CN107800996A - Road vehicles traveling monitoring system based on Internet of Things - Google Patents

Abstract

The present invention relates to a kind of road vehicles based on Internet of Things to travel monitoring system, including vehicle control apparatus, AVR32 chips, high-definition camera and image processing equipment, high-definition camera, it is arranged on inside road vehicles, for being taken pictures to driver to obtain high definition face image, image processing equipment is used to carry out image procossing to high definition face image, AVR32 chips are connected with vehicle control apparatus and image processing equipment respectively, and the control model to vehicle control apparatus is determined for the output based on image processing equipment.By means of the invention it is possible to ensure the legal driving of authorized user's road pavement vehicle.

Description

Road vehicles traveling monitoring system based on Internet of Things

Technical field

The present invention relates to field of vehicle control, more particularly to a kind of road vehicles traveling monitoring system based on Internet of Things.

Background technology

Vehicle is " car " and the general name of the unit " " of car.Car, refer to the vehicles that land wheel rotates；, Metering method from ancient times to car.Car at that time is usually two wheels, therefore Che Yicheng claims one or two, just writes later .As can be seen here, the literal sense of vehicle refers to do not have dynamic car in itself, is carriage with Malaysia traction, employment is people to draw or push away Power car.With the development of science and technology, have again with steam engine automobile for drawing etc..

Although the species of vehicle is more, construction is similar.This is the contribution of standardization, and large-scale production stream The needs of waterline.With the developing of society, the progress of science and technology and the change of demand, the profile of rolling stock begun with change, Especially passenger car is no longer whole-colored familiar faces.But their essential structure does not have great change, simply has The parts of body have more scientific advanced structure design.In general, the essential structure of vehicle is by car body, body frame, traveling Portion, coupler and draft gear and the most of composition of brake apparatus five.

In the prior art, the road vehicles of the road vehicles of traditional energy and the electronic energy turn into family expenses or public main flow Vehicle, generally, the personnel that road vehicles are all recognized by car owner or car owner drive, but criminal's hijacking vehicle also occurs Situation occurs, therefore, it is desirable to which road vehicles differentiate to criminal in itself, and make the action that refusal continues traveling, so The criminal offence of criminal can be contained, avoid traffic accident generation, protects personal safety and the economic interests of car owner.

However, in the prior art and in the absence of such authentication scheme, therefore a kind of, it is necessary to new road vehicles monitoring side Case, authentication scheme can be introduced unauthorized person is effectively differentiated.

The content of the invention

In order to solve the above problems, the invention provides a kind of road vehicles based on Internet of Things to travel monitoring system, changes Road vehicles traveling monitoring system in the prior art is made, human face detection tech is introduced and introduces technology of Internet of things road pavement vehicle Driver carries out identity discriminating, and is reacted in time when finding unauthorized user, is automatically stopped traveling behavior.

According to an aspect of the present invention, there is provided a kind of road vehicles traveling monitoring system based on Internet of Things, the system System includes vehicle control apparatus, AVR32 chips, high-definition camera and image processing equipment, high-definition camera, is arranged on road surface car Inside, for being taken pictures to driver to obtain high definition face image, image processing equipment is used for high definition face image Image procossing is carried out, AVR32 chips are connected with vehicle control apparatus and image processing equipment respectively, for being set based on image procossing Standby output determines the control model to vehicle control apparatus.

