CN113777941B - Equipment operation control method, device, equipment and storage medium - Google Patents
Equipment operation control method, device, equipment and storage medium Download PDFInfo
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- CN113777941B CN113777941B CN202111033927.1A CN202111033927A CN113777941B CN 113777941 B CN113777941 B CN 113777941B CN 202111033927 A CN202111033927 A CN 202111033927A CN 113777941 B CN113777941 B CN 113777941B
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B15/00—Systems controlled by a computer
- G05B15/02—Systems controlled by a computer electric
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/26—Pc applications
- G05B2219/2642—Domotique, domestic, home control, automation, smart house
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The application relates to a device operation control method, a device, equipment and a storage medium, and relates to the technical field of intelligent device control. The equipment operation control method comprises the following steps: acquiring operation parameters of each intelligent device in a preset time period, wherein the operation parameters comprise operation times of each intelligent device in each time period, and each time period belongs to the preset time period; acquiring a user habit parameter according to the operation parameter; and controlling the target intelligent equipment to operate in a target time period according to the using habit parameters of the user, wherein the target time period belongs to each time period. The intelligent control method and the intelligent control system are used for solving the problem that the running of the household electrical appliance depends on active operation of a user and is not intelligent enough.
Description
Technical Field
The application relates to the technical field of intelligent equipment control, in particular to an equipment operation control method, an equipment operation control device, equipment and a storage medium.
Background
Today in smart home development, manufacturers of the internet of things have completed how to remotely view and operate home appliances through terminal equipment, so as to realize preliminary intellectualization of user life. However, there is still room for improvement in that the user is still required to actively operate the home appliance.
Disclosure of Invention
The application provides a device operation control method, device, equipment and storage medium, which are used for solving the problem that the operation of household appliances depends on active operation of users and is not intelligent enough.
In a first aspect, an embodiment of the present application provides an apparatus operation control method, including:
acquiring operation parameters of each intelligent device in a preset time period, wherein the operation parameters comprise operation times of each intelligent device in each time period, and each time period belongs to the preset time period;
acquiring a user habit parameter according to the operation parameter;
and controlling the operation of the target intelligent equipment in a target time period according to the user using habit parameters, wherein the target time period belongs to each time period.
Optionally, the user using habit parameters include the support degree and the confidence degree of each intelligent device running in each time period;
and controlling the operation of the target intelligent device in a target time period according to the user habit parameters, wherein the method comprises the following steps:
for the support and confidence of any one of the intelligent devices operating in any one of the time periods, the following process is executed:
comparing the support degree with a minimum support degree threshold value;
comparing the confidence level to a minimum confidence level threshold;
and if the support degree is greater than the minimum support degree threshold and the confidence degree is greater than the minimum confidence degree threshold, taking any intelligent device as the target intelligent device, taking any time period as the target time period, and controlling the target intelligent device to run in the target time period.
Optionally, the acquiring the operation parameters of each intelligent device in the preset time period includes:
acquiring power consumption change parameters of each intelligent device in each time period;
the following procedure is performed for any one of the time periods:
according to the power consumption change parameters, screening intelligent equipment with the power consumption unchanged, and controlling the running times of the first intelligent equipment to be unchanged as the first intelligent equipment;
and screening the intelligent equipment with increased power consumption according to the power consumption change parameters, and controlling the running times of the second intelligent equipment to be increased by a preset value as the second intelligent equipment.
Optionally, the obtaining the user habit parameters according to the operation parameters includes:
and the support degree and the confidence degree of the operation of any intelligent device in any time period are obtained according to the following procedures:
according to the operation parameters, obtaining the total operation times of any intelligent device in the preset time period and the first operation times of any intelligent device in at least two time periods, wherein the at least two time periods comprise any time period, and obtaining the second operation times of any intelligent device in time periods except any time period in the at least two time periods;
calculating a first ratio of the first operation times to the total operation times, and taking the first ratio as the support degree of any intelligent equipment operated in any time period;
and calculating a second ratio of the first operation times to the second operation times, and taking the second ratio as the confidence coefficient of the operation of any intelligent device in any time period.
