CN113650557B - Intelligent vehicle monitoring and early warning system based on mobile police service Internet of things - Google Patents
Intelligent vehicle monitoring and early warning system based on mobile police service Internet of things Download PDFInfo
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- CN113650557B CN113650557B CN202110972218.3A CN202110972218A CN113650557B CN 113650557 B CN113650557 B CN 113650557B CN 202110972218 A CN202110972218 A CN 202110972218A CN 113650557 B CN113650557 B CN 113650557B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q5/00—Arrangement or adaptation of acoustic signal devices
- B60Q5/005—Arrangement or adaptation of acoustic signal devices automatically actuated
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
- H04L67/63—Routing a service request depending on the request content or context
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/08—Access security
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
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Abstract
The invention discloses an intelligent vehicle monitoring and early warning system based on a mobile police Internet of things, which belongs to the field of mobile police and is used for solving the problems that dangerous driving behaviors of police vehicles cannot be effectively monitored and differentiated access cannot be realized according to the authority of a mobile police terminal.
Description
Technical Field
The invention belongs to the field of mobile police, relates to a vehicle monitoring and early warning technology, and particularly relates to a vehicle intelligent monitoring and early warning system based on mobile police Internet of things.
Background
The mobile police service is an informatization means for completing police service law enforcement work by using mobile terminals such as mobile phones, PDAs or notebooks to realize access to police service information through a wireless network. The system for realizing the mobile police service is also called police service, and comprises a mobile terminal, a background processing platform and a corresponding network security mechanism. The integration network of the advanced mobile police service comprises public integration, wide integration and narrow integration, integration access of the Internet of things and the video private network, and the integration can be realized from three layers of a communication network segment, a service network segment and a service application end and meets the safety architecture specification of the existing mobile police service network.
In the prior art, in the police internet of things, various police vehicles are managed to have more dead zones, such as the running state of the vehicle, and the dangerous driving behavior of the vehicle cannot be effectively and safely early-warned and monitored; when the mobile police terminal is connected with the service data of the Internet of things, the mobile police terminal cannot be subjected to differentiated access according to the authority of the mobile police terminal, and fusion scheduling performance and safety are poor.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a vehicle intelligent monitoring and early warning system based on mobile police Internet of things.
The technical problems to be solved by the invention are as follows:
(1) How to effectively pre-warn and monitor dangerous driving behaviors of various police vehicles;
(2) When the mobile police terminal is connected with the service data of the Internet of things, how to realize differentiated access according to the authority of the mobile police terminal.
The aim of the invention can be achieved by the following technical scheme:
the intelligent vehicle monitoring and early warning system based on the mobile police Internet of things comprises a mobile police terminal, an Internet of things server and a vehicle-mounted Internet of things terminal, wherein the Internet of things server comprises a deviation early warning module, a speed monitoring module and a fusion scheduling module, the Internet of things server is connected with the vehicle-mounted Internet of things terminal, the Internet of things server is connected with the fusion scheduling module, the fusion scheduling module is connected with the mobile police terminal, and the Internet of things server is in data connection with the mobile police terminal through the fusion scheduling module;
the mobile police terminal is used for sending a data access request by police personnel and sending the data access request to the fusion scheduling module; after the converged scheduling module receives a data access request sent by the mobile police terminal, the converged scheduling module is used for performing access scheduling between the mobile police terminal and the Internet of things server, and the working process is as follows:
step S1: the IP address of the mobile police terminal is obtained, and the mobile police terminal is marked as a first access terminal and a second access terminal through IP address comparison;
