CN108710898A - Travel safety ensuring system based on Multi-sensor Fusion and method - Google Patents
Travel safety ensuring system based on Multi-sensor Fusion and method Download PDFInfo
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Abstract
The invention discloses a kind of travel safety ensuring system and method based on Multi-sensor Fusion, wherein system includes master control borad, sensor group, gsm communication module, cloud Data Analysis Platform.Terminal of the master control borad as cloud Data Analysis Platform is uploaded to cloud Data Analysis Platform by gsm communication module, while the early warning and evaluation that cloud Data Analysis Platform is made is fed back to user；Gsm module completes the communication between terminal and cloud Data Analysis Platform by GSM；Sensor group includes multiple sensors, including gas sensor, alcohol sensor, video sensor, speech transducer, six axle sensors.Cloud Data Analysis Platform, connect with master control borad, and the signal for being acquired according to sensor group carries out road illegal activities analysis, vehicle density information inquiry, the analysis of bad steering custom and recommends.
Description
Technical field
The invention belongs to operation safety technical field, it is related to a kind of traffic safety on-line monitoring early warning and evaluation feedback
A kind of system, and in particular to operation safety on-line monitoring early warning system based on Multi-sensor Fusion.
Background technology
With being continuously increased for vehicle ownership, all kinds of safety accidents take place frequently, and cause huge economic loss, seriously affect
The safe operation of road traffic, carrying out effective monitoring and warning to traffic safety becomes the task of top priority.Related data are shown, because dredging
Suddenly general idea, drive over the speed limit, improper measures, illegal passing, not according to regulations, violation road occupying traveling, driving when intoxicated causes death
Number accounts for the 51.3% of the dead sum of traffic accident, accounts for automobile driver reason and causes death the 65.3% of sum.Wherein drive
The person of sailing when driving dispersion attention, excessive fatigue, rest it is insufficient, have not enough sleep, drive when intoxicated, physical condition
Not good enough equal potential psychology, physiological reasons, cause delay of response and lead to traffic accident.Driver's driving technology is not familiar, feelings
Thread is unstable, can also cause traffic accident.Meanwhile in the driver of 2-3,4-5 traffic accident occurs for the driving age often, it is dead
Number is more, and driver's number that the driving age is 1 year is not dominant in driver's sum, but the ratio to cause damages is most
Big.And all kinds of emergency situations outside vehicle are also the main reason for causing road safety accident.
In existing travel safety ensuring system, function integration problem is complicated, and the data mode of multi-sensor collection is different, has
Digital image information processing and various sensor level signals, intractability are also different；Data flow is more and complicated, it is difficult to unified
Processing；Data volume is larger, it is difficult to carry out uploading to cloud platform carrying out analysis prediction in time, it is difficult to which the low time delay for reaching this process is wanted
It asks.
Currently, in driving security fields, without a comprehensive travel safety ensuring system.Due to condition of road surface by with
Machine factor influences big so that the outer road condition predicting of vehicle is difficult to realize.Meanwhile the bad steering custom of driver is also difficult to predict
And specification.
Invention content
The technical problem to be solved in the present invention is in the prior art without a comprehensive operation safety
The defect of system provides a kind of travel safety ensuring system based on Multi-sensor Fusion effectively improving traffic safety and side
Method.
Technical solution is used by the present invention solves its technological difficulties：
A kind of operation safety on-line monitoring early warning system based on Multi-sensor Fusion, including master control borad, biography are provided
Sensor group, gsm communication module, cloud Data Analysis Platform, wherein
Terminal of the master control borad as cloud Data Analysis Platform is uploaded to cloud Data Analysis Platform, together by gsm communication module
When early warning and evaluation that cloud Data Analysis Platform is made fed back into user；
Gsm module completes the communication between terminal and cloud Data Analysis Platform by GSM；
Sensor group includes multiple sensors, including gas sensor, alcohol sensor, video sensor, voice sensing
Device, six axle sensors；
Gas sensor：For CO2 the and CO concentration in collecting vehicle, concentration signal is converted into voltage signal, and pass through
Master control borad is issued after amplification；
Alcohol sensor：For the alcohol concentration in collecting vehicle, concentration signal is converted into voltage signal, and by amplification
After issue master control borad；
Video sensor：By the information of driver in camera collecting vehicle, and image recognition is carried out, by recognition result
It is sent to master control borad；
Speech transducer：By sound in collecting vehicle, by being sent to master control borad after filtering；
Six axle sensors：Deviation for measuring vehicle and acceleration obtain vehicle posture by master control borad；
Cloud Data Analysis Platform, connect with master control borad, and the signal for being acquired according to sensor group carries out the illegal row of road
For analysis, vehicle density information inquiry, the analysis of bad steering custom and recommend.