Optionally, the obtaining the user habit parameters according to the operation parameters includes:
the following procedure is performed for any one of the time periods:
obtaining the sum of the total operation times of each intelligent device in the preset time period as a third operation time according to the operation parameters, and obtaining a fourth operation time corresponding to any time period; the fourth operation times are times that the third intelligent device operates in any time period and the fourth intelligent device operates in an adjacent time period of any time period; and acquiring the running times of the fourth intelligent device in the adjacent time period of any time period as a fifth running time;
calculating a third ratio of the fourth operation times to the third operation times, and taking the third ratio as the support degree of the third intelligent device operated in any time period;
and calculating a fourth ratio of the fourth operation times to the fifth operation times, and taking the fourth ratio as the confidence of the third intelligent device operated in any time period.
Optionally, the method further comprises:
acquiring user parameters of each intelligent device;
acquiring the minimum support threshold according to a first mapping relation between the user parameters and the minimum support threshold;
and acquiring the minimum confidence coefficient threshold according to a second mapping relation between the user parameter and the minimum confidence coefficient threshold.
Optionally, the controlling the operation of the target intelligent device in the target time period according to the user habit parameters includes:
acquiring a historical operation mode of the target intelligent device;
and controlling the target intelligent equipment to operate according to the historical operation mode in the target time period.
In a second aspect, an embodiment of the present application provides an apparatus operation control device, including:
the first acquisition module is used for acquiring operation parameters of each intelligent device in a preset time period, wherein the operation parameters comprise operation times of each intelligent device in each time period, and each time period belongs to the preset time period;
the second acquisition module is used for acquiring the use habit parameters of the user according to the operation parameters;
and the processing module is used for controlling the operation of the target intelligent equipment in a target time period according to the user using habit parameters, wherein the target time period belongs to each time period. In a third aspect, an embodiment of the present application provides an electronic device, including: the device comprises a processor, a memory and a communication bus, wherein the processor and the memory are communicated with each other through the communication bus;
the memory is used for storing a computer program;
the processor is configured to execute the program stored in the memory, and implement the device operation control method according to the first aspect.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program, where the computer program implements the device operation control method according to the first aspect when executed by a processor.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages: according to the method provided by the embodiment of the application, the operation parameters of each intelligent device in the preset time period are obtained, the operation parameters comprise the operation times of each intelligent device in each time period, each time period belongs to the preset time period, the use habit parameters of the user are obtained according to the operation parameters, and the operation of the target intelligent device is controlled in the target time period according to the use habit parameters of the user, wherein the target time period belongs to each time period. For the running dependence user initiative operation of tame electric installation among the prior art, this application is through obtaining the number of times of operation of each smart machine in each time quantum, and the analysis user uses the habit of each smart machine, obtains user's use habit parameter, and then control object smart machine operation in the target time quantum, make the operation of smart machine more accord with user's habit, and need not user initiative operation, just can control object smart machine operation, promote the intelligent level of smart machine operation, the operation dependence user initiative operation of tame electric installation has been solved, the problem of inadequately intelligent.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart of a method for controlling operation of a device according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for obtaining support and confidence in an embodiment of the present application;
FIG. 3 is a flowchart of a method for obtaining support and confidence in an embodiment of the present application;
FIG. 4 is a flowchart of a method for controlling operation of a target smart device in a target time period according to a user habit parameter in an embodiment of the present application;
FIG. 5 is a flow chart of a method for controlling operation of a device according to an embodiment of the present application;
FIG. 6 is a schematic structural diagram of an apparatus operation control device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present application based on the embodiments herein.
In the embodiment of the application, a device operation control method is provided, and the method can be applied to a server, and of course, can also be applied to other electronic devices, such as terminals (mobile phones, tablet computers, etc.). In the embodiment of the present application, an example of applying the method to a server will be described.