step S2: the secondary access terminal is marked as u, u=1, 2, … …, x, x is a positive integer; acquiring generation time of a data access request sent by a secondary access terminal, and marking the generation time as TSu;
step S3: obtaining an access level of a secondary access terminal, and obtaining an access authority coefficient FQxu corresponding to the secondary access terminal through the access level;
step S4: acquiring the request times of the secondary access terminal for sending the data access request, and marking the request times as QCu; obtaining access time of the secondary access terminal for accessing the Internet of things server each time, and obtaining access average time JFtu of the secondary access terminal by adding and summing the access time of the Internet of things server each time and dividing the access time by the request times;
step S5: by the formulaCalculating to obtain an access value FWu of the secondary access terminal; wherein, c1 and c2 are fixed values of the proportionality coefficient, and the values of c1 and c2 are larger than zero;
step S6: if the access value FWu of the secondary access terminal is greater than or equal to Y2, marking the secondary access terminal as an active access terminal;
if the access value FWu of the secondary access terminal is greater than or equal to Y1 and less than Y2, marking the secondary access terminal as a medium access terminal;
if the access value FWu of the secondary access terminal is smaller than Y1, marking the secondary access terminal as a cold access terminal; wherein Y1 and Y2 are access thresholds, and Y1 is less than Y2;
the fusion scheduling module feeds back an active access terminal, a medium access terminal, a cold access terminal or a first access terminal to an Internet of things server, and the Internet of things server sets access rights for a mobile police terminal according to the active access terminal, the medium access terminal, the cold access terminal or the first access terminal;
the vehicle-mounted internet of things terminal is connected with a data acquisition module and an alarm module, and the alarm module is used for alarming dangerous driving behaviors of a vehicle; the vehicle-mounted internet of things terminal is used for transmitting the driving data of the vehicle to an internet of things server, and the internet of things server is used for transmitting the driving data of the vehicle to a deviation early warning module and a speed monitoring module respectively;
the deviation early-warning module is connected with a timing unit, the timing unit is used for timing the deviation time of the vehicle and sending timing data to the deviation early-warning module, the deviation early-warning module is used for carrying out deviation early warning on a driving lane of the vehicle, if the vehicle is in a normal driving state, a overtaking state or a lane changing state, no signal is generated, and if the vehicle is judged to be in an abnormal driving state, a lane deviation signal is generated;
the lane departure warning module sends lane departure signals to the Internet of things server, the Internet of things server feeds the lane departure signals back to the vehicle-mounted Internet of things terminal, the vehicle-mounted Internet of things terminal converts the lane departure signals into warning signals, the vehicle-mounted Internet of things terminal loads the warning signals to the warning module, and the warning module sounds a warning;
the speed monitoring module is used for safely monitoring the abnormal running speed of the vehicle, generating no signal if the real-time speed of the vehicle is in a normal state, generating a cautious driving signal if the real-time speed of the vehicle is in an abnormal state, and generating a dangerous driving signal if the real-time speed of the vehicle is in a dangerous state;
the speed monitoring module sends a cautious driving signal or a dangerous driving signal to the Internet of things server, the Internet of things server feeds the cautious driving signal or the dangerous driving signal back to the vehicle-mounted Internet of things terminal, the vehicle-mounted Internet of things terminal sends the dangerous driving signal to the alarm module, the alarm module sends out alarm sound after receiving the dangerous driving signal, and the Internet of things server displays the cautious driving signal on a vehicle-mounted central control screen of the vehicle;
the Internet of things server records dangerous driving behaviors of the vehicle, integrates the recorded dangerous driving behaviors into driving data, and sends the driving data of the vehicle to the mobile police terminal through the data connection module.
Further, the internet of things server is connected with a vehicle-mounted internet of things terminal, the internet of things server is connected with a data connection module, the data connection module is connected with a mobile police terminal, and the internet of things server is in data connection with the mobile police terminal through the data connection module.
