CN109489223A - Data processing method, device and equipment and air conditioner - Google Patents
Data processing method, device and equipment and air conditioner Download PDFInfo
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- CN109489223A CN109489223A CN201811104256.1A CN201811104256A CN109489223A CN 109489223 A CN109489223 A CN 109489223A CN 201811104256 A CN201811104256 A CN 201811104256A CN 109489223 A CN109489223 A CN 109489223A
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- 238000003672 processing method Methods 0.000 title claims abstract description 22
- 238000000034 method Methods 0.000 claims abstract description 23
- 238000001514 detection method Methods 0.000 claims description 11
- 238000009827 uniform distribution Methods 0.000 claims description 8
- 238000004590 computer program Methods 0.000 claims description 7
- 238000001914 filtration Methods 0.000 claims description 7
- 238000010586 diagram Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 10
- 230000006870 function Effects 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
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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
- F24F11/89—Arrangement or mounting of control or safety devices
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
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- General Engineering & Computer Science (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The invention relates to a data processing method, a data processing device, equipment and an air conditioner, wherein the method comprises the following steps: acquiring current acquisition data of a point to be measured; detecting whether the current collected data is fluctuation data; if the current collected data is detected to be fluctuation data, processing the current collected data to obtain processed collected data; and uploading the processed collected data. By adopting the technical scheme of the invention, the reliability of the acquired data can be improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a data processing method, a data processing device, data processing equipment and an air conditioner.
Background
In the prior art, an acquisition module in the monitoring system acquires relevant data and uploads the data to a processor, and the processor processes the acquired data to complete monitoring.
However, because the acquisition module is interfered by external environmental factors, such as long-term exposure outdoors, temperature, humidity, electrical radiation, channel interference in the data transmission process, and the like, the acquired data of the acquisition module often does not conform to the actual data, so that the obtained result is inaccurate when the processor processes the data, and the reliability of the acquired data is reduced.
Disclosure of Invention
In view of this, the present invention aims to overcome the defects in the prior art, and provide a data processing method, an apparatus, a device and an air conditioner, so as to solve the problem in the prior art that the acquired data of the acquisition module does not match the actual data, so that the obtained result is not accurate when the processor performs data processing, and the reliability of the acquired data is reduced.
To achieve the above object, the present invention provides a data processing method, comprising:
acquiring current acquisition data of a point to be measured;
detecting whether the current collected data is fluctuation data;
if the current collected data is detected to be fluctuation data, processing the current collected data to obtain processed collected data;
and uploading the processed collected data.
The present invention also provides a data processing apparatus comprising:
the acquisition module is used for acquiring current acquisition data of the point to be measured;
the detection module is used for detecting whether the current collected data is fluctuation data;
the processing module is used for processing the current acquired data to obtain processed acquired data if the detection module detects that the current acquired data is fluctuating data;
and the uploading module is used for uploading the processed acquired data.
The invention also provides data processing equipment which is characterized by comprising a processor and a memory;
the processor is connected with the memory;
the memory is used for storing a computer program, and the computer program is at least used for storing the data processing method;
the processor is used for calling and executing the computer program.
The invention also provides an air conditioner, which comprises acquisition equipment and the data processing equipment;
the acquisition equipment is connected with the data processing equipment.
According to the data processing method, the data processing device, the data processing equipment and the air conditioner, the current acquisition data of the point to be measured is acquired; detecting whether the current collected data is fluctuation data; if the current collected data is detected to be fluctuation data, processing the current collected data to obtain processed collected data; the processed collected data are uploaded, so that the collected data received by the processor are consistent with the actual data, and the obtained result is more accurate when the data are processed. By adopting the technical scheme of the invention, the reliability of the acquired data can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention 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 invention, 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 of a first embodiment of a data processing method according to the present invention;
FIG. 2 is a schematic diagram of a predetermined data format;
FIG. 3 is a flowchart of a second embodiment of a data processing method according to the present invention;
FIG. 4 is a diagram illustrating a first exemplary embodiment of a data processing apparatus according to the present invention;
FIG. 5 is a diagram illustrating a second embodiment of a data processing apparatus according to the present invention;
FIG. 6 is a schematic diagram of a data processing apparatus according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an embodiment of an air conditioner according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
Fig. 1 is a flowchart of a first embodiment of a data processing method according to the present invention, and as shown in fig. 1, the data processing method of this embodiment may specifically include the following steps:
100. acquiring current acquisition data of a point to be measured;
in a specific implementation process, the current acquisition data of the point to be measured may be acquired by the acquisition module for the point to be measured, and after the acquisition module acquires the current acquisition data of the point to be measured, the current acquisition data of the point to be measured may be acquired, for example, after the current acquisition data of the point to be measured of the acquisition module is acquired, the current acquisition data may be uploaded according to a predetermined data format, so that the current acquisition data of the point to be measured may be acquired. Wherein,
fig. 2 is a schematic structural diagram of a predetermined data format, and as shown in fig. 2, the data format may include a data header 201, a data type 202, a start address 203, a data number 204, valid data 205, a check value 206, and the like, where the data number 204 is a number corresponding to the valid data 205.