Connect above-mentioned technical proposal, the signal of sensor group acquisition include it is lack of standardization turns to, bring to a halt, it is anxious accelerate, interior sky
Makings amount and interior alcohol concentration；Wherein lack of standardization turn to includes not opening steering indicating light, opens steering indicating light apart from turnaround time
Gap is too short；Bad steering custom analysis result includes fatigue driving and drunk driving, and fatigue driving includes driver's facial information, violent
It holds steering wheel or suddenly touches on the brake, automobile shake is anxious suddenly to slow down；Drunk driving includes that interior alcohol concentration is higher, vehicle body travel route
Bending, vehicle body frequently shake etc.；
Cloud Data Analysis Platform establishes driving dangerousness behavior mathematical model by the signal that sensor group acquires and sample is instructed
Practice, and judge the traffic safety state of vehicle according to the signal synthesis of acquisition, realizes to dangerous driving behavior early warning.
Above-mentioned technical proposal is connect, the cloud Data Analysis Platform is additionally operable to position vehicle, be sent using gsm module
Location information to cloud Data Analysis Platform and preserves when driving process location information or vehicle stall.
Connect above-mentioned technical proposal, cloud Data Analysis Platform by the gathered data of video sensor and six axle sensors come
Judge vehicle appearance, hand is played when obtaining the vehicle behavior aspect of model, then being identified by dangerous driving behavior recognizer including driving
Machine, fatigue driving bad steering behavior.
Above-mentioned technical proposal is connect, cloud Data Analysis Platform is specifically used for：
CO and CO2 concentration is monitored, when concentration reaches set limiting value alarm；
Alcohol concentration in air is monitored, the data for coordinating video sensor and six axle sensors to measure, obtain including
The frequency of left and right zig zag, the aspect of model of frequency of bringing to a halt and situation of driving over the speed limit, and identified and calculated by dangerous driving behavior
Method makes differentiation and alarms；
To bad steering behavior monitoring, according to steering indicating light opening imformation, then pass through video sensor and six axle sensors
Judge vehicle appearance, realizes the early warning for the bad steering behavior for not opening steering indicating light steering or the understeer of steering indicating light opening time；
All kinds of bad steering behaviors are sent to cloud Data Analysis Platform by gsm module, pass through cloud Data Analysis Platform
Driving behavior evaluation system assess the driving behavior of driver and make suggestion, when driver occur again it is similar
It is prompted before bad steering behavior and provides suggestion.
Above-mentioned technical proposal is connect, the address space of the on-chip memory of master control borad is divided into 5 regions, including start
Area, application area, gsm module memory block, user data area and cloud platform information processing area；It is responsible for hardware in system in promoter region
Clock frequency setting and other initialization；It is responsible for processing and analyzes each collected real-time number of sensor in application area
According to；It is responsible for the network data transmission with cloud Data Analysis Platform in gsm module memory block；User data area is run for save routine
The middle data for needing to store, with loss of data after anti-power failure；Cloud platform information processing area is mainly handled to be obtained from cloud data platform
Evaluation advisory information, driver is fed back to by speech transducer later.