Further, the working process of the deviation early warning module is specifically as follows:
step P1: the method comprises the steps that a vehicle preset running route is obtained through a data acquisition module, a lane of the vehicle preset running route is obtained, a plurality of first deviation detection points are set at equal intervals on the left limit of the lane, and a plurality of second deviation detection points are set at equal intervals on the left limit of the lane;
step P2: when the vehicle runs on a preset running route, the first deviation detection point is always positioned at the left side of the vehicle, and the second deviation detection point is always positioned at the right side of the vehicle; the method comprises the steps of dotting four groups of tires of a vehicle, connecting two points of a left front wheel and a left rear wheel, extending front and back to form a left side deviation early warning line, connecting two points of a right front wheel and a right rear wheel, and extending front and back to form a right side deviation early warning line;
step P3: when the vehicle is in a running process, if the first deviation detection point is positioned at the left side of the left deviation early warning line and the second deviation detection point is positioned at the right side of the right deviation early warning line, judging that the vehicle is in a normal running state, and generating no signal;
step P4: if the first deviation detection point is positioned on the right side of the left deviation early warning line or the second deviation detection point is positioned on the left side of the right deviation early warning line, acquiring driving time of the vehicle in an abnormal driving state through a timing unit, and marking the driving time as Tp;
if Tp is less than or equal to Ty, judging that the vehicle is in a overtaking state, and generating no signal;
if Tp is more than Ty, judging that the vehicle is in an abnormal running state, and generating a lane departure signal; wherein Ty is a time threshold;
step P5: acquiring a first deviation detection point and a second deviation detection point of an adjacent lane, and judging that the vehicle changes the lane state if the first deviation detection point of the adjacent lane is positioned at the left side of the left deviation early warning line and the second deviation detection point of the adjacent lane is positioned at the right side of the right deviation early warning line, and generating no signal.
Further, the safety monitoring steps of the speed monitoring module are specifically as follows:
step one: marking the vehicle as i, i=1, 2, … …, z, z being a positive integer; acquiring a running route of a vehicle, and acquiring real-time vehicle flow CLi on the running route through the running route;
step two: acquiring the front vehicle distance between the vehicle and the front vehicle, and marking the front vehicle distance as QCi; acquiring the rear vehicle distance between the vehicle and the rear vehicle, and marking the rear vehicle distance as HCi; the front vehicle distance and the rear vehicle distance are both provided with a safety distance, and if the front vehicle distance and the rear vehicle distance exceed the safety distance, the values of QCi and HCi are zero;
step three: acquiring the real-time speed of the vehicle, and marking the real-time speed as CSI;
step four: the abnormal speed value YCi of the vehicle is calculated by combining a formula, and the formula is specifically as follows:
wherein a1 and a2 are fixed values of a proportionality coefficient, the values of a1 and a2 are larger than zero, and e is a natural constant;
step five: if YCi is less than X1, judging that the real-time speed of the vehicle is in a normal state, and generating no signal;
step six: if X1 is less than or equal to YCi and less than X2, judging that the real-time speed of the vehicle is in an abnormal state, and generating a cautious driving signal;
step seven: if X2 is less than or equal to YCi, judging that the real-time speed of the vehicle is in a dangerous state, and generating a dangerous driving signal; wherein X1 and X2 are both vehicle speed thresholds, and X1 is less than X2.
Further, the data acquisition module is a vehicle-mounted camera, a GPS, a speed sensor, alarm equipment and a range finder.
Further, dangerous driving behaviors specifically include:
a1, lane departure early warning: the driving speed is greater than the threshold speed, and the vehicle is provided with an early warning when one side of the vehicle passes through a lane line and a turn signal is not turned on;
a2, forward collision early warning: early warning when the driving speed is greater than the threshold speed and the expected time of collision with the front vehicle at the relative speed is smaller than the threshold value;
a3, alarming in sharp turning: abnormal sharp turn warning in driving process
A4, overspeed alarm: abnormal overspeed warning in the driving process;
a5, alarming in a rapid acceleration mode: abnormal rapid acceleration warning in the driving process;
a6, alarming when the speed is suddenly reduced: and alarming when the vehicle is in abnormal rapid deceleration.