More specifically, in the road vehicles traveling monitoring system based on Internet of Things, including：Vehicle control apparatus, Road pavement vehicle is controlled, for when receiving validated user signal, safeguarding that driver's road pavement vehicle continues to drive, It is additionally operable to when receiving disabled user's signal, road vehicles pulling over observing is controlled according to surface conditions；AVR32 chips, respectively More sub- with characteristic vector equipment and vehicle control apparatus are connected, for when receiving recognition of face pass signal, sending conjunction Method subscriber signal, it is additionally operable to receiving recognition of face failure signal, sends disabled user's signal；High-definition camera, it is arranged on Inside road vehicles, for being taken pictures to driver to obtain high definition face image；Intensity compensation devices, with high-definition camera Connection, for receiving high definition face image, the gray value based on each pixel in high definition face image determines high definition face image Mean flow rate, and by the mean flow rate of high definition face image compared with predetermined luminance, when being averaged for high definition face image Brightness is more than or equal to predetermined luminance, and luminance-reduction adjustment is carried out to high definition face image to obtain brightness adjustment image, works as high definition The mean flow rate of face image is less than predetermined luminance, and luminance raising adjustment is carried out to high definition face image to obtain brightness adjustment figure Picture；Gaussian smoothing equipment, it is connected with intensity compensation devices to receive brightness adjustment image, carrying out Gauss to brightness adjustment image puts down It is sliding to handle to obtain smoothed image；Gray processing processing equipment, it is connected with Gaussian smoothing equipment to receive smoothed image, and to smooth Image performs gray processing processing to obtain gray level image；Histogram equalization equipment, it is connected with gray processing processing equipment to receive Gray level image, and histogram equalization processing is performed to gray level image to obtain equilibrium figures picture；Feature extracting device, respectively with Histogram equalization equipment unpacks equipment with IP and connected, and the equilibrium figures picture received is handled；Feature extracting device includes ripple Dynamic threshold value selects sub- equipment, the sub- equipment of processes pixel, the sub- equipment of matrix-split, the decimal system to change sub- equipment, characteristic vector acquisition The sub- more sub- equipment of equipment and characteristic vector；Fluctuation threshold selects sub- equipment to be connected with histogram equalization equipment, for calculating The complexity of weighing apparatus image, the complexity selection fluctuation threshold size based on equilibrium figures picture, the complexity of equilibrium figures picture is higher, selection Fluctuation threshold it is bigger, fluctuation threshold is positive number；The sub- equipment of processes pixel selects sub- equipment and histogram with fluctuation threshold respectively Balancing equipment is connected, and for receiving equilibrium figures picture, following locate is performed as object pixel for each pixel of equilibrium figures picture Reason：The pixel centered on object pixel, the object pixel matrix of 3 × 3 sizes is obtained in equilibrium figures picture, by object pixel matrix Interior each pixel in addition to object pixel as reference pixel compared with object pixel, to obtain binaryzation square Battle array, binaryzation matrix is 3 × 3 sizes, and binaryzation matrix is made up of 8 binaryzation pixels, and reference pixel is more than or equal to subject image Element and fluctuation threshold sum, then the pixel value of binaryzation pixel corresponding to reference pixel is 1, and reference pixel subtracts less than object pixel The difference gone after fluctuation threshold, then the pixel value of binaryzation pixel corresponding to reference pixel is ﹣ 1, the reference pixel of other values The pixel value of corresponding binaryzation pixel is 0；The sub- equipment of matrix-split is connected with the sub- equipment of processes pixel, for each is right Binaryzation matrix conversion is into a positive binaryzation matrix and a negative binaryzation matrix as corresponding to pixel, positive binaryzation matrix by 8 binaryzation pixel values composition, negative binaryzation matrix are also made up of 8 binaryzation pixel values, positive binaryzation matrix each Binaryzation pixel value subtracts the binaryzation pixel value of negative binaryzation matrix relevant position, and can to obtain corresponding binaryzation matrix corresponding The pixel value of the binaryzation pixel of position；The decimal system is changed sub- equipment and is connected with the sub- equipment of matrix-split, for each is right All binaryzation pixel values of positive binaryzation matrix as corresponding to pixel press its position in positive binaryzation matrix with first left back Right first up and then down order again forms a binary number and changed into as the positive binary number of target, then by the positive binary number of target Decimal number is as the positive decimal number of target, to be additionally operable to that all the two of binaryzation matrix will be born corresponding to each object pixel Value pixel value forms a binary system by its position in negative binaryzation matrix with first left and then right first up and then down order again Number is used as target negative binary number, then target negative binary number is changed into decimal number to bear decimal number as target；It is special Sign vector, which obtains sub- equipment, to be changed sub- equipment with histogram equalization equipment and the decimal system respectively and be connected, for will be in equilibrium figures picture often The pixel value of one object pixel is substituted for positive goal decimal number corresponding to the object pixel and according to object pixel in equilibrium Positive goal decimal number corresponding to all object pixels is formed positive one-dimensional characteristic vector by the position in image, special as positive goal Sign vector output, it is additionally operable to equilibrium figures the pixel value of each object pixel as in and is substituted for bear mesh corresponding to the object pixel Mark decimal number and target decimal number will be born corresponding to all object pixels according to position of the object pixel in equilibrium figures as in Negative one dimensional feature vector is formed, is exported as negative target feature vector；The more sub- equipment of characteristic vector obtains with characteristic vector respectively Take sub- equipment and IP to unpack equipment connect, for by the characteristic vector progress positive with each benchmark respectively of positive goal characteristic vector Match somebody with somebody, negative target feature vector is matched with each benchmark negative feature vector respectively, all the match is successful and matches for the two The authorized user's title phase corresponding with the benchmark negative feature vector matched of authorized user's title corresponding to the positive characteristic vector of benchmark Meanwhile recognition of face pass signal and the corresponding authorized user's title of the positive characteristic vector of the benchmark with matching then are exported, it is no Recognition of face failure signal will then be exported；IP unpacks equipment, for being connected with long-range data server network, is connect by network The IP packets at data server are received, and IP packets are unpacked to obtain 6LowPAN packets；Wherein, IP data Bag is that 6LowPAN packets are carried out to beat after IP bags the packet obtained, and the load in 6LowPAN packets includes data clothes The positive characteristic vector of each benchmark and each benchmark negative feature at business device is vectorial, and the head in 6LowPAN packets is compression number According to the head in 6LowPAN packets after decompression is used to parse the load in 6LowPAN packets；Wherein, it is each The individual positive characteristic vector of benchmark is that corresponding authorized user's benchmark face-image is carried out and feature extracting device same operation in advance Positive characteristic vector pickup and the vector obtained, each benchmark negative feature vector are pre- to corresponding authorized user's benchmark face-image First carry out the vector for extracting and obtaining with the negative feature of feature extracting device same operation vector；Edge sensing equipment, solved with IP Bag equipment is connected, and the 6LowPAN packets of equipment output are unpacked for receiving IP, obtains the 6LowPAN for being rendered as compressed data The head of packet, the heads of 6LowPAN packets is decompressed with the head in the 6LowPAN packets after being decompressed； 6LowPAN unpacks equipment, is connected with edge sensing equipment, for receiving 6LowPAN packets to obtain in 6LowPAN packets Load, and the load in 6LowPAN packets is parsed based on the head in the 6LowPAN packets after decompression, with Obtain the positive characteristic vector of each benchmark and each benchmark negative feature vector；Wherein, alternatively, replaced using wavelet filtering equipment high This smoothing arrangement, wavelet filtering equipment are connected to receive brightness adjustment image with intensity compensation devices, brightness adjustment image are entered Row wavelet filtering is handled to obtain smoothed image.