In this embodiment of the present application, as shown in fig. 1, a method flow for controlling operation of a device mainly includes:
The preset time period may be 1 month, 3 months or 1 year. Each intelligent device can be intelligent equipment such as intelligent stereo set, intelligent air conditioner, intelligent refrigerator, intelligent television, intelligent lampblack absorber, intelligent washing machine, intelligent photo holder frame, intelligent wardrobe, router. The respective time periods may be time periods in which 1 day is divided, 1 day may be divided uniformly into respective time periods, 1 day may be divided unevenly into respective time periods, for example, the respective time periods may be [00:00-4:00 ], [4:00-8:00 ], [8:00-12:00 ], [12:00-16:00 ], [16:00-20:00 ], [ 20:00-24:00), the respective time periods may be [00:00-8:00 ], [8:00-10:00 ], [10:00-12:00 ], [12:00-16:00 ], [ 16:00-18:00) ], [ 18:00-22:00) ], the respective time periods may be divided uniformly into respective time periods in which 1 week is divided, or the respective time periods may be divided unevenly in 1 week.
The operation parameters include the number of operations of each smart device in each time period, for example: the preset time period is 1 month, the operation times of the intelligent washing machine at [ 12:00-16:00) are 4 times, the operation times of the intelligent washing machine at [ 18:00-22:00) are 10 times, the operation times of the intelligent air conditioner at [ 6:00-8:00) are 8 times, and the operation times of the intelligent air conditioner at [ 19:00-22:00) are 20 times.
In a specific embodiment, acquiring the operation parameters of each intelligent device in a preset time period includes: acquiring power consumption change parameters of each intelligent device in each time period; the following procedure is performed for any period of time: according to the power consumption change parameters, screening intelligent equipment with the power consumption unchanged, and controlling the operation times of the first intelligent equipment to be unchanged as the first intelligent equipment; and screening the intelligent equipment with increased power consumption according to the power consumption change parameters, and controlling the running times of the second intelligent equipment to be increased by a preset value as the second intelligent equipment.
Wherein the preset value may be 1.
The power consumption change parameters comprise power consumption which is kept unchanged and power consumption which is increased, and the power consumption change parameters are acquired through the intelligent electric meter. For example: in [ 11:00-12:30), the first intelligent device with constant power consumption is a bedroom air conditioner, the bedroom air conditioner is not operated in the [ 11:00-12:30) time period, the operating times of the bedroom air conditioner in the [ 11:00-12:30) time period are controlled to be constant, in the [ 11:00-12:30), the second intelligent device with increased power consumption is a washing machine, a refrigerator and a living room air conditioner, the power consumption can be suddenly increased or the power consumption can be stably increased, and the operating times of the washing machine, the refrigerator and the living room air conditioner in the [ 11:00-12:30) time period are controlled to be increased by 1.
Through the power consumption change parameters, the operation parameters of each intelligent device in a preset time period can be accurately obtained.
In a specific embodiment, acquiring the operation parameters of each intelligent device in a preset time period includes: acquiring the running state of each intelligent device sent in each time period, wherein the running state comprises running or not running; and obtaining the operation times of each intelligent device in each time period according to the operation state.
The running times of each intelligent device in each time period can be calculated through the running state actively uploaded by each intelligent device.
In one embodiment, the user usage habit parameters include the support and confidence that each smart device is operating for each time period.
The support degree and the confidence degree are terms in an Apriori algorithm (association rule mining algorithm), the support degree refers to the probability that an event A and an event B occur simultaneously, the confidence degree refers to the ratio of the probability that the event A and the event B occur simultaneously to the probability that the event A occurs, namely the confidence degree refers to the probability that the event B occurs under the condition that the event A occurs, and the probability belongs to conditional probability. The Apriori algorithm is to mine the association relationship between the event a and the event B.
In order to mine the association relation of the same intelligent device running in different time periods, in a specific embodiment, as shown in fig. 2, the support degree and the confidence degree of any intelligent device running in any time period are obtained according to the following procedures:
And 203, calculating a second ratio of the first operation times to the second operation times, and taking the second ratio as the confidence of any intelligent device operation in any time period.