The present invention also provides a kind of, and the operation safety based on Multi-sensor Fusion monitors method for early warning on-line, including
Following steps：
The mathematical model for establishing all kinds of dangerous driving behaviors extracts its model by founding mathematical models and sample training
Feature builds dangerous driving behavior recognizer with this；
Do not stop the various information in collecting vehicle and outside vehicle by various sensors, and gives master control borad and handled；Specifically
Including：
1. air quality sensor carries out CO and CO2 concentration measurement and controls, set limiting value alarm is reached；
It is monitored 2. alcohol concentration sensor carries out alcohol concentration in air, video sensor, six axle sensors is coordinated to measure
Data, obtain include left and right zig zag frequency, frequency of bringing to a halt and situation of driving over the speed limit the aspect of model, driven by danger
Activity recognition algorithm is sailed to be differentiated and alarmed；
3. judging vehicle appearance by the measurement data of video sensor and six axle sensors, the aspect of model is obtained, finally
The bad steering behavior including playing mobile phone, fatigue driving when driving is told by dangerous driving behavior recognizer.
4. acquiring steering indicating light opening imformation, then the survey by video sensor and six axle sensors by speech transducer
Amount data judge vehicle appearance, realize the pre- of the bad steering behavior for not opening steering indicating light steering or the understeer of steering indicating light opening time
It is alert.
5. obtaining geographic location signal by gsm module and passing to master control borad, master control borad is sent to by gsm module again
Cloud server end, car owner can monitor the position of the vehicle of oneself by accessing high in the clouds, antitheft to achieve the purpose that.
6. being sent to cloud data analysis by gsm module by master control borad in all kinds of bad steering behaviors that front end is realized to put down
Platform is assessed and is made to the driving behavior of driver by the driving behavior evaluation system in cloud Data Analysis Platform and built
View prompts before similar bad steering behavior occurs again in driver and provides suggestion.
The beneficial effect comprise that：The present invention measures the measurement index of corresponding function using multisensor, passes through
Algorithm is fitted with existing dangerous driving behavior, is realized the monitoring to all kinds of dangerous driving behaviors, is substantially increased differentiation
Precision；All kinds of dangerous driving behavior distinguished numbers are realized based on vehicle appearance, based on being ground to dangerous driving behavior related data early period
Study carefully, is based on cloud platform data analysis, the error of data can be greatly reduced, improve the fitting precision of data；It is wireless using GPRS
The communication technology carries out real time information upload, it can be achieved that the tracking to vehicle and anti-theft feature to vehicle；By by car drive with
The outer road conditions of vehicle are combined, based on development of Mobile Internet technology can better support vehicles safety traffic state；In addition, based on deep
The traffic safety evaluation model for spending study realizes that individual subscriber driving characteristics are handed over road by the continuous study and training of model
Logical safety behavior is combined, and keeps evaluating result science comprehensive.
Description of the drawings
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing：
Fig. 1 is the embodiment of the present invention based on the on-line monitoring early warning system structural representation of multisensor operation safety
Figure；
Fig. 2 is the operation safety on-line monitoring early warning system medium cloud based on Multi-sensor Fusion of the embodiment of the present invention
Data Analysis Platform is to driver's early warning and suggests flow chart；
Fig. 3 is the embodiment of the present invention based on multisensor operation safety on-line monitoring method for early warning flow chart.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
It please refers to Fig.1 and Fig. 2, the embodiment of the present invention includes：Operation safety based on Multi-sensor Fusion is supervised online
Detection early warning system is mainly by multiple sensors, master control borad, gsm module and Cloud Server composition.Do not stop to adopt by various sensors
Collection is interior and vehicle outside various information, and give master control borad and handled, master control borad is responsible for receiving the information of each sensor simultaneously
It is pre-processed, information is transferred to cloud Data Analysis Platform by gsm module, cloud Data Analysis Platform carries out these information
Certain classification is handled data by traffic safety early warning system and personalized traffic safety evaluation system, and will processing
Obtained vehicle location later, the traffic safety state of comprehensive descision gained vehicle, and proposed using deep learning algorithm
Personalized traffic safety assessment and traffic safety suggestion etc. driver is fed back to by cloud platform.
