CN113435760B - Data processing method and device, storage medium, electronic device and smart home system - Google Patents

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

Data processing method and device, storage medium, electronic device and smart home system

technical field

The present invention relates to the field of home appliance control, in particular to a data processing method and device, a storage medium, an electronic device and a smart home system.

Background technique

The intelligence of home appliances is already a major trend in the field of home appliances. Take the air conditioner as an example. After the air conditioner is turned on, the user often needs to adjust it to switch to the user's favorite mode. Such interaction affects the user's experience. In the prior art, the conventional method for setting the start-up mode of the air conditioner is generally to record the mode used by the user last time, and automatically switch to the mode used by the user last time when the user turns on the air conditioner again, that is, by recording the mode used last time, the mode setting for the next start-up is performed. However, this setting will cause the user to adjust the air conditioner mode under certain conditions, and the next time the air conditioner is turned on, the mode automatically used by the user will not be the mode that the user likes.

Contents of the invention

Embodiments of the present invention provide a data processing method and device, a storage medium, an electronic device, and a smart home system, so as to at least solve the problem of poor user experience in related technologies.

According to an embodiment of the present invention, a data processing method is provided, comprising: obtaining historical work log information of multiple devices, wherein the historical work log information includes at least the work mode executed by each device when working in different working hours; based on the historical work log information, calculating the scoring value of each of the devices when executing the corresponding working mode in the different working hours;

In an exemplary embodiment, the method further includes: receiving startup information of the device to be detected, wherein the startup information is information generated when the device to be detected is started, and at least includes working hours of the device to be detected; determining a current working period of the device to be detected based on the working time of the device 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 of the devices when executing the corresponding work mode in the different working hours includes: based on the historical work log information, judging whether the device identification information in the historical work log information is the same, and if the device identification information is the same, putting the historical work log information containing the same device identification information into a first information set. There are multiple first information sets, and the first information set corresponds to the device identification information one by one; Whether the time information contained in the historical work log information in the information set is in the same working period, and if it is in the same working period, then place the historical work log information including time information in the same working period in the second information set, the second information set is multiple, and the second information set corresponds to the working period one by one; score the multiple working modes in the multiple second information sets, and obtain the score value of each working mode of the device in multiple 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 of the devices when executing the corresponding work mode in the different work periods includes: based on the mode use date information and the mode use duration information, scoring a plurality of the work modes in the plurality of second information sets, and calculating the score value of each of the devices when executing the corresponding work mode in the different work periods.

In an exemplary embodiment, the method for aggregating the scoring values includes: determining whether the scoring values satisfy a preset condition, and if the preset conditions are met, marking the working mode corresponding to the scoring value as the optimal working mode of the device within the working period.

According to another embodiment of the embodiment of the present invention, there is also provided a data processing apparatus, including: an acquisition module, configured to acquire historical work log information of at least one device; a calculation module, configured to calculate, based on the historical work log information, the scoring value of each of the devices when executing a corresponding working mode in the different working hours; a determining module, configured to aggregate the scoring values based on different working hours, and determine the optimal working mode of each of the devices in the different working hours.

In an exemplary embodiment, the processing device further includes: a receiving module configured to receive startup information of the device to be detected, wherein the startup information is information generated when the device to be detected is started, and at least includes working hours of the device to be detected; a determining module is configured to determine a current working period of the device to be detected based on the working time of the device to be detected; an obtaining module is configured to acquire a working mode of the device to be detected based on the determined working period, wherein the working mode is the optimal working mode of the device to be detected.

According to yet 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 yet another aspect of the embodiments of the present invention, an electronic device is also provided, including a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein the processor executes the above data processing method through the computer program.

According to yet another aspect of the embodiments of the present invention, there is also provided a smart home system, including an electronic device, where the electronic device is the above-mentioned electronic device.

In the embodiment of the present invention, by obtaining the historical work log information of each device, the score value of the work mode executed by each device at different time periods is calculated, and based on the score value, the optimal work mode of each device in each work period is determined. Through this processing method, based on the user's past usage habits, the user's most frequently used or favorite device working mode at each time period can be inferred. Compared with the prior art that only records the user's last used working mode information, the optimal working mode recorded by the technical solution of the present application is more in line with the user's preferences. Even if the user changes the used device working mode under certain conditions, after processing, the system records the user's most commonly used or favorite working mode. The optimal working mode can be recommended to users as an option to increase user experience.