101. Detecting whether the current collected data is fluctuation data;
in a specific implementation process, since the acquisition module is interfered by external environmental factors, such as long-term exposure outdoors, temperature, humidity, electrical radiation, channel interference in a data transmission process, and the like, which often causes the acquired data of the acquisition module to be inconsistent with actual data, in this embodiment, the acquired data inconsistent with the actual data may be defined as fluctuating data. For example, it may be detected whether the current collected data is consistent with the last collected data adjacent thereto; if the data are inconsistent, the currently acquired data are determined to be the fluctuation data, and if the data are consistent, the currently acquired data can be determined not to be the fluctuation data.
Specifically, analyzing the current acquired data to obtain a first starting address and a first data number of the current acquired data; analyzing the last acquired data to obtain a second initial address and a second data number of the last acquired data; determining whether a changed data segment exists by comparing the first initial address with the second initial address and comparing the first data number with the second data number; and if so, determining that the current acquired data is inconsistent with the last acquired data. And if the current collected data does not exist, determining that the current collected data is consistent with the last collected data.
102. If the current collected data is detected to be fluctuation data, processing the current collected data to obtain processed collected data;
in this embodiment, if it is detected that the currently-acquired data is the fluctuation data, it is indicated that the currently-acquired data does not match the actual data, and therefore, in order to ensure that the obtained result is relatively accurate when data processing is performed, in this embodiment, the currently-acquired data needs to be processed to obtain the processed acquired data, for example, a changed data segment may be updated to an effective data portion, that is, effective data in the last-time acquired data is updated to the changed data segment, so that the processed data is effective data.
103. And uploading the processed collected data.
After the processed collected data are obtained, the processed collected data can be uploaded, so that the processor can analyze, calculate and the like according to the processed collected data to obtain a more accurate result. For example, the processed collected data is preferably uploaded in a graphical form and sent to a client, such as a graph. The main body of the data processing method of this embodiment may be a data processing device, and the data processing device may be integrated by software, for example, the data processing device may be an application, and this application is not limited thereto.
In the data processing method of the embodiment, currently acquired data of a point to be measured is acquired; detecting whether the current collected data is fluctuation data; if the current collected data is detected to be fluctuation data, processing the current collected data to obtain processed collected data; the processed collected data are uploaded, so that the collected data received by the processor are consistent with the actual data, and the obtained result is more accurate when the data are processed. By adopting the technical scheme of the invention, the reliability of the acquired data can be improved.
Fig. 3 is a flowchart of a second embodiment of the data processing method of the present invention, and as shown in fig. 3, the data processing method of this embodiment further describes the technical solution of the present invention in more detail based on the embodiment shown in fig. 1. As shown in fig. 3, the data processing method of this embodiment may specifically include the following steps:
300. acquiring current acquisition data of a point to be measured;
301. detecting whether the current collected data is fluctuation data, if so, executing step 302, otherwise, executing step 306;
302. judging whether the fluctuation degree of the current acquired data reaches a preset degree, if so, executing step 303, and if not, executing step 304;
for example, if it is detected that the acquired data obtained each time changes, it may be determined that the current acquired data obeys uniform distribution, and at this time, an expected value and a variance value of the current acquired data may be further determined; detecting whether the expected value is matched with a preset expected value or not, and detecting whether the variance value is matched with a preset variance value or not; if the expected value is matched with the preset expected value and the variance value is matched with the preset variance value, determining that the fluctuation degree of the currently acquired data reaches the preset degree; and if the expectation is detected to be not matched with the preset expectation value and/or if the variance value is detected to be not matched with the preset variance value, determining that the fluctuation degree of the current acquired data does not reach the preset degree.
For example, if it is determined that the current collected data obeys uniform distribution, the corresponding probability density function is formula (1):
wherein, f (x) is probability density, and a and b are respectively the upper limit and the lower limit of the data to be collected.
The expected values and variance values corresponding to the probability density function under the characteristic uniform distribution can be obtained from formula (2) and formula (3), respectively:
wherein E (X) is an expected value under uniform distribution, D (X) is a variance value under uniform distribution, and E (X) and D (X) are fixed values.