For example, the support and confidence level for bedroom air conditioner operation at [ 11:00-12:30) is obtained according to the following procedure: the total number of times of operation of the bedroom air conditioner in 1 month was obtained as 20 times, and the first number of times of operation of the bedroom air conditioner in [ 11:00-12:30) and [ 19:00-22:00) was obtained as 4 times, and the second number of times of operation of the bedroom air conditioner in [ 19:00-22:00) was obtained as 10 times. Calculating a first ratio of the first operation times to the total operation times to be 4/20=20%, wherein the support degree of the operation of the bedroom air conditioner at [ 11:00-12:30) is 20%, namely the probability of the operation of the bedroom air conditioner at [ 11:00-12:30) and [ 19:00-22:00) is 20%, calculating a second ratio of the first operation times to the second operation times to be 4/10=40%, and the confidence degree of the operation of the bedroom air conditioner at [ 11:00-12:30) is 40%, namely the probability of the operation of the bedroom air conditioner at [ 11:00-12:30) is 40% under the condition that the bedroom air conditioner at [ 19:00-22:00) is operated.
For another example, the support and confidence level for bedroom air conditioner operation at [ 11:00-12:30) is obtained according to the following procedure: the total number of operation times of the bedroom air conditioner in 1 month was obtained as 20 times, and the first number of operation times of the bedroom air conditioner in [11:00-12:30 ], [ 14:00-16:00) and [ 19:00-22:00) were all operated as 4 times, and the second number of operation times of the bedroom air conditioner in [ 14:00-16:00) and [ 19:00-22:00) were obtained as 10 times. Calculating a first ratio of the first operation times to the total operation times to be 4/20=20%, wherein the support degree of the operation of the bedroom air conditioner at [ 11:00-12:30) is 20%, namely the probability of the operation of the bedroom air conditioner at [ 11:00-12:30), [ 14:00-16:00) and [ 19:00-22:00) is 20%, calculating a second ratio of the first operation times to the second operation times to be 4/10=40%, and the confidence degree of the operation of the bedroom air conditioner at [ 11:00-12:30) is 40%, namely the probability of the operation of the bedroom air conditioner at [ 11:00-12:30) is 40% under the conditions that the bedroom air conditioner at [ 14:00-16:00) and [ 19:00-22:00) are all operated.
The association relation of the same intelligent device running in different time periods can be mined, the possibility of running in any time period under the condition that the same intelligent device runs in time periods except any time period in at least two time periods is analyzed, whether the same intelligent device is controlled to run in any time period is further determined, and the habit of using a single intelligent device by a user is more met.
In order to mine the association between different intelligent devices running in adjacent time periods, in a specific embodiment, as shown in fig. 3, the following procedure is performed for any time period:
And 302, calculating a third ratio of the fourth operation times to the third operation times, and taking the third ratio as the support degree of the third intelligent device operated in any time period.
And 303, calculating a fourth ratio of the fourth operation times to the fifth operation times, and taking the fourth ratio as the confidence level of the third intelligent device operated in any time period.
For example, for [11:00-12:30 ]) the following procedure is performed: obtaining a sum of total operation times of each intelligent device in the families such as a washing machine, a refrigerator, a living room air conditioner and a dryer in 1 month as a third operation time, and obtaining that the washing machine operates in [ 11:00-12:30), the fourth operation time of the dryer operates in the adjacent time period [12:30-14:00 ] of [ 11:00-12:30) is 20 times, and obtaining that the fifth operation time of the dryer operates in the adjacent time period [12:30-14:00 ] of [ 11:00-12:30) is 25. Calculating a third ratio of the fourth operation times to the third operation times, which is 20/50=40%, wherein the support degree of the operation of the washing machine in [ 11:00-12:30) is 40%, namely the operation probability of the washing machine in [ 11:00-12:30) is 40%, and the operation probability of the drying machine in [ 12:30-14:00) is 40%, calculating a fourth ratio of the fourth operation times to the fifth operation times, which is 20/25=80%, wherein the confidence degree of the operation of the washing machine in [ 11:00-12:30) is 80%, namely the operation probability of the washing machine in [ 11:00-12:30) is 80% under the condition that the drying machine in [ 12:30-14:00) is operated.