Description of drawings

The accompanying drawings described here are used to provide a further understanding of the present invention and constitute a part of the application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations to the present invention. In the attached picture:

Fig. 1 is the hardware structural block diagram of the computer terminal of a kind of data processing method of the embodiment of the present invention;

Fig. 2 is a flowchart of a data processing method according to an embodiment of the present invention;

3 is a schematic diagram of a data processing method according to an embodiment of the present invention;

Fig. 4 is a flow chart of a data algorithm according to an embodiment of the present invention;

Fig. 5 is a schematic diagram of a calculation process of data according to an embodiment of the present invention;

6 is a schematic diagram of an air conditioner free operating system according to an embodiment of the present invention;

Fig. 7 is a structural block diagram of a data processing device according to an embodiment of the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having", and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or elements is not necessarily limited to those steps or elements explicitly listed, but may include other steps or elements not expressly listed or inherent to the process, method, product or device.

The method embodiments provided in the embodiments of the present application may be executed in a computer terminal, a computer terminal, or a similar computing device. Taking running on 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 Figure 1, the computer terminal can include one or more (only one is shown in Figure 1) processors 102 (processor 102 can include but not limited to microprocessor MCU or programmable logic device FPGA etc. processing device) and memory 104 for storing data, in an exemplary embodiment, above-mentioned computer terminal can also include the transmission device 106 and input-output device 108 for communication function. Those skilled in the art can understand that the structure shown in FIG. 1 is only for illustration, and it does not limit the structure of the above computer terminal. For example, the computer terminal may also include more or less components than those shown in FIG. 1 , or have a different configuration with functions equivalent to those shown in FIG. 1 or more functions than those shown in FIG. 1 .

The memory 104 can 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, that is, realizes 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 a memory that is remotely located relative to the processor 102, and these remote memories may be connected to a computer terminal through a network. Examples of the aforementioned 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 to receive or transmit data via a network. The specific example of the above-mentioned network may include a wireless network provided by the communication provider of the computer terminal. In one example, the transmission device 106 includes a network interface controller (NIC for short), 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 (Radio Frequency, RF for short) module, which is used to communicate with the Internet in a wireless manner.

This embodiment provides a data processing method, which is applied to the above-mentioned computer terminal. FIG. 2 is a flowchart of a data processing method according to an embodiment of the present invention. The process includes the following steps:

Step S202, acquiring historical work log information of multiple devices, wherein the historical work log information at least includes the working modes executed by each device when working in different working periods.

Step S204, based on the historical work log information, calculating the score value of each of the devices when executing the corresponding work mode in the different work periods.

Step S206, based on the different working periods, aggregate the scoring values to determine the optimal working mode of each of the devices under the different working periods.

In the above-mentioned data processing method, firstly, this application can be used for data processing of multiple devices. When acquiring data, the historical work log information of multiple devices can be obtained. In the historical work log information, at least there should be the working mode executed by each device when working in different time periods. Based on the historical work logs of multiple devices, multiple devices can be processed. It should be noted that, when obtaining historical log information, historical work log information within a certain period of time may be selected. Taking the air conditioner as an example, when obtaining the historical work log information of multiple air conditioners, you can choose to obtain the historical work log information of the air conditioners within one month, or obtain the historical work log information of the air conditioners within one week. The historical work log information should at least include the working mode of the air conditioner when it works in different time periods. The working mode can include the temperature information, wind speed information, fan speed information, and wind direction information of the air conditioner during heating, and the temperature information, wind speed information, fan speed information, and wind direction information of the equipment during cooling. Among them, the working period of the air conditioner can be preset.

According to the obtained historical work log information, calculate the scoring value of each device executing the corresponding working mode in different working hours, that is to say, in each device, each working mode has a scoring value in different working hours, and the scoring values obtained by the same working mode in different working hours of different devices are not necessarily the same. Based on different working periods, the scoring values of different periods are aggregated, and finally the optimal working mode of each device under different working periods is obtained. There are multiple aggregation processing methods, which can be selected according to actual application scenarios.

