CN111603185A - Driving habit big data analysis system for new energy automobile - Google Patents
Driving habit big data analysis system for new energy automobile Download PDFInfo
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- CN111603185A CN111603185A CN202010493254.7A CN202010493254A CN111603185A CN 111603185 A CN111603185 A CN 111603185A CN 202010493254 A CN202010493254 A CN 202010493254A CN 111603185 A CN111603185 A CN 111603185A
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- 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
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
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- G—PHYSICS
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- 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
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Abstract
The invention discloses a driving habit big data analysis system for a new energy automobile, belonging to the technical field of driving habits, the driving habit big data analysis system comprises an induction neck ring and a client, wherein the induction neck ring is provided with a wavelength collection unit, a respiratory frequency detection unit, a blood pressure detection unit, a pulse detection unit and a body surface temperature detection unit, the invention is scientific and reasonable, the use is safe and convenient, the breathing frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of speaking visceral words in each hour of the user are collected through the neck ring, wavelet transformation and comparison are respectively carried out, whether the user is in the road rage state or not is judged, the color changes of the left cheek and the right cheek of the user in the normal state and the driving state are collected, and the weight value and the result of the wavelet transformation are solved to assist in judging whether the user is in the road rage emotion or not.
Description
Technical Field
The invention relates to the technical field of driving habit analysis, in particular to a driving habit big data analysis system for a new energy automobile.
Background
With the improvement of economic level, new energy automobiles have already gone into our lives, and with the popularization of new energy automobiles, more and more automobile drivers begin to suffer from road rage, which is an overstimulated emotional reaction of drivers in the driving process, and the driven automobiles chase after the emotion is out of control at high speed, so that the driven automobiles become a tool for hurting people, the damage is huge, group death and group injury can be caused, and 3 billion traffic accidents are caused by road rage every year around the world, and the damage is very large. The invention detects the emotional condition of the driver in real time by means of light wave induction, heartbeat, pulse and the like, and adjusts the emotion of the driver when the emotion of the driver is in the road rage state, thereby relieving the emotion of the driver and preventing irreparable consequences of the driver caused by emotion anger.
At present, when the driver is in the anger symptom state of the way, thereby prior art judges whether driver is in under the anger symptom state of the way for utilizing response bracelet to detect driver's physiological state, but uses generally the bracelet to detect heartbeat, pulse or respiratory rate and need cause the influence with bracelet and the operation of pasting tight arm to user's driving vehicle, so inconvenient.
Disclosure of Invention
The invention aims to provide a driving habit big data analysis system for a new energy automobile, and aims to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a big data analysis system of driving habit for new energy automobile which characterized in that: the driving habit big data analysis system comprises an induction neck ring and a client, wherein the induction neck ring comprises a neck ring body and a mounting belt, the mounting belt is arranged on the inner side of the induction neck ring, an information acquisition device, a state analysis device, a communication device, an adjusting device, a control device and a storage device are fixed on the mounting belt, and an image acquisition device is installed on the neck ring body.
Preferably, the state analysis device analyzes the information input by the information acquisition device, the communication device state analysis device sends the analyzed and processed information to the control device through the communication device, and the control device sends an instruction to the adjusting device according to the obtained information; the information acquisition device is used for collecting the respiratory frequency of a user acquired by the respiratory frequency detection unit, the blood pressure value of the user acquired by the blood pressure detection unit, the pulse beating times of one minute of an agent acquired by the pulse detection unit, the body surface temperature of the agent acquired by the body surface temperature detection unit, the color of the face of the agent acquired by the image unit and the times of words of the zang language of the agent per hour in the driving process of the agent acquired by the speech acquisition unit.
