CN109116746A - A kind of smart home system - Google Patents
A kind of smart home system Download PDFInfo
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- CN109116746A CN109116746A CN201810960921.0A CN201810960921A CN109116746A CN 109116746 A CN109116746 A CN 109116746A CN 201810960921 A CN201810960921 A CN 201810960921A CN 109116746 A CN109116746 A CN 109116746A
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- 238000012544 monitoring process Methods 0.000 claims abstract description 42
- 230000007123 defense Effects 0.000 claims abstract description 20
- 230000007613 environmental effect Effects 0.000 claims abstract description 17
- 238000004891 communication Methods 0.000 claims abstract description 6
- 230000004913 activation Effects 0.000 claims description 16
- 238000013507 mapping Methods 0.000 claims description 15
- 238000004364 calculation method Methods 0.000 claims description 11
- 238000012360 testing method Methods 0.000 claims description 9
- 230000005284 excitation Effects 0.000 claims description 4
- 238000000034 method Methods 0.000 claims description 4
- 239000000284 extract Substances 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 2
- 238000005457 optimization Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 claims description 2
- 230000008901 benefit Effects 0.000 abstract description 2
- 238000001514 detection method Methods 0.000 description 5
- 238000012549 training Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- KLDZYURQCUYZBL-UHFFFAOYSA-N 2-[3-[(2-hydroxyphenyl)methylideneamino]propyliminomethyl]phenol Chemical compound OC1=CC=CC=C1C=NCCCN=CC1=CC=CC=C1O KLDZYURQCUYZBL-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 201000001098 delayed sleep phase syndrome Diseases 0.000 description 1
- 208000033921 delayed sleep phase type circadian rhythm sleep disease Diseases 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 238000013519 translation 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
- 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] or computer integrated manufacturing [CIM]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/26—Pc applications
- G05B2219/2642—Domotique, domestic, home control, automation, smart house
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- Quality & Reliability (AREA)
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Abstract
The present invention provides a kind of smart home system, including environmental monitoring system, safety defense monitoring system, home gateway and intelligent terminal；The environmental monitoring system and safety defense monitoring system with the home gateway communication connection；The home gateway is used to the monitoring information that the environmental monitoring system and safety defense monitoring system respectively obtain being sent to intelligent terminal in real time, and household terminal is controlled according to the control signal that the intelligent terminal is sent, the environmental monitoring system is for detecting air quality, and the safety defense monitoring system is for obtaining off-the-air picture and detecting to act of violence in image.The invention has the benefit that providing a kind of smart home system, Intelligent housing and security protection are realized.
Description
Technical field
The present invention relates to Smart Home technical fields, and in particular to a kind of smart home system.
Background technique
With the rapid development of science and technology, smart home system has become the project of industry focus.Intelligent family
Residence be using house as platform, it is related with home life using network communication technology, security precautions technology, automatic control technology etc.
Equipment is integrated, and the management system of schedule affairs in efficient housing facilities and family is constructed, and promotes house security, convenience
Property, comfort.
Summary of the invention
In view of the above-mentioned problems, the present invention provides a kind of smart home system.
The purpose of the present invention is realized using following technical scheme:
Provide a kind of smart home system, including environmental monitoring system, safety defense monitoring system, home gateway and intelligence
Terminal；The environmental monitoring system and safety defense monitoring system with the home gateway communication connection；The home gateway is used for
The monitoring information that the environmental monitoring system and safety defense monitoring system respectively obtain is sent to intelligent terminal in real time, and according to institute
The control signal control household terminal of intelligent terminal transmission is stated, the environmental monitoring system is used to detect air quality,
The safety defense monitoring system is for obtaining off-the-air picture and detecting to act of violence in image.
The invention has the benefit that providing a kind of smart home system, Intelligent housing and security protection are realized.