Using the above data processing method, by obtaining the historical work log information of each device, calculate the score value of the work mode executed by each device when it works at different time periods, and determine the optimal work mode of each device in each work period based on the score value. Through this processing method, based on the user's past usage habits, the user's most frequently used or favorite device working mode at each time period can be inferred. Compared with the prior art that only records the user's last used working mode information, the optimal working mode recorded by the technical solution of the present application is more in line with the user's preferences. Even if the user changes the used device working mode under certain conditions, after processing, the system records the user's most commonly used or favorite working mode. The optimal working mode can be recommended to users as an option to increase user experience.

In an exemplary embodiment, after determining the optimal working mode of each of the devices under the different working periods, as shown in FIG. 3 , the method further includes:

S302. Receive startup information of the device to be detected, wherein the startup information is information generated when the device to be detected is started, and at least includes working hours of the device to be detected;

S304. Based on the working time of the device to be detected, determine the current working period of the device to be detected;

S306. Acquire a working mode of the device to be detected based on the determined working period, where the working mode is the optimal working mode of the device to be detected.

That is to say, after receiving the activation information of the device to be detected, based on the activation information, the current working period of the device can be determined and the optimal working mode of the device in this working period can be obtained. By adopting the above method, after turning on a certain device, the user can directly obtain the optimal working mode of the device in the current working period, which avoids that if the user adjusts the device mode under certain conditions, the device needs to be adjusted multiple times when the device is turned on again in order to obtain the preferred working mode of the device. This setting reduces the interaction between the user and the device and improves the user experience.

In an exemplary embodiment, the historical work log information includes device identification information and time information, and the method for calculating the scoring value of each of the devices when executing the corresponding working mode in the different working hours includes: based on the historical work log information, judging whether the device identification information in the historical work log information is the same, and if the device identification information is the same, putting the historical work log information containing the same device identification information into a first information set. There are multiple first information sets, and the first information set corresponds to the device identification information one by one; Whether the time information contained in the historical work log information in the first information set is in the same working period, and if it is in the same working period, then place the historical work log information including time information in the same working period in the second information set, the second information set is multiple, and the second information set corresponds to the working period one by one; score the multiple working modes in the multiple second information sets, and obtain the score value of each working mode of the device in multiple working periods.

Specifically, the device identification information may be a device ID or a machine code, and the device ID corresponds to each device one by one. 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 set is the same as the number of device IDs, that is, the number of devices. According to the time information, the historical work log information in the first information set is grouped for the second time. Based on the divided working periods, the historical work log information corresponding to the time information falling into the same working period is in the same second information set. For example, if a working period is divided from 1:00 pm to 2:00 pm, then the historical work log information generated at 1:15 pm and the historical work log information generated at 1:30 pm are in the same second information set. The division of working periods can be modified according to actual application scenarios and equipment. Using the above-mentioned processing method, the historical work log information set of each device in each working period can be obtained, which is convenient for subsequent determination of the optimal working mode of each device in each working period.

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 of the devices when executing the corresponding work mode in the different work periods includes: based on the mode use date information and the mode use duration information, scoring a plurality of the work modes in the plurality of second information sets, and calculating the score value of each of the devices when executing the corresponding work mode in the different work periods.

In other words, the mode use duration information and the mode use date information are used to score the work mode performed by each device at different time periods. In actual application, other information can be selected for scoring according to the device parameters, and the scoring method can be adjusted according to the scoring standards and parameters. Taking an air conditioner as an example, the following formula can be used when scoring based on the mode usage duration information and mode usage date information:

Among them, k represents the difference between the current working mode use date and the calculation date (i.e. the date of data processing), N represents the maximum calculation date (freely definable), x represents the mode use duration, and L represents the maximum time length defined when obtaining historical work log information (i.e. the difference between the earliest date and the latest date in the obtained work log information). Optionally, the measurement unit of k is day, the measurement unit of N is day, the measurement unit of x is minute, and the measurement unit of L is minute.

In an exemplary embodiment, the method for aggregating the scoring values includes determining whether the scoring values satisfy a preset condition, and if the preset conditions are met, marking the working mode corresponding to the scoring value as the optimal working mode of the device within the working period.

That is to say, during data aggregation processing, by judging whether the scoring value satisfies the preset condition, it is determined that the working mode corresponding to the scoring value satisfying the preset condition is the optimal working mode of the device in the working period. Optionally, the working mode corresponding to the highest scoring value can be set as the optimal working mode. In practical applications, different judgment conditions can be set according to different devices, different application scenarios, and environmental conditions, so as to obtain the most suitable optimal working mode.