Assuming that the acquisition data uploaded by the acquisition module has d1 and d2 … … di (1< i < n), the expected value and the variance value of the current acquisition data di at the current time can be obtained from formula (4) and formula (5), respectively:
where u is the mean value of the data di, i.e. the expected value, s2The variance value of di.
At a certain sampling time, E (X) and mu, and D (X) and s are uniformly distributed by comparing2Setting a desired threshold value X for correcting deviation data, wherein the variance threshold value is Y, and if and only if the deviation degree of E (X) and mu satisfies E (X) -X<μ<E (X) + X; and D (X) and s2The degree of deviation of (A) satisfies D (X) -Y<s2<D (x) + Y, it may be determined that the fluctuation range of di is small, i.e. the desired value matches the predetermined desired value, and that the variance value matches the predetermined variance value, it may be determined that the preset degree is not reached, step 204 is executed, otherwise, if only one of the conditions is not satisfied, it may be determined that the fluctuation range is large, i.e. the preset degree is reached, step 203 is executed.
303. Filtering the current collected data;
if the fluctuation degree of the current collected data is judged to reach the preset degree, the current collected data needs to be filtered so as to omit the current collected data, the uploaded collected data are guaranteed to be valid data, and the reliability of the collected data is improved.
304. Processing the current collected data to obtain processed collected data;
and if the fluctuation degree of the current acquired data is judged not to reach the preset degree, processing the current acquired data to obtain the processed acquired data.
The detailed process may refer to the related description of step 103 in the embodiment shown in fig. 1, and is not described herein again.
305. Uploading the processed collected data;
306. determining a timing duration between a first time corresponding to the currently acquired data and a second time corresponding to the last uploaded data;
in practical application, the storage module and the processor in the monitoring system have overlarge pressure because the acquisition module continuously acquires and reports the acquired data. Therefore, in order to relieve the stress on the storage module and the processor, in this embodiment, when the fluctuation data is not detected, the acquisition module may upload the acquisition data according to a specified time length, that is, according to a preset period, for example, the specified time length may be 20s, 30s, and the like. Therefore, if the current collected data is detected not to be the fluctuation data, the timing duration between the first time and the second time can be determined according to the first time corresponding to the current collected data and the second time corresponding to the last uploaded data.
307. Detecting whether the timing duration reaches a specified duration, if so, executing a step 308, otherwise, returning to the step 300;
after the timing duration between the first time corresponding to the currently acquired data and the second time corresponding to the last uploaded data is determined, whether the timing duration reaches a specified duration or not can be detected, if yes, step 308 is executed, and if not, the step 300 is returned.
308. And uploading the current collected data.
And if the timing duration between the first time corresponding to the current acquired data and the second time corresponding to the last uploaded data reaches the specified duration, uploading the current acquired data to reduce the uploaded data volume and reduce the number of redundant data in the database.
The following are exemplified: before the technical scheme of the invention is not adopted, the total number of database records in a single table is 16033 within 9 hours, and the average reporting rate is 2.024 seconds per database; after the technical scheme of the invention is adopted, the total number of the database records in the single table is 7704 in 12 hours, and the average reporting rate is increased to 5.619 seconds per table. The reduction of database redundancy records is 51.9%.
According to the data processing method, when the fluctuation data are detected, the data with the larger fluctuation degree are discarded, and the data with the smaller fluctuation degree are reserved, so that the uploaded collected data are consistent with the actual data, and the reliability of the collected data is improved. Meanwhile, when the fluctuation data is not detected, the acquired data is uploaded according to the specified duration, so that the data uploading amount is reduced, and the number of redundant data in the database is reduced.
Further, in the above embodiment, if it is determined that the degree of fluctuation reaches the preset degree, the current collected data may be sent to the user client. For example, the data can be sent to the client in a log or direct sending mode, or the current collected data can be converted into data in a chart mode; and sending the data in the form of the graph to a user client so that the user can analyze the reason of fluctuation of the acquired data according to the received data, or confirm whether errors exist in the detection result, and further perform corresponding operations, such as maintaining the acquisition module, replacing the acquisition module and the like. The chart can be a graph and/or a statistical table, etc.
Fig. 4 is a schematic structural diagram of a first data processing apparatus according to an embodiment of the present invention, and as shown in fig. 4, the data processing apparatus according to the embodiment includes an obtaining module 10, a detecting module 11, a processing module 12, and an uploading module 13:
the acquisition module 10 is used for acquiring current acquisition data of a point to be measured;
the detection module 11 is configured to detect whether currently acquired data is fluctuation data;
for example, the detecting module 11 is specifically configured to detect whether the current collected data is consistent with the last collected data adjacent to the current collected data; and if the current collected data are inconsistent, determining that the current collected data are fluctuating data. Specifically, analyzing the current acquired data to obtain a first starting address and a first data number of the current acquired data; analyzing the last acquired data to obtain a second initial address and a second data number of the last acquired data; determining whether a changed data segment exists by comparing the first initial address with the second initial address and comparing the first data number with the second data number; and if so, determining that the current acquired data is inconsistent with the last acquired data, and further determining that the current acquired data is fluctuation data.
The processing module 12 is configured to, if the detection module 11 detects that the currently acquired data is the fluctuation data, process the currently acquired data to obtain processed acquired data;
and the uploading module 13 is used for uploading the processed acquired data.
The data processing device of the embodiment acquires the current acquired data of the point to be measured; detecting whether the current collected data is fluctuation data; if the current collected data is detected to be fluctuation data, processing the current collected data to obtain processed collected data; the processed collected data are uploaded, so that the collected data received by the processor are consistent with the actual data, and the obtained result is more accurate when the data are processed. By adopting the technical scheme of the invention, the reliability of the acquired data can be improved.
Fig. 5 is a schematic structural diagram of a second data processing apparatus according to an embodiment of the present invention, and as shown in fig. 5, the data processing apparatus according to this embodiment may further include a determining module 14 and a filtering module 15 based on the embodiment shown in fig. 4.
The judging module 14 is configured to judge whether the fluctuation degree of the currently acquired data reaches a preset degree;
for example, the determining module 14 is specifically configured to:
if the current collected data are determined to be subjected to uniform distribution, determining an expected value and a variance value of the current collected data;
detecting whether the expected value is matched with a preset expected value or not, and detecting whether the variance value is matched with a preset variance value or not;
if the expected value is matched with the preset expected value and the variance value is matched with the preset variance value, determining that the fluctuation degree of the currently acquired data reaches the preset degree;
and if the expectation is detected to be not matched with the preset expectation value and/or if the variance value is detected to be not matched with the preset variance value, determining that the fluctuation degree of the current acquired data does not reach the preset degree.
The filtering module 15 is used for filtering the currently acquired data if the fluctuation degree reaches a preset degree;
the processing module 12 is specifically configured to, if the fluctuation degree does not reach the preset degree, process the current collected data to obtain processed collected data.
As shown in fig. 5, the data processing apparatus of this embodiment may further include a sending module 16, configured to send the currently acquired data to the user client if the fluctuation degree reaches a preset degree. For example, the currently acquired data may be converted into data in the form of a graph; and sending the data in the form of the graph to the user client.
In a specific implementation process, the detection module 11 is further configured to determine a timing duration between a first time corresponding to the currently acquired data and a second time corresponding to the last uploaded data if it is detected that the currently acquired data is not fluctuating data; detecting whether the timing time reaches a specified time; the uploading module 13 is further configured to upload the currently acquired data if the timing duration reaches a specified duration.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Fig. 6 is a schematic structural diagram of an embodiment of a data processing apparatus of the present invention, and as shown in fig. 6, a data processing apparatus 40 of the present embodiment includes a processor 20 and a memory 21;
the processor 20 is connected to the memory 21;
a memory 21 for storing a computer program for storing the data processing method of the above-described embodiment;
and a processor 20 for calling and executing the computer program.
Fig. 7 is a schematic structural diagram of an embodiment of the air conditioner of the present invention, and as shown in fig. 7, the air conditioner of the present embodiment includes a collecting device 30 and a data processing device 40 as in the above embodiment;
the acquisition device 30 is connected to a data processing device 40.
In this embodiment, the collecting device 30 is used for collecting relevant data of points to be measured in the air conditioner, such as operation data, fault data, and the like, and the data processing device 40 is used for executing the data processing method.
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 the terms "first," "second," and the like in the description of the present invention are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present invention, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention 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 present invention.
It should be understood that portions of the present invention 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 invention 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, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean 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 invention. 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 invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (15)
1. A data processing method, comprising:
acquiring current acquisition data of a point to be measured;
detecting whether the current collected data is fluctuation data;
if the current collected data is detected to be fluctuation data, processing the current collected data to obtain processed collected data;
and uploading the processed collected data.
2. The method of claim 1, wherein detecting whether the currently acquired data is fluctuating data comprises:
detecting whether the current collected data is consistent with the last collected data adjacent to the current collected data;
and if the current collected data are inconsistent, determining that the current collected data are fluctuating data.