The method has the advantages that the association relation of different intelligent devices in operation in adjacent time periods can be mined, the possibility that the third intelligent device operates in any time period under the condition that the fourth intelligent device operates in the adjacent time period in any time period is analyzed, whether the third intelligent device operates in any time period is further determined, and the habit of using a plurality of intelligent devices by a user is more met.
And step 103, controlling the operation of the target intelligent device in a target time period according to the using habit parameters of the user, wherein the target time period belongs to each time period.
In a specific embodiment, as shown in fig. 4, according to the usage habit parameters of the user, controlling the operation of the target smart device in the target period of time includes:
for the support and confidence of any intelligent device running in any time period, the following process is executed:
The minimum support threshold and the minimum confidence threshold may be values set by the user, for example, the minimum support threshold is 30%, and the minimum confidence threshold is 70%.
In a specific embodiment, the device operation control method further includes: acquiring user parameters of each intelligent device; acquiring a minimum support threshold according to a first mapping relation between the user parameter and the minimum support threshold; and acquiring the minimum confidence coefficient threshold according to the second mapping relation between the user parameter and the minimum confidence coefficient threshold.
Wherein the user parameter includes at least one of a user age and a user gender.
The user parameters of each intelligent device can be obtained by obtaining the user parameters input when the user controls each intelligent device through the APP, or by shooting the user image when the user uses each intelligent device, and obtaining the user parameters by identifying the user image. The user parameters include at least one of a user age and a user gender, and the user parameters may also include other parameters, and no limitation is made herein to the specific parameters included in the user parameters.
The first mapping relationship between the user parameter and the minimum support threshold may be that the minimum support threshold is 40% when the user parameter is elderly, and the minimum support threshold is 30% when the user parameter is middle-aged. The second mapping relationship between the user parameter and the minimum confidence coefficient threshold may be that the minimum confidence coefficient threshold is 80% when the user parameter is old, and the minimum confidence coefficient threshold is 70% when the user parameter is middle-aged.
Different minimum support thresholds and minimum confidence thresholds can be set according to different user parameters, so that habits of different people are met.
And step 403, if the support degree is greater than the minimum support degree threshold and the confidence degree is greater than the minimum confidence degree threshold, taking any intelligent device as a target intelligent device, taking any time period as a target time period, and controlling the target intelligent device to operate in the target time period.
For example: the support degree of the running of the bedroom air conditioner at the step [11:00-12:30 ] is 40%, the confidence coefficient is 80%, the minimum support degree threshold value is 30%, the minimum confidence degree threshold value is 70%, the support degree is larger than the minimum support degree threshold value, the confidence degree is larger than the minimum confidence degree threshold value, and the running of the bedroom air conditioner is controlled at the step [11:00-12:30 ").
In a specific embodiment, according to the user using habit parameters, controlling the operation of the target intelligent device in the target time period includes: acquiring a historical operation mode of the target intelligent device; and in the target time period, controlling the target intelligent equipment to operate according to the historical operation mode.
For example: the support degree of the running of the bedroom air conditioner is 40 percent in [11:00-12:30 ], the confidence coefficient is 80 percent, the minimum support degree threshold value is 30 percent, the minimum confidence degree threshold value is 70 percent, the support degree is larger than the minimum support degree threshold value, the confidence degree is larger than the minimum confidence degree threshold value, the historical running mode of the bedroom air conditioner is 27 degrees and the bedroom air conditioner is refrigerated, and the bedroom air conditioner is controlled to run according to 27 degrees and the refrigerating in [11:00-12:30 ].
In one embodiment, as shown in fig. 5, a method flow of device operation control includes:
And step 503, controlling the operation of the target intelligent device in the target time period according to the operation times.