Further, the access level of the secondary access terminal is divided into: the access permission coefficient corresponding to the first level access level is larger than the access permission coefficient corresponding to the second level access level, and the access permission coefficient corresponding to the second level access level is larger than the access permission coefficient corresponding to the third level access level;
the access authority of the first access terminal is browsing of business data of the Internet of things;
the access authority of the cold access terminal is browsing and downloading of business data of the Internet of things;
the access authority of the medium access terminal is browsing, downloading and uploading of the business data of the Internet of things;
the access authority of the active access terminal is browsing, downloading, uploading and deleting of the business data of the Internet of things.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, a deviation pre-warning module is used for carrying out deviation pre-warning on a driving lane of a vehicle, a plurality of first deviation detection points and second deviation detection points are set according to the lane of a preset driving route of the vehicle, and a deviation pre-warning line of the vehicle is established;
2. the invention is used for carrying out access scheduling between the mobile police terminal and the Internet of things server through the fusion scheduling module, dividing the mobile police terminal into a first access terminal and a second access terminal through IP address comparison, calculating to obtain an access value of the second access terminal according to the access authority coefficient, the request times, the access average time and the generation time of the data access request of the second access terminal, dividing the second access terminal into an active access terminal, a medium access terminal and a cold access terminal after the access value comparison sets a threshold value, and setting the access authority for the active access terminal, the medium access terminal, the cold access terminal or the first access terminal through the Internet of things server.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
Fig. 1 is an overall system block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a vehicle intelligent monitoring and early warning system based on mobile police internet of things comprises a mobile police terminal, an internet of things server and a vehicle-mounted internet of things terminal, wherein the vehicle-mounted internet of things terminal comprises a data acquisition module and an alarm module, the internet of things server comprises a deviation early warning module, a speed monitoring module and a fusion scheduling module, the internet of things server is connected with the vehicle-mounted internet of things terminal, the internet of things server is connected with the fusion scheduling module, the fusion scheduling module is connected with the mobile police terminal, and the internet of things server is in data connection with the mobile police terminal through the fusion scheduling module;
the internet of things server transmits sensing data into an operator public network through a data connection module, the server deployed at the internet side accesses a mobile information network through a mobile internet service sub-platform, the internet of things server in the mobile information network provides internet of things data service support for other mobile police service applications through a micro service interface mode, the internet of things server is respectively deployed on the internet and the mobile information network, the two internet of things servers are interconnected and intercommunicated through boundaries, and the main application scene of the design of the access mode is as follows: collecting information data such as vehicle position, speed, state and the like;
the server of the Internet of things: support the tandem of various sensor data, including driving speed, driving acceleration, steering angle, distance of front vehicle, facial features of driver, etc.; support intelligent data analysis: a vehicle condition history and a travel history of the specific vehicle; driving habit and dangerous driving behavior characteristics of specific drivers; analyzing and extracting behavior characteristics and trend of vehicles and drivers related to factors such as time, region, motorcade and the like; supporting management of a dispatching desk and a mobile terminal APP;
vehicle-mounted internet of things terminal: support multichannel video acquisition input, can realize driving state, the surrounding driving environment detection early warning based on machine vision and artificial intelligence, include: driver fatigue state, driver smoke, driver mobile phone, vehicle forward collision, lane departure;
providing real-time warning reminding for drivers for various behaviors which impair safe driving, and uploading relevant state information and associated multimedia evidence (video and pictures) to a cloud data platform in real time;
support a variety of sensor data: GPS/BD positioning and gyroscope sensing detection support vehicle OBD and other sensors to collect vehicle running data in an expanding way;
supporting a 2G/3G/4G public network transmission mode, and uploading cloud data platforms in real time for various sensor data, personnel information, vehicle condition data and the like;
the special vehicle-mounted design is adopted, so that the automobile power supply is suitable for automobile power supplies, and the automobile power supply can be effectively suitable for power supply conditions of different vehicles and current impact and attenuation caused by starting and accelerating and decelerating of the vehicles;
the high anti-seismic design is adopted, and mechanical shock absorption, electronic shock absorption and software shock absorption are combined, so that the stability of the system is improved, and the system is suitable for different vehicle conditions and road conditions;
the system supports public network 2G/3G/4G communication and 4-path video real-time video recording, and can realize functions of vehicle and driver behavior feature extraction, trend analysis, vehicle remote monitoring, vehicle remote management, audio and video playback analysis, networking alarm and the like;
