CN113435760A - Data processing method and device, storage medium, electronic device and intelligent home system - Google Patents
Data processing method and device, storage medium, electronic device and intelligent home system Download PDFInfo
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Abstract
The invention discloses a data processing method and device, a storage medium, an electronic device and an intelligent home system, wherein the data processing method comprises the following steps: acquiring historical work log information of a plurality of devices, wherein the historical work log information at least comprises work modes executed when each device works in different work periods; calculating the score value of each device when executing the corresponding working mode in different working periods based on the historical working log information; and aggregating the score values based on different working periods, and determining the optimal working mode of each device in different working periods. The mode can deduce the most common or favorite working mode of the user in each time period based on the past use habits of the user, and even if the user changes the working mode of the used device under certain conditions, the working mode recorded by the system is still the most common or favorite working mode of the user after processing, so that the user experience is improved.
Description
Technical Field
The invention relates to the field of household appliance control, in particular to a data processing method and device, a storage medium, an electronic device and an intelligent home system.
Background
The intellectualization of household appliances is a big trend in the field of household appliances at present. Taking the air conditioner as an example, the air conditioner often needs to be adjusted by the user to switch to a mode that the user likes after being started, and the experience of the user is influenced by the interaction. In the prior art, a conventional method for setting a start-up mode of an air conditioner generally records a mode used by a user last time, and automatically switches to the mode used by the user last time when the user turns on the air conditioner again, that is, sets a mode for starting up the air conditioner next time by recording the mode used last time. However, if the air-conditioning mode is adjusted under certain conditions, the mode of the air conditioner for automatic use when the user starts the air conditioner next time is not the mode preferred by the user, and the user needs to adjust the air conditioner for multiple times when the user starts the air conditioner again to obtain the preferred mode, so that the interaction of the user is increased, and the user experience is reduced.
Disclosure of Invention
The embodiment of the invention provides a data processing method and device, a storage medium, an electronic device and an intelligent home system, and aims to at least solve the problem of poor user experience in the related technology.
According to an embodiment of the present invention, there is provided a data processing method, including: acquiring historical work log information of a plurality of devices, wherein the historical work log information at least comprises work modes executed when each device works in different work periods; calculating the score value of each device when executing the corresponding working mode in the different working periods based on the historical working log information; and performing aggregation processing on the scoring values based on the different working periods, and determining the optimal working mode of each device in the different working periods.
In one exemplary embodiment, the method further comprises: receiving starting information of equipment to be detected, wherein the starting information is information generated when the equipment to be detected is started and at least comprises working time of the equipment to be detected; determining the current working time period of the device to be detected based on the working time of the device to be detected; and acquiring the working mode of the equipment to be detected based on the determined working time period, wherein the working mode is the optimal working mode of the equipment to be detected.
In an exemplary embodiment, the historical work log information includes device identification information and time information, and the method for calculating the score value of each device when executing the corresponding work mode in the different work period includes: judging whether the equipment identification information in the historical working log information is the same or not based on the historical working log information, if so, putting the historical working log information containing the same equipment identification information into a first information set, wherein the first information set is multiple and corresponds to the equipment identification information one by one; judging whether the time information contained in the historical working log information in the first information set is in the same working period or not based on the first information set, and if so, placing the historical working log information containing the time information in the same working period into a plurality of second information sets, wherein the second information sets are in one-to-one correspondence with the working periods; and scoring the plurality of working modes in the plurality of second information sets to obtain the scoring value of each working mode of the equipment in a plurality of working periods.
In an exemplary embodiment, the historical work log information further includes mode use date information and mode use duration information, and the method for calculating the score value of each device when executing the corresponding work mode in the different work period includes: and scoring the plurality of working modes in the plurality of second information sets based on the mode use date information and the mode use duration information, and calculating score values when each device executes the corresponding working mode in the different working periods.
In one exemplary embodiment, the method for aggregating the score values includes: and determining whether the score value meets a preset condition, and if so, marking the working mode corresponding to the score value as the optimal working mode of the equipment in the working period.
According to another embodiment of the present invention, there is also provided a data processing apparatus including: the acquisition module is used for acquiring historical work log information of at least one device; the calculation module is used for calculating the score value of each piece of equipment when executing the corresponding working mode in different working periods based on the historical working log information; and the determining module is used for carrying out aggregation processing on the scoring values based on different working periods and determining the optimal working mode of each device in the different working periods.
In one exemplary embodiment, the processing apparatus further includes: the device comprises a receiving module and a processing module, wherein the receiving module is used for receiving starting information of the device to be detected, the starting information is information generated when the device to be detected is started, and the starting information at least comprises working time of the device to be detected; the determining module is used for determining the current working time period of the device to be detected based on the working time of the device to be detected; and the acquisition module is used for acquiring the working mode of the equipment to be detected based on the determined working time period, wherein the working mode is the optimal working mode of the equipment to be detected.
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the above data processing method when running.
According to another aspect of the embodiments of the present invention, there is also provided an electronic apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the method for processing data through the computer program.
According to another aspect of the embodiment of the present invention, there is also provided an intelligent home system, including an electronic device, where the electronic device is the electronic device described above.
In the embodiment of the invention, the score values of the working modes executed when each device works in different periods are calculated by acquiring the historical working log information of each device, and the optimal working mode of each device in each working period is determined based on the score values. Through the processing mode, the working mode of the equipment which is most frequently used or most favored by the user at each time interval can be deduced based on the past use habits of the user, compared with the prior art that the information of the working mode which is used by the user last time is only recorded, the optimal working mode recorded by the technical scheme of the application is more in line with the preference of the user, and even if the working mode of the equipment which is used is changed by the user under certain conditions, the working mode which is most frequently used or most favored by the user is recorded by the system after processing. The optimal working mode can be recommended to the user as a choice, and the user experience is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware configuration of a computer terminal of a data processing method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of processing data according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a method of processing data according to an embodiment of the invention;
FIG. 4 is a flow chart of an algorithm for data according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a process of computing data according to an embodiment of the invention;
FIG. 6 is a schematic diagram of an air conditioner no-operation system according to an embodiment of the present invention;
fig. 7 is a block diagram of a data processing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The method provided by the embodiment of the application can be executed in a computer terminal, a computer terminal or a similar operation device. Taking the example of the present invention running on a computer terminal, fig. 1 is a block diagram of a hardware structure of a computer terminal of a data processing method according to an embodiment of the present invention. As shown in fig. 1, the computer terminal may include one or more (only one shown in fig. 1) processors 102 (the processors 102 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and in an exemplary embodiment, may also include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the computer terminal. For example, the computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration with equivalent functionality to that shown in FIG. 1 or with more functionality than that shown in FIG. 1.
The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the data processing method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the above-mentioned method. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to a computer terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In this embodiment, a data processing method is provided, which is applied to the computer terminal, and fig. 2 is a flowchart of the data processing method according to the embodiment of the present invention, where the flowchart includes the following steps:
step S202, obtaining historical work log information of a plurality of devices, wherein the historical work log information at least comprises work modes executed when each device works in different work periods.
Step S204, calculating the score value of each device when executing the corresponding working mode in the different working time periods based on the historical working log information.
Step S206, based on the different working periods, the score values are aggregated, and the optimal working mode of each device in the different working periods is determined.
In the data processing method, firstly, the application can be used for data processing of a plurality of devices, historical work log information of the plurality of devices can be obtained when the data is obtained, the historical work log information at least needs to have work modes executed when each device works at different time periods, and the plurality of devices can be processed based on the historical work logs of the plurality of devices. It should be noted that, when obtaining the historical log information, the historical work log information in a certain time period may be selected. Taking the air conditioner as an example, when historical work log information of a plurality of air conditioners is acquired, historical work log information of the air conditioners within one month can be selected to be acquired, and historical work log information of the air conditioners within one week can also be acquired. The historical working log information at least comprises working modes executed when the air conditioner works at different time periods, the working modes can comprise temperature information, wind speed information, fan rotating speed information and wind direction information of the air conditioner during heating and temperature information, wind speed information, fan rotating speed information and wind direction information of the equipment during refrigeration, wherein the working time period of the air conditioner can be preset, for example, the working time period can be set from 1 to 2 pm or from 1 to 3 pm, and the specific setting mode can be selected according to actual application equipment and scenes.
According to the acquired historical work log information, calculating the score values of the corresponding work modes executed by each device in different work periods, namely, in each device, each work mode has the score value in different work periods, and the score values obtained by the same work mode in different work periods of different devices are not necessarily the same. And aggregating the score values of different time periods based on different working time periods to finally obtain the optimal working mode of each device in different working time periods. The aggregation processing mode is various and can be selected according to the actual application scene.
By adopting the data processing method, the score values of the working modes executed when each device works at different time periods are calculated by acquiring the historical working log information of each device, and the optimal working mode of each device at each working time period is determined based on the score values. Through the processing mode, the working mode of the equipment which is most frequently used or most favored by the user at each time interval can be deduced based on the past use habits of the user, compared with the prior art that the information of the working mode which is used by the user last time is only recorded, the optimal working mode recorded by the technical scheme of the application is more in line with the preference of the user, and even if the working mode of the equipment which is used is changed by the user under certain conditions, the working mode which is most frequently used or most favored by the user is recorded by the system after processing. The optimal working mode can be recommended to the user as a choice, and the user experience is improved.
In an exemplary embodiment, after determining the optimal operation mode of each of the devices in the different operation periods, as shown in fig. 3, the method further comprises:
s302, receiving starting information of equipment to be detected, wherein the starting information is information generated when the equipment to be detected is started and at least comprises working time of the equipment to be detected;
s304, determining the current working time period of the device to be detected based on the working time of the device to be detected;
s306, acquiring the working mode of the equipment to be detected based on the determined working time period, wherein the working mode is the optimal working mode of the equipment to be detected.
That is, after receiving the start-up information of the device to be tested, based on the start-up information, it is possible to determine the current working period of the device and obtain the optimal working mode of the device in this working period. By adopting the method, after a user starts a certain device, the user can directly obtain the optimal working mode of the device in the current working period, and the condition that the user needs to adjust the device for many times to obtain the favorite working mode when the user starts the device again after adjusting the device mode under certain conditions is avoided. The setting reduces the interaction between the user and the equipment and improves the experience of the user.
In an exemplary embodiment, the historical working log information includes device identification information and time information, and the method for calculating the score value of each device when executing the corresponding working mode in the different working period comprises: judging whether the equipment identification information in the historical working log information is the same or not based on the historical working log information, if so, putting the historical working log information containing the same equipment identification information into a first information set, wherein the first information set is multiple and corresponds to the equipment identification information one by one; judging whether the time information contained in the historical working log information in the first information set is in the same working period or not based on the first information set, and if so, placing the historical working log information containing the time information in the same working period into a plurality of second information sets, wherein the second information sets are in one-to-one correspondence with the working periods; and scoring the plurality of working modes in the plurality of second information sets to obtain the scoring value of each working mode of the equipment in a plurality of working periods.
Specifically, the device identification information may be a device ID or a machine code, the device ID corresponds to each device one to one, and after the historical working log information is grouped according to the device ID, the historical working log information of the same device is in the same first information set, where the number of the first information sets is the same as the number of the device IDs, that is, the number of the devices. The historical working log information in the first information set is grouped for the second time according to the time information, based on the divided working periods, the historical working log information corresponding to the time information falling into the same working period is in the same second information set, for example, if the working period is divided into 1 pm to 2 pm, the historical working log information generated in fifteen minutes in the afternoon and the historical working log information generated in thirty minutes in the afternoon are in the same second information set, the division of the working periods can be modified according to actual application scenes and equipment, and the number of the second information sets is the same as that of the working periods. By adopting the processing mode, the historical working log information set of each device in each working period can be obtained, and the optimal working mode of each device in each working period can be conveniently determined in the follow-up process.
In an exemplary embodiment, the historical work log information further includes mode use date information and mode use duration information, and the method for calculating the score value of each device when executing the corresponding work mode in the different work period includes: and scoring the plurality of working modes in the plurality of second information sets based on the mode use date information and the mode use duration information, and calculating score values when each device executes the corresponding working mode in the different working periods.
In other words, the mode use duration information and the mode use date information are used to score the operation mode performed by each device at different periods. In practical application, other information can be selected according to equipment parameters for grading, and the grading mode is adjusted according to grading standards, parameters and the like. Taking an air conditioner as an example, when scoring is performed based on the mode use duration information and the mode use date information, the following calculation formula may be used:
where k denotes a difference between the current operation mode use date and the calculation date (i.e., the date of data processing), N denotes a maximum calculation date (freely definable), x denotes a mode use time period, and L denotes a maximum time length defined when the history work log information is acquired (i.e., a difference between the earliest date and the latest date in the acquired work log information). Alternatively, k is measured in days, N is measured in days, x is measured in minutes, and L is measured in minutes.
In an exemplary embodiment, the method for aggregating the score values includes determining whether the score values meet a preset condition, and if the score values meet the preset condition, marking the working mode corresponding to the score value as an optimal working mode of the device in the working period.
That is, during the aggregation processing of the data, the working mode corresponding to the score value meeting the preset condition is determined as the optimal working mode of the device in the working period by judging whether the score value meets the preset condition, and optionally, the working mode corresponding to the highest score value can be set as the optimal working mode. In practical application, different judgment conditions can be set according to different devices, different application scenes, environmental conditions and the like so as to obtain the most appropriate optimal working mode.
By the data processing mode, the optimal working mode of each device in different working periods is obtained based on the historical log information of each device, when a certain device is started, the working period of the device is determined according to the starting information generated by the device, and the working mode of the device is obtained, wherein the working mode is the optimal working mode of the device in the current working period. By adopting the data processing mode, the most common or favorite working mode of each device of the user can be obtained according to the previous use habits of the user, the user does not need to adjust when starting the device every time, the device starts the favorite working mode of the user, the problem that in the prior art, after the user changes the working mode under certain conditions, the user needs to adjust the device for multiple times to obtain the favorite working mode can be avoided when starting the device next time, the interaction between the user and the device is reduced, and the experience of the user is improved. Meanwhile, the data processing method can be used for processing a plurality of devices, and can be used for setting a plurality of air conditioners and also can be used for setting household appliances such as televisions, air purifiers and the like.
In order to better understand the process of the data processing method, the following describes a flow of an implementation method of the data processing with reference to an optional embodiment, but the flow is not limited to the technical solution of the embodiment of the present invention.
Fig. 4 is a flowchart of the algorithm of this embodiment, and a data processing procedure in a calculation process is shown in fig. 5. Specifically, the flow of the algorithm is as follows:
step one, preprocessing data. Selecting a user use log (namely the historical working log information) in a period of time as calculation data, and defining the period of time as L;
it should be noted that the time length L may be changed, and the value of L may be changed according to the device and the application scenario in practical applications.
Step two, performing mac grouping on the data in the step one;
and Mac corresponds to the equipment one by one, each equipment has unique Mac different from other equipment, and a plurality of Mac groups are obtained after all the user use logs in the step one are grouped according to the Mac.
And step three, segmenting the mode. Segmenting by time intervals (namely the working period) on the basis of the step two;
that is, the log information in each mac group formed after the grouping process needs to be segmented according to the time interval, and the log information in the same time interval is in the same segment.
And step four, calculating the mode score. And calculating scores for the working modes in each time period in each mac grouping based on the grouping segmentation results of the second step and the third step, wherein each score value represents the score of the equipment when the working mode is executed in the time interval. Specifically, the current pattern score may be calculated based on the pattern use period (i.e., the above-described pattern use period information), the pattern use actual date (i.e., the pattern use date information);
the calculation formula is as follows:
wherein k represents the difference between the mode use date and the calculation date, N represents the maximum calculation date, x represents the user use time length, and L represents the maximum time length defined in the first step. Alternatively, k is measured in days, N is measured in days, x is measured in minutes, and L is measured in minutes.
And step five, score aggregation. And performing aggregation sequencing on the behavior scores of the segments to obtain the optimal use mode (namely the optimal working mode) of the user in the current segment.
After the data are processed through the steps, the optimal working mode of each air conditioner in each time interval is obtained and stored in the database.
Fig. 6 is a schematic diagram of an air conditioner operation-free system with the above algorithm, and as shown in fig. 6, when a user starts a certain air conditioner, starting information is generated, a real-time environment state is reported, and according to the starting information and the real-time environment state, a best mode (i.e., a best usage mode) of the air conditioner is issued by big data.
The method for evaluating the optimal usage mode by modeling the usage duration and the usage time period of the air-conditioning mode provided in the embodiment can enable the air-conditioning mode obtained by the user when the user starts the machine in different time periods to be the mode favored by the user, and avoids the problem that in the prior art, if the user adjusts the air-conditioning mode under certain conditions, the start-up mode obtained by the next start-up still keeps the last usage mode, so that the user needs to adjust the air-conditioning mode for multiple times to obtain the mode favored by the user. By adopting the operation-free recall algorithm for air conditioner starting, a user can obtain the favorite mode of the user in different time periods when starting at different time periods, so that the user experience is improved, the market acceptance is increased, and the economic benefit is further improved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
An embodiment of the present invention further provides a data processing apparatus, where the data processing apparatus includes: the acquisition module is used for acquiring historical work log information of at least one device; the processing module is used for obtaining the score value of each device when executing the corresponding working mode in the different working time periods based on the historical working log information; and the determining module is used for carrying out aggregation processing on the scoring values based on the different working periods and determining the optimal working mode of each device in the different working periods.
Fig. 7 is a block diagram of a data processing apparatus according to an embodiment of the present invention; as shown in fig. 4, includes:
an obtaining module 72, which obtains historical work log information of a plurality of devices;
the historical work log information at least comprises work modes executed when each device works in different work periods.
A calculating module 74, configured to calculate, based on the historical work log information, a score value of each of the devices when executing the corresponding work mode in the different work time period;
and the determining module 76 is configured to aggregate the score values based on the different working periods, and determine an optimal working mode of each device in the different working periods.
With the above apparatus, after the obtaining module 72 obtains the historical working log information of the multiple devices, the calculating module 74 may calculate, according to the historical working log information, a score value of each device when executing the corresponding working mode in the different working time periods, and based on the score value, the determining module 76 may determine the optimal working mode of each device in the different working time periods. Through the structural arrangement, the working mode of the equipment which is most frequently used or most favored by the user at each time interval can be deduced based on the past use habits of the user, compared with the prior art that the information of the working mode which is used by the user last time is only recorded, the optimal working mode recorded by the technical scheme of the application is more in line with the preference of the user, and even if the working mode of the equipment which is used is changed by the user under certain conditions, the working mode which is most frequently used or most favored by the user is recorded by the system after processing. The optimal working mode can be recommended to the user as a choice, and the user experience is improved.
In one exemplary embodiment, the processing apparatus further includes: the device comprises a receiving module and a processing module, wherein the receiving module is used for receiving starting information of the device to be detected, the starting information is information generated when the device to be detected is started, and the starting information at least comprises working time of the device to be detected; the determining module is used for determining the current working time period of the device to be detected based on the working time of the device to be detected; and the acquisition module is used for acquiring the working mode of the equipment to be detected based on the determined working time period, wherein the working mode is the optimal working mode of the equipment to be detected.
That is to say, the determining module may determine the current working period of the device to be detected by receiving the starting information of the device to be detected received by the receiving module, and based on the working period, the obtaining module obtains the working mode of the device to be detected, that is, the optimal working mode of the device to be detected. The structure arrangement enables a user to directly obtain the optimal working mode of the equipment in the current working period after the user starts the equipment, avoids the condition that the user needs to adjust the equipment for many times after the user performs equipment mode adjustment under certain conditions, and can obtain the favorite equipment working mode only by starting the equipment again, reduces the interaction between the user and the equipment, and improves the experience of the user.
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the above data processing method when running.
Alternatively, in the present embodiment, the storage medium may be configured to store program codes for performing the following steps:
s1, acquiring historical work log information of a plurality of devices;
s2, calculating the score value of each device when executing the corresponding working mode in the different working time periods based on the historical working log information;
and S3, aggregating the score values based on the different working periods, and determining the optimal working mode of each device in the different working periods.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring historical work log information of a plurality of devices;
s2, calculating the score value of each device when executing the corresponding working mode in the different working time periods based on the historical working log information;
and S3, aggregating the score values based on the different working periods, and determining the optimal working mode of each device in the different working periods.
According to another aspect of the embodiment of the present invention, there is also provided an intelligent home system, including an electronic device, where the electronic device is described above. For example, the smart home system may comprise an air conditioning system comprising an air conditioner provided with an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for processing data, comprising:
acquiring historical work log information of a plurality of devices, wherein the historical work log information at least comprises work modes executed when each device works in different work periods;
calculating the score value of each device when executing the corresponding working mode in the different working periods based on the historical working log information;
and performing aggregation processing on the scoring values based on the different working periods, and determining the optimal working mode of each device in the different working periods.
2. The method of processing data according to claim 1, wherein after determining the optimal operating mode of each of the devices during the different operating periods, the method further comprises:
receiving starting information of equipment to be detected, wherein the starting information is information generated when the equipment to be detected is started and at least comprises working time of the equipment to be detected;
determining the current working time period of the device to be detected based on the working time of the device to be detected;
and acquiring the working mode of the equipment to be detected based on the determined working time period, wherein the working mode is the optimal working mode of the equipment to be detected.
3. The data processing method according to claim 1, wherein the historical work log information includes device identification information and time information, and the method of calculating the score value of each device when executing the corresponding work mode in the different work period comprises:
judging whether the equipment identification information in the historical working log information is the same or not based on the historical working log information, if so, putting the historical working log information containing the same equipment identification information into a first information set, wherein the first information set is multiple and corresponds to the equipment identification information one by one;
judging whether the time information contained in the historical working log information in the first information set is in the same working period or not based on the first information set, and if so, placing the historical working log information containing the time information in the same working period into a plurality of second information sets, wherein the second information sets are in one-to-one correspondence with the working periods;
and scoring the plurality of working modes in the plurality of second information sets to obtain the scoring value of each working mode of the equipment in a plurality of working periods.
4. The method according to claim 3, wherein the historical working log information further includes pattern use date information and pattern use time length information, and the method for calculating the score value when each of the devices executes the corresponding working pattern in the different working period comprises:
and scoring the plurality of working modes in the plurality of second information sets based on the mode use date information and the mode use duration information, and calculating score values when each device executes the corresponding working mode in the different working periods.
5. The method for processing data according to claim 4, wherein the method for aggregating the score values comprises:
and determining whether the score value meets a preset condition, and if so, marking the working mode corresponding to the score value as the optimal working mode of the equipment in the working period.
6. An apparatus for processing data, the apparatus comprising:
the acquisition module is used for acquiring historical work log information of at least one device;
the calculation module is used for calculating the score value of each device when executing the corresponding working mode in different working periods based on the historical working log information;
and the determining module is used for carrying out aggregation processing on the scoring values based on the different working periods and determining the optimal working mode of each device in the different working periods.
7. The processing apparatus according to claim 6, characterized in that the processing apparatus further comprises:
the device comprises a receiving module and a processing module, wherein the receiving module is used for receiving starting information of the device to be detected, the starting information is information generated when the device to be detected is started, and the starting information at least comprises working time of the device to be detected;
the determining module is used for determining the current working time period of the device to be detected based on the working time of the device to be detected;
and the acquisition module is used for acquiring the working mode of the equipment to be detected based on the determined working time period, wherein the working mode is the optimal working mode of the equipment to be detected.
8. A computer-readable storage medium, comprising a stored program, wherein the program is operable to perform the method of any one of claims 1 to 5.
9. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 5 by means of the computer program.
10. An intelligent home system comprising an electronic device, wherein the electronic device is the electronic device according to claim 9.
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