In summary, according to the method provided by the embodiment of the application, the operation parameters of each intelligent device in a preset time period are obtained, the operation parameters comprise the operation times of each intelligent device in each time period, each time period belongs to the preset time period, the use habit parameters of the user are obtained according to the operation parameters, and the operation of the target intelligent device is controlled in a target time period according to the use habit parameters of the user, wherein the target time period belongs to each time period. For the running dependence user initiative operation of tame electric installation among the prior art, this application is through obtaining the number of times of operation of each smart machine in each time quantum, and the analysis user uses the habit of each smart machine, obtains user's use habit parameter, and then control object smart machine operation in the target time quantum, make the operation of smart machine more accord with user's habit, and need not user initiative operation, just can control object smart machine operation, promote the intelligent level of smart machine operation, the operation dependence user initiative operation of tame electric installation has been solved, the problem of inadequately intelligent.
Based on the same conception, the embodiment of the present application provides an apparatus operation control device, and the specific implementation of the apparatus may be referred to the description of the embodiment of the method, and the repetition is omitted, as shown in fig. 6, where the apparatus mainly includes:
a first obtaining module 601, configured to obtain operation parameters of each intelligent device in a preset time period, where the operation parameters include operation times of each intelligent device in each time period, and each time period belongs to the preset time period;
a second obtaining module 602, configured to obtain a user usage habit parameter according to the operation parameter;
and the processing module 603 is configured to control the target intelligent device to operate within a target time period according to the user usage habit parameter, where the target time period belongs to each time period.
Based on the same concept, the embodiment of the application also provides an electronic device, as shown in fig. 7, where the electronic device mainly includes: a processor 701, a memory 702, and a communication bus 703, wherein the processor 701 and the memory 702 perform communication with each other through the communication bus 703. The memory 702 stores a program executable by the processor 701, and the processor 701 executes the program stored in the memory 702 to implement the following steps:
acquiring operation parameters of each intelligent device in a preset time period, wherein the operation parameters comprise operation times of each intelligent device in each time period, and each time period belongs to the preset time period; acquiring a user habit parameter according to the operation parameter; and controlling the target intelligent equipment to operate in a target time period according to the using habit parameters of the user, wherein the target time period belongs to each time period.
The communication bus 703 mentioned in the above-mentioned electronic device may be a peripheral component interconnect standard (Peripheral Component Interconnect, abbreviated to PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated to EISA) bus, or the like. The communication bus 703 may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 7, but not only one bus or one type of bus.
The memory 702 may include random access memory (Random Access Memory, RAM) or may include non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor 701.
The processor 701 may be a general-purpose processor including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), a digital signal processor (Digital Signal Processing, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a Field programmable gate array (Field-Programmable Gate Array, FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components.
In yet another embodiment of the present application, there is also provided a computer-readable storage medium having stored therein a computer program which, when run on a computer, causes the computer to execute the apparatus operation control method described in the above embodiment.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions described in accordance with the embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, by a wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, microwave, etc.) means from one website, computer, server, or data center to another. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape, etc.), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk), etc.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A device operation control method, characterized by comprising:
acquiring operation parameters of each intelligent device in a preset time period, wherein the operation parameters comprise operation times of each intelligent device in each time period, and each time period belongs to the preset time period;
obtaining a user use habit parameter according to the operation parameter, wherein the user use habit parameter comprises the support degree and the confidence degree of each intelligent device in each time period operation;
controlling the operation of target intelligent equipment in a target time period according to the user using habit parameters, wherein the target time period belongs to each time period;
wherein, according to the operation parameters, obtaining the user habit parameters includes:
and the support degree and the confidence degree of the operation of any intelligent device in any time period are obtained according to the following procedures:
according to the operation parameters, obtaining the total operation times of any intelligent device in the preset time period and the first operation times of any intelligent device in at least two time periods, wherein the at least two time periods comprise any time period, and obtaining the second operation times of any intelligent device in time periods except any time period in the at least two time periods;
calculating a first ratio of the first operation times to the total operation times, and taking the first ratio as the support degree of any intelligent equipment operated in any time period;
and calculating a second ratio of the first operation times to the second operation times, and taking the second ratio as the confidence coefficient of the operation of any intelligent device in any time period.
