CN105629947B - Home equipment monitoring method, home equipment monitoring device and terminal - Google Patents
Home equipment monitoring method, home equipment monitoring device and terminal Download PDFInfo
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- CN105629947B CN105629947B CN201510863954.XA CN201510863954A CN105629947B CN 105629947 B CN105629947 B CN 105629947B CN 201510863954 A CN201510863954 A CN 201510863954A CN 105629947 B CN105629947 B CN 105629947B
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- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000012544 monitoring process Methods 0.000 title claims abstract description 18
- 238000012806 monitoring device Methods 0.000 title claims abstract description 16
- 230000002159 abnormal effect Effects 0.000 claims abstract description 34
- 230000008569 process Effects 0.000 claims description 11
- 238000001816 cooling Methods 0.000 claims description 9
- 238000010606 normalization Methods 0.000 claims description 5
- 230000006399 behavior Effects 0.000 abstract description 16
- 238000001514 detection method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 238000010801 machine learning Methods 0.000 description 5
- 238000011156 evaluation Methods 0.000 description 4
- 238000003909 pattern recognition Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000007405 data analysis Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 206010000117 Abnormal behaviour Diseases 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 2
- 238000004378 air conditioning Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000012502 risk assessment Methods 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000005406 washing Methods 0.000 description 1
Classifications
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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
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
-
- 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] or computer integrated manufacturing [CIM]
-
- 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] or computer integrated manufacturing [CIM]
- G05B19/4183—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] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
-
- 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
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0267—Fault communication, e.g. human machine interface [HMI]
- G05B23/027—Alarm generation, e.g. communication protocol; Forms of alarm
-
- 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
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0286—Modifications to the monitored process, e.g. stopping operation or adapting control
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Human Computer Interaction (AREA)
- Alarm Systems (AREA)
- Telephonic Communication Services (AREA)
Abstract
The invention proposes a kind of home equipment monitoring method, a kind of home equipment monitoring device and a kind of terminals, wherein the home equipment monitoring method includes: the real-time traffic information for acquiring home equipment；According to the real-time traffic information, characteristic model is established for the home equipment；The characteristic model is compared with the preset model of the safety of the home equipment by Bayes classifier, whether is abnormal with the determination real-time traffic information.According to the technical solution of the present invention, the different usage behaviors and inertia mode of user can be distinguished, identify the abnormal real-time traffic information of home equipment in time in this feature model and the preset unmatched models of safety, safety and convenience of the user using home equipment are improved, is also convenient for adjusting the operating status of home equipment according to the practical habit of user.
Description
Technical field
The present invention relates to field of terminal technology, in particular to a kind of home equipment monitoring method, a kind of home equipment
Monitoring device and a kind of terminal.
Background technique
Currently, smart home (smart home) is a branch of technology of Internet of things, smart home passes through Internet of Things skill
Art is by the various equipment in subscriber household, for example, the control of video system, lighting system, curtain, airconditioning control, security system, net
Network household electrical appliances etc. connect together, and provide home wiring control, Lighting control, remote control using telephone, indoor and outdoor remote control, burglar alarm, ring
Multiple functions and the means such as border monitoring, HVAC control, infrared forwarding and programmable Timer control.
Presently, there are smart home system be confined to one-to-one control action mostly, or using mobile terminal to intelligence
The remote control of energy household is lacked one and is effectively fed back based on user behavior or using the risk assessment of inertia and trusted
System.In addition, many preset programs are all factory settings, the actual demand of each family can not be met very well.
Therefore a kind of new technical solution is needed, safety and convenience that user uses home equipment can be further promoted
Property.
Summary of the invention
The present invention is based on the above problems, proposes a kind of new technical solution, can further promote user's use
The safety of home equipment and convenience.
In view of this, an aspect of of the present present invention proposes a kind of home equipment monitoring method, comprising: acquire home equipment
Real-time traffic information；According to the real-time traffic information, characteristic model is established for the home equipment；Pass through Bayes classifier
The characteristic model is compared with the preset model of the safety of the home equipment, with the determination real-time traffic information whether
It is abnormal.