Preferably, the system comprises a method, which is divided into four steps:
s1: collecting the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature, the color of the face and the times of speaking visceral words in each hour of a user by using an information collecting unit;
s2: carrying out data summarizing processing on the acquired information;
s3: analyzing the summarized data so as to judge whether the state of the driver is in the road rage emotion or not;
s4: performing emotion adjustment processing on a driver in the road rage emotion;
s5: the time when the user is in the road rage emotion in the driving state and the total time in the driving process of the user are subjected to ratio processing to obtain the driving habit of the user;
the step S1 is used for collecting data of a user in a normal state and data of a user in a driving state, and the step S2 is used for performing data summarization processing on the collected data in the normal state and the data in the driving state in the steps and then comparing the data, wherein the processing mode comprises wavelet transformation and wavelength comparison processing so as to judge whether the driver is in road rage emotion; in the step S4, performing emotion adjustment processing on the driver in the road rage emotion, where the emotion adjustment processing may be performed in various manners, including but not limited to playing light music, massaging and the like; in the step S5, the driving habit of the user is obtained by processing the ratio of the time when the user is in the road rage mood during the driving state to the total time during the driving process of the user.
Preferably, the step S1 includes two steps:
s11, collecting the state information of the user in the normal state;
and S12, collecting the state information of the user when driving the automobile.
Preferably, the step of S2 includes two steps:
s21, performing wavelet transformation on the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of speaking visceral words in each hour of a user in a normal state, and performing wavelet transformation and wavelength comparison on the color of the face of the person;
s22, processing the data in the driving process of the user in the same way;
and the step S3 is to compare the result obtained by wavelet transform in the normal state of the user and the weight value obtained by processing with the data in the driving state, so as to obtain whether the driver is in the road rage emotion.
Preferably, the formula of the wavelet transform is as follows:
wherein f (t) is a signal to be processed; ω (f, g) (t) is a wavelet function; f is the scale of wavelet transform, and controls the expansion and contraction of the wavelet function, corresponding to the frequency; g is an offset, and the translation of the wavelet function is controlled, corresponding to time;
using a wavelength collection unit to collect wavelengths of light reflected off the left and right cheeks of a human user, defining the wavelengths of light as R when in the red color phase and G when in the non-red color phase, using the formula of a human using wavelet transform processing as follows:
wherein f (t)i) Is a signal to be processed;
(c，d)(ti) Is a wavelet function; c is the scale of wavelet transform, controlling the expansion and contraction of the wavelet function, corresponding to the frequency; d is an offset, controlling the translation of the wavelet function, corresponding to time;
partitioning the left cheek and the right cheek of a user, wherein the left cheek is divided into 9 regions, and the collected light wavelength in red stage is respectively listed as I1、II1、III1、IV1V1、VI1、VII1、VIII1、IX1The right cheek is divided into 9 zones, and the collected light wavelength is in red stage for I2、II2、III2、IV2、V2、VI2、VII2、VIII2、IX2：
The same area of the left and right cheeks was summed:
∑I＝I1+I2；
∑II＝II1+II2；
∑III＝III1+III2；
∑IV＝IV1+IV2；
∑V＝V1+V2；
∑VI＝VI1+VI2；
∑VII＝VII1+VII2；
∑VIII＝VIII1+VIII2；
∑IX＝IX1+IX2；
then according to the formula:
setting e as sigma I + sigma III + sigma VII + sigma IX;
g＝∑II+∑IV+∑VI+∑VIII；
l＝∑V
e is the sum of the first, third, seventh and ninth regions of the cheek, g is the sum of the second, fourth, sixth and eighth regions, l is the sum of the fifth region, and K is the weight value;
determining whether the user is in the road rage emotion in the driving process according to the weight value K and the result of the wavelet transformation;
firstly, respectively carrying out wavelet transformation on the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of speaking visceral words per hour of a user in a normal state, wherein the formula of the wavelet transformation is as follows:
wherein f (t) is a signal to be processed; ω (f, g) (t) is a wavelet function; f is the scale of wavelet transform, and controls the expansion and contraction of the wavelet function, corresponding to the frequency; g is an offset, and the translation of the wavelet function is controlled, corresponding to time; the processing can clearly observe the physiological state difference of the user in the driving process and the normal state by utilizing the waveform, thereby judging whether the user is in the emotion of road rage in the driving process;
using a wavelength collection unit to collect wavelengths of light reflected off the left and right cheeks of a human user, defining the wavelengths of light as R when in the red color phase and G when in the non-red color phase, using the formula of a human using wavelet transform processing as follows:
wherein f (t)i) Is a signal to be processed;
(c，d)(ti) Is a wavelet function; c is the scale of wavelet transform, controlling the expansion and contraction of the wavelet function, corresponding to the frequency; d is an offset, controlling the translation of the wavelet function, corresponding to time; the processing can clearly observe the difference of the colors of the cheeks of the user in the driving process and the normal state by utilizing the waveform, thereby assisting in judging whether the user is in the emotion of the road rage in the driving process;
partitioning the left cheek and the right cheek of a user, wherein the left cheek is divided into 9 regions, and the collected light wavelength in red stage is respectively listed as I1、II1、III1、IV1V1、VI1、VII1、VIII1、IX1The right cheek is divided into 9 zones, and the collected light wavelength is in red stage for I2、II2、III2、IV2、V2、VI2、VII2、VIII2、IX2: because the color change of the face is unequal under the angry condition of a person, when a driver is in the road anger emotion, the color in the middle of the face can be displayed more, and the color change of the edge of the face cannot be displayed accurately in time, so that the part of the face where the user uses is divided, and different proportions are given to each area;
the user's left and right cheeks were then subjected to a summation operation using the same area:
∑I＝I1+I2；
∑II＝II1+II2；
∑III＝III1+III2；
∑IV＝IV1+IV2；
∑V＝V1+V2；
∑VI＝VI1+VI2；
∑VII＝VII1+VII2；
∑VIII＝VIII1+VIII2；
∑IX＝IX1+IX2；
then according to the formula:
setting e as sigma I + sigma III + sigma VII + sigma IX;
g＝∑II+∑IV+∑VI+∑VIII；
l＝∑V
e is the sum of the first, third, seventh, ninth regions of the cheek, g is the sum of the second, fourth, sixth, eighth regions, l is the sum of the fifth region;
k is a weighted value;
determining whether the user is in the road rage emotion in the driving process according to the weight value K and the result of the wavelet transformation;
firstly, solving the value of f obtained according to wavelet transformation, and calculating whether f is greater than u; (phi)
Then, the value of c is solved according to the wavelet transformation, and whether c is larger than p is calculated; (2)
Then, solving a weight value K according to the region division and a formula, and calculating whether K is greater than v; (iii)
C and f are transformation scales, and u, p and v are self-defined constants;
if the first condition is met and the second and third conditions are not met, the user is judged to be in a mild state of the road rage; if the first condition is met, the second condition or the third condition is met, the user is judged to be in the serious road rage state.
Preferably, the image unit comprises a camera, the camera is mounted at the central position of the neck ring body, a wavelength collecting unit is arranged in the camera, light supplementing lamps are arranged at two ends of the camera, a speech acquisition module is arranged outside the light supplementing lamps, and an adjusting module is arranged outside the speech acquisition module;
above-mentioned camera is inside to be provided with wavelength collection unit, wavelength collection unit can gather the wavelength of reflection light-emitting on the user's cheek to send state analysis device after making statistics with the wavelength and the acquisition time of the light of gathering, the light filling lamp can be under the dim circumstances of light, for the cheek light filling, wavelength collection unit can normally gather.
Preferably, a baffle is arranged outside the light supplement lamp, the baffle can adjust the angle, the bottom end of the baffle is fixed on an adjusting rod, an adjusting body is fixed on the adjusting rod, the adjusting body comprises an inner core, a first connecting rod, a second connecting rod and a third connecting rod, the first connecting rod is provided with first connecting teeth, the second connecting rod is provided with second connecting teeth and third connecting teeth, and the third connecting rod is provided with fourth connecting teeth;
the baffle is arranged on the outer side of the light supplement lamp, the angle can be adjusted through the baffle, and a user can adjust the angle of the baffle when the light supplement lamp works, so that the part irradiated by the light beam of the light supplement lamp is a cheek, and the light supplement lamp is prevented from directly irradiating eyes to influence the driving of the user; the baffle bottom mounting is on adjusting the second connecting rod on the pole, in the second connecting tooth on the second connecting rod is not blocked in the first connecting tooth on the first connecting rod, third connecting tooth on the second connecting rod is not blocked in the fourth connecting tooth on the third connecting rod, so can realize that the second connecting rod drives the baffle and rotates under the condition of not driving first connecting rod and third connecting rod.
Preferably, the client is a mobile terminal, a handheld terminal and a cloud platform, the client and the induction neck ring are connected in a wireless mode, and the wireless connection mode is bluetooth, a local area network or 4G and 5G network connection.
Preferably, the tail end of the induction neck ring is provided with a buckle and a clamping shell, the buckle can be buckled into the clamping shell to realize connection, a power supply anode, a spring and a battery are distributed in the buckle from top to bottom, and a power supply cathode is arranged in the clamping shell;
the buckle has the positive pole of power, spring and battery from last to distributing down, be provided with the power negative pole in the card shell, in the buckle detained the card shell, can realize connecting with the circular telegram.
Compared with the prior art, the invention has the beneficial effects that: according to the method, the neck ring is used for acquiring the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of words of dirty words in each hour of a user, respectively performing wavelet transformation and comparison to judge whether the user is in a road rage symptom state in a driving state, then acquiring the color changes of a left cheek and a right cheek of the user in a normal state and a driving state through the neck ring, and dividing the cheeks into 9 regions; the neck ring is used for collecting numerical values, so that the operation of a user in the vehicle driving process is not influenced, and the neck ring is safe and convenient.
Drawings
FIG. 1 is a schematic structural diagram of a driving habit big data analysis system module for a new energy automobile according to the invention;
FIG. 2 is a schematic view of the appearance structure of a neck ring of a driving habit big data analysis system for a new energy automobile according to the invention;
FIG. 3 is a schematic structural diagram of a regulator of the driving habit big data analysis system for a new energy automobile according to the invention;
FIG. 4 is a schematic structural diagram of signal transmission of a driving habit big data analysis system for a new energy automobile according to the invention;
FIG. 5 is a schematic structural diagram of an installation belt of the driving habit big data analysis system for a new energy automobile according to the invention;
FIG. 6 is a schematic structural diagram of a method step of a driving habit big data analysis system for a new energy automobile according to the invention;
fig. 7 is a detailed method step structure diagram of the driving habit big data analysis system for the new energy automobile according to the invention.
Reference numbers in the figures: 1. buckling; 1.1, a power supply anode; 1.2, a spring; 1.3, a battery; 2. clamping a shell; 2.1, a power supply cathode; 3. a neck ring body; 4. a camera; 5. an adjustment device; 6. a speech acquisition unit; 7. an information acquisition device; 7.1, a respiratory frequency detection unit; 7.2, a blood pressure detection unit; 7.3, a pulse detection unit; 7.4, a body surface temperature detection unit; 7.5, an image unit; 8. a state analyzing device; 9. a control device; 10. an infrared light supplement lamp; 11. a baffle plate; 12. mounting a belt; 13. a communication device; 14. a storage device; 15. an adjuster; 15.1, a first connecting rod; 15.2, a second connecting rod; 15.3, a third connecting rod; 15.4, first connecting teeth; 15.5, second connecting teeth; 15.6, third connecting teeth; 15.7, a fourth connecting tooth; 16. and adjusting the rod.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b): as shown in fig. 1 to 7, a driving habit big data analysis system for a new energy automobile is characterized in that: the driving habit big data analysis system comprises an induction neck ring and a client, wherein the induction neck ring comprises a neck ring body 3 and a mounting belt 12, the mounting belt is arranged on the inner side of the induction neck ring, an information acquisition device 7, a state analysis device 8, a communication device 13, an adjusting device 5, a control device 9 and a storage device 14 are fixed on the mounting belt, and an image acquisition device is installed on the neck ring body 3.
The state analysis device 8 analyzes the information input by the information acquisition device 7, the communication device 13 and the state analysis device 8 send the analyzed information to the control device 9 through the communication device 13, and the control device 9 sends an instruction to the adjusting device 5 according to the obtained information; the information acquisition device 7 is used for collecting the breathing frequency of the user collected by the breathing frequency detection unit 7.1, the blood pressure value of the user collected by the blood pressure detection unit 7.2, the pulse beating times of the actor per minute collected by the pulse detection unit 7.3, the body surface temperature of the actor collected by the body surface temperature detection unit 7.4, the color of the face volume of the actor collected by the image unit 7.5 and the times of the words of the actor per hour during driving, collected by the speech acquisition unit 6.
The system comprises a method, and the method comprises four steps:
s1: collecting the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature, the color of the face and the times of speaking visceral words in each hour of a user by using an information collecting unit;
s2: carrying out data summarizing processing on the acquired information;
s3: analyzing the summarized data so as to judge whether the state of the driver is in the road rage emotion or not;
s4: performing emotion adjustment processing on a driver in the road rage emotion;
s5: the driving habit of the user is obtained by processing the ratio of the time when the user is in the road rage emotion in the driving state to the total time when the user drives.
S1, acquiring data of a user in a normal state and data of a user in a driving state, and S2, performing data summarizing processing on the acquired data in the normal state and the data in the driving state in the steps, and then comparing the data, wherein the processing mode comprises wavelet transformation and wavelength comparison processing so as to judge whether the driver is in road rage emotion; in the step S4, performing emotion adjustment processing on the driver in the road rage emotion, wherein the emotion adjustment processing may be performed in various manners, including but not limited to playing light music, massaging and the like; in step S5, the driving habit of the user is obtained by processing the ratio of the time when the user is in the road rage mood during the driving state to the total time during the driving process of the user.
The step S1 includes two steps:
s11, collecting the state information of the user in the normal state;
and S12, collecting the state information of the user when driving the automobile.
The step S2 includes two steps:
s21, respectively performing wavelet transformation on the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of speaking visceral words in each hour of a user in a normal state, and performing wavelet transformation and wavelength comparison on the color of the face of the user;
s22, processing the data in the driving process of the user in the same way;
and step S3, comparing the result obtained by wavelet transform in the normal state of the user and the processed weight value with the data in the driving state, thereby obtaining whether the driver is in the road rage emotion.
The formula of the wavelet transform is:
wherein f (t) is a signal to be processed; ω (f, g) (t) is a wavelet function; f is the scale of wavelet transform, and controls the expansion and contraction of the wavelet function, corresponding to the frequency; g is an offset, and the translation of the wavelet function is controlled, corresponding to time;
using a wavelength collection unit to collect wavelengths of light reflected off the left and right cheeks of a human user, defining the wavelengths of light as R when in the red color phase and G when in the non-red color phase, using the formula of a human using wavelet transform processing as follows:
wherein f (t)i) Is a signal to be processed;
(c，d)(ti) Is a wavelet function; c is the scale of wavelet transform, controlling the expansion and contraction of the wavelet function, corresponding to the frequency; d is an offset, controlling the translation of the wavelet function, corresponding to time;
partitioning the left cheek and the right cheek of a user, wherein the left cheek is divided into 9 regions, and the collected light wavelength in red stage is respectively listed as I1、II1、III1、IV1V1、VI1、VII1、VIII1、IX1The right cheek is divided into 9 zones, and the collected light wavelength is in red stage for I2、II2、III2、IV2、V2、VI2、VII2、VIII2、IX2：
The same area of the left and right cheeks was summed:
∑I＝I1+I2；
∑II＝II1+II2；
∑III＝III1+III2；
∑IV＝IV1+IV2；
∑V＝V1+V2；
∑VI＝VI1+VI2；
∑VII＝VII1+VII2；
∑VIII＝VIII1+VIII2；
∑IX＝IX1+IX2；
then according to the formula:
setting e as sigma I + sigma III + sigma VII + sigma IX;
g＝∑II+∑IV+∑VI+∑VIII；
l＝∑V
k is a weighted value;
determining whether the user is in the road rage emotion in the driving process according to the weight value K and the result of the wavelet transformation;
firstly, respectively carrying out wavelet transformation on the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of speaking visceral words per hour of a user in a normal state, wherein the formula of the wavelet transformation is as follows:
wherein f (t) is a signal to be processed; ω (f, g) (t) is a wavelet function; f is the scale of wavelet transform, and controls the expansion and contraction of the wavelet function, corresponding to the frequency; g is an offset, and the translation of the wavelet function is controlled, corresponding to time; the processing can clearly observe the physiological state difference of the user in the driving process and the normal state by utilizing the waveform, thereby judging whether the user is in the emotion of road rage in the driving process;
collecting light wavelengths reflected on a left cheek and a right cheek of a user by using a wavelength collection unit, wherein the wavelength collection unit is an interferometer wavelength automatic measuring device, the light wavelength is defined as R when in a red stage, and the light wavelength is defined as G when in a non-red stage, and then a formula processed by using wavelet transform by the user is as follows:
wherein f (t)i) Is a signal to be processed;
(c，d)(ti) Is a wavelet function; c is the scale of wavelet transform, controlling the expansion and contraction of the wavelet function, corresponding to the frequency; d is an offset, controlling the translation of the wavelet function, corresponding to time; the processing can clearly observe the difference of the colors of the cheeks of the user in the driving process and the normal state by utilizing the waveform, thereby assisting in judging whether the user is in the emotion of the road rage in the driving process;
partitioning the left cheek and the right cheek of a user, wherein the left cheek is divided into 9 regions, and the collected light wavelength in red stage is respectively listed as I1、II1、III1、IV1V1、VI1、VII1、VIII1、IX1The right cheek is divided into 9 zones, and the collected light wavelength is in red stage for I2、II2、III2、IV2、V2、VI2、VII2、VIII2、IX2: because the color change of the face is not equal under the angry condition of a person, when a driver is in the road anger emotion, the color in the middle of the face can be displayed more, and the color change of the edge of the face cannot be displayed accurately, the color change of the face is not displayed more accurately, so that the part of the face where the person is using is madeDivision is carried out, and different proportions are given to each area;
the user's left and right cheeks were then subjected to a summation operation using the same area:
∑I＝I1+I2；
∑II＝II1+II2；
∑III＝III1+III2；
∑IV＝IV1+IV2；
∑V＝V1+V2；
∑VI＝VI1+VI2；
∑VII＝VII1+VII2；
∑VIII＝VIII1+VIII2；
∑IX＝IX1+IX2；
then according to the formula:
setting e as sigma I + sigma III + sigma VII + sigma IX;
g＝∑II+∑IV+∑VI+∑VIII；
l＝∑II+∑IV+∑VI+∑VIII
l＝∑V
e is the sum of the first, third, seventh, ninth regions of the cheek, g is the sum of the second, fourth, sixth, eighth regions, l is the sum of the fifth region;
k is a weighted value;
determining whether the user is in the road rage emotion in the driving process according to the weight value K and the result of the wavelet transformation;
firstly, solving the value of f obtained according to wavelet transformation, and calculating whether f is greater than u; (phi)
Then, the value of c is solved according to the wavelet transformation, and whether c is larger than p is calculated; (2)
Then, solving a weight value K according to the region division and a formula, and calculating whether K is greater than v; (iii)
c, f is a transformation scale, and u, p and v are self-defined constants;
if the first condition is met and the second and third conditions are not met, the user is judged to be in a mild state of the road rage; if the first condition is met, the second condition or the third condition is met, the user is judged to be in the serious road rage state.
The image unit 7.5 comprises a camera 4, the camera 4 is arranged at the central position of the neck ring body 3, a wavelength collecting unit is arranged in the camera, light supplementing lamps 10 are arranged at two ends of the camera 4, a speech acquisition module 6 is arranged outside the light supplementing lamps 10, and an adjusting module 5 is arranged outside the speech acquisition module 6;
above-mentioned camera is inside to be provided with wavelength collection unit, and wavelength collection unit can gather the wavelength of reflection light-emitting on the user's cheek to send state analysis device after making statistics with the wavelength and the acquisition time of the light of gathering, the light filling lamp can be under the dim circumstances of light, for the cheek light filling, wavelength collection unit can normally gather.
The light supplementing lamp 10 is provided with a baffle 11 at the outer side, the baffle 11 can adjust the angle, the bottom end of the baffle 11 is fixed on an adjusting rod 16, an adjusting body 15 is fixed on the adjusting rod 16, the adjusting body 15 comprises an inner core, a first connecting rod 15.1, a second connecting rod 15.2 and a third connecting rod 15.3, the first connecting rod 15.1 is provided with a first connecting tooth 15.4, the second connecting rod 15.2 is provided with a second connecting tooth 15.5 and a third connecting tooth 15.6, and the third connecting rod 15.3 is provided with a fourth connecting tooth 15.7;
the baffle is arranged on the outer side of the light supplement lamp, the angle can be adjusted by the baffle, and a user can adjust the angle of the baffle when the light supplement lamp works, so that the part irradiated by the light beam of the light supplement lamp is a cheek, and the light supplement lamp is prevented from directly irradiating eyes to influence driving of the user; the baffle bottom mounting is on adjusting the second connecting rod on the pole, and in the second connecting tooth on the second connecting rod was not gone into the first connecting tooth on the head rod, the third connecting tooth on the second connecting rod was not gone into the fourth connecting tooth on the third connecting rod, so can realize that the second connecting rod drives the baffle and rotates under the condition of not driving head rod and third connecting rod.
The client side is a mobile terminal, a handheld terminal and a cloud platform, the connection mode of the client side and the induction neck ring is wireless connection, and the wireless connection mode is Bluetooth, a local area network or 4G and 5G network connection.
The tail end of the induction neck ring is provided with a buckle 1 and a clamping shell 2, the buckle 1 can be buckled into the clamping shell 2 so as to realize connection, a power supply anode 1.1, a spring 1.2 and a battery 1.3 are distributed in the buckle 1 from top to bottom, and a power supply cathode 2.1 is arranged in the clamping shell 2;
the buckle distributes from last to having power positive pole, spring and battery down, is provided with the power negative pole in the card shell, in the buckle detained the card shell, can realize connecting with the circular telegram.
The working principle is as follows: according to the method, the neck ring is used for acquiring the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of words of dirty words in each hour of a user, respectively performing wavelet transformation and comparison to judge whether the user is in a road rage symptom state in a driving state, then acquiring the color changes of a left cheek and a right cheek of the user in a normal state and a driving state through the neck ring, and dividing the cheeks into 9 regions; the neck ring is used for collecting the numerical value, so that the operation of a user in the process of driving the vehicle is not influenced.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. The utility model provides a big data analysis system of driving habit for new energy automobile which characterized in that: the driving habit big data analysis system comprises an induction neck ring and a client, wherein the induction neck ring comprises a neck ring body (3) and a mounting band (12), the mounting band is arranged on the inner side of the induction neck ring, an information acquisition device (7), a state analysis device (8), a communication device (13), an adjusting device (5), a control device (9) and a storage device (14) are fixed on the mounting band, and an image acquisition device is installed on the neck ring body (3).
2. The driving habit big data analysis system for the new energy automobile according to claim 1, wherein: the state analysis device (8) analyzes the information input by the information acquisition device (7), the communication device (13) and the state analysis device (8) transmit the analyzed information to the control device (9) through the communication device (13), and the control device (9) sends an instruction to the adjusting device (5) according to the obtained information; the information acquisition device (7) is used for collecting the respiratory frequency of a user acquired by the respiratory frequency detection unit (7.1), the blood pressure value of the user acquired by the blood pressure detection unit (7.2), the pulse beating times of an actor per minute acquired by the pulse detection unit (7.3), the body surface temperature of the actor acquired by the body surface temperature detection unit (7.4), the color of the face of the actor acquired by the image unit (7.5) and the visceral words times per hour in the driving process of the actor acquired by the speech acquisition unit (6).
3. The driving habit big data analysis system for the new energy automobile according to claim 2, wherein: the system comprises a method which is divided into four steps:
s1: collecting the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature, the color of the face and the times of speaking visceral words in each hour of a user by using an information collecting unit;
s2: carrying out data summarizing processing on the acquired information;
s3: analyzing the summarized data so as to judge whether the state of the driver is in the road rage emotion or not;
s4: performing emotion adjustment processing on a driver in the road rage emotion;
s5: the driving habit of the user is obtained by processing the ratio of the time when the user is in the road rage emotion in the driving state to the total time when the user drives.
4. The driving habit big data analysis system for the new energy automobile according to claim 3, wherein: the step S1 includes two steps:
s11, collecting the state information of the user in the normal state;
and S12, collecting the state information of the user when driving the automobile.
5. The driving habit big data analysis system for the new energy automobile according to claim 3, wherein: the step S2 includes two steps:
s21, respectively performing wavelet transformation on the respiratory frequency, the blood pressure value, the pulse beating times in one minute, the body surface temperature and the times of speaking visceral words in each hour of a user in a normal state, and performing wavelet transformation and wavelength comparison on the color of the face of the user;
s22, processing the data in the driving process of the user in the same way;
and the step S3 is to compare the result obtained by wavelet transform in the normal state of the user and the weight value obtained by processing with the data in the driving state, so as to obtain whether the driver is in the road rage emotion.
6. The method of claim 5The utility model provides a big data analysis system of driving habit for new energy automobile which characterized in that: the formula of the wavelet transform is as follows:
wherein f (t) is a signal to be processed; ω (f, g) (t) is a wavelet function; f is the scale of wavelet transform, and controls the expansion and contraction of the wavelet function, corresponding to the frequency; g is an offset, and the translation of the wavelet function is controlled, corresponding to time;
using a wavelength collection unit to collect wavelengths of light reflected off the left and right cheeks of a human user, defining the wavelengths of light as R when in the red color phase and G when in the non-red color phase, using the formula of a human using wavelet transform processing as follows:
wherein f (t)i) Is a signal to be processed;
is a wavelet function; c is the scale of wavelet transform, controlling the expansion and contraction of the wavelet function, corresponding to the frequency; d is an offset, controlling the translation of the wavelet function, corresponding to time;
partitioning the left cheek and the right cheek of a user, wherein the left cheek is divided into 9 regions, and the collected light wavelength in red stage is respectively listed as I1、II1、III1、IV1V1、VI1、VII1、VIII1、IX1The right cheek is divided into 9 zones, and the collected light wavelength is in red stage for I2、II2、III2、IV2、V2、VI2、VII2、VIII2、IX2：
The same area of the left and right cheeks was summed:
∑I＝I1+I2；
∑II＝II1+II2；
∑III＝III1+III2；
∑IV＝IV1+IV2；
∑V＝V1+V2；
∑VI＝VI1+VI2；
∑VII＝VII1+VII2；
∑VIII＝VIII1+VIII2；
∑IX＝IX1+IX2；
then according to the formula:
setting e as sigma I + sigma III + sigma VII + sigma IX;
g＝∑II+∑IV+∑VI+∑VIII；
l＝∑V
e is the sum of the first, third, seventh, ninth regions of the cheek, g is the sum of the second, fourth, sixth, eighth regions, l is the sum of the fifth region, and K is the weight value.
7. The driving habit big data analysis system for the new energy automobile according to claim 2, wherein: image unit (7.5) include camera (4), install on neck ring body (3) central point puts camera (4), the unit is collected to the inside wavelength that is provided with of camera, camera (4) both ends are provided with light filling lamp (10), the light filling lamp (10) outside is provided with speech acquisition module (6), speech acquisition module (6) outside is provided with adjusting module (5).
8. The driving habit big data analysis system for the new energy automobile according to claim 7, wherein: light filling lamp (10) outside is provided with baffle (11), baffle (11) can angle regulation, baffle (11) bottom mounting is on adjusting pole (16), it has regulation body (15) to be fixed with on adjusting pole (16), regulation body (15) include inner core, head rod (15.1), second connecting rod (15.2) and third connecting rod (15.3), be provided with first connecting tooth (15.4) on head rod (15.1), be provided with second on second connecting rod (15.2) and connect tooth (15.5) and third and connect tooth (15.6), be provided with fourth on third connecting rod (15.3) and connect tooth (15.7).
9. The driving habit big data analysis system for the new energy automobile according to claim 1, wherein: the client side is a mobile terminal, a handheld terminal and a cloud platform, the client side and the induction neck ring are connected in a wireless mode, and the wireless connection mode is Bluetooth, a local area network or 4G and 5G network connection.
10. The driving habit big data analysis system for the new energy automobile according to claim 1, wherein: the end of the induction neck ring is provided with a buckle (1) and a clamping shell (2), the buckle (1) can be buckled into the clamping shell (2) so as to realize connection, a power anode (1.1), a spring (1.2) and a battery (1.3) are distributed in the buckle (1) from top to bottom, and a power cathode (2.1) is arranged in the clamping shell (2).
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