2. The device operation control method according to claim 1, wherein the user usage habit parameters include a degree of support and a degree of confidence that the respective smart devices are operated in the respective periods of time;
and controlling the operation of the target intelligent device in a target time period according to the user habit parameters, wherein the method comprises the following steps:
for the support and confidence of any one of the intelligent devices operating in any one of the time periods, the following process is executed:
comparing the support degree with a minimum support degree threshold value;
comparing the confidence level to a minimum confidence level threshold;
and if the support degree is greater than the minimum support degree threshold and the confidence degree is greater than the minimum confidence degree threshold, taking any intelligent device as the target intelligent device, taking any time period as the target time period, and controlling the target intelligent device to run in the target time period.
3. The device operation control method according to claim 1, wherein the obtaining the operation parameters of each intelligent device in the preset period of time includes:
acquiring power consumption change parameters of each intelligent device in each time period;
the following procedure is performed for any one of the time periods:
according to the power consumption change parameters, screening intelligent equipment with the power consumption unchanged, and controlling the running times of the first intelligent equipment to be unchanged as the first intelligent equipment;
and screening the intelligent equipment with increased power consumption according to the power consumption change parameters, and controlling the running times of the second intelligent equipment to be increased by a preset value as the second intelligent equipment.
4. The apparatus operation control method according to claim 2, wherein the obtaining the user usage habit parameters according to the operation parameters includes:
the following procedure is performed for any one of the time periods:
obtaining the sum of the total operation times of each intelligent device in the preset time period as a third operation time according to the operation parameters, and obtaining a fourth operation time corresponding to any time period; the fourth operation times are times that the third intelligent device operates in any time period and the fourth intelligent device operates in an adjacent time period of any time period; and acquiring the running times of the fourth intelligent device in the adjacent time period of any time period as a fifth running time;
calculating a third ratio of the fourth operation times to the third operation times, and taking the third ratio as the support degree of the third intelligent device operated in any time period;
and calculating a fourth ratio of the fourth operation times to the fifth operation times, and taking the fourth ratio as the confidence of the third intelligent device operated in any time period.
5. The apparatus operation control method according to claim 2, characterized in that the method further comprises:
acquiring user parameters of each intelligent device;
acquiring the minimum support threshold according to a first mapping relation between the user parameters and the minimum support threshold;
and acquiring the minimum confidence coefficient threshold according to a second mapping relation between the user parameter and the minimum confidence coefficient threshold.
6. The device operation control method according to claim 1, wherein the controlling the operation of the target smart device within the target period according to the user usage habit parameter comprises:
acquiring a historical operation mode of the target intelligent device;
and controlling the target intelligent equipment to operate according to the historical operation mode in the target time period.
7. An apparatus operation control device, comprising:
the first acquisition module is used for acquiring operation parameters of each intelligent device in a preset time period, wherein the operation parameters comprise operation times of each intelligent device in each time period, and each time period belongs to the preset time period;
the second acquisition module is used for acquiring user use habit parameters according to the operation parameters, wherein the user use habit parameters comprise the support degree and the confidence degree of each intelligent device in each time period;
the processing module is used for controlling the operation of the target intelligent equipment in a target time period according to the user habit parameters, wherein the target time period belongs to each time period;
wherein, the second acquisition module is used for:
and the support degree and the confidence degree of the operation of any intelligent device in any time period are obtained according to the following procedures:
according to the operation parameters, obtaining the total operation times of any intelligent device in the preset time period and the first operation times of any intelligent device in at least two time periods, wherein the at least two time periods comprise any time period, and obtaining the second operation times of any intelligent device in time periods except any time period in the at least two time periods;
calculating a first ratio of the first operation times to the total operation times, and taking the first ratio as the support degree of any intelligent equipment operated in any time period;
and calculating a second ratio of the first operation times to the second operation times, and taking the second ratio as the confidence coefficient of the operation of any intelligent device in any time period.
8. An electronic device, comprising: the device comprises a processor, a memory and a communication bus, wherein the processor and the memory are communicated with each other through the communication bus;
the memory is used for storing a computer program;
the processor is configured to execute a program stored in the memory, and implement the device operation control method according to any one of claims 1 to 6.
9. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the apparatus operation control method according to any one of claims 1 to 6.
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