More specifically, in the road vehicles traveling monitoring system based on Internet of Things：High-definition camera also includes dodging Light lamp controller and flash lamp.

More specifically, in the road vehicles traveling monitoring system based on Internet of Things：High-definition camera also includes bright Sensor is spent, for detecting real time environment brightness.

More specifically, in the road vehicles traveling monitoring system based on Internet of Things：Photoflash controller is based on real When ambient brightness control flash lamp opening and closing.

More specifically, in the road vehicles traveling monitoring system based on Internet of Things：Photoflash controller is based on real When ambient brightness control flash lamp opening and closing include：When real time environment brightness is more than predetermined luminance threshold value, flash lamp is closed.

More specifically, in the road vehicles traveling monitoring system based on Internet of Things：Photoflash controller is based on real When ambient brightness control flash lamp opening and closing include：When real time environment brightness is less than or equal to predetermined luminance threshold value, flash of light is opened Lamp and according to the flash luminance of real time environment brightness adjustment flash lamp, real time environment brightness is lower, and the flash luminance of flash lamp is got over It is high.

Brief description of the drawings

Embodiment of the present invention is described below with reference to accompanying drawing, wherein：

Fig. 1 is the structure side of the traveling monitoring system of the road vehicles based on Internet of Things according to embodiment of the present invention Block diagram.

Reference：1 vehicle control apparatus；2AVR32 chips；3 high-definition cameras；4 image processing equipments

Embodiment

The embodiment of the traveling monitoring system of the road vehicles based on Internet of Things of the present invention is entered below with reference to accompanying drawings Row describes in detail.

Currently, road vehicles traveling monitoring system lacks the safe access control equipment differentiated to driver identity, Cause the security performance of road vehicles not high, it is easy to carry out criminal offence to criminal's hijacking vehicle and bring convenience, so as to Infringement is produced in personal safety and economic interests to car owner.

In order to overcome above-mentioned deficiency, the present invention has built a kind of road vehicles traveling monitoring system based on Internet of Things, profit Monitoring system is travelled with existing road vehicles, it is transformed to increase face recognition device and network communication equipment, it is complete The accurate discriminating of paired road vehicles driver identity.

Fig. 1 is the structure side of the traveling monitoring system of the road vehicles based on Internet of Things according to embodiment of the present invention Block diagram, the system include vehicle control apparatus, AVR32 chips, high-definition camera and image processing equipment, high-definition camera, It is arranged on inside road vehicles, for being taken pictures to driver to obtain high definition face image, image processing equipment is used for pair High definition face image carries out image procossing, and AVR32 chips are connected with vehicle control apparatus and image processing equipment respectively, for base The control model to vehicle control apparatus is determined in the output of image processing equipment.

Then, continue to enter traveling one to the concrete structure of the traveling monitoring system of the road vehicles based on Internet of Things of the present invention The explanation of step.

The system includes：Vehicle control apparatus, road pavement vehicle are controlled, for receiving validated user signal When, safeguard that driver's road pavement vehicle continues to drive, and is additionally operable to when receiving disabled user's signal, according to surface conditions control Road vehicles pulling over observing processed.

The system includes：AVR32 chips, respectively more sub- with characteristic vector equipment and vehicle control apparatus be connected, use When recognition of face pass signal is being received, validated user signal is sent, is additionally operable to receiving recognition of face failure signal, Send disabled user's signal；High-definition camera, it is arranged on inside road vehicles, for being taken pictures driver to obtain high definition Face image.

The system includes：Intensity compensation devices, it is connected with high-definition camera, for receiving high definition face image, is based on The gray value of each pixel determines the mean flow rate of high definition face image, and putting down high definition face image in high definition face image Equal brightness is compared with predetermined luminance, when the mean flow rate of high definition face image is more than or equal to predetermined luminance, to high definition face Image carries out luminance-reduction adjustment to obtain brightness adjustment image, when the mean flow rate of high definition face image is less than predetermined luminance, Luminance raising adjustment is carried out to high definition face image to obtain brightness adjustment image.

The system includes：Gaussian smoothing equipment, it is connected with intensity compensation devices to receive brightness adjustment image, to brightness Adjustment image carries out Gaussian smoothing to obtain smoothed image；Gray processing processing equipment, it is connected with Gaussian smoothing equipment to connect Smoothed image is received, and gray processing processing is performed to smoothed image to obtain gray level image.

The system includes：Histogram equalization equipment, it is connected with gray processing processing equipment to receive gray level image, and it is right Gray level image performs histogram equalization processing to obtain equilibrium figures picture.

The system includes：Feature extracting device, unpack equipment with histogram equalization equipment and IP respectively and be connected, to receiving To equilibrium figures picture handled；Feature extracting device includes fluctuation threshold and selects sub- equipment, the sub- equipment of processes pixel, matrix to tear open Molecular Devices, the decimal system change sub- equipment, characteristic vector obtains sub- equipment and the more sub- equipment of characteristic vector；Fluctuation threshold selects Sub- equipment is connected with histogram equalization equipment, for calculating the complexity of equilibrium figures picture, the complexity selection based on equilibrium figures picture Fluctuation threshold size, the complexity of equilibrium figures picture is higher, and the fluctuation threshold of selection is bigger, and fluctuation threshold is positive number；Processes pixel Sub- equipment selects sub- equipment and histogram equalization equipment to be connected with fluctuation threshold respectively, for receiving equilibrium figures picture, for equilibrium Each pixel of image performs following handle as object pixel：The pixel centered on object pixel, obtained in equilibrium figures picture The object pixel matrix of 3 × 3 sizes is taken, using each pixel in object pixel matrix in addition to object pixel as reference Pixel is compared with object pixel, and to obtain binaryzation matrix, binaryzation matrix is 3 × 3 sizes, and binaryzation matrix is by 8 Binaryzation pixel forms, and reference pixel is more than or equal to object pixel and fluctuation threshold sum, then binaryzation corresponding to reference pixel The pixel value of pixel is 1, and reference pixel subtracts the difference after fluctuation threshold less than object pixel, then two-value corresponding to reference pixel The pixel value for changing pixel is ﹣ 1, and the pixel value of binaryzation pixel corresponding to the reference pixel of other values is 0；Matrix-split is set It is standby to be connected with the sub- equipment of processes pixel, for by binaryzation matrix conversion corresponding to each object pixel into a positive binaryzation Matrix and a negative binaryzation matrix, positive binaryzation matrix are made up of 8 binaryzation pixel values, bear binaryzation matrix also by 8 Binaryzation pixel value forms, and each binaryzation pixel value of positive binaryzation matrix subtracts the two of negative binaryzation matrix relevant position Value pixel value can obtain the pixel value of the binaryzation pixel of corresponding binaryzation matrix relevant position；The decimal system changes sub- equipment It is connected with the sub- equipment of matrix-split, for by all binaryzation pixel values of positive binaryzation matrix corresponding to each object pixel One binary number is formed using first left and then right first up and then down order again by its position in positive binaryzation matrix and is used as target Positive binary number, then the positive binary number of target is changed into decimal number so that as the positive decimal number of target, being additionally operable to will be each All binaryzation pixel values that binaryzation matrix is born corresponding to individual object pixel press its position in negative binaryzation matrix with elder generation Left back right first up and then down order again forms a binary number as target negative binary number, then by target negative binary number turn Decimal number is melted into bear decimal number as target；Characteristic vector obtains sub- equipment and entered respectively with histogram equalization equipment and ten System changes sub- equipment connection, for by equilibrium figures, the pixel value of each object pixel to be substituted for corresponding to the object pixel as in Positive goal decimal number simultaneously enters positive goal ten corresponding to all object pixels according to position of the object pixel in equilibrium figures as in Array processed is exported as positive goal characteristic vector, is additionally operable to each subject image in equilibrium figures picture into positive one-dimensional characteristic vector The pixel value of element, which is substituted for, bears target decimal number and the position according to object pixel in equilibrium figures picture corresponding to the object pixel Target decimal number composition negative one dimensional feature vector will be born by putting corresponding to all object pixels, defeated as negative target feature vector Go out；The more sub- equipment of characteristic vector obtains sub- equipment with characteristic vector respectively and IP unpacks equipment and is connected, for positive goal is special Sign vector is matched respectively with the positive characteristic vector of each benchmark, by negative target feature vector respectively with each benchmark negative feature to Amount matched, the two all the match is successful and the positive characteristic vector of benchmark that matches corresponding to authorized user's title and match When authorized user's title corresponding to benchmark negative feature vector is identical, then recognition of face pass signal and the base with matching are exported Authorized user's title corresponding to accurate positive characteristic vector, otherwise will export recognition of face failure signal.

The system includes：IP unpack equipment, for being connected with long-range data server network, by network reception come Unpacked from the IP packets at data server, and to IP packets to obtain 6LowPAN packets；Wherein, IP packets are To 6LowPAN packets beat the packet of acquisition after IP bags, the load in 6LowPAN packets includes data server The positive characteristic vector of each benchmark and each benchmark negative feature at place are vectorial, and the head in 6LowPAN packets is compressed data, solution The head in 6LowPAN packets after pressure is used to parse the load in 6LowPAN packets；Wherein, each base Accurate positive characteristic vector is to carry out the positive spy with feature extracting device same operation in advance to corresponding authorized user's benchmark face-image The vector that sign vector is extracted and obtained, each benchmark negative feature vector are pre- advanced to corresponding authorized user's benchmark face-image The vector that row and the negative feature vector of feature extracting device same operation are extracted and obtained.

The system includes：Edge sensing equipment, unpack equipment with IP and be connected, equipment output is unpacked for receiving IP 6LowPAN packets, the head for the 6LowPAN packets for being rendered as compressed data is obtained, the head of 6LowPAN packets is solved Pressure is with the head in the 6LowPAN packets after being decompressed.

The system includes：6LowPAN unpacks equipment, is connected with edge sensing equipment, for receiving 6LowPAN packets To obtain the load in 6LowPAN packets, and based on the head in the 6LowPAN packets after decompression to 6LowPAN data Load in bag is parsed, to obtain the positive characteristic vector of each benchmark and each benchmark negative feature vector.

Wherein, alternatively, Gaussian smoothing equipment is replaced using wavelet filtering equipment, wavelet filtering equipment is set with luminance compensation Standby connection carries out wavelet filtering processing to brightness adjustment image to obtain smoothed image to receive brightness adjustment image.

Alternatively, in the control platform：High-definition camera also includes photoflash controller and flash lamp；High-definition camera Head also includes luminance sensor, for detecting real time environment brightness；Photoflash controller is glistened based on real time environment brilliance control The opening and closing of lamp；Opening and closing of the photoflash controller based on real time environment brilliance control flash lamp includes：When real time environment brightness is more than During predetermined luminance threshold value, flash lamp is closed；And opening and closing bag of the photoflash controller based on real time environment brilliance control flash lamp Include：When real time environment brightness is less than or equal to predetermined luminance threshold value, opens flash lamp and glistened according to real time environment brightness adjustment The flash luminance of lamp, real time environment brightness is lower, and the flash luminance of flash lamp is higher.

In addition, wave filter, is the device filtered to ripple as its name suggests." ripple " is that a very extensive physics is general Read, in electronic technology field, the value that " ripple " is narrowly confined to refer in particular to describe various physical quantitys is with time fluctuations Process.The process is converted into the function of time of voltage or electric current, referred to as various physical quantitys by the effect of various kinds of sensors Time waveform, or referred to as signal.Because the independent variable time is continuous value, referred to as continuous time signal, Habitually it is referred to as analog signal again.

With the generation and rapid development of digital electronic computer technology, for the ease of computer to signal at Reason, generate the complete theoretical and method that continuous time signal is transformed into discrete-time signal under sampling theorem guidance. That is, primary signal only can be expressed without losing with sample value of the original analog signal on series of discrete time coordinate point Lose any information since the expression of ripple, waveform, signal these concepts be various physical quantitys in objective world change, naturally It is the carrier for the various information that modern society depends on for existence.Information needs to propagate, and what is leaned on is exactly the transmission of waveform signal.Signal exists Its generation, conversion, each link of transmission may be distorted due to the presence of environment and interference, even quite a lot of In the case of, this distortion is also very serious, causes signal and its entrained information to be embedded in dearly among noise.In order to These noises are filtered out, recover the signal of script, it is necessary to be filtered processing using various wave filters.

Monitoring system is travelled using the road vehicles based on Internet of Things of the present invention, can not be road surface car for prior art Provide driver identity authentication scheme technical problem, pass through road vehicles travel monitoring system in integrate high-precision people The network communication equipment of face feature extraction matching unit and Large Copacity, criminal is found in time, and braked rapidly, so as to The security performance of road vehicles is improved on the whole.

It is understood that although the present invention is disclosed as above with preferred embodiment, but above-described embodiment and it is not used to Limit the present invention.For any those skilled in the art, without departing from the scope of the technical proposal of the invention, Many possible changes and modifications are all made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as With the equivalent embodiment of change.Therefore, every content without departing from technical solution of the present invention, the technical spirit pair according to the present invention Any simple modifications, equivalents, and modifications made for any of the above embodiments, still fall within the scope of technical solution of the present invention protection It is interior.

Claims (7)

1. a kind of road vehicles traveling monitoring system based on Internet of Things, the system include vehicle control apparatus, AVR32 cores Piece, high-definition camera and image processing equipment, high-definition camera, are arranged on inside road vehicles, for clapping driver According to obtain high definition face image, image processing equipment is used to carry out high definition face image image procossing, AVR32 chips difference It is connected with vehicle control apparatus and image processing equipment, is determined for the output based on image processing equipment to vehicle control apparatus Control model.

2. the road vehicles traveling monitoring system based on Internet of Things as claimed in claim 1, it is characterised in that the system bag Include：

Vehicle control apparatus, road pavement vehicle are controlled, for when receiving validated user signal, safeguarding that driver satisfies the need Face vehicle continues to drive, and is additionally operable to when receiving disabled user's signal, controls road vehicles to keep to the side to stop according to surface conditions Car；

AVR32 chips, respectively more sub- with characteristic vector equipment and vehicle control apparatus be connected, for receiving recognition of face During pass signal, validated user signal is sent, is additionally operable to receiving recognition of face failure signal, sends disabled user's signal；

High-definition camera, it is arranged on inside road vehicles, for being taken pictures to driver to obtain high definition face image；

Intensity compensation devices, it is connected with high-definition camera, for receiving high definition face image, based on each in high definition face image The gray value of pixel determines the mean flow rate of high definition face image, and the mean flow rate of high definition face image is entered with predetermined luminance Row compares, when the mean flow rate of high definition face image is more than or equal to predetermined luminance, to high definition face image progress luminance-reduction tune It is whole to obtain brightness adjustment image, when the mean flow rate of high definition face image is less than predetermined luminance, high definition face image is carried out Luminance raising is adjusted to obtain brightness adjustment image；

Gaussian smoothing equipment, it is connected with intensity compensation devices to receive brightness adjustment image, Gauss is carried out to brightness adjustment image Smoothing processing is to obtain smoothed image；

Gray processing processing equipment, it is connected with Gaussian smoothing equipment to receive smoothed image, and smoothed image is performed at gray processing Manage to obtain gray level image；

Histogram equalization equipment, it is connected to receive gray level image, and gray level image is performed straight with gray processing processing equipment Square figure equilibrium treatment is to obtain equilibrium figures picture；

Feature extracting device, unpack equipment with histogram equalization equipment and IP respectively and be connected, the equilibrium figures picture received is carried out Processing；Feature extracting device includes fluctuation threshold and selects sub- equipment, the sub- equipment of processes pixel, the sub- equipment of matrix-split, the decimal system Change sub- equipment, characteristic vector obtains sub- equipment and the more sub- equipment of characteristic vector；Fluctuation threshold selects sub- equipment and histogram Balancing equipment connects, for calculating the complexity of equilibrium figures picture, the complexity selection fluctuation threshold size based on equilibrium figures picture, The complexity of weighing apparatus image is higher, and the fluctuation threshold of selection is bigger, and fluctuation threshold is positive number；The sub- equipment of processes pixel respectively with fluctuation Threshold value selects sub- equipment to be connected with histogram equalization equipment, for receiving equilibrium figures picture, for each pixel of equilibrium figures picture Following handle is performed as object pixel：The pixel centered on object pixel, the object of 3 × 3 sizes is obtained in equilibrium figures picture Picture element matrix, each pixel in object pixel matrix in addition to object pixel is entered as reference pixel and object pixel Row compares, and to obtain binaryzation matrix, binaryzation matrix is 3 × 3 sizes, and binaryzation matrix is made up of 8 binaryzation pixels, ginseng Pixel is examined more than or equal to object pixel and fluctuation threshold sum, then the pixel value of binaryzation pixel corresponding to reference pixel is 1, ginseng Examine pixel and subtract the difference after fluctuation threshold less than object pixel, then the pixel value of binaryzation pixel corresponding to reference pixel is ﹣ 1, the pixel value of binaryzation pixel corresponding to the reference pixel of other values is 0；The sub- equipment of matrix-split is set with processes pixel Standby connection, for by binaryzation matrix conversion corresponding to each object pixel into a positive binaryzation matrix and a negative two-value Change matrix, positive binaryzation matrix is made up of 8 binaryzation pixel values, and negative binaryzation matrix is also made up of 8 binaryzation pixel values, The binaryzation pixel value that each binaryzation pixel value of positive binaryzation matrix subtracts negative binaryzation matrix relevant position can obtain To the pixel value of the binaryzation pixel of corresponding binaryzation matrix relevant position；The decimal system changes sub- equipment and the sub- equipment of matrix-split Connection, for all binaryzation pixel values of positive binaryzation matrix corresponding to each object pixel to be pressed into it in positive binaryzation square Position in battle array forms a binary number as the positive binary number of target using first left and then right first up and then down order again, then by mesh Mark positive binary number and change into decimal number as the positive decimal number of target, to be additionally operable to bear corresponding to each object pixel All binaryzation pixel values of binaryzation matrix are by its position in negative binaryzation matrix with first left and then right first up and then down again Order form a binary number as target negative binary number, then by target negative binary number change into decimal number using as Target bears decimal number；Characteristic vector obtains sub- equipment and is connected respectively with histogram equalization equipment and the sub- equipment of decimal system conversion, For by equilibrium figures, the pixel value of each object pixel to be substituted for positive goal decimal number corresponding to the object pixel simultaneously as in Positive goal decimal number corresponding to all object pixels is formed into just one-dimensional spy according to position of the object pixel in equilibrium figures as in Sign vector, exports as positive goal characteristic vector, is additionally operable to the pixel value of each object pixel in equilibrium figures picture being substituted for Target decimal number is born corresponding to the object pixel and according to position of the object pixel in equilibrium figures picture by all object pixels Corresponding negative target decimal number composition negative one dimensional feature vector, is exported as negative target feature vector；Characteristic vector is more sub Equipment obtains sub- equipment with characteristic vector respectively and IP unpacks equipment and is connected, for by positive goal characteristic vector respectively with each base Accurate positive characteristic vector is matched, and negative target feature vector is matched with each benchmark negative feature vector respectively, the two is all Authorized user's title corresponding to the positive characteristic vector of benchmark that the match is successful and matches and the benchmark negative feature vector matched are right When the authorized user's title answered is identical, then exports recognition of face pass signal and the positive characteristic vector of the benchmark with matching is corresponding Authorized user's title, otherwise will export recognition of face failure signal；

IP unpacks equipment, for being connected with long-range data server network, is received by network at data server IP packets, and IP packets are unpacked to obtain 6LowPAN packets；Wherein, IP packets are that 6LowPAN packets are entered Row beats the packet of acquisition after IP bags, and each benchmark that the load in 6LowPAN packets is included at data server is just special Levy vector sum each benchmark negative feature vector, the head in 6LowPAN packets is compressed data, the 6LowPAN numbers after decompression It is used to parse the load in 6LowPAN packets according to the head in bag；Wherein, the positive characteristic vector of each benchmark is pair Corresponding authorized user's benchmark face-image carries out the positive characteristic vector pickup with feature extracting device same operation in advance and obtained Vector, each benchmark negative feature vector be to corresponding authorized user's benchmark face-image in advance carry out and feature extracting device The vector that the negative feature vector of same operation is extracted and obtained；

Edge sensing equipment, unpack equipment with IP and be connected, the 6LowPAN packets of equipment output are unpacked for receiving IP, are obtained The head of the 6LowPAN packets of compressed data is rendered as, after decompressing the heads of 6LowPAN packets to be decompressed Head in 6LowPAN packets；

6LowPAN unpacks equipment, is connected with edge sensing equipment, for receiving 6LowPAN packets to obtain 6LowPAN data Load in bag, and the load in 6LowPAN packets is solved based on the head in the 6LowPAN packets after decompression Analysis, to obtain the positive characteristic vector of each benchmark and each benchmark negative feature vector；

Wherein, alternatively, Gaussian smoothing equipment is replaced using wavelet filtering equipment, wavelet filtering equipment connects with intensity compensation devices Connect to receive brightness adjustment image, wavelet filtering processing is carried out to brightness adjustment image to obtain smoothed image.

3. the road vehicles traveling monitoring system based on Internet of Things as claimed in claim 2, it is characterised in that：

High-definition camera also includes photoflash controller and flash lamp.

4. the road vehicles traveling monitoring system based on Internet of Things as claimed in claim 3, it is characterised in that：

High-definition camera also includes luminance sensor, for detecting real time environment brightness.

5. the road vehicles traveling monitoring system based on Internet of Things as claimed in claim 4, it is characterised in that：

Opening and closing of the photoflash controller based on real time environment brilliance control flash lamp.

6. the road vehicles traveling monitoring system based on Internet of Things as claimed in claim 5, it is characterised in that：

Opening and closing of the photoflash controller based on real time environment brilliance control flash lamp includes：When real time environment brightness is bright more than default When spending threshold value, flash lamp is closed.

7. the road vehicles traveling monitoring system based on Internet of Things as claimed in claim 5, it is characterised in that：

Opening and closing of the photoflash controller based on real time environment brilliance control flash lamp includes：When real time environment brightness is less than or equal in advance If during luminance threshold, open flash lamp and got over according to the flash luminance of real time environment brightness adjustment flash lamp, real time environment brightness Low, the flash luminance of flash lamp is higher.