3. The method of claim 2, wherein detecting whether the current collected data is consistent with the last collected data adjacent to the current collected data comprises:
analyzing the current collected data to obtain a first starting address and a first data number of the current collected data;
analyzing the last acquired data to obtain a second initial address and a second data number of the last acquired data;
determining whether a changed data segment exists by comparing the first starting address with the second starting address and comparing the first data number with the second data number;
and if so, determining that the current acquired data is inconsistent with the last acquired data.
4. The method of claim 1, wherein processing the current collected data further comprises, prior to obtaining processed collected data:
judging whether the fluctuation degree of the current acquired data reaches a preset degree or not;
if the fluctuation degree reaches a preset degree, filtering the currently acquired data;
processing the current collected data to obtain processed collected data, including:
and if the fluctuation degree does not reach the preset degree, processing the current collected data to obtain the processed collected data.
5. The method of claim 4, wherein determining whether the current data fluctuation degree reaches a preset degree comprises:
if the current collected data are determined to be subjected to uniform distribution, determining an expected value and a variance value of the current collected data;
detecting whether the expected value is matched with a preset expected value or not, and detecting whether the variance value is matched with a preset variance value or not;
if the expected value is detected to be matched with the preset expected value, and if the variance value is detected to be matched with the preset variance value, determining that the fluctuation degree of the current collected data reaches the preset degree;
and if the expectation is detected to be not matched with the preset expectation value, and/or if the variance value is detected to be not matched with the preset variance value, determining that the fluctuation degree of the current acquired data does not reach the preset degree.
6. The method of claim 4, further comprising:
and if the fluctuation degree reaches a preset degree, sending the current collected data to a user client.
7. The method of any one of claims 1-6, further comprising:
if the current collected data is detected not to be the fluctuation data, determining the timing duration between the first time corresponding to the current collected data and the second time corresponding to the last uploaded data;
detecting whether the timing duration reaches a specified duration or not;
and if the timing duration reaches the specified duration, uploading the current acquisition data.
8. A data processing apparatus, comprising:
the acquisition module is used for acquiring current acquisition data of the point to be measured;
the detection module is used for detecting whether the current collected data is fluctuation data;
the processing module is used for processing the current acquired data to obtain processed acquired data if the detection module detects that the current acquired data is fluctuating data;
and the uploading module is used for uploading the processed acquired data.
9. The apparatus according to claim 8, wherein the detection module is specifically configured to:
detecting whether the current collected data is consistent with the last collected data adjacent to the current collected data;
and if the current collected data are inconsistent, determining that the current collected data are fluctuating data.
10. The apparatus of claim 8, wherein the detection module further comprises:
the judging module is used for judging whether the fluctuation degree of the current acquired data reaches a preset degree or not;
the filtering module is used for filtering the currently acquired data if the fluctuation degree reaches a preset degree;
and the processing module is specifically used for processing the current acquired data to obtain the processed acquired data if the fluctuation degree does not reach the preset degree.
11. The apparatus of claim 10, wherein the determining module is specifically configured to:
if the current collected data are determined to be subjected to uniform distribution, determining an expected value and a variance value of the current collected data;
detecting whether the expected value is matched with a preset expected value or not, and detecting whether the variance value is matched with a preset variance value or not;
if the expected value is detected to be matched with the preset expected value, and if the variance value is detected to be matched with the preset variance value, determining that the fluctuation degree of the current collected data reaches the preset degree;
and if the expectation is detected to be not matched with the preset expectation value, and/or if the variance value is detected to be not matched with the preset variance value, determining that the fluctuation degree of the current acquired data does not reach the preset degree.
12. The apparatus of claim 10, further comprising:
and the sending module is used for sending the current acquired data to the user client side if the fluctuation degree reaches a preset degree.
13. The apparatus of any one of claims 8-12, wherein the detection module is further configured to:
if the current collected data is detected not to be the fluctuation data, determining the timing duration between the first time corresponding to the current collected data and the second time corresponding to the last uploaded data; detecting whether the timing duration reaches a specified duration or not;
the uploading module is further used for uploading the current acquisition data if the timing duration reaches a specified duration.
14. A data processing apparatus comprising a processor and a memory;
the processor is connected with the memory;
the memory for storing a computer program for storing at least the data processing method of any one of claims 1 to 7;
the processor is used for calling and executing the computer program.
15. An air conditioner characterized by comprising an acquisition device and a data processing device according to claim 15;
the acquisition equipment is connected with the data processing equipment.
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| CN201811104256.1A CN109489223A (en) | 2018-09-20 | 2018-09-20 | Data processing method, device and equipment and air conditioner |
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| CN201811104256.1A CN109489223A (en) | 2018-09-20 | 2018-09-20 | Data processing method, device and equipment and air conditioner |
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Cited By (2)
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