing the computer program, further performs the steps of: respectively preprocessing data in each air conditioner data class to be analyzed; respectively aggregating and clustering the preprocessed data in each air conditioner data class to be analyzed; and respectively carrying out data visualization on the aggregated and clustered air conditioner data classes to be analyzed.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring collected air conditioner full life cycle data and corresponding internet of things card information;
determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card;
dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas;
and analyzing the air conditioner data classes to be analyzed corresponding to the climate areas respectively.
In one embodiment, the computer program when executed by the processor further performs the steps of: accessing a positioning interface of an operator, and requesting corresponding geographical position information from the operator according to the Internet of things card information; and determining the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information according to the geographical position information of the Internet of things card information returned by the operator.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining a provincial and urban area to which the Internet of things card information belongs according to the geographical position information; and determining the climate area to which the provincial and urban areas belong to obtain the climate area of the air conditioner full life cycle data corresponding to the Internet of things information.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining air conditioner parameters influenced by climate; and screening and deleting data corresponding to the air conditioner parameters from the air conditioner data class to be analyzed to obtain the final air conditioner data class to be analyzed.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring mode parameters corresponding to each data in the air conditioner data class to be analyzed; and carrying out mode classification on the data in the air conditioner data class to be analyzed according to the mode parameters to obtain the final air conditioner data class to be analyzed.
In one embodiment, the computer program when executed by the processor further performs the steps of: respectively preprocessing data in each air conditioner data class to be analyzed; respectively aggregating and clustering the preprocessed data in each air conditioner data class to be analyzed; and respectively carrying out data visualization on the aggregated and clustered air conditioner data classes to be analyzed.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. An air conditioner data analysis method is characterized by comprising the following steps:
acquiring collected air conditioner full life cycle data and corresponding internet of things card information;
determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card;
dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas;
and analyzing the air conditioner data class to be analyzed corresponding to each climate area respectively.
2. The method of claim 1, wherein the determining the climate zone to which the full life cycle data of each air conditioner belongs according to the internet of things card information comprises:
accessing a positioning interface of an operator, and requesting corresponding geographical position information from the operator according to the Internet of things card information;
and determining the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information according to the geographical position information of the Internet of things card information returned by the operator.
3. The method according to claim 2, wherein the determining the climate zone of the air conditioner full life cycle data corresponding to the internet of things card information according to the geographical location information of the internet of things card information returned by the operator comprises:
determining the provincial and urban areas to which the Internet of things card information belongs according to the geographical position information;
and determining the climate area to which the provincial region belongs to obtain the climate area of the air conditioner full life cycle data corresponding to the Internet of things card information.
4. The method of claim 1, wherein after the dividing of the full-life cycle data of each air conditioner according to the climate zones to obtain the air conditioner data classes to be analyzed corresponding to the climate zones, the method further comprises:
determining air conditioner parameters influenced by climate;
and screening and deleting data corresponding to the air conditioner parameters from the air conditioner data class to be analyzed to obtain the final air conditioner data class to be analyzed.
5. The method according to claim 1 or 4, wherein before analyzing the air-conditioning data to be analyzed corresponding to each of the climate zones, the method further comprises:
acquiring mode parameters corresponding to all data in the air conditioner data class to be analyzed;
and carrying out mode classification on the data in the air conditioner data class to be analyzed according to the mode parameters to obtain the final air conditioner data class to be analyzed.
6. The method according to claim 1, wherein the analyzing the air conditioner data to be analyzed corresponding to each climate zone comprises:
respectively preprocessing the data in each air conditioner data class to be analyzed;
aggregating and clustering the preprocessed data in each air conditioner data class to be analyzed;
and respectively carrying out data visualization on the aggregated and clustered air conditioner data classes to be analyzed.
7. An air conditioner data analysis apparatus, characterized in that the apparatus comprises:
the acquisition module is used for acquiring the acquired air conditioner full life cycle data and the corresponding internet of things card information;
the determining module is used for determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card;
the dividing module is used for dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas;
and the analysis module is used for analyzing the air conditioner data to be analyzed corresponding to each climate area respectively.
8. An air conditioning data analysis system, the system comprising: the system comprises an air conditioner, a data acquisition device, a cloud server, a terminal and a data processing server;
the data acquisition device is arranged on the air conditioner and is used for acquiring the air conditioner full life cycle data of the air conditioner and acquiring corresponding Internet of things card information;
the cloud server is used for receiving the air conditioner full life cycle data uploaded by the data acquisition device and corresponding internet of things card information;
the data processing server is used for acquiring the air conditioner full life cycle data and corresponding internet of things card information from the cloud server; determining the climate area to which the full life cycle data of each air conditioner belongs according to the information of the Internet of things card; dividing the full life cycle data of each air conditioner according to the climate areas to obtain the data classes of the air conditioners to be analyzed corresponding to the climate areas; analyzing the air conditioner data class to be analyzed corresponding to each climate area respectively;
and the data processing server is also used for carrying out data visualization processing on the analyzed result and then sending the result to the terminal for displaying.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113483452A (en) * | 2021-07-13 | 2021-10-08 | 珠海格力电器股份有限公司 | Weather parameter acquisition method and device based on electric appliance, storage medium and electric appliance |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19834275A1 (en) * | 1998-07-30 | 2000-02-24 | Rud Otto Meyer Gmbh & Co Kg | Method of controlling and regulating air conditioning systems made up of several individually adjustable units to achieve required room temperature and humidity combining optimal control and conventional regulation |
| CN107480457A (en) * | 2017-08-22 | 2017-12-15 | 广东美的制冷设备有限公司 | Information processing method and device |
| US20190268177A1 (en) * | 2018-02-26 | 2019-08-29 | Tri Cascade, Inc. | Wireless internet of things, climate control and smart home system |
-
2020
- 2020-04-13 CN CN202010283599.XA patent/CN111651495A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19834275A1 (en) * | 1998-07-30 | 2000-02-24 | Rud Otto Meyer Gmbh & Co Kg | Method of controlling and regulating air conditioning systems made up of several individually adjustable units to achieve required room temperature and humidity combining optimal control and conventional regulation |
| CN107480457A (en) * | 2017-08-22 | 2017-12-15 | 广东美的制冷设备有限公司 | Information processing method and device |
| US20190268177A1 (en) * | 2018-02-26 | 2019-08-29 | Tri Cascade, Inc. | Wireless internet of things, climate control and smart home system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113483452A (en) * | 2021-07-13 | 2021-10-08 | 珠海格力电器股份有限公司 | Weather parameter acquisition method and device based on electric appliance, storage medium and electric appliance |
| CN113483452B (en) * | 2021-07-13 | 2022-03-08 | 珠海格力电器股份有限公司 | Weather parameter acquisition method and device based on electric appliance, storage medium and electric appliance |
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