Detailed description of the invention
The present invention will be further described with reference to the accompanying drawings, but the embodiment in attached drawing is not constituted to any limit of the invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is structural schematic diagram of the invention；
Appended drawing reference:
Environmental monitoring system 1, safety defense monitoring system 2, home gateway 3, intelligent terminal 4.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of smart home system of the present embodiment, including environmental monitoring system 1, safety defense monitoring system 2, family
Occupy gateway 3 and intelligent terminal 4；The environmental monitoring system 1 and safety defense monitoring system 2, which are communicated with the home gateway 3, to be connected
It connects；The monitoring information that the home gateway 3 is used to respectively obtain the environmental monitoring system 1 and safety defense monitoring system 2 is real-time
It is sent to intelligent terminal 4, and household terminal, the environmental monitoring system are controlled according to the control signal that the intelligent terminal 4 is sent
System 1 is for detecting air quality, and the safety defense monitoring system 2 is for obtaining off-the-air picture and to act of violence in image
It is detected.
A kind of smart home system is present embodiments provided, Intelligent housing and security protection are realized.
Preferably, the safety defense monitoring system 2 includes the first model unit, the second model unit, third model unit, the
Four model units, image output unit, first model unit are used to extract the global characteristics of image, second model
Unit is used for by extracted image overall Fusion Features in depth network model, and the third model unit is based on the second mould
Type unit determines violence testing result, and the 4th model unit is described for optimizing third model unit violence testing result
Image output unit is used to export the violence testing result of optimization.
This preferred embodiment safety defense monitoring system effectively raises the accuracy rate of violence detection.
Preferably, first model unit includes input layer, convolutional calculation layer, excitation layer, pond layer；The input layer
The image of input is pre-processed；The convolutional calculation layer is filtered to image and convolution operation；The excitation layer handle
The output result of convolutional calculation layer does Nonlinear Mapping；The pond layer is for the image after compressive non-linearity mapping；
In convolutional calculation layer, by convolution operation to pretreated image zooming-out local neighborhood feature, change by multilayer
In generation, extracts the global characteristics of image by two-dimensional convolution:In formula
In,Indicating the weight of convolution kernel, i indicates that the convolutional layer that image is currently located, j indicate the Feature Mapping quantity of this layer,Indicate that the activation value in i-th layer of j-th of Feature Mapping at the position (x, y), this activation value are exactly that the two dimension of image is global
Feature；F () indicates activation primitive, wherein H, W respectively indicate the height of two-dimensional convolution core, the size of width；Indicate activation value of (i-1)-th layer of d-th of the Feature Mapping at (x, y), bijIndicate bias vector.
The first model unit of this preferred embodiment by two-dimensional convolution can easily abstract image spatial information, letter
Just, application range is most wide for folk prescription, but is not sufficient to carry out expressed intact to video merely with these appearance features, can make video
It is lacked.
Preferably, the two-dimensional convolution core in the first model unit is generated three by spatial spread by second model unit
Convolution kernel is tieed up, the Three dimensional convolution at pixel (x, y, z) calculates is defined as:In formula,Indicate the weight of convolution kernel, i table
The convolutional layer that diagram picture is currently located, j indicate the Feature Mapping quantity of this layer,It indicates in i-th layer of j-th of Feature Mapping
Activation value at upper position (x, y, z)；This activation value is exactly the three-dimensional global characteristics of image；F () indicates activation primitive,
In, H, W, T respectively indicate the size on height, width and the time dimension of three dimensional convolution kernel；Indicate the
Activation value of i-1 d-th of the Feature Mapping of layer at (x, y, z), bijIndicate bias vector.
Compared with two-dimensional convolution formula, this preferred embodiment the second model unit Three dimensional convolution is to convolution kernel and pixel
Expression on both increase time dimension.After convolution kernel is extended to three-dimensional space, when carrying out convolution to image sequence, convolution
Operation will carried out spatially and temporally simultaneously, and in this way after the operation of convolution sum pondization, the characteristic pattern of output remains image
Sequence can be very good to retain the space time information in video.By the feature extraction of multiple Three dimensional convolutions, so that it may extract view
The global space-time characteristic of frequency.