Through the above data processing method, based on the historical log information of each device, the optimal working mode of each device in different working hours is obtained. When a certain device is started, according to the startup information generated by the device, the working period of the device is determined and the working mode of the device is obtained. The working mode is the optimal working mode of the device in the current working period. With this data processing method, the most commonly used or favorite working mode of each device of the user can be obtained according to the user's past usage habits. When the user starts the device every time, the device does not need to be adjusted, and the device starts the user's favorite working mode. This avoids the problem in the prior art that after the user changes the working mode under certain conditions, the next time the device is turned on, the device needs to be adjusted several times to obtain its favorite working mode, which reduces the interaction between the user and the device and increases the user experience. At the same time, since the above-mentioned data processing method can process multiple devices, it can be used not only for the setting of multiple air conditioners, but also for the setting of household appliances such as television sets and air purifiers.

In order to better understand the process of the above-mentioned data processing method, the flow of the above-mentioned data processing implementation method will be described below in conjunction with optional embodiments, but it is not used to limit the technical solutions of the embodiments of the present invention.

This embodiment provides an algorithm for recalling the optimal mode of the air conditioner without operation when starting up. FIG. 4 is a flow chart of the algorithm in this embodiment. The data processing process during the calculation process is shown in FIG. 5 . Specifically, the algorithm flow is as follows:

Step 1, preprocessing data. Select the user usage log (that is, the above-mentioned historical work log information) within a period of time as the calculation data, and define the length of this period of time as L;

It should be noted that the length of time L can be changed, and the value of L can be changed according to devices and application scenarios in actual applications.

Step 2, performing mac grouping on the data in step 1;

There is a one-to-one correspondence between Macs and devices, and each device has a unique mac that is different from other devices. After grouping all user usage logs in step 1 according to mac, multiple mac groups are obtained.

Step three, pattern segmentation. On the basis of step 2, segment by time interval (that is, the above-mentioned working period);

That is to say, the log information in each mac group formed after step 2 grouping needs to be segmented according to the time interval, and the log information in the same time interval is in the same segment.

Step 4, calculate the pattern score. Based on the grouping and segmentation results of steps 2 and 3, a score is calculated for the working mode in each time period in each mac group, and each score value represents the score when the device executes the working mode in this time period. Specifically, the current mode score can be calculated based on the mode use duration (i.e. the above-mentioned mode use duration information), the mode use actual date (i.e. the mode use date information);

Calculated as follows:

Among them, k represents the difference between the mode use date and the calculation date, N represents the maximum calculation date, x represents the user's usage time, and L represents the maximum time length defined in step 1. Optionally, the measurement unit of k is day, the measurement unit of N is day, the measurement unit of x is minute, and the measurement unit of L is minute.

Step five, score aggregation. The behavior scores of each segment are aggregated and sorted to obtain the user's best usage mode in the current segment (that is, the above-mentioned optimal working mode).

After the data is processed through the above steps, the optimal working mode of each air conditioner in each time interval is obtained and stored in the database.

Figure 6 is a schematic diagram of an air conditioner free of operating system with the above algorithm. As shown in Figure 6, when a user turns on a certain air conditioner, start-up information is generated and the real-time environment status is reported. According to the start-up information and real-time environment status, the best mode of the air conditioner (that is, the best use mode) is issued based on big data.

The evaluation method provided in this embodiment to obtain the best use mode by modeling the use duration and use time period of the air conditioner mode can make the air conditioner mode obtained by the user when starting up at different time periods be the user's favorite mode, avoiding the problem in the prior art that if the user adjusts the air conditioner mode under certain conditions, the start-up mode obtained when the user starts the next time remains the last use mode, so that the user needs to perform multiple adjustments to obtain the mode he likes. By adopting the operation-free recall algorithm for starting the air conditioner in this embodiment, the user can get the mode he likes when starting up at different time periods, which improves user experience, increases market recognition, and further improves economic benefits.

Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is a better implementation. Based on such an understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), and includes several instructions to make a terminal device (which can be a mobile phone, computer, server, or network equipment, etc.) execute the methods of various embodiments of the present invention.

An embodiment of the present invention also provides a data processing device, the processing device comprising: an acquisition module, configured to obtain historical work log information of at least one device; a processing module, configured to obtain, based on the historical work log information, a score value of each of the devices when executing a corresponding working mode in the different working hours; a determination module, configured to aggregate the scoring values based on the different working hours, and determine the optimal working mode of each of the devices in different working hours.