In the technical scheme, characteristic model, and and home equipment are established by the real-time traffic information for home equipment
The preset model of safety matched, the different usage behaviors and inertia mode of user can be distinguished, this feature model and peace
The abnormal real-time traffic information for identifying home equipment when complete preset unmatched models in time improves user and uses home equipment
Safety and convenience are also convenient for adjusting the operating status of home equipment according to the practical habit of user.In addition, exception information is commented
Estimate the Bayes classifier with detection using minimum risk, Bayesian network of the Bayes classifier for classification, evaluation
The standard of this classifier is average risk, its average risk is minimum, carries out real-time control to household by this classifier,
Can protect home equipment using safe, reduce risk.
In the above-mentioned technical solutions, it is preferable that it is described according to the real-time traffic information, it is established for the home equipment special
Model is levied, specifically includes: being that each home equipment establishes a corresponding n dimensional vector n in every kind of real-time traffic information；
According to it is described establish a corresponding n dimensional vector n as a result, establishing corresponding characteristic model for every kind of real-time traffic information.
In the technical scheme, corresponding characteristic model, each character modules can all be established for every kind of real-time traffic information
Each home equipment has a corresponding n dimensional vector n in type.Specifically, pattern-recognition can be used and machine learning building is used
The characteristic model when normal use at family, it is right for predicting the abnormal use information of home equipment jointly with the preset model of safety
In every kind of real-time traffic information, different home equipments is represented using a n dimensional vector n, for example, for using duration, because
The distinct device of each family be using duration it is inconsistent, there are use habit, the influence of the variance factors such as rule of life,
Therefore to when using the duration to model, if vector P_order={ p0, p1..., pi..., pN-1, pN, wherein 0≤i < N,
N is the number of home equipment, piFor the use duration of each home equipment, every kind of real-time traffic information is established in this way
Characteristic vector, to obtain characteristic model.
In any of the above-described technical solution, it is preferable that before the real-time traffic information of the acquisition home equipment, also wrap
It includes: acquiring the initial run information of the home equipment；According to the initial run information, for described in home equipment foundation
The preset model of safety.
In the technical scheme, need to acquire the initial run information of home equipment, to determine the usage behavior of user
And inertia mode, and the preset model of safety is established with this, so as to the characteristic model that will be obtained by the real-time traffic information of user with
The preset model of safety determines whether real-time traffic information meets the inertia mode of user compared to relatively, can be judged as when not meeting
It is abnormal, it is i.e. capable of emitting at this time to warn, or directly stop the running of the home equipment.By the technical solution, it is convenient for
The abnormal real-time traffic information for further identifying home equipment in time in characteristic model and the preset unmatched models of safety, is promoted
User uses the safety of home equipment.
In any of the above-described technical solution, it is preferable that be the home equipment described according to the real-time traffic information
It establishes before characteristic model, further includes: the collected real-time traffic information is pre-processed, the pretreatment includes losing
Abandon invalid data；The pretreated real-time traffic information is normalized.
In the technical scheme, before modeling, data prediction can be carried out, it is invalid in real-time traffic information to remove
Information retains effective information, promotes treatment effeciency in the next steps.In addition, pretreated real-time traffic information is carried out
Normalized carries out pretreated real-time traffic information according to the type of real-time traffic information, each home equipment
Classification, to promote modeling efficiency.
In any of the above-described technical solution, it is preferable that the real-time traffic information includes at least one of or combinations thereof:
The time of running uses duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation
Control Cooling, for operate control home equipment terminal parameter.
In the technical scheme, real-time traffic information includes but is not limited at least one of or combinations thereof: the time of running,
Using duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation Control Cooling,
For operating the parameter of the terminal of control home equipment.By the technical solution, diversified real-time traffic information is built
Mould, can identify the accuracy of the abnormal real-time traffic information of home equipment, and guarantee that user uses the safety of home equipment.