Preferably, the third model unit is based on the second model unit and uses tri- convolutional calculation layers of CA1, CA2, CA3,
The three dimensional convolution kernel size that CA1, CA2 and CA3 are used is respectively 7 × 7 × 5,5 × 5 × 5 and 3 × 3 × 3 pixels；
The input of the third model unit is the image segments X being made of 40 frame consecutive images；Picture frame is by pre-
After processing, it is normalized to 60 × 90 pixel sizes and is converted to grayscale image；Scalar Y scalar is exported, for indicating model to image
The testing result of input, for trained model, if in test image including Violent scene, output Y is 1, otherwise
Exporting result is 0；
The third model unit carries out pondization operation, the pond to the characteristic pattern that the first two convolutional calculation layer is calculated
Change operation using two-dimentional pondization operation, the pond factor is set to 3 × 3 and 2 × 2 pixels；
During model training, the third model unit cost function are as follows:
In formula, G is pattern function, and θ is model parameter, and X is training sample, and N is sample size, andIt is sample reality
Label, k ∈ [1, N], N ∈ [1 ,+∞], DG1(X, θ) indicates third model unit cost function；Cost function value is smaller to be shown
It is better that model is fitted with training set；
On the one hand this preferred embodiment third model unit can be further reduced network parameter, on the other hand also give
The characteristics such as characteristic pattern translation invariant and invariable rotary, so that the feature acquired is more robust.
Preferably, the 4th model unit is based on third model unit, and input is that 40 frames of 128 × 128 pixels connect
Continuous image, consecutive image are Three Channel Color image；
Three dimensional convolution kernel is uniformly set as to 3 × 3 × 3 pixels, in convolution operation, the 4th model unit carries out characteristic pattern
Padding, so that the size before the characteristic pattern obtained after convolution and calculating holding；Also using three-dimensional during pond
Pondization operation carries out down-sampled operation to input feature vector graphic sequence in time dimension, the pond factor is set as 2 × 2 × 2 pixels；
During model training, the cost function of the 4th model unit are as follows:
In formula, G is pattern function, and θ is model parameter, XkFor k-th of training sample, m is classification number, and N is every class sample
This number,It is k-th of data physical tags；K ∈ [1, N], N ∈ [1 ,+∞], l ∈ [1, m], m ∈ [1 ,+∞], DG2(X, θ) table
Show the 4th model unit cost function.
The 4th model unit of this preferred embodiment uses more complicated structure, therefore the image data dimension handled can
With higher, the extraction of image temporal information can be accelerated in this way, remove bulk redundancy therein.
Safety monitoring is carried out using smart home system of the present invention, 5 families is chosen and is tested, respectively family 1, family
Front yard 2, family 3, family 4, family 5 count violence Detection accuracy and violence detection speed, compared with violence detection system
System is compared, and generation has the beneficial effect that shown in table:
| Violence Detection accuracy improves | Violence detects speed and improves | |
| Family 1 | 29% | 27% |
| Family 2 | 27% | 26% |
| Family 3 | 26% | 26% |
| Family 4 | 25% | 24% |
| Family 5 | 24% | 22% |
Through the above description of the embodiments, those skilled in the art can be understood that it should be appreciated that can
To realize the embodiments described herein with hardware, software, firmware, middleware, code or its any appropriate combination.For hardware
It realizes, processor can be realized in one or more the following units: specific integrated circuit (ASIC), digital signal processor
(DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processing
Device, controller, microcontroller, microprocessor, other electronic units designed for realizing functions described herein or combinations thereof.
For software implementations, some or all of embodiment process can instruct relevant hardware to complete by computer program.
When realization, above procedure can be stored in computer-readable medium or as the one or more on computer-readable medium
Instruction or code are transmitted.Computer-readable medium includes computer storage media and communication media, wherein communication media packet
It includes convenient for from a place to any medium of another place transmission computer program.Storage medium can be computer can
Any usable medium of access.Computer-readable medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other
Optical disc storage, magnetic disk storage medium or other magnetic storage apparatus or can be used in carry or store have instruction or data
The desired program code of structure type simultaneously can be by any other medium of computer access.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered
Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (7)
1. a kind of smart home system, which is characterized in that including environmental monitoring system, safety defense monitoring system, home gateway and
Intelligent terminal；The environmental monitoring system and safety defense monitoring system with the home gateway communication connection；The home gateway
Monitoring information for respectively obtaining the environmental monitoring system and safety defense monitoring system is sent to intelligent terminal, and root in real time
Household terminal is controlled according to the control signal that the intelligent terminal is sent, the environmental monitoring system is for examining air quality
It surveys, the safety defense monitoring system is for obtaining off-the-air picture and detecting to act of violence in image.
2. smart home system according to claim 1, which is characterized in that the safety defense monitoring system includes the first model
Unit, the second model unit, third model unit, the 4th model unit, image output unit, first model unit are used for
The global characteristics of image are extracted, second model unit is used for extracted image overall Fusion Features in depth network
In model, the third model unit determines violence testing result based on the second model unit, and the 4th model unit is used for
Optimize third model unit violence testing result, described image output unit is used to export the violence testing result of optimization.
3. smart home system according to claim 2, which is characterized in that first model unit include input layer,
Convolutional calculation layer, excitation layer, pond layer；The input layer pre-processes the image of input；The convolutional calculation layer is to figure
Picture is filtered and convolution operation；The output result of convolutional calculation layer is done Nonlinear Mapping by the excitation layer；The pond
Layer is for the image after compressive non-linearity mapping.
4. smart home system according to claim 3, which is characterized in that in the convolutional calculation layer, grasped by convolution
Pretreated image zooming-out local neighborhood feature of opposing extracts the overall situation of image by two-dimensional convolution by Multilevel Iteration
Feature:In formula,Indicate the weight of convolution kernel, i indicates figure
As the convolutional layer being currently located, j indicates the Feature Mapping quantity of this layer,Indicate in i-th layer of j-th of Feature Mapping (x,
Y) activation value at position, this activation value are exactly the two-dimentional global characteristics of image；F () indicates activation primitive, wherein H, W points
Not Biao Shi two-dimensional convolution core height, the size of width；Indicate (i-1)-th layer of d-th of Feature Mapping at (x, y)
The activation value at place, bijIndicate bias vector.
5. smart home system according to claim 4, which is characterized in that second model unit is by the first model list
Two-dimensional convolution core in member generates three dimensional convolution kernel by spatial spread, and the Three dimensional convolution at pixel (x, y, z) calculates fixed
Justice are as follows:In formula,Indicate the power of convolution kernel
Weight, i indicate that the convolutional layer that image is currently located, j indicate the Feature Mapping quantity of this layer,It indicates in i-th layer of j-th of spy
Sign maps the activation value at upper position (x, y, z)；This activation value is exactly the three-dimensional global characteristics of image；F () indicates activation letter
Number, wherein H, W, T respectively indicate the size on height, width and the time dimension of three dimensional convolution kernel；
Indicate activation value of (i-1)-th layer of d-th of the Feature Mapping at (x, y, z), bijIndicate bias vector.
6. smart home system according to claim 5, which is characterized in that the third model unit is based on the second model
Unit uses tri- convolutional calculation layers of CAl, CA2, CA3, and the three dimensional convolution kernel size that CA1, CA2 and CA3 are used is respectively 7 × 7
× 5,5 × 5 × 5 and 3 × 3 × 3 pixels.
7. smart home system according to claim 6, which is characterized in that the input of the third model unit is by 40
The image segments X that frame consecutive image is constituted；Picture frame is normalized to 60 × 90 pixel sizes and is converted to after pretreatment
Grayscale image；Scalar Y scalar is exported, for indicating testing result that model input image, for trained model, if survey
Attempt comprising Violent scene as in, then output Y is 1, otherwise exporting result is 0.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112560625A (en) * | 2020-12-09 | 2021-03-26 | 河海大学 | Intelligent household system based on space-time joint response network and control method thereof |
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Cited By (2)
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