CN108052010B - Intelligent electric appliance self-adjusting method and device, computer equipment and storage medium - Google Patents
Intelligent electric appliance self-adjusting method and device, computer equipment and storage medium Download PDFInfo
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- CN108052010B CN108052010B CN201711260870.2A CN201711260870A CN108052010B CN 108052010 B CN108052010 B CN 108052010B CN 201711260870 A CN201711260870 A CN 201711260870A CN 108052010 B CN108052010 B CN 108052010B
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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
Abstract
The invention discloses a method and a device for self-adjustment of an intelligent electric appliance, computer equipment and a readable storage medium, wherein the method comprises the following steps: the processing center acquires state parameters of the intelligent electric appliance to form a state record; the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance; the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter a response state; the method, the computer readable storage medium and the device enable the intelligent electric appliance to be capable of recording the state of the automatic regulator by combining the history of the intelligent electric appliance without the need of operating or setting the intelligent electric appliance by a user, so that the intelligent degree of the intelligent electric appliance can be realized, the user operation can be saved, and the user experience is improved.
Description
Technical Field
The invention relates to the field of intelligent electric appliances, in particular to a method and a device for self-adjustment of an intelligent electric appliance, computer equipment and a storage medium.
Background
In the prior art, a user sets the intelligent electric appliance regularly, and sets the intelligent electric appliance to be started up after the duration of the intelligent electric appliance from the set time passes through the duration by estimating the duration between the set time and the preset starting-up time. Such as: when a user sets the air conditioner to start up at home nine hours after going out eight o' clock in the morning (namely seven pm), the air conditioner can start up at the right time at seven pm. However, if the user arrives home earlier than seven pm or later than seven pm, a setting error may be caused, resulting in a failure in adapting the turn-on time of the air conditioner to the user's return time. Moreover, when regularly setting up at every turn, still need to set up the work of intelligent electrical apparatus and fill, if: the control temperature of the air conditioner is set. Moreover, the setting needs to be carried out every day, so that the intelligent electric appliance is very inconvenient, if a user forgets the setting, the intelligent electric appliance cannot automatically enter the working state, and the working state does not meet the user experience.
Disclosure of Invention
The invention mainly aims to provide a method and a device for self-adjustment of an intelligent electric appliance, computer equipment and a storage medium, so that the intelligent electric appliance can automatically adjust the state of the intelligent electric appliance by combining with the historical record of the intelligent electric appliance without the operation or the setting of the intelligent electric appliance by a user, the intelligent degree of the intelligent electric appliance can be improved, the operation of the user can be saved, and the user experience is improved.
According to one aspect of the invention, a method for self-adjusting of intelligent electric appliances is provided, wherein the intelligent electric appliances are successfully distributed, and the method comprises the following steps: the processing center acquires state parameters of the intelligent electric appliance to form a state record; the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance; the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter a response state.
Optionally, the obtaining, by the processing center, the state parameter of the intelligent electrical appliance to form a state record includes: the processing center periodically forms a state record according to the state parameters of the intelligent electrical appliance acquired in the preset time period.
Optionally, before the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electrical appliance, the method further includes: judging whether the state record meets a preset condition or not; under the condition that a preset condition is met, the processing center determines to analyze the state record according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance; and under the condition that the preset condition is not met, the intelligent electric appliance enters a preset state according to default preset.
Optionally, the state parameter includes a time parameter for turning on and turning off the intelligent electrical appliance; the processing center obtains the state parameter of intelligent electrical apparatus in order to form the state record, includes: the processing center acquires the time parameters of the on-off of the intelligent electric appliance to form an on-off record; the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance, and the handling state comprises the following steps: the processing center processes the startup and shutdown records according to a preset algorithm to obtain the startup and shutdown time of the intelligent electric appliance; the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter a handling state, and the method comprises the following steps: the processing center sends a startup and shutdown instruction to the intelligent electric appliance to control the intelligent electric appliance to be started and shut down at the startup and shutdown time.
Optionally, the time parameter includes: the user ID, the SSID and the MAC address of the intelligent household appliance and the time for the intelligent household appliance to be connected with the network.
Optionally, the state parameter includes a working parameter of the intelligent electrical appliance; the processing center obtains the state parameter of intelligent electrical apparatus in order to form the state record, includes: the processing center acquires working parameters of the intelligent electrical appliance to form a working record; the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance, and the handling state comprises the following steps: the processing center processes the working record according to a preset algorithm to obtain the working state of the intelligent electric appliance; the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter a handling state, and the method comprises the following steps: and the processing center issues a working state adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter a working state.
Optionally, the operating parameters include: the running state of the intelligent household appliance, the working time period of the intelligent household appliance, the working date of the intelligent household appliance, the MAC address and the starting-up times.
Optionally, the preset algorithm includes a big data hadoop computing framework.
According to a second aspect of the present invention, there is provided an apparatus for self-adjusting an intelligent electrical appliance, the apparatus comprising: the recording module is used for acquiring the state parameters of the intelligent electrical appliance by the processing center to form a state record; the algorithm module is used for analyzing the state record by the processing center according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance; and the adjusting module is used for issuing an adjusting instruction to the intelligent electric appliance by the processing center based on the acquired response state so as to control the intelligent electric appliance to enter the response state.
Optionally, the recording module includes: and the recording unit is used for periodically forming a state record by the processing center according to the state parameters of the intelligent electrical appliance acquired in the preset time period.
Optionally, the apparatus further comprises: the judging module is used for judging whether the state record meets a preset condition or not before the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance; the state acquisition module is used for determining that the state record is analyzed according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance under the condition that the preset condition is met; and the preset state entering module is used for entering the preset state of the intelligent electric appliance according to default preset under the condition that the preset condition is not met.
Optionally, the state parameter includes a time parameter for turning on and turning off the intelligent electrical appliance; the recording module is specifically configured to: the processing center acquires the time parameters of the on-off of the intelligent electric appliance to form an on-off record; the algorithm module is specifically configured to: the processing center processes the startup and shutdown records according to a preset algorithm to obtain the startup and shutdown time of the intelligent electric appliance; the adjusting module is specifically configured to: and based on the obtained on-off time, the processing center issues an on-off instruction to the intelligent electric appliance to control the intelligent electric appliance to be turned on and off at the on-off time.
Optionally, the time parameter includes: the user ID, the SSID and the MAC address of the intelligent household appliance and the time for the intelligent household appliance to be connected with the network.
Optionally, the state parameter includes a working parameter of the intelligent electrical appliance; the device still includes: the recording module is specifically configured to: the processing center acquires working parameters of the intelligent electrical appliance to form a working record; the algorithm module is specifically configured to: the processing center processes the working record according to a preset algorithm to obtain the working state of the intelligent electric appliance; the adjusting module is specifically configured to: based on the obtained working state, the processing center issues a working state adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the working state.
Optionally, the operating parameters include: the running state of the intelligent household appliance, the working time period of the intelligent household appliance, the working date of the intelligent household appliance, the MAC address and the starting-up times.
Optionally, the preset algorithm includes a big data hadoop computing framework.
According to a third aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the methods described above when executing the program.
According to a fourth aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any one of the methods described above.
The invention has the following beneficial effects: according to the method and device for self-adjustment of the intelligent electric appliance, the computer equipment and the storage medium, the intelligent electric appliance can be combined with the state of the automatic regulator of the history record, and the intelligent electric appliance does not need to be operated or set by a user, so that the intelligent degree of the intelligent electric appliance can be increased, the user operation can be saved, and the user experience is improved.
Drawings
Fig. 1 is a flowchart illustrating a setup process of an intelligent air conditioner in the prior art;
FIG. 2 is a flow chart of a method for self-adjusting an intelligent electrical appliance according to a first embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a big data Haodu computing framework according to the present invention;
FIG. 4 is a flow chart illustrating a self-tuning process for an intelligent home for an intelligent air conditioner;
FIG. 5 is a schematic diagram of a state of the intelligent air conditioner for training;
fig. 6 is a flow chart of an apparatus for self-adjusting an intelligent electrical appliance according to a second embodiment of the present invention.
The objects, features and advantages of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
In order to facilitate understanding of the embodiments of the present invention, the following detailed description of the embodiments of the present invention is provided.
Fig. 1 is a flowchart illustrating a setting process of an intelligent air conditioner in the prior art. According to fig. 1, in the prior art, a user sets a timing and an operating state of a smart appliance at all times, and if the user arrives home in advance or delays to home, the smart appliance cannot adjust itself according to the user. Moreover, when regularly setting up at every turn, still need to set up the work of intelligent electrical apparatus and fill, if: the control temperature of the air conditioner is set. Moreover, the setting needs to be carried out every day, so that the intelligent electric appliance is very inconvenient, if a user forgets the setting, the intelligent electric appliance cannot automatically enter the working state, and the working state does not meet the user experience.
To this end, in a first embodiment of the present invention, a method for self-adjusting an intelligent appliance is provided, where the intelligent appliance has been successfully distributed, the method includes: the processing center acquires state parameters of the intelligent electric appliance to form a state record; the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance; the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter a response state.
Therefore, the intelligent electric appliance can be combined with the state of the history automatic regulator, the user does not need to operate or set the intelligent electric appliance, the intelligent degree of the intelligent electric appliance can be increased, the user operation can be saved, the user does not need to set the intelligent electric appliance, and the user experience is improved.