Another aspect of the present invention proposes a kind of home equipment monitoring device, comprising: the first acquisition unit acquires household
The real-time traffic information of equipment；Modeling unit establishes characteristic model according to the real-time traffic information for the home equipment；
Comparing unit is compared the characteristic model with the preset model of the safety of the home equipment by Bayes classifier,
Whether it is abnormal with the determination real-time traffic information.
In the technical scheme, characteristic model, and and home equipment are established by the real-time traffic information for home equipment
The preset model of safety matched, the different usage behaviors and inertia mode of user can be distinguished, this feature model and peace
The abnormal real-time traffic information for identifying home equipment when complete preset unmatched models in time improves user and uses home equipment
Safety and convenience are also convenient for adjusting the operating status of home equipment according to the practical habit of user.In addition, exception information is commented
Estimate the Bayes classifier with detection using minimum risk, Bayesian network of the Bayes classifier for classification, evaluation
The standard of this classifier is average risk, its average risk is minimum, carries out real-time control to household by this classifier,
Can protect home equipment using safe, reduce risk.
In the above-mentioned technical solutions, it is preferable that the modeling unit is specifically used for: in every kind of real-time traffic information
Establish a corresponding n dimensional vector n for each home equipment, and according to it is described establish a corresponding n dimensional vector n as a result, for institute
It states every kind of real-time traffic information and establishes corresponding characteristic model.
In the technical scheme, corresponding characteristic model, each character modules can all be established for every kind of real-time traffic information
Each home equipment has a corresponding n dimensional vector n in type.Specifically, pattern-recognition can be used and machine learning building is used
The characteristic model when normal use at family, it is right for predicting the abnormal use information of home equipment jointly with the preset model of safety
In every kind of real-time traffic information, different home equipments is represented using a n dimensional vector n, for example, for using duration, because
The distinct device of each family be using duration it is inconsistent, there are use habit, the influence of the variance factors such as rule of life,
Therefore to when using the duration to model, if vector P_order={ p0, p1..., pi..., pN-1, pN, wherein 0≤i < N,
N is the number of home equipment, piFor the use duration of each home equipment, every kind of real-time traffic information is established in this way
Characteristic vector, to obtain characteristic model.
In any of the above-described technical solution, it is preferable that further include: the second acquisition unit, in the acquisition home equipment
Before real-time traffic information, the initial run information of the home equipment is acquired；Initial modeling unit, according to the initial launch
Information establishes the preset model of the safety for the home equipment.
In the technical scheme, need to acquire the initial run information of home equipment, to determine the usage behavior of user
And inertia mode, and the preset model of safety is established with this, so as to the characteristic model that will be obtained by the real-time traffic information of user with
The preset model of safety determines whether real-time traffic information meets the inertia mode of user compared to relatively, can be judged as when not meeting
It is abnormal, it is i.e. capable of emitting at this time to warn, or directly stop the running of the home equipment.By the technical solution, it is convenient for
The abnormal real-time traffic information for further identifying home equipment in time in characteristic model and the preset unmatched models of safety, is promoted
User uses the safety of home equipment.
In any of the above-described technical solution, it is preferable that further include: pretreatment unit, described according to the real time execution
Information is established before characteristic model for the home equipment, is pre-processed to the collected real-time traffic information, described
Pretreatment includes abandoning invalid data；Place is normalized to the pretreated real-time traffic information in normalization unit
Reason.
In the technical scheme, before modeling, data prediction can be carried out, it is invalid in real-time traffic information to remove
Information retains effective information, promotes treatment effeciency in the next steps.In addition, pretreated real-time traffic information is carried out
Normalized carries out pretreated real-time traffic information according to the type of real-time traffic information, each home equipment
Classification, to promote modeling efficiency.
In any of the above-described technical solution, it is preferable that the real-time traffic information includes at least one of or combinations thereof:
The time of running uses duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation
Control Cooling, for operate control home equipment terminal parameter.
In the technical scheme, real-time traffic information includes but is not limited at least one of or combinations thereof: the time of running,
Using duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation Control Cooling,
For operating the parameter of the terminal of control home equipment.By the technical solution, diversified real-time traffic information is built
Mould, can identify the accuracy of the abnormal real-time traffic information of home equipment, and guarantee that user uses the safety of home equipment.
Another aspect of the invention proposes a kind of terminal, including home equipment described in any one of above-mentioned technical proposal
Monitoring device, therefore, the terminal have skill identical with the home equipment monitoring device described in any one of above-mentioned technical proposal
Art effect, details are not described herein.
By above technical scheme, the different usage behaviors and inertia mode of user can be distinguished, this feature model with
The abnormal real-time traffic information for identifying home equipment when the preset unmatched models of safety in time improves user and uses home equipment
Safety and convenience, be also convenient for according to the practical habit of user adjust home equipment operating status.
Detailed description of the invention
Fig. 1 shows the flow chart of home equipment monitoring method according to an embodiment of the invention；
Fig. 2 shows the block diagrams of home equipment monitoring device according to an embodiment of the invention；
Fig. 3 shows the block diagram of terminal according to an embodiment of the invention；
Fig. 4 shows the flow chart of home equipment monitoring method according to another embodiment of the invention；
Fig. 5 shows the block diagram of home equipment monitoring device according to another embodiment of the invention.
Specific embodiment
To better understand the objects, features and advantages of the present invention, with reference to the accompanying drawing and specific real
Applying mode, the present invention is further described in detail.It should be noted that in the absence of conflict, the implementation of the application
Feature in example and embodiment can be combined with each other.
In the following description, numerous specific details are set forth in order to facilitate a full understanding of the present invention, still, the present invention may be used also
To be implemented using other than the one described here other modes, therefore, protection scope of the present invention is not by described below
Specific embodiment limitation.
Fig. 1 shows the flow chart of home equipment monitoring method according to an embodiment of the invention.
As shown in Figure 1, home equipment monitoring method according to an embodiment of the invention, comprising:
Step 102, the real-time traffic information of home equipment is acquired；
Step 104, according to the real-time traffic information, characteristic model is established for the home equipment；
Step 106, compared by safety preset model of the Bayes classifier to characteristic model and the home equipment
Compared with whether being abnormal with the determination real-time traffic information.
In the technical scheme, characteristic model, and and home equipment are established by the real-time traffic information for home equipment
The preset model of safety matched, the different usage behaviors and inertia mode of user can be distinguished, this feature model and peace
The abnormal real-time traffic information for identifying home equipment when complete preset unmatched models in time improves user and uses home equipment
Safety and convenience are also convenient for adjusting the operating status of home equipment according to the practical habit of user.In addition, exception information is commented
Estimate the Bayes classifier with detection using minimum risk, Bayesian network of the Bayes classifier for classification, evaluation
The standard of this classifier is average risk, its average risk is minimum, carries out real-time control to household by this classifier,
Can protect home equipment using safe, reduce risk.
In the above-mentioned technical solutions, it is preferable that step 104 specifically includes: being every in every kind of real-time traffic information
A home equipment establishes a corresponding n dimensional vector n；According to it is described establish a corresponding n dimensional vector n as a result, for described every kind
Real-time traffic information establishes corresponding characteristic model.
In the technical scheme, corresponding characteristic model, each character modules can all be established for every kind of real-time traffic information
Each home equipment has a corresponding n dimensional vector n in type.Specifically, pattern-recognition can be used and machine learning building is used
The characteristic model when normal use at family, it is right for predicting the abnormal use information of home equipment jointly with the preset model of safety
In every kind of real-time traffic information, different home equipments is represented using a n dimensional vector n, for example, for using duration, because
The distinct device of each family be using duration it is inconsistent, there are use habit, the influence of the variance factors such as rule of life,
Therefore to when using the duration to model, if vector P_order={ p0, p1..., pi..., pN-1, pN, wherein 0≤i < N,
N is the number of home equipment, piFor the use duration of each home equipment, every kind of real-time traffic information is established in this way
Characteristic vector, to obtain characteristic model.
In any of the above-described technical solution, it is preferable that before step 102 further include: acquire the first of the home equipment
Beginning operation information；According to the initial run information, the preset model of the safety is established for the home equipment.