the vehicle-mounted Internet of things terminal is in data connection with a data acquisition module and an alarm module, wherein the data acquisition module comprises a vehicle-mounted camera, a GPS, a speed sensor, alarm equipment, a range finder, external expansion equipment and the like; the camera, the GPS, the external expansion equipment and the like form a data acquisition module for acquiring the running environment on the vehicle, so that the functions of safety precaution, bad behavior precaution, recording, video recording, alarming, video recording, inquiring and replaying and the like can be completed, the GPS/BD (global positioning system) is also utilized for providing information such as audio and video, geographic position, speed and the like of the vehicle, and audio data, alarming information, GPS positioning data and other control information are transmitted to an Internet of things server;
the terminal of the internet of things is connected with two types of data: sensor data, in-vehicle video data. When the video transmission channel is closed under normal driving and the internet of things terminal judges that certain parameters exceed a threshold value, namely, the terminal judges that the driving behavior is a potential dangerous behavior, at the moment, the terminal selects a corresponding video transmission mode and uploads a fragment image and a photo to the mobile police terminal, the method comprises the following steps:
A. active safety pre-warning (ADAS) for vehicle: the driving image is acquired in real time through the forward camera, the lane line position and the distance from the front vehicle to the relative speed are intelligently identified, and the following main safety early warning functions are provided through intelligent judgment:
a1, lane departure early warning: the driving speed is greater than the threshold speed, and the vehicle is provided with an early warning when one side of the vehicle passes through a lane line and a turn signal is not turned on;
a2, forward collision early warning: early warning when the driving speed is greater than the threshold speed and the expected time of collision with the front vehicle at the relative speed is smaller than the threshold value;
a3, early warning modes: the voice prompts the driver to keep the lane/pay attention to the distance between vehicles, and a plurality of synthesized pictures upload management platforms are used as evidence for storage;
B. bad driving behavior early warning (DMS): the face and peripheral images of the driver during driving are collected in real time through the inward camera, the bad behavior of the driver endangering driving safety is intelligently recognized, and the following real-time alarm function is provided:
b1, a driver dozing/eye-closing alarm, a continuous eye-closing dozing alarm in the driving process, a driver smoking alarm, a smoke drawing in the driving process, a driver mobile phone alarm, a call receiving alarm in the driving process, a yawning alarm in the driver, a yawning alarm in the driving process, a driver distraction alarm, a distraction alarm in the driving process, a non-fleet driver alarm and a non-appointed driver of an actual driver;
b2, early warning mode: voice prompt driver to concentrate on driving and report an emergency and ask for help or increased vigilance some video clips upload the management platform as evidence to remain
C. Vehicle overspeed and three emergency alerts: the vehicle overspeed and three emergency warning functions are provided by combining GPS/Beidou positioning with a built-in accelerometer/gyroscope, and the vehicle overspeed and three emergency warning functions comprise:
c1, overspeed alarm: abnormal overspeed warning in the driving process;
and C2, alarming in a rapid acceleration mode: abnormal rapid acceleration warning in the driving process;
and C3, alarming for sudden deceleration: alarming during driving in case of abnormal rapid deceleration;
and C4, alarming in sharp turning: alarming during driving in abnormal sharp turns;
the server of the Internet of things: the system is used for storing a large amount of related historical data, including various normal running data and abnormal data of people and vehicles, big data analysis, vehicle condition histories of specific vehicles, running histories, driving habits of specific drivers and dangerous driving behavior characteristics;
in specific implementation, a corresponding micro service module which accords with a service bus standard is designed according to the data service characteristics of a specific Internet of things server, and a data interface is opened to a mobile police service terminal through a Restful API interface and a video SDK of the micro service module, so that other various police service can conveniently access Internet of things service data according to corresponding authorities and a unified interface mode, fusion unified scheduling of Internet of things service and mobile police service is realized, and the use safety of the Internet of things service data is improved;
the mobile police terminal is used for sending a data access request by police personnel and sending the data access request to the fusion scheduling module; after the converged scheduling module receives a data access request sent by the mobile police terminal, the converged scheduling module is used for performing access scheduling between the mobile police terminal and the Internet of things server, and the working process is as follows:
step S1: the IP address of the mobile police terminal is obtained, and the mobile police terminal is marked as a first access terminal and a second access terminal through IP address comparison;
step S2: the secondary access terminal is marked as u, u=1, 2, … …, x, x is a positive integer; acquiring generation time of a data access request sent by a secondary access terminal, and marking the generation time as TSu;
step S3: obtaining an access level of a secondary access terminal, and obtaining an access authority coefficient FQxu corresponding to the secondary access terminal through the access level;
the access level of the secondary access terminal is divided into: the access permission coefficient corresponding to the first level access level is larger than the access permission coefficient corresponding to the second level access level, