CN113435760B - 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 by each device when working in different working periods; calculating a scoring value of each device when executing a corresponding working mode under different working time periods based on the historical working log information; and (3) carrying out aggregation processing on the scoring values based on different working periods, and determining the optimal working mode of each device under the different working periods. The mode can infer the most common or favorite working modes of the equipment in each period based on the past use habits of the user, even if the user changes the working modes of the equipment in use under certain conditions, the working modes recorded by the system are still the most common or favorite working modes of the user after the working modes are processed, and 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 household system.
Background
Home appliance intellectualization is a great trend in the field of home appliances. Taking an air conditioner as an example, after the air conditioner is started, a user is often required to adjust to switch to a favorite mode of the user, and the interaction affects the experience of the user. In the prior art, a conventional method for setting a startup mode of an air conditioner generally records a mode used by a user last time, and when the user turns on the air conditioner again, the mode is automatically switched to the mode used by the user last time, namely, the mode setting of startup next time is performed by recording the mode used last time. However, if the air conditioner mode is adjusted under certain conditions, the mode of automatic use of the air conditioner when the user starts up next time is not the favorite mode of the user, and the user needs to adjust the air conditioner for a plurality of times when the user starts up again, so that the favorite mode of the user can be obtained.
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, which are used for at least solving 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 by each device when working in different working periods; calculating a scoring value of each device when executing a corresponding working mode in different working periods based on the historical working log information; and 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.
In an 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 period of the equipment to be detected based on the working time of the equipment to be detected; and acquiring the working mode of the equipment to be detected based on the determined working 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 periods includes: judging whether the equipment identification information in the historical work log information is the same or not based on the historical work log information, if the equipment identification information is the same, putting the historical work log information containing the same equipment identification information into a first information set, wherein the first information set is a plurality of, and the first information set corresponds to the equipment identification information one by one; judging whether time information contained in the historical work log information in the first information set is in the same working period or not based on the first information set, if so, placing the historical work log information containing the time information in the same working period in a second information set, wherein the second information set is a plurality of, and the second information set corresponds to the working period one by one; and scoring the plurality of working modes in the plurality of second information sets to obtain scoring values of the working modes of the equipment in a plurality of working time periods.
In an exemplary embodiment, the historical work log information further includes mode use date information and mode use time length information, and the method for calculating the score value of each device when executing the corresponding work mode in the different work periods includes: and scoring a plurality of working modes in a plurality of second information sets based on the mode using date information and the mode using time length information, and calculating scoring values of each device when executing corresponding working modes in different working periods.
In an exemplary embodiment, the method for aggregating the scoring values includes: and determining whether the grading value meets a preset condition, and if so, marking the working mode corresponding to the grading 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 a scoring value of each device when executing a corresponding working mode under 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 different working periods and determining the optimal working mode of each device under the different working periods.
In an exemplary embodiment, the processing device further includes: the device comprises a receiving module, a detecting module and a judging module, wherein the receiving module is used for receiving starting information of equipment to be detected, the starting information is generated when the equipment to be detected is started, and the starting information at least comprises working time of the equipment to be detected; the determining module is used for determining the current working period of the equipment to be detected based on the working time of the equipment to be detected; the acquisition module is used for acquiring the working mode of the equipment to be detected based on the determined working period, wherein the working mode is the optimal working mode of the equipment to be detected.
According to a further aspect of embodiments of the present invention, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described data processing method when run.
According to still another aspect of the embodiments of the present invention, there is further provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the data processing method described above through the computer program.
According to still another aspect of the embodiment of the present invention, there is further provided an intelligent home system, including an electronic device, where the electronic device is the above-mentioned electronic device.
In the embodiment of the invention, the evaluation value of the working mode executed by each device when working in different time periods is 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 evaluation value. By the processing mode, the working mode of the most-used or favorite equipment of the user in each period can be deduced based on the past use habit of the user, and compared with the prior art that only the last-used working mode information of the user is recorded, the optimal working mode recorded by the technical scheme of the method is more in line with the preference of the user, and even if the user changes the used equipment working mode under certain conditions, the most-used or favorite working mode of the user is still recorded by the system after the processing. The optimal working mode can be used as a selection recommendation for users, 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 embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on 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 invention;
FIG. 5 is a schematic diagram of a data calculation process 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 that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise 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 embodiments provided by the embodiments of the present application may be performed in a computer terminal, or a similar computing device. Taking a computer terminal as an example, fig. 1 is a block diagram of a hardware structure of a computer terminal according to 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 is shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data, and in one exemplary embodiment, may also include a transmission device 106 for communication functions and an input-output device 108. It will be appreciated by those skilled in the art that the configuration shown in fig. 1 is merely illustrative and is not intended to limit the configuration of the computer terminal described above. For example, a computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than the equivalent functions shown in FIG. 1 or more than the functions shown in FIG. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to a method for processing data in an embodiment of the present invention, and the processor 102 executes the computer program stored in the memory 104 to perform various functional applications and data processing, that is, to implement the above-mentioned method. 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 remotely located relative to the processor 102, which may be connected to the computer terminal via 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 means 106 is arranged to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, simply referred to as NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used to communicate with the internet wirelessly.
In this embodiment, a data processing method is provided and applied to the computer terminal, and fig. 2 is a flowchart of a data processing method according to an embodiment of the present invention, where the flowchart includes the following steps:
step S202, historical work log information of a plurality of devices is obtained, wherein the historical work log information at least comprises work modes executed when each device works in different work periods.
Step S204, calculating a scoring value of each device when executing corresponding working modes in different working periods based on the historical working log information.
And step S206, carrying out aggregation processing on the grading values based on the different working periods, and determining the optimal working mode of each device in the different working periods.
In the data processing method, firstly, the method can be used for data processing of a plurality of devices, when data are acquired, history work log information of the plurality of devices can be acquired, and the history work log information at least has work modes executed when each device works in different time periods and can be used for processing the plurality of devices based on the history work logs of the plurality of devices. It should be noted that, when the history log information is obtained, the history log information in a certain period of time may be selected. Taking air conditioning equipment as an example, when acquiring the historical work log information of a plurality of air conditioners, the historical work log information of the air conditioners within one month can be selectively acquired, and the historical work log information of the air conditioners within one week can also be acquired. The historical work log information at least comprises work modes executed when the air conditioner works in different time periods, the work modes can comprise temperature information, wind speed information, fan rotating speed information and wind direction information of the air conditioner during heating, temperature information, wind speed information, fan rotating speed information and wind direction information of the equipment during cooling and the like, the work periods of the air conditioner can be preset, for example, one work period can be set from 1 pm to 2 pm, one work period can also be set from 1 pm to 3 pm, and specific setting modes can be selected according to practical application equipment and scenes.
And calculating the grading value of each equipment for executing the corresponding working mode under different working time periods according to the acquired historical working log information, namely, each working mode has the grading value under different working time periods in each equipment, and the grading values obtained by the same working mode in different working time periods of different equipment are not necessarily the same. And (3) based on different working time periods, carrying out aggregation processing on the scoring values of the different time periods, and finally obtaining the optimal working mode of each device under the different working time periods. The aggregation processing modes are various and can be selected according to actual application scenes.
By adopting the data processing method, the evaluation value of the working mode executed by each device when working in different time periods is 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 evaluation value. By the processing mode, the working mode of the most-used or favorite equipment of the user in each period can be deduced based on the past use habit of the user, and compared with the prior art that only the last-used working mode information of the user is recorded, the optimal working mode recorded by the technical scheme of the method is more in line with the preference of the user, and even if the user changes the used equipment working mode under certain conditions, the most-used or favorite working mode of the user is still recorded by the system after the processing. The optimal working mode can be used as a selection recommendation for users, 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, the method further includes, as shown in fig. 3:
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 period of the equipment to be detected based on the working time of the equipment to be detected;
s306, acquiring the working mode of the equipment to be detected based on the determined working 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 detected, based on the start-up information, it is possible to determine the operation period in which the device is currently located and acquire the optimal operation mode of the device in this operation period. By adopting the method, after a certain device is started, a user can directly obtain the optimal working mode of the device in the current working period, so that the situation that the user needs to adjust the device for multiple times when restarting the device after adjusting the device mode under certain conditions is avoided, and the favorite working mode of the device can be obtained. The setting reduces the interaction between the user and the equipment and improves the experience of the user.
In an exemplary embodiment, the historical work log information includes device identification information and time information, and a method of calculating a score value for each of the devices when executing a corresponding work mode in the different work periods includes: judging whether the equipment identification information in the historical work log information is the same or not based on the historical work log information, if the equipment identification information is the same, putting the historical work log information containing the same equipment identification information into a first information set, wherein the first information set is a plurality of, and the first information set corresponds to the equipment identification information one by one; judging whether time information contained in the historical work log information in the first information set is in the same working period or not based on the first information set, if so, placing the historical work log information containing the time information in the same working period in a second information set, wherein the second information set is a plurality of, and the second information set corresponds to the working period one by one; and scoring the plurality of working modes in the plurality of second information sets to obtain scoring values of the working modes of the equipment in a plurality of working time periods.
Specifically, the device identification information may be a device ID or a machine code, where the device ID corresponds to each device one by one, and after the historical work log information is grouped according to the device ID, the historical work log information of the same device is in the same first information set, and 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 work log information in the first information set is grouped for the second time according to the time information, based on the divided work time periods, the historical work log information corresponding to the time information falling into the same work time period is in the same second information set, for example, the time period from 1 pm to 2 pm is divided, the historical work log information generated in fifteen pm and the historical work log information generated in three ten pm are in the same second information set, the division of the work time 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 work time periods. By adopting the processing mode, the historical work log information set of each device under each working period can be obtained, so that the optimal working mode of each device under each working period can be conveniently determined later.
In an exemplary embodiment, the historical work log information further includes mode use date information and mode use time length information, and the method for calculating the score value of each device when executing the corresponding work mode in the different work periods includes: and scoring a plurality of working modes in a plurality of second information sets based on the mode using date information and the mode using time length information, and calculating scoring values of each device when executing corresponding working modes in different working periods.
In other words, the pattern use time-length information and the pattern use date information are used to score the operation patterns performed by each device at different periods. In practical application, other information can be selected for scoring according to equipment parameters, and the scoring mode is adjusted according to scoring standards, parameters and the like. Taking an air conditioner as an example, when scoring based on pattern use time length information and pattern use date information, the following calculation formula may be used:
where k represents a difference between a current operation mode use date and a calculation date (i.e., date of data processing), N represents a maximum calculation date (freely definable), x represents a mode use period, and L represents a maximum time length defined when the history work log information is acquired (i.e., a difference between an earliest date and a 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 scoring values includes determining whether the scoring values meet a preset condition, and if so, marking the operation mode corresponding to the scoring values as an optimal operation mode of the device in the operation period.
That is, in the aggregation processing of the data, by determining whether the score value satisfies the preset condition, the operation mode corresponding to the score value satisfying the preset condition is determined to be the optimal operation mode of the device in the operation period, and alternatively, the operation mode corresponding to the highest score value may be set to be the optimal operation mode. In practical application, different judging conditions can be set according to different devices, different application scenes, environmental conditions and the like so as to obtain the most suitable optimal working mode.
According to the data processing mode, the optimal working mode of each device under different working time periods is obtained based on the history log information of each device, when a certain device is started, the working time 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 time 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 past use habit of the user, the user does not need to adjust when starting the device each time, the device starts the favorite working mode of the user, the problem that the user can obtain the favorite working mode only by adjusting the device for a plurality of times after the user changes the working mode under certain conditions in the prior art is avoided, the interaction between the user and the device is reduced, and the experience of the user is improved. Meanwhile, the data processing method can process a plurality of devices, so that the method can be used for setting a plurality of air conditioners and can also 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 description is provided with reference to an implementation method flow of the data processing in the alternative embodiment, but the implementation method flow is not limited to the technical solution of the embodiment of the present invention.
The embodiment provides an air conditioner startup operation-free optimal mode recall algorithm, fig. 4 is a flowchart of the algorithm of the embodiment, and a data processing process in the calculation process is shown in fig. 5. Specifically, the algorithm flow is as follows:
step one, preprocessing data. Selecting a user use log (namely the historical work 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 application.
Step two, mac grouping is carried out on the data in the step one;
mac corresponds to the equipment one by one, each equipment is provided with a unique Mac which is different from other equipment, and a plurality of Mac groups are obtained after all user use logs in the step one are grouped according to the Mac.
And step three, pattern segmentation. Segmenting the second step with a time interval (namely the working period);
that is, the log information in each mac packet formed after the second packet is processed needs to be segmented according to the time interval in which the log information in the same time interval is located in the same segment.
And step four, calculating a mode score. Based on the packet segmentation results of steps two and three, a score is calculated for each mode of operation in each mac packet for each time period, each score value representing the score of the device when executing that mode of operation for that time interval. Specifically, the current pattern score may be calculated based on the pattern use time period (i.e., the pattern use time period information described above), the pattern use actual date (i.e., the pattern use date information);
the calculation formula is as follows:
wherein k represents a difference value of the pattern use date distance calculation date, N represents a maximum calculation date, x represents a user use duration, and L represents a maximum time length defined in the step one. Alternatively, k is measured in days, N is measured in days, x is measured in minutes, and L is measured in minutes.
And fifthly, scoring and polymerizing. And (3) aggregating and sequencing 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 by the steps, the optimal working mode of each air conditioner in each time interval is obtained and stored in a database.
Fig. 6 is a schematic diagram of an operation-free system of an air conditioner with the algorithm, 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, the best mode (namely the best use mode) of the air conditioner is issued by big data.
The method for evaluating the optimal use mode by modeling the use duration and the use time period of the air-conditioning mode can enable the air-conditioning mode obtained by a user when the user starts up in different time periods to be the favorite mode of the user, and solves the problem that in the prior art, if the user performs air-conditioning mode adjustment under certain conditions, the startup mode obtained by the user when the user starts up next time still keeps the last use mode, so that the user needs to perform multiple adjustments to obtain the favorite mode of the user. By adopting the operation-free recall algorithm for the air conditioner startup, the user can obtain the favorite modes of the user in different periods, the user experience is improved, the market acceptance is increased, and the economic benefit is further improved.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the various embodiments of the present invention.
The embodiment of the invention also provides a data processing device, which comprises: the acquisition module is used for acquiring historical work log information of at least one device; the processing module is used for obtaining a grading value of each device when executing corresponding working modes under 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 under 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 acquisition module 72 that acquires historical work log information of a plurality of devices;
wherein the historical work log information at least comprises work modes executed by each device when working under different working periods.
A calculation module 74 that calculates a score value for each of the devices when executing a corresponding operation mode in the different operation periods based on the historical operation log information;
a determining module 76 aggregates the scoring values based on the different operating periods and determines an optimal operating mode for each of the devices during the different operating periods.
By the above means, after the obtaining module 72 obtains the historical operation log information of the plurality of devices, the calculating module 74 may calculate the score value of each of the devices when executing the corresponding operation mode in the different operation periods according to the historical operation log information, and based on the score value, the determining module 76 may determine the optimal operation mode of each of the devices in the different operation periods. Through the structure, the working mode of the most-used or favorite equipment of the user in each period can be deduced based on the past use habit of the user, and compared with the prior art that only the last-used working mode information of the user is recorded, the optimal working mode recorded by the technical scheme of the application is more accordant with the preference of the user, and even if the user changes the used equipment working mode under certain conditions, the most-used or favorite working mode of the user is still recorded by the system after processing. The optimal working mode can be used as a selection recommendation for users, and the user experience is improved.
In an exemplary embodiment, the processing device further includes: the device comprises a receiving module, a detecting module and a judging module, wherein the receiving module is used for receiving starting information of equipment to be detected, the starting information is generated when the equipment to be detected is started, and the starting information at least comprises working time of the equipment to be detected; the determining module is used for determining the current working period of the equipment to be detected based on the working time of the equipment to be detected; the acquisition module is used for acquiring the working mode of the equipment to be detected based on the determined working period, wherein the working mode is the optimal working mode of the equipment to be detected.
That is, the determining module may determine, by using the start information of the device to be detected received by the receiving module, a current working period of the device to be detected, and based on this 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 setting enables a user to directly obtain the optimal working mode of the equipment in the current working period after starting a certain equipment, avoids the situation that the favorite equipment working mode can be obtained only by adjusting the equipment for a plurality of times after the user starts the equipment again under certain conditions, reduces interaction between the user and the equipment, and improves experience of the user.
According to a further aspect of embodiments of the present invention, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described data processing method when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of:
s1, acquiring historical work log information of a plurality of devices;
s2, calculating a scoring value of each device when executing a corresponding working mode in different working periods based on the historical working log information;
and S3, carrying out aggregation processing on the grading values based on the different working periods, and determining an optimal working mode of each device in the different working periods.
An embodiment of the invention also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described 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 a scoring value of each device when executing a corresponding working mode in different working periods based on the historical working log information;
and S3, carrying out aggregation processing on the grading values based on the different working periods, and determining an optimal working mode of each device in the different working periods.
According to still another aspect of the embodiment of the present invention, there is further provided an intelligent home system, including an electronic device, where the electronic device is the electronic device 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 and a processor, the memory having stored therein a computer program arranged to run the computer program to perform the steps of any of the method embodiments described above.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A method of 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 by each device when working in different working periods;
calculating a scoring value of each device when executing a corresponding working mode in different working periods based on the historical working log information;
based on the different working periods, carrying out aggregation processing on the grading values, and determining an optimal working mode of each device in the different working periods;
the method for calculating the scoring value of each device when executing the corresponding working mode in different working time periods comprises the following steps:
judging whether the equipment identification information in the historical work log information is the same or not based on the historical work log information, if the equipment identification information is the same, putting the historical work log information containing the same equipment identification information into a first information set, wherein the first information set is a plurality of, and the first information set corresponds to the equipment identification information one by one;
judging whether time information contained in the historical work log information in the first information set is in the same working period or not based on the first information set, if so, placing the historical work log information containing the time information in the same working period in a second information set, wherein the second information set is a plurality of, and the second information set corresponds to the working period one by one;
scoring a plurality of the working modes in a plurality of the second information sets to obtain scoring values of the working modes of the equipment in a plurality of working time periods;
the method for calculating the scoring value of each device when executing the corresponding working mode in different working periods comprises the following steps:
and scoring a plurality of working modes in a plurality of second information sets based on the mode using date information and the mode using time length information, and calculating scoring values of each device when executing corresponding working modes in different working periods.
2. The method of processing data according to claim 1, wherein after determining an optimal operation mode for each of the devices at the different operation 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 period of the equipment to be detected based on the working time of the equipment to be detected;
and acquiring the working mode of the equipment to be detected based on the determined working period, wherein the working mode is the optimal working mode of the equipment to be detected.
3. The method for processing data according to claim 1, wherein the method for aggregating the scoring values comprises:
and determining whether the grading value meets a preset condition, and if so, marking the working mode corresponding to the grading value as the optimal working mode of the equipment in the working period.
4. A data processing apparatus, characterized in that the data processing apparatus comprises:
the acquisition module is used for acquiring historical work log information of at least one device;
the calculation module is used for calculating the grading value of each device when executing the corresponding working mode under different working time periods based on the historical working log information;
the determining module is used for carrying out aggregation processing on the scoring values based on the different working periods and determining an optimal working mode of each device in the different working periods;
the method for calculating the scoring value of each device when executing the corresponding working mode in different working time periods comprises the following steps:
judging whether the equipment identification information in the historical work log information is the same or not based on the historical work log information, if the equipment identification information is the same, putting the historical work log information containing the same equipment identification information into a first information set, wherein the first information set is a plurality of, and the first information set corresponds to the equipment identification information one by one;
judging whether time information contained in the historical work log information in the first information set is in the same working period or not based on the first information set, if so, placing the historical work log information containing the time information in the same working period in a second information set, wherein the second information set is a plurality of, and the second information set corresponds to the working period one by one;
scoring a plurality of the working modes in a plurality of the second information sets to obtain scoring values of the working modes of the equipment in a plurality of working time periods;
the method for calculating the scoring value of each device when executing the corresponding working mode in different working periods comprises the following steps:
and scoring a plurality of working modes in a plurality of second information sets based on the mode using date information and the mode using time length information, and calculating scoring values of each device when executing corresponding working modes in different working periods.
5. The processing device of claim 4, wherein the processing device further comprises:
the device comprises a receiving module, a detecting module and a judging module, wherein the receiving module is used for receiving starting information of equipment to be detected, the starting information is generated when the equipment to be detected is started, and the starting information at least comprises working time of the equipment to be detected;
the determining module is used for determining the current working period of the equipment to be detected based on the working time of the equipment to be detected;
the acquisition module is used for acquiring the working mode of the equipment to be detected based on the determined working period, wherein the working mode is the optimal working mode of the equipment to be detected.
6. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program when run performs the method of any of the preceding claims 1 to 3.
7. 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 according to any of the claims 1 to 3 by means of the computer program.
8. An intelligent home system comprising an electronic device, wherein the electronic device is the electronic device of claim 7.
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