In the technical scheme, need to acquire the initial run information of home equipment, to determine the usage behavior of user
And inertia mode, and the preset model of safety is established with this, so as to the characteristic model that will be obtained by the real-time traffic information of user with
The preset model of safety determines whether real-time traffic information meets the inertia mode of user compared to relatively, can be judged as when not meeting
It is abnormal, it is i.e. capable of emitting at this time to warn, or directly stop the running of the home equipment.By the technical solution, it is convenient for
The abnormal real-time traffic information for further identifying home equipment in time in characteristic model and the preset unmatched models of safety, is promoted
User uses the safety of home equipment.
In any of the above-described technical solution, it is preferable that before step 104 further include: to the collected real-time fortune
Row information is pre-processed, and the pretreatment includes abandoning invalid data；The pretreated real-time traffic information is carried out
Normalized.
In the technical scheme, before modeling, data prediction can be carried out, it is invalid in real-time traffic information to remove
Information retains effective information, promotes treatment effeciency in the next steps.In addition, pretreated real-time traffic information is carried out
Normalized carries out pretreated real-time traffic information according to the type of real-time traffic information, each home equipment
Classification, to promote modeling efficiency.
In any of the above-described technical solution, it is preferable that the real-time traffic information includes at least one of or combinations thereof:
The time of running uses duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation
Control Cooling, for operate control home equipment terminal parameter.
In the technical scheme, real-time traffic information includes but is not limited at least one of or combinations thereof: the time of running,
Using duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation Control Cooling,
For operating the parameter of the terminal of control home equipment.By the technical solution, diversified real-time traffic information is built
Mould, can identify the accuracy of the abnormal real-time traffic information of home equipment, and guarantee that user uses the safety of home equipment.
Fig. 2 shows the block diagrams of home equipment monitoring device according to an embodiment of the invention.
As shown in Fig. 2, home equipment monitoring device 200 according to an embodiment of the invention, comprising: the first acquisition is single
Member 202, modeling unit 204 and comparing unit 206.
Wherein, the first acquisition unit 202 is used to acquire the real-time traffic information of home equipment；Modeling unit 204 is used for root
According to real-time traffic information, characteristic model is established for home equipment；Comparing unit 206 is used for through Bayes classifier to character modules
Type is compared with the preset model of the safety of home equipment, to determine whether real-time traffic information is abnormal.
In the technical scheme, characteristic model, and and home equipment are established by the real-time traffic information for home equipment
The preset model of safety matched, the different usage behaviors and inertia mode of user can be distinguished, this feature model and peace
The abnormal real-time traffic information for identifying home equipment when complete preset unmatched models in time improves user and uses home equipment
Safety and convenience are also convenient for adjusting the operating status of home equipment according to the practical habit of user.In addition, exception information is commented
Estimate the Bayes classifier with detection using minimum risk, Bayesian network of the Bayes classifier for classification, evaluation
The standard of this classifier is average risk, its average risk is minimum, carries out real-time control to household by this classifier,
Can protect home equipment using safe, reduce risk.
In the above-mentioned technical solutions, it is preferable that modeling unit 204 is specifically used for: being every in every kind of real-time traffic information
A home equipment establishes a corresponding n dimensional vector n, and establishes transporting in real time as a result, being every kind for a corresponding n dimensional vector n according to described
Row information establishes corresponding characteristic model.
In the technical scheme, corresponding characteristic model, each character modules can all be established for every kind of real-time traffic information
Each home equipment has a corresponding n dimensional vector n in type.Specifically, pattern-recognition can be used and machine learning building is used
The characteristic model when normal use at family, it is right for predicting the abnormal use information of home equipment jointly with the preset model of safety
In every kind of real-time traffic information, different home equipments is represented using a n dimensional vector n, for example, for using duration, because
The distinct device of each family be using duration it is inconsistent, there are use habit, the influence of the variance factors such as rule of life,
Therefore to when using the duration to model, if vector P_order={ p0, p1..., pi..., pN-1, pN, wherein 0≤i < N,
N is the number of home equipment, piFor the use duration of each home equipment, every kind of real-time traffic information is established in this way
Characteristic vector, to obtain characteristic model.
In any of the above-described technical solution, it is preferable that further include: the second acquisition unit 208 and initial modeling unit 210.
Wherein, the second acquisition unit 208 is used for before the real-time traffic information of acquisition home equipment, acquires home equipment
Initial run information；Initial modeling unit 210 is used for according to initial run information, establishes the preset mould of safety for home equipment
Type.
In the technical scheme, need to acquire the initial run information of home equipment, to determine the usage behavior of user
And inertia mode, and the preset model of safety is established with this, so as to the characteristic model that will be obtained by the real-time traffic information of user with
The preset model of safety determines whether real-time traffic information meets the inertia mode of user compared to relatively, can be judged as when not meeting
It is abnormal, it is i.e. capable of emitting at this time to warn, or directly stop the running of the home equipment.By the technical solution, it is convenient for
The abnormal real-time traffic information for further identifying home equipment in time in characteristic model and the preset unmatched models of safety, is promoted
User uses the safety of home equipment.
In any of the above-described technical solution, it is preferable that further include: pretreatment unit 212 and normalization unit 214.
Wherein, pretreatment unit 212 is used to establish before characteristic model according to real-time traffic information for home equipment,
Collected real-time traffic information is pre-processed, pretreatment includes abandoning invalid data；Normalization unit 214 for pair
Pretreated real-time traffic information is normalized.
In the technical scheme, before modeling, data prediction can be carried out, it is invalid in real-time traffic information to remove
Information retains effective information, promotes treatment effeciency in the next steps.In addition, pretreated real-time traffic information is carried out
Normalized carries out pretreated real-time traffic information according to the type of real-time traffic information, each home equipment
Classification, to promote modeling efficiency.
In any of the above-described technical solution, it is preferable that real-time traffic information includes at least one of or combinations thereof: operation
Moment is controlled using duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation
Type, for operate control home equipment terminal parameter.
In the technical scheme, real-time traffic information includes but is not limited at least one of or combinations thereof: the time of running,
Using duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments, operation Control Cooling,
For operating the parameter of the terminal of control home equipment.By the technical solution, diversified real-time traffic information is built
Mould, can identify the accuracy of the abnormal real-time traffic information of home equipment, and guarantee that user uses the safety of home equipment.
Fig. 3 shows the block diagram of terminal according to an embodiment of the invention.
As shown in figure 3, terminal 300 according to an embodiment of the invention, including Fig. 2 shows home equipment monitor dress
Set 200, therefore, the terminal 300 have and Fig. 2 shows the identical technical effect of home equipment monitoring device 200, herein no longer
It repeats.
Fig. 4 shows the flow chart of home equipment monitoring method according to another embodiment of the invention.
As shown in figure 4, home equipment monitoring method according to another embodiment of the invention, comprising:
Step 402, pass through the real-time traffic information of data collecting module collected home equipment.For example, whether detecting air-conditioning
It opens, whether curtain is pulled on, and whether door closes, and whether washing machine operates, indoor temperature value, humidity value etc..
Step 404, information pre-processing is carried out for home equipment.
Step 406, it is modeled according to pretreated real-time traffic information.
Step 408, determine whether real-time traffic information is abnormal by Bayes classifier, when judging result is yes
When, 410 are entered step, otherwise, return step 402.
Step 410, it issues warning and/or security control is carried out to fitment.
Specifically, as shown in figure 5, step described in embodiment in combination with Fig. 4, home equipment monitor system 500
Including data analysis module 502 and data acquisition module 504.
Wherein, data analysis module 502 receive data acquisition module 504 from the upload data that home equipment 600 obtains into
Row analysis, carries out Modeling analysis, and user uses the characteristic model 506 and the built-in preset model 508 of safety established in real time
It is matched.The result of analysis is sent to data feedback module 510 by data analysis module 502.