In the preferred embodiment of the present invention, the operation safety on-line monitoring early warning system based on Multi-sensor Fusion
System includes master control borad, sensor group, gsm communication module, cloud Data Analysis Platform, wherein
Terminal of the master control borad as cloud Data Analysis Platform is uploaded to cloud Data Analysis Platform, together by gsm communication module
When early warning and evaluation that cloud Data Analysis Platform is made fed back into user；
Gsm module completes the communication between terminal and cloud Data Analysis Platform by GSM；
Sensor group includes multiple sensors, including gas sensor, alcohol sensor, video sensor, voice sensing
Device, six axle sensors；
Gas sensor：For CO2 the and CO concentration in collecting vehicle, concentration signal is converted into voltage signal, and pass through
Master control borad is issued after amplification；
Alcohol sensor：For the alcohol concentration in collecting vehicle, concentration signal is converted into voltage signal, and by amplification
After issue master control borad；
Video sensor：By the information of driver in camera collecting vehicle, and image recognition is carried out, by recognition result
It is sent to master control borad；
Speech transducer：By sound in collecting vehicle, by being sent to master control borad after filtering；
Six axle sensors：Deviation for measuring vehicle and acceleration obtain vehicle posture by master control borad；
Cloud Data Analysis Platform, connect with master control borad, and the signal for being acquired according to sensor group carries out the illegal row of road
For analysis, vehicle density information inquiry, the analysis of bad steering custom and recommend.
Further, the signal of sensor group acquisition include it is lack of standardization turns to, bring to a halt, anxious acceleration, in-car air quality
And interior alcohol concentration；Wherein lack of standardization turn to includes not opening steering indicating light, opens steering indicating light apart from turnaround time gap mistake
It is short；It includes fatigue driving and drunk driving that bad steering, which is accustomed to analysis result, and fatigue driving includes driver's facial information, holds direction suddenly
Disk suddenly touches on the brake, automobile shake, anxious suddenly to slow down；Drunk driving includes that interior alcohol concentration is higher, the bending of vehicle body travel route, vehicle
Body frequently shake etc.；
Cloud Data Analysis Platform establishes driving dangerousness behavior mathematical model by the signal that sensor group acquires and sample is instructed
Practice, and judge the traffic safety state of vehicle according to the signal synthesis of acquisition, realizes to dangerous driving behavior early warning.
The cloud Data Analysis Platform is additionally operable to position vehicle, and sending driving process position using gsm module believes
Location information to cloud Data Analysis Platform and preserves when breath or vehicle stall.
Cloud Data Analysis Platform judges vehicle appearance by the gathered data of video sensor and six axle sensors, obtains vehicle
Behavior model feature, then while being identified by dangerous driving behavior recognizer including driving, play mobile phone, fatigue driving not
Good driving behavior.
Further, cloud Data Analysis Platform is specifically used for：
CO and CO2 concentration is monitored, when concentration reaches set limiting value alarm；
Alcohol concentration in air is monitored, the data for coordinating video sensor and six axle sensors to measure, obtain including
The frequency of left and right zig zag, the aspect of model of frequency of bringing to a halt and situation of driving over the speed limit, and identified and calculated by dangerous driving behavior
Method makes differentiation and alarms；
To bad steering behavior monitoring, according to steering indicating light opening imformation, then pass through video sensor and six axle sensors
Judge vehicle appearance, realizes the early warning for the bad steering behavior for not opening steering indicating light steering or the understeer of steering indicating light opening time；
All kinds of bad steering behaviors are sent to cloud Data Analysis Platform by gsm module, pass through cloud Data Analysis Platform
Driving behavior evaluation system assess the driving behavior of driver and make suggestion, when driver occur again it is similar
It is prompted before bad steering behavior and provides suggestion.
In one embodiment of the present of invention, using STM32 as master control borad, hardware of the Raspberry Pi as image procossing core
Framework.The address space of the on-chip memory of STM32 is divided, and then is handled by the spy after Raspberry Pi image procossing
Reference ceases and the collected information of other sensors.It is specific as follows：The address space of the on-chip memory of STM32 is divided into 5
A region is promoter region, application area, gsm module memory block, user data area, cloud platform information processing area respectively.Start
It is responsible for the clock frequency setting of hardware in system and other initialization in area；It is responsible for processing and analyzes each sensor in application area
Collected real time data；It is responsible for the network data transmission with cloud Data Analysis Platform in gsm module memory block；User data area is used
The data stored are needed in save routine operation, with loss of data after anti-power failure；Cloud platform information processing area mainly handle from
The information such as the evaluation suggestion that cloud data platform obtains, feed back to driver by voice module later.