Fig. 7 is a structural block diagram of a data processing device according to an embodiment of the present invention; as shown in Fig. 4 , it includes:

Obtaining module 72, obtaining the historical work log information of multiple devices;

Wherein, the historical work log information at least includes the working modes executed by each device when working in different working periods.

Calculation module 74, based on the historical work log information, calculates the scoring value of each of the devices when executing the corresponding working mode in the different working hours;

The determining module 76 performs aggregation processing on the scoring values based on the different working periods, and determines the optimal working mode of each device under the different working periods.

Through the above-mentioned means, after the acquisition module 72 acquires the historical work log information of multiple devices, the calculation module 74 can calculate the scoring value of each of the devices when executing the corresponding working mode in the different working hours according to the historical working log information, and based on the scoring value, the determining module 76 can determine the optimal working mode of each of the devices in the different working hours. Through this structural setting, based on the user’s past usage habits, the working mode of the user’s most commonly used or favorite device at each time period can be deduced. Compared with the prior art that only records the working mode information used by the user last time, the optimal working mode recorded by the technical solution of the present application is more in line with the user’s preferences. Even if the user changes the working mode of the device used under certain conditions, after processing, the system records the most commonly used or favorite working mode of the user. The optimal working mode can be recommended to users as an option to increase user experience.

In an exemplary embodiment, the processing device further includes: a receiving module configured to receive startup information of the device to be detected, wherein the startup information is information generated when the device to be detected is started, and at least includes working hours of the device to be detected; a determination module is configured to determine a current working period of the device to be detected based on the working time of the device to be detected; an acquisition module is configured to acquire a working mode of the device to be detected based on the determined working period, wherein the working mode is the optimal working mode of the device to be detected.

That is to say, by accepting the startup information of the device to be detected received by the module, the determination module can determine the current working period of the device to be detected, and based on this working period, the acquisition module obtains the working mode of the device to be detected as the optimal working mode of the device to be detected. This structural setting enables the user to directly obtain the optimal working mode of the device in the current working period after turning on a device, avoiding the situation that the user needs to adjust the device multiple times to get the working mode of the device after restarting the device after adjusting the device mode under certain conditions, which reduces the interaction between the user and the device and improves the user experience.

According to yet 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.

Optionally, in this embodiment, the above-mentioned storage medium may be configured to store program codes for performing the following steps:

S1, obtaining historical work log information of multiple devices;

S2. Based on the historical work log information, calculate the scoring value of each of the devices when executing the corresponding working mode in the different working hours;

S3. Based on the different working periods, perform aggregation processing on the scoring values to determine an optimal working mode of each of the devices under the different working periods.

An embodiment of the present invention also provides an electronic device, including a memory and a processor, where a computer program is stored in the memory, and the processor is configured to run the computer program to perform the steps in any one of the above method embodiments.

Optionally, the above-mentioned electronic device may further include a transmission device and an input-output device, wherein the transmission device is connected to the above-mentioned processor, and the input-output device is connected to the above-mentioned processor.

Optionally, in this embodiment, the above-mentioned processor may be configured to execute the following steps through a computer program:

S1, obtaining historical work log information of multiple devices;

S2. Based on the historical work log information, calculate the scoring value of each of the devices when executing the corresponding working mode in the different working hours;

S3. Based on the different working periods, perform aggregation processing on the scoring values to determine an optimal working mode of each of the devices under the different working periods.

According to yet another aspect of the embodiments of the present invention, there is also provided a smart home system, including an electronic device, the electronic device being the above-mentioned electronic device. For example, the smart home system may include an air-conditioning system, the air-conditioning system includes an air conditioner, the air conditioner is provided with an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor is configured to run the computer program to perform the steps in any one of the above method embodiments.

Optionally, in this embodiment, the above-mentioned storage medium may include but not limited to: various media that can store program codes such as USB flash drives, read-only memory (Read-Only Memory, ROM for short), random access memory (Random Access Memory, RAM for short), mobile hard disks, magnetic disks, or optical disks.

Optionally, for specific examples in this embodiment, reference may be made to the examples described in the foregoing embodiments and optional implementation manners, and details are not repeated in this embodiment.

Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computing device, and they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices. The steps are implemented as a single integrated circuit module. As such, the present invention is not limited to any specific combination of hardware and software.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention shall 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.