Wherein, the behavior pattern of user includes: setting time, i.e. the time to home equipment setting；Setup parameter is used
The parameter that family is often set；Setting sequence, i.e., the operating process of any home equipment and the operation order of single home equipment；Make
With duration, i.e. Various Seasonal, the period is to the use durations of different home equipments；Action type, including mobile terminal operation, family
Front yard computer operation, cloud platform operation etc.；Device parameter is operated, for example, the operation device parameter of mobile terminal includes that operation is set
Standby model, producer address, identification code address etc., the operation device parameter of cloud platform operation include including browser type, version
Deng.
In addition, home equipment monitoring system 500 further includes data preprocessing module, for handling acquisition data, remain with
With data, hash is abandoned, carries out data normalization processing.
It further includes characteristic vector generation module that home equipment, which monitors system 500, can be for every kind of real-time traffic information all
Corresponding characteristic model is established, each home equipment has a corresponding n dimensional vector n in each characteristic model.It specifically, can be with
The characteristic model when normal use of use pattern identification and machine learning building user, for jointly pre- with the preset model of safety
The abnormal use information for surveying home equipment represents different households using a n dimensional vector n for every kind of real-time traffic information
Equipment, for example, for using duration because the distinct device of each family be using duration it is inconsistent, exist using practising
It is used, the influence of the variance factors such as rule of life, therefore to when using the duration to model, if vector P_order={ p0,
p1..., pi..., pN-1, pN, wherein 0≤i < N, N are the number of home equipment, piFor each home equipment use when
It is long, characteristic vector is established for every kind of real-time traffic information in this way, to obtain characteristic model.
It further includes Bayes classifier that home equipment, which monitors system 500, by the normal and abnormal state information of home equipment
Feed back to user.User is as needed, can carry out real-time operation to home equipment.Wherein exception information assessment is usually adopted with detection
With Least risk Bayes classifier.Bayes classifier is the Bayesian network for classification, should include class knot in the network
Point C, wherein the value of C is from class set { c1, c2..., cm, it also include one group of node X={ X1, X2.., Xn, it indicates to use
In the feature of classification.For Bayes classifier, if a certain sample D to be sorted, characteristic of division value is x={ x1, x2...,
xn, then sample D belongs to classification ciProbability P (C=ci|X1=x1, X2={ x2..., Xn=xn, { i=1,2 ..., m } should expire
Foot formula:
P (C=ci| X=x)=ax { P (C=c1| X=x), P (C=c2| X=x) ..., P (C=cm| X=x) }
Due to the complexity of objective things and the Different Effects of extraneous factor, Bayes classifier classifier is made respectively
Risk when kind judgement is different.For example, abnormal behaviour is mistaken for the risk of normal behaviour just than missing normal behaviour
The risk for being judged to abnormal behaviour is big.Therefore, the concept that risk is introduced in Bayes classifier, needs root in practical applications
The size of various risks is determined according to concrete condition, usually with one group of coefficient CijIt indicates, CijPresentation class device is by identified sample
It is classified as ωi, and the real classification of the sample is ωjWhen risk.The basic thought of design minimum risk classifier is: after use
It tests probability calculation and x is classified as ωiMore each R of conditional riski(x) size classification corresponding with minimum value is the knot of classification
Fruit.The standard for evaluating this classifier is average risk, its average risk is minimum.
Home equipment monitoring system 500 further includes abnormality warnings and control module 512, abnormality warnings and control module 512
According to abstract characteristics, user behavior vector is established, is modeled and is assessed by Bayes classifier and detecting step is to user 700
Abnormal use information is prompted, the instruction of user 700 is received, real-time control is carried out to household, to protect the use of smart home
Safety reduces risk.
The technical scheme of the present invention has been explained in detail above with reference to the attached drawings, according to the technical solution of the present invention, can distinguish
The different usage behaviors and inertia mode of user identify that household is set when this feature model is with the preset unmatched models of safety in time
Standby abnormal real-time traffic information improves safety and convenience of the user using home equipment, is also convenient for according to user's
The operating status of practical habit adjustment home equipment.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (7)
1. a kind of home equipment monitoring method characterized by comprising
Acquire the real-time traffic information of home equipment；
According to the real-time traffic information, characteristic model is established for the home equipment；
Characteristic model is compared with the preset model of the safety of the home equipment by Bayes classifier, described in determination
Whether real-time traffic information is abnormal；
Before the real-time traffic information of the acquisition home equipment, further includes:
Acquire the initial run information of the home equipment；
According to the initial run information, the preset model of the safety is established for the home equipment；
It is described according to the real-time traffic information, establish characteristic model for the home equipment, specifically include:
It is that each home equipment establishes a corresponding n dimensional vector n in every kind of real-time traffic information；
According to it is described establish a corresponding n dimensional vector n as a result, establishing corresponding character modules for every kind of real-time traffic information
Type.
2. home equipment monitoring method according to claim 1, which is characterized in that believed described according to the real time execution
Breath is established before characteristic model for the home equipment, further includes:
The collected real-time traffic information is pre-processed, the pretreatment includes abandoning invalid data；
The pretreated real-time traffic information is normalized.
3. home equipment monitoring method according to claim 2, which is characterized in that the real-time traffic information includes following
At least one or combinations thereof:
The time of running, using duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments,
Operate Control Cooling, for operating the parameter for controlling the terminal of home equipment.
4. a kind of home equipment monitoring device characterized by comprising
First acquisition unit acquires the real-time traffic information of home equipment；
Modeling unit establishes characteristic model according to the real-time traffic information for the home equipment；
Comparing unit is compared by the preset model of safety of the Bayes classifier to the characteristic model and the home equipment
Compared with whether being abnormal with the determination real-time traffic information；
Second acquisition unit acquires the initial of the home equipment before the real-time traffic information of the acquisition home equipment
Operation information；
Initial modeling unit establishes the preset model of the safety according to the initial run information for the home equipment；
The modeling unit is specifically used for:
It is that each home equipment establishes a corresponding n dimensional vector n, and is built according to described in every kind of real-time traffic information
Stand a corresponding n dimensional vector n as a result, establish corresponding characteristic model for every kind of real-time traffic information.
5. home equipment monitoring device according to claim 4, which is characterized in that further include:
Pretreatment unit is established before characteristic model described according to the real-time traffic information for the home equipment, to adopting
The real-time traffic information collected is pre-processed, and the pretreatment includes abandoning invalid data；
The pretreated real-time traffic information is normalized in normalization unit.
6. home equipment monitoring device according to claim 5, which is characterized in that the real-time traffic information includes following
At least one or combinations thereof:
The time of running, using duration, operating parameter, the operating process of any home equipment, the operation order of multiple home equipments,
Operate Control Cooling, for operating the parameter for controlling the terminal of home equipment.
7. a kind of terminal, which is characterized in that including the home equipment monitoring device as described in any one of claim 4 to 6.
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| CN106842970B (en) * | 2017-02-24 | 2019-09-20 | 清华大学 | A kind of monitoring device and monitoring method |
| CN108415262A (en) * | 2018-03-06 | 2018-08-17 | 西北工业大学 | Control method of the intelligent gateway to household appliance |
| CN110209127A (en) * | 2019-03-29 | 2019-09-06 | 深圳市九洲电器有限公司 | Intelligent house security control method |
| CN112165453B (en) * | 2020-09-01 | 2021-07-20 | 珠海格力电器股份有限公司 | Intelligent equipment anti-intrusion method and device, intelligent equipment and server |
| CN112346349B (en) * | 2020-10-22 | 2022-07-15 | 珠海格力电器股份有限公司 | Control method and device of intelligent equipment, electronic equipment and storage medium |
| CN112415981A (en) * | 2020-11-10 | 2021-02-26 | 珠海格力电器股份有限公司 | Abnormal state detection method of intelligent household appliance, storage medium and computer equipment |
| CN112558493A (en) * | 2020-12-22 | 2021-03-26 | 珠海格力电器股份有限公司 | Intelligent equipment interaction method and device, intelligent central control equipment and storage medium |
| CN114265324B (en) * | 2021-12-23 | 2023-07-28 | 建信金融科技有限责任公司 | Method and device for monitoring running state of equipment and terminal equipment |
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