The data of cloud Data Analysis Platform are uploaded and communicated, provide the data frame format of system first, it is stringent to control
The data volume of biography uploads to cloud platform using the MQTT communication technologys later and is analyzed.MQTT agreements are by release model and subscription
Two kinds of communication patterns of pattern are constituted, and release model is used for the transmission of data, and subscribing mode is used for the acquisition of data.When subscriber orders
Read corresponding release model ID just can get the real time information that publishing side is provided in real time.Biography needed for MQTT agreements
Defeated byte is considerably less, can establish and complete stable data transmission on the basis of Socket, and minimum bandwidth consumption can be big
It is big to save transmission cost and ensure propagation delay time.
Cloud Data Analysis Platform program is mainly responsible for be communicated with the ends STM32.It is responsible for driving states data at the ends STM32
Acquisition, keep long connection to carry out real-time Data Transmission using MQTT agreements and Socket and high in the clouds.Letter of the cloud platform to upload
Breath is evaluated and is predicted, is provided driving later and is suggested.
The course of work of control system of the present invention：
The model for initially setting up all kinds of dangerous driving modes is instructed by establishing driving dangerousness behavior mathematical model and sample
Practice, extracts its aspect of model and dangerous driving behavior recognizer is built with this.
Do not stop the various information in collecting vehicle and outside vehicle by various sensors, and gives master control borad and handled.Such as Fig. 3
It is shown, sensor is divided into operation detection sensor and state detection sensor first, operation detection sensor is mainly six axis
Sensor detects the turning in driving conditions and velocity variations；State detection sensor includes gas sensor, alcohol sensing
Device, video sensor, sound transducer detect each side's surface state in driving conditions.
Driving behavior is divided into various driving modes by the present invention, and particularly, dangerous driving behavior is also driver's behavior
One mode, further describe, now write a Chinese character in simplified form typical driving condition for convenience, following table is the partial content in writing a Chinese character in simplified form.
| Alcohol concentration is normal | E |
| Alcohol concentration is excessively high | HE |
| Driver's frequency of wink is normal | F |
| Driver's frequency of wink is excessively high | HF |
| At the uniform velocity | A |
| It is normal to accelerate | B |
| It is normal to slow down | C |
| It is anxious to accelerate | AB |
| It is anxious to slow down | AC |
| Turn left | L |
| It turns right | R |
| Frequently turning | D |
It is distinguished according to different actions, the sequence of operations of driver can be divided into the combination of typicalness, and different is
Various combination of the row operation with typicalness.
The form for using questionnaire survey later, obtains it is believed that belonging to the dangerous driving behaviors such as drunk driving, fatigue driving
Sequence of maneuvers, such as HE-HF-AB-AC-D etc..By using SVM classifier, mark out manually belong to dangerous driving behavior be
Row operation and the sequence of maneuvers for being not belonging to dangerous driving behavior, sum up dangerous driving behavior model.
First, sensor group acquisition driving conditions in corresponding vehicle appearance information, with the combination of typicalness be depicted come,
It is comprehensive to generate the characteristic model for describing real-time driving states.Later, with the combination of the typicalness just generated, and pass through before
The existing model that dangerous driving behavior obtained from deep learning and sample training identifies matches, if it exceeds the threshold of setting
Value then carries out early warning and alarm to driver.
Specifically include following steps：
1. air quality sensor is mainly responsible for CO and CO2 concentration measurement and controls, set limiting value alarm is reached；
It is monitored 2. alcohol concentration sensor is responsible for alcohol concentration in air, coordinates video monitoring, what six axle sensors measured
Data obtain the aspect of model such as frequency, frequency of bringing to a halt and the situation of driving over the speed limit of left and right zig zag, pass through dangerous driving behavior
Recognizer makes differentiation and alarms；
3. concentration problem can not realize differentiation to driver attention by similar approach yet, pass through video monitoring and six axis
The measurement data of sensor judges vehicle appearance, obtains the aspect of model, goes out to drive respectively finally by dangerous driving behavior recognizer
The behaviors such as mobile phone, fatigue driving are played when sailing.
4. acquiring steering indicating light opening imformation by audio collection module, (when opening steering, there are one specific frequency is " ticking for meeting
It is ticking " sound, can judge whether steering indicating light is opened by acquiring this sound), then pass through video monitoring and six axis sensing
Device judges vehicle appearance, realizes the early warning for the bad steering behavior for not opening steering indicating light steering or the understeer of steering indicating light opening time.
5. geographic location signal is obtained by the gsm module built in traffic safety cloud bodyguard and passes to STM32 master control borads,
Then STM32 is sent to cloud server end by gsm module, and car owner can monitor the position of the vehicle of oneself by accessing high in the clouds
It sets, it is antitheft to achieve the purpose that.
6. being sent to cloud server end by gsm module by STM32 in all kinds of bad steering behaviors that front end is realized, pass through
Driving behavior evaluation system in Cloud Server assesses the driving behavior of driver and makes suggestion, when driver is another
It is secondary to occur being prompted before similar bad steering behavior and providing suggestion.
Above functions is pre-processed by master control borad, and acquired sensor information is then passed through GSM moulds by master control borad
Block uploads to cloud Data Analysis Platform, and cloud Data Analysis Platform carries out these information certain classification, the processing such as summary, and incites somebody to action
Obtained vehicle location after processing, traffic safety early warning and drive advice etc. feed back to driver by gsm module.
It should be understood that for those of ordinary skills, it can be modified or changed according to the above description,
And all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Claims (7)
1. a kind of operation safety based on Multi-sensor Fusion monitors early warning system on-line, which is characterized in that including master control
Plate, sensor group, gsm communication module, cloud Data Analysis Platform, wherein
Terminal of the master control borad as cloud Data Analysis Platform is uploaded to cloud Data Analysis Platform by gsm communication module, simultaneously will
The early warning and evaluation that cloud Data Analysis Platform is made feed back to user；
Gsm module completes the communication between terminal and cloud Data Analysis Platform by GSM；
Sensor group includes multiple sensors, including gas sensor, alcohol sensor, video sensor, speech transducer, six
Axle sensor；
Gas sensor：For CO2 the and CO concentration in collecting vehicle, concentration signal is converted into voltage signal, and by amplification
After issue master control borad；
Alcohol sensor：For the alcohol concentration in collecting vehicle, concentration signal is converted into voltage signal, and sent out after amplification
To master control borad；
Video sensor：By the information of driver in camera collecting vehicle, and image recognition is carried out, recognition result is sent
To master control borad；
Speech transducer：By sound in collecting vehicle, by being sent to master control borad after filtering；
Six axle sensors：Deviation for measuring vehicle and acceleration obtain vehicle posture by master control borad；
Cloud Data Analysis Platform, connect with master control borad, and the signal for being acquired according to sensor group carries out road illegal activities point
Analysis, vehicle density information inquiry, the analysis of bad steering custom and recommendation.
2. the operation safety according to claim 1 based on Multi-sensor Fusion monitors early warning system on-line, special
Sign is, the signal of sensor group acquisition include it is lack of standardization turns to, bring to a halt, it is anxious accelerate, in-car air quality and car wine
Smart concentration；Wherein lack of standardization turn to includes not opening steering indicating light, and it is too short apart from turnaround time gap to open steering indicating light；Bad steering
Custom analysis result includes fatigue driving and drunk driving, and fatigue driving includes driver's facial information, holds steering wheel suddenly or suddenly step on brake
Vehicle, automobile shake are anxious suddenly to slow down；Drunk driving includes that interior alcohol concentration is higher, and vehicle body travel route bending, vehicle body is frequently shaken
Deng；
Cloud Data Analysis Platform establishes driving dangerousness behavior mathematical model and sample training by the signal that sensor group acquires, and
The traffic safety state of vehicle is judged according to the signal synthesis of acquisition, is realized to dangerous driving behavior early warning.
3. the operation safety described in accordance with the claim 1 based on Multi-sensor Fusion monitors early warning system on-line, special
Sign is that the cloud Data Analysis Platform is additionally operable to position vehicle, and driving process location information is sent using gsm module
Or location information to cloud Data Analysis Platform and preserves when vehicle stall.
4. the operation safety according to claim 1 based on Multi-sensor Fusion monitors early warning system on-line, special
Sign is that cloud Data Analysis Platform judges vehicle appearance by the gathered data of video sensor and six axle sensors, obtains vehicle
Behavior model feature, then while being identified by dangerous driving behavior recognizer including driving, play mobile phone, fatigue driving not
Good driving behavior.
5. the operation safety according to claim 1 based on Multi-sensor Fusion monitors early warning system on-line, special
Sign is that cloud Data Analysis Platform is specifically used for：
CO and CO2 concentration is monitored, when concentration reaches set limiting value alarm；
Alcohol concentration in air is monitored, the data for coordinating video sensor and six axle sensors to measure are obtained including left and right
The aspect of model of the frequency of zig zag, frequency of bringing to a halt and situation of driving over the speed limit, and made by dangerous driving behavior recognizer
Go out differentiation and alarms；
To bad steering behavior monitoring, judge according to steering indicating light opening imformation, then by video sensor and six axle sensors
Che Zi realizes the early warning for the bad steering behavior for not opening steering indicating light steering or the understeer of steering indicating light opening time；
All kinds of bad steering behaviors are sent to cloud Data Analysis Platform by gsm module, pass through driving for cloud Data Analysis Platform
It sails behavior evaluation system and assesses the driving behavior of driver and make suggestion, when driver occurs again similar to bad
It is prompted before driving behavior and provides suggestion.
6. the operation safety based on Multi-sensor Fusion monitors early warning system on-line, which is characterized in that by the piece of master control borad
The address space of built-in storage is divided into 5 regions, including promoter region, application area, gsm module memory block, user data
Area and cloud platform information processing area；It is responsible for the clock frequency setting of hardware in system and other initialization in promoter region；Using journey
It is responsible for processing and analyzes each collected real time data of sensor in sequence area；It is responsible for and cloud Data Analysis Platform gsm module memory block
Network data transmission；User data area in save routine operation for needing the data stored, with loss of data after anti-power failure；
Cloud platform information processing area mainly handles the evaluation advisory information obtained from cloud data platform, is fed back later by speech transducer
To driver.
7. a kind of operation safety based on Multi-sensor Fusion monitors method for early warning on-line, which is characterized in that including following
Step：
The mathematical model for establishing all kinds of dangerous driving behaviors extracts its aspect of model by founding mathematical models and sample training
Dangerous driving behavior recognizer is built with this；
Do not stop the various information in collecting vehicle and outside vehicle by various sensors, and gives master control borad and handled；It specifically includes：
1. air quality sensor carries out CO and CO2 concentration measurement and controls, set limiting value alarm is reached；
It is monitored 2. alcohol concentration sensor carries out alcohol concentration in air, coordinates video sensor, the number that six axle sensors measure
According to, obtain include left and right zig zag frequency, frequency of bringing to a halt and situation of driving over the speed limit the aspect of model, pass through dangerous driving row
Differentiated for recognizer and is alarmed；
3. judging vehicle appearance by the measurement data of video sensor and six axle sensors, the aspect of model is obtained, finally by
Dangerous driving behavior recognizer tells the bad steering behavior including playing mobile phone, fatigue driving when driving；
4. acquiring steering indicating light opening imformation by speech transducer, then pass through video sensor and the measurement number of six axle sensors
It is judged that vehicle appearance, realizes the early warning for the bad steering behavior for not opening steering indicating light steering or the understeer of steering indicating light opening time；
5. obtaining geographic location signal by gsm module and passing to master control borad, master control borad is sent to cloud clothes by gsm module again
Business device end, car owner can monitor the position of the vehicle of oneself by accessing high in the clouds, antitheft to achieve the purpose that；
6. being sent to cloud Data Analysis Platform by gsm module by master control borad in all kinds of bad steering behaviors that front end is realized, lead to
The driving behavior evaluation system crossed in cloud Data Analysis Platform assesses the driving behavior of driver and makes suggestion, when driving
Being prompted before similar bad steering behavior and providing suggestion occur again in the person of sailing.
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