Specifically, fig. 1 is a flowchart of this embodiment, and according to fig. 1, a method for self-adjusting an intelligent electrical appliance provided by a first embodiment of the present invention is provided, where the intelligent electrical appliance has been successfully distributed, and the method includes:
s1: the processing center acquires state parameters of the intelligent electric appliance to form a state record;
after a user purchases the intelligent electric appliance, the intelligent electric appliance is firstly connected to a network in a distribution mode. The intelligent electric appliance uploads the state parameters of the intelligent electric appliance to the processing center in real time so as to perform machine learning, and the state parameters represent the state of the intelligent electric appliance.
Wherein, the self state of intelligent electrical apparatus includes at least: whether the intelligent electric appliance is in a starting state and a working state of the intelligent electric appliance, taking an intelligent air conditioner as an example: the intelligent air conditioner can upload the temperature of whether the intelligent air conditioner is in the starting state or not and the control temperature of the intelligent air conditioner to the processing center in real time.
The state parameters of the intelligent electrical appliance are uploaded to the processing center in real time, in the embodiment, the state parameters of the intelligent electrical appliance need to be uploaded to the cloud platform through the gateway, and the cloud platform transmits the state parameters to the processing center to be stored so as to form the state record. Of course, the processing center may obtain the status parameters from the cloud platform through subscription. In this embodiment, the manner in which the processing center obtains the state parameters from the cloud platform is not limited, and it is only necessary that the method meets the requirements of this embodiment, and the method and the system of the present invention belong to the protection scope of the present invention. The processing center can be a background operation program.
Optionally, obtaining the state parameters of the intelligent electrical appliance for the processing center to form a state record, including: the processing center periodically forms a state record according to the state parameters of the intelligent electrical appliance acquired in the preset time period.
Specifically, in this embodiment, the processing center obtains the state parameters of the smart appliance to form the state record, including: the processing center acquires state parameters of the intelligent electric appliance; and the processing center forms a state record according to the state parameters acquired in the preset time period. Namely, after the processing center obtains the state parameters of the intelligent electrical appliance, the processing center can periodically process the state parameters obtained within the preset time to form a state record. Such as: the processing center processes the state parameters acquired thirty days before every week.
S2: the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance;
based on the state record, the processing center can calculate the state record according to a preset algorithm so as to obtain the current state of the intelligent electric appliance. Specifically, in this embodiment, the state record is a history record of past states of the smart appliance. Optimally, the processing center can calculate by combining the state record and the obtained latest state parameter according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance, and the current state of the intelligent electric appliance can be more approximate by combining the latest state parameter, so that the calculation precision can be effectively improved, and the error can be reduced.
S3: the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter a response state.
After the processing center obtains the response state of the intelligent electric appliance, the processing center can issue an adjusting instruction to the intelligent electric appliance so as to control the intelligent electric appliance to enter the response state of the intelligent electric appliance. Therefore, the intelligent electric appliance can be combined with the state of the history record automatic regulator, and the user does not need to operate or set the intelligent electric appliance, such as: the intelligent electrical apparatus can be automatically turned on and turned off within corresponding time according to historical switch records of the intelligent electrical apparatus, so that the intelligent degree of the intelligent electrical apparatus can be increased, the user operation can be saved, the user does not need to set the intelligent electrical apparatus, and the user experience is improved.
Optionally, before the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electrical appliance, the method further includes: judging whether the state record meets a preset condition or not; under the condition that a preset condition is met, the processing center determines to analyze the state record according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance; and under the condition that the preset condition is not met, the intelligent electric appliance enters a preset state according to default preset.
Specifically, before the processing center obtains the handling state of the intelligent electrical appliance according to the preset algorithm based on the state record, the processing center needs to judge whether the state record meets the preset condition, and under the condition that the state record meets the preset condition, the processing center can determine to perform operation according to the preset algorithm and based on the state record so as to obtain the handling state of the intelligent electrical appliance. However, if the status record does not satisfy the preset condition, the smart appliance intelligence enters a preset status according to its own preset, such as: if the intelligent air conditioner does not generate the state parameters or the number of the state parameters is too small, so that the state records obtained by the processing center are too small, the intelligent air conditioner is automatically started to start working when the indoor temperature is 27 degrees.
Aiming at the state parameters, the state parameters comprise time parameters of the on-off of the intelligent electric appliance; moreover, the processing center acquires the state parameters of the intelligent electric appliance to form a state record, and the state record comprises the following steps: the processing center acquires the time parameters of the on-off of the intelligent electric appliance to form an on-off record; the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance, and the handling state comprises the following steps: the processing center processes the startup and shutdown records according to a preset algorithm to obtain the startup and shutdown time of the intelligent electric appliance; based on the acquired response state, the processing center issues an adjustment instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the response state, and the method comprises the following steps: and based on the obtained on-off time, the processing center issues an on-off instruction to the intelligent electric appliance to control the intelligent electric appliance to be turned on and off at the on-off time.
Namely: in this embodiment, the status parameters include time parameters for turning on and off the smart appliance, such as: historical on-off time of the intelligent air conditioner. After the processing center obtains the time parameters of the on/off of the intelligent electrical appliance, a power-on record is generated, namely the time record of the historical on/off of the intelligent electrical appliance is generated. And the processing center calculates the startup and shutdown records according to a preset algorithm to obtain the startup and shutdown time of the intelligent electric appliance. Optimally, the processing center can calculate by combining the startup and shutdown records with the latest acquired startup and shutdown time parameters of the intelligent electrical appliance according to a preset algorithm to acquire the startup and shutdown time of the intelligent electrical appliance, and the current state of the intelligent electrical appliance can be closer by combining the latest startup and shutdown time parameters of the intelligent electrical appliance, so that the calculation precision of the startup and shutdown time can be effectively improved, and the error is reduced. After the on-off time of the intelligent electric appliance is obtained, the processing center sends an on-off instruction to the intelligent electric appliance so as to control the intelligent electric appliance to be turned on and off at the on-off time. Therefore, the intelligent electric appliance can be automatically switched on and off at corresponding time according to the historical records without switching on and off and setting operation of a user.
Further, the time parameters include: the user ID, the SSID and the MAC address of the intelligent household appliance and the time for the intelligent household appliance to be connected with the network. Such as:
exp { "userId": 213023213412412"," SSID ": QWQ 1212", "mac": ASDFG123456"," ASDFG123456"]," connectitTime ": 2017-07-1405:24:53" }. In this embodiment, the time when the intelligent appliance is connected to the network is taken as an example for explanation, and the network accessed by the intelligent appliance when the network distribution is successful is taken as the home WIFI network. After the intelligent electric appliance is successfully distributed with the network, if the mobile terminal of the user is connected with the family WIFI network in the process of returning the user home, the user can be regarded as having returned the home, and the time point can be used as the time parameter for starting the intelligent electric appliance. Certainly, in the process that the user leaves home, if the mobile terminal of the user is disconnected from the home WIFI network, the user can be regarded as leaving home, and the time point can be used as a time parameter for the intelligent electric appliance to be powered off.
In addition, the state parameters can also comprise working parameters of the intelligent electric appliance; the processing center obtains the state parameter of intelligent electrical apparatus in order to form the state record, includes: the processing center acquires working parameters of the intelligent electrical appliance to form a working record; the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance, and the handling state comprises the following steps: the processing center processes the working record according to a preset algorithm to obtain the working state of the intelligent electric appliance; based on the acquired response state, the processing center issues an adjustment instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the response state, and the method comprises the following steps: based on the obtained working state, the processing center issues a working state adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the working state.
Namely: in this embodiment, the status parameters include operating parameters of the smart appliance, such as: the control temperature of intelligence air conditioner. After the processing center obtains the working parameters of the intelligent electrical appliance, a working record is generated, namely a historical working record of the intelligent electrical appliance is generated, such as: historical control temperature records of the air conditioner. And the processing center calculates the working record according to a preset algorithm to obtain the working state of the intelligent electric appliance. Optimally, the processing center can calculate by combining the working record and the acquired latest working parameters of the intelligent electrical appliance according to a preset algorithm to acquire the working state of the intelligent electrical appliance, and the current state of the intelligent electrical appliance can be closer by combining the latest working parameters of the intelligent electrical appliance, so that the calculation precision of the working state of the intelligent electrical appliance can be effectively improved, and the error is reduced. After the working state of the intelligent electric appliance is obtained, the processing center sends a working state adjusting instruction to the intelligent electric appliance so as to control the intelligent electric appliance to enter the working state. Therefore, the intelligent electric appliance can automatically enter the working state according to the historical record without the operation of the working state and the setting operation of the working state by a user.
For the operating parameters, it comprises at least: the running state of the intelligent household appliance, the working time period of the intelligent household appliance, the working date of the intelligent household appliance, the MAC address and the starting-up times.
Aiming at a preset algorithm, the method comprises a big data Haodu computing framework. Fig. 3 is a schematic structural diagram of a big data hadoop computing framework in the present invention, and according to fig. 3, after the state parameters of the intelligent electrical appliance are reported to the processing center, the state parameters are all collected into the HDFS for analysis and processing, so as to issue a command.
Specifically, the most core design in the big data hadoop computing framework is as follows: MapReduce and HDFS. MapReduce is just the "decomposition of tasks and summary of results". HDFS is an abbreviation of the Distributed File System (Hadoop Distributed File System) of the big data Hadoop computing framework, providing underlying support for Distributed computing storage.
HDFS is a storage cornerstone of distributed computing, and the distributed file system of the big data hadoop computing framework and other distributed file systems have many similar traits. Several basic features of distributed file systems:
1. there is a single namespace for the entire cluster.
2. And (4) data consistency. The model is suitable for write-once and read-many, and a client cannot see the existence of a file before the file is not successfully created.
3. The file is divided into a plurality of file blocks, each file block is allocated to be stored on the data node, and the data security is ensured by copying the file blocks according to the configuration.
For convenience of understanding the flow of the present embodiment, the scheme of the present embodiment is described in detail with specific embodiments.
Fig. 4 is a flow chart illustrating self-adjustment of an intelligent home for an intelligent air conditioner. And the intelligent electrical appliance takes an intelligent air conditioner as an example.
It is first necessary to make the smart air conditioner capable of learning. The machine learning is a multi-field cross subject and relates to a plurality of subjects such as probability theory, statistics, approximation theory, convex analysis and algorithm complexity theory. The special research on how a computer simulates or realizes the learning behavior of human beings so as to acquire new knowledge or skills and reorganize the existing knowledge structure to continuously improve the performance of the computer. It is the core of artificial intelligence, is the fundamental way to make computers have intelligence, and its application is spread over various fields of artificial intelligence.
The Boosting algorithm establishes M models (for example, classification) for a piece of data, the models are generally simple, each time the weak classifier (weak classifier) is used for classifying, the weight of the data which is classified last time is increased by a little, and then the classification is carried out, so that the finally obtained classifier can obtain better results on test data and training data.
The method for Boosting by using the Gradient is mainly characterized in that each time of modeling is to build the Gradient descending direction of a model loss function in the previous modeling. The loss function (loss function) describes the degree of the spectrum dependence of the model, and the larger the loss function is, the more error-prone the model is. If we model can make the loss function continuously decrease, we show that we model is continuously improving, and the best way is to make the loss function decrease in the direction of its Gradient (Gradient).
Specifically, the intelligent air conditioner needs to first determine whether the user is at home. And the user opens the App, and the App transmits the information of the WiFi connected by the user to the cloud platform. And if the user is connected with the WiFi, the processing center monitors the WiFi in real time. The intelligent electric appliance can use a network accessed when the distribution network of the intelligent electric appliance is successful as a family WIFI network.
The time parameters reported by the intelligent air conditioner are as follows: the user ID, the SSID and the MAC address of the intelligent household appliance and the time for the intelligent household appliance to be connected with the network. Specifically, the time parameters are as follows:
Exp{"userId":"213023213412412"，"SSID":"QWWQ1212"，"mac":["ASDFG123456"，"ASDFG123456"]，"connectTime":"2017-07-1405:24:53"}
take the time when the intelligent household electrical appliance is connected with the network as an example: after the intelligent electric appliance is successfully distributed with the network, if the mobile terminal of the user is connected with the family WIFI network in the process of returning the user home, the user can be regarded as having returned the home, and the front and rear five minutes of the time point can be used as the time parameter for starting the intelligent electric appliance. Certainly, in the process that the user leaves home, if the mobile terminal of the user is disconnected from the home WIFI network, the user can be regarded as leaving home, and the front and rear five minutes of the time point can be used as the time parameter for turning off the intelligent electric appliance.
The processing center performs operation according to the startup and shutdown record of the time parameter so as to obtain proper startup and shutdown time.
FIG. 5 is a schematic diagram of a state of the intelligent air conditioner for training; as shown in fig. 5, when the user is at home, the intelligent air conditioner selects the corresponding on-off time and controls the temperature according to the usage habit of the user and the current ambient temperature.
Specifically, the processing center may perform an operation according to the working record of the working parameter reported by the intelligent air conditioner, for example: control temperature record in the past of intelligence to make intelligent air conditioner adjust it to suitable control temperature, wherein, operating parameter includes: the running state of the intelligent household appliance, the working time period of the intelligent household appliance, the working date of the intelligent household appliance, the MAC address and the starting-up times. Such as: vectorrassembler (inputCols [ "indoor temperature", "small period", "working date of intelligent household appliance", "mac", "boot frequency" ], outputcols [ "lives"), wherein the working date of the intelligent household appliance may be a specific day of the week, such as: on Monday.
The processing center performs calculation according to the working record of the time parameter so as to obtain a proper control temperature.
Specifically, the processing center processes the state parameters acquired thirty days before every week to help the intelligent air conditioner to predict the state data of the next week.
And aiming at the obtained startup and shutdown records and work records, the intelligent air conditioner adopts decisionTree to collect and combines a data Haidupu calculation framework to carry out operation.
Prediction time interval: months 6-9 (summer), months 11-2 (winter), and other times are not considered for the moment because the parameter set data is less.
If the intelligent air conditioner does not generate the state parameters or the number of the state parameters is too small, so that the state records obtained by the processing center are too small, the intelligent air conditioner is automatically started to start working when the indoor temperature is 27 degrees.
Specifically, 1, historical startup and shutdown parameters and working parameters of the intelligent air conditioner are counted, and environmental data and setting data during a startup and shutdown period can be counted.
2. The power-on and power-off period should include: setting air speed data according to the latest indoor temperature, set temperature and set mode when the mobile phone leaves the mobile phone within five minutes before starting the mobile phone; setting wind speed data for the last indoor temperature, set temperature and set mode within three minutes after starting up; and the latest one after three minutes after starting the machine sets the temperature, the setting mode and the data of which the set wind speed has change.
3. When the state combination appearing in the on-cycle record of a single user is greater than or equal to 80% of the possibility of the on-state combination thereof, it is regarded that the air conditioner operation behavior of the user has been successfully learned by the air conditioner itself.
4. The air conditioner which has been successfully self-learned can obtain the air conditioner setting (setting within three minutes after starting) which is most frequently used by the user at the starting time by inputting the specified parameters and multiplying the specified parameters by the specific coefficients through the program, thereby achieving the intellectualization, the automation and the individualization of the air conditioner.
5. When the optimal setting of the air conditioner is calculated and before the control command is issued, the air conditioner mode of the client can be directly set to be automatic until the command is successfully issued.
Fig. 6 is a schematic structural diagram of an apparatus for self-adjustment of an intelligent electrical appliance according to a second embodiment of the present invention. According to the second embodiment of the present invention, as shown in fig. 6, there is provided an apparatus for self-adjusting an intelligent electrical appliance, the apparatus including: the recording module is used for acquiring the state parameters of the intelligent electrical appliance by the processing center to form a state record; the algorithm module is used for analyzing the state record by the processing center according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance; and the adjusting module is used for issuing an adjusting instruction to the intelligent electric appliance by the processing center based on the acquired response state so as to control the intelligent electric appliance to enter the response state.
Optionally, the recording module includes: and the recording unit is used for periodically forming a state record by the processing center according to the state parameters of the intelligent electrical appliance acquired in the preset time period.
Optionally, the apparatus further comprises: the judging module is used for judging whether the state record meets a preset condition or not before the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance; the state acquisition module is used for determining that the state record is analyzed according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance under the condition that the preset condition is met; and the preset state entering module is used for entering the preset state of the intelligent electric appliance according to default preset under the condition that the preset condition is not met.
Optionally, the state parameter includes a time parameter for turning on and turning off the intelligent electrical appliance; the recording module is specifically configured to: the processing center acquires the time parameters of the on-off of the intelligent electric appliance to form an on-off record; the algorithm module is specifically configured to: the processing center processes the startup and shutdown records according to a preset algorithm to obtain the startup and shutdown time of the intelligent electric appliance; the adjusting module is specifically configured to: and based on the obtained on-off time, the processing center issues an on-off instruction to the intelligent electric appliance to control the intelligent electric appliance to be turned on and off at the on-off time.
Optionally, the time parameter includes: the user ID, the SSID and the MAC address of the intelligent household appliance and the time for the intelligent household appliance to be connected with the network.
Optionally, the state parameter includes a working parameter of the intelligent electrical appliance; the device still includes: the recording module is specifically configured to: the processing center acquires working parameters of the intelligent electrical appliance to form a working record; the algorithm module is specifically configured to: the processing center processes the working record according to a preset algorithm to obtain the working state of the intelligent electric appliance; the adjusting module is specifically configured to: based on the obtained working state, the processing center issues a working state adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the working state.
Optionally, the operating parameters include: the running state of the intelligent household appliance, the working time period of the intelligent household appliance, the working date of the intelligent household appliance, the MAC address and the starting-up times.
Optionally, the preset algorithm includes a big data hadoop computing framework.
Therefore, the state parameters are acquired through the recording module, the handling state of the intelligent electric appliance is obtained through the algorithm module, then the intelligent electric appliance enters the handling state through the adjusting module, the intelligent electric appliance can be combined with the state of the history automatic adjuster, the intelligent electric appliance does not need to be operated or set by a user, the intelligent degree of the intelligent electric appliance can be increased, the user operation can be saved, and the user experience is improved.
A second embodiment of the invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of any one of the methods described above.
Since the method for self-adjusting the smart appliance has been described in detail in the first embodiment, the implementation process of the method is not repeated in this embodiment.
A second embodiment of the invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the methods described above when executing the program.
Since the method for self-adjusting the smart appliance has been described in detail in the first embodiment, the implementation process of the method is not repeated in this embodiment.
It should be noted that, in this document, 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 an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (12)
1. A method for self-adjustment of intelligent electric appliances is characterized by comprising the following steps:
the processing center acquires state parameters of the intelligent electric appliance to form a state record;
the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance;
the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the handling state;
the method comprises the steps that a home WIFI network is accessed when the intelligent electric appliance distribution network is successful, the state parameters comprise the time parameters of the on-off of the intelligent electric appliance, the time point when a user mobile terminal is connected with the home WIFI network is used as the time parameters of the on-off of the intelligent electric appliance, and the time point when the user mobile terminal is disconnected with the home WIFI network is used as the time parameters of the on-off of the intelligent electric appliance;
the state parameters further include: environmental data and setup data during the power-on and power-off cycle;
the environmental data and setting data during the power on and power off cycle include: the latest indoor temperature, set mode and set wind speed data at the departure time within five minutes before starting up; setting the temperature, the mode and the wind speed data of the last indoor temperature within three minutes after starting up; and the latest data with changed set temperature, set mode and set wind speed three minutes after starting the machine.
2. The method of claim 1, wherein the processing center obtaining the state parameters of the smart appliance to form a state record comprises:
and the processing center periodically forms a state record according to the state parameters of the intelligent electric appliance acquired in a preset time period.
3. The method according to claim 1, wherein before the processing center analyzes the status record according to a preset algorithm to obtain the handling status of the smart appliance, the method further comprises:
judging whether the state record meets a preset condition or not;
under the condition that a preset condition is met, the processing center determines to analyze the state record according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance;
and under the condition that the preset condition is not met, the intelligent electric appliance enters a preset state according to default preset.
4. The method of claim 1,
the processing center obtains the state parameters of the intelligent electrical appliance to form a state record, and the state record comprises the following steps: the processing center acquires the time parameters of the on-off of the intelligent electric appliance to form an on-off record;
the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance, and the method comprises the following steps: the processing center processes the startup and shutdown record according to the preset algorithm to obtain the startup and shutdown time of the intelligent electric appliance;
the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the handling state, and the method comprises the following steps: and the processing center issues a power on/off instruction to the intelligent electric appliance to control the intelligent electric appliance to be powered on/off at the power on/off time.
5. The method of claim 4, wherein the time parameter comprises: the method comprises the steps of user ID, SSID (service set identifier) and MAC (media access control) address of the intelligent electric appliance and the time for the intelligent electric appliance to be connected with a network.
6. The method of claim 1, wherein the status parameters include operating parameters of the smart appliance;
the processing center obtains the state parameters of the intelligent electrical appliance to form a state record, and the state record comprises the following steps: the processing center acquires working parameters of the intelligent electric appliance to form a working record;
the processing center analyzes the state record according to a preset algorithm to obtain the handling state of the intelligent electric appliance, and the method comprises the following steps: the processing center processes the working record according to the preset algorithm to obtain the working state of the intelligent electric appliance;
the processing center issues an adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the handling state, and the method comprises the following steps: and the processing center issues a working state adjusting instruction to the intelligent electric appliance to control the intelligent electric appliance to enter the working state.
7. The method of claim 6, wherein the operating parameters comprise:
the running state of the intelligent electric appliance, the working time period of the intelligent electric appliance, the working date of the intelligent electric appliance, the MAC address and the starting-up times.
8. The method of any one of claims 1 to 7, wherein the pre-set algorithm comprises a big data Haodu computing framework.
9. An apparatus for self-adjusting an intelligent electrical appliance, the apparatus comprising:
the recording module is used for acquiring the state parameters of the intelligent electrical appliance by the processing center to form a state record;
the algorithm module is used for analyzing the state record by the processing center according to a preset algorithm to obtain the corresponding state of the intelligent electric appliance;
the adjusting module is used for issuing an adjusting instruction to the intelligent electric appliance by the processing center based on the acquired handling state so as to control the intelligent electric appliance to enter the handling state;
the method comprises the steps that a home WIFI network is accessed when the intelligent electric appliance distribution network is successful, the state parameters comprise the time parameters of the on-off of the intelligent electric appliance, the time point when a user mobile terminal is connected with the home WIFI network is used as the time parameters of the on-off of the intelligent electric appliance, and the time point when the user mobile terminal is disconnected with the home WIFI network is used as the time parameters of the on-off of the intelligent electric appliance;
the state parameters further include: environmental data and setup data during the power-on and power-off cycle;
the environmental data and setting data during the power on and power off cycle include: the latest indoor temperature, set mode and set wind speed data at the departure time within five minutes before starting up; setting the temperature, the mode and the wind speed data of the last indoor temperature within three minutes after starting up; and the latest data with changed set temperature, set mode and set wind speed three minutes after starting the machine.
10. The apparatus of claim 9, wherein the recording module comprises:
and the recording unit is used for periodically forming a state record by the processing center according to the state parameters of the intelligent electrical appliance acquired within a preset time period.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method of any one of claims 1 to 8 when executing the program.
12. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.
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Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109240114A (en) * | 2018-10-26 | 2019-01-18 | 无锡小天鹅股份有限公司 | Appliances equipment control method, device, electronic equipment and storage medium |
| CN109669361A (en) * | 2018-12-26 | 2019-04-23 | 北京理工华汇智能科技有限公司 | Intelligentized Furniture system control method and device |
| CN110542806B (en) * | 2019-07-23 | 2020-10-23 | 珠海格力电器股份有限公司 | Method and system for self-checking electric appliance fault |
| CN110687817B (en) * | 2019-11-05 | 2023-03-21 | 深圳市欧瑞博科技股份有限公司 | Intelligent household control method and device, terminal and computer readable storage medium |
| CN110794700A (en) * | 2019-11-26 | 2020-02-14 | 国网电子商务有限公司 | Family energy efficiency optimization system, method and device |
| CN111680057B (en) * | 2020-06-15 | 2023-09-26 | 广州兰石技术开发有限公司 | Intelligent control method for thermal parameter laboratory |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013012547A1 (en) * | 2011-06-30 | 2013-01-24 | Lutron Electronics Co., Inc. | Load control device having internet connectivity, and method of programming the same using a smart phone |
| CN104350335A (en) * | 2013-02-20 | 2015-02-11 | 松下电器（美国）知识产权公司 | Program and method for controlling portable information terminal |
| CN104866250A (en) * | 2014-06-27 | 2015-08-26 | 广东美的环境电器制造有限公司 | Household appliance, control system and method of household appliance, mobile terminal and cloud server |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101861013B (en) * | 2010-04-30 | 2013-06-05 | 鸿富锦精密工业（深圳）有限公司 | Intelligent lamp and control method thereof |
| CN101937194B (en) * | 2010-09-27 | 2012-12-19 | 鸿富锦精密工业（深圳）有限公司 | Intelligence control system with learning function and method thereof |
| CN102945029B (en) * | 2012-10-31 | 2014-12-10 | 鸿富锦精密工业（深圳）有限公司 | Intelligent gateway, smart home system and intelligent control method for home appliance equipment |
| CN104092775B (en) * | 2014-07-24 | 2017-11-03 | 福州瑞芯微电子股份有限公司 | Intelligent appliance self-learning method and system |
| TWI607191B (en) * | 2014-08-15 | 2017-12-01 | 台達電子工業股份有限公司 | Ventilation equipment having dirty filter detecting function and detecting method of the ventilation equipment |
| CN104618441A (en) * | 2014-12-30 | 2015-05-13 | 广东美的制冷设备有限公司 | Control method and device of controlled device, server, and control terminal of internet of things |
| CN104618443B (en) * | 2014-12-30 | 2019-03-08 | 广东美的制冷设备有限公司 | Control method and device, server, the Internet of Things controlling terminal of controlled device |
| CN104881983B (en) * | 2015-05-22 | 2018-12-25 | 广东美的暖通设备有限公司 | Household electrical appliances self-learning method, household electrical appliances self learning system and household electrical appliances |
| CN106200410A (en) * | 2016-08-31 | 2016-12-07 | 山东智慧生活数据系统有限公司 | A kind of for home intelligent energy-saving control system |
| CN106383450A (en) * | 2016-11-10 | 2017-02-08 | 北京工商大学 | Smart home user behavior analyzing system and smart home user behavior analyzing method based on big data |
-
2017
- 2017-12-04 CN CN201711260870.2A patent/CN108052010B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013012547A1 (en) * | 2011-06-30 | 2013-01-24 | Lutron Electronics Co., Inc. | Load control device having internet connectivity, and method of programming the same using a smart phone |
| CN104350335A (en) * | 2013-02-20 | 2015-02-11 | 松下电器（美国）知识产权公司 | Program and method for controlling portable information terminal |
| CN104866250A (en) * | 2014-06-27 | 2015-08-26 | 广东美的环境电器制造有限公司 | Household appliance, control system and method of household appliance, mobile terminal and cloud server |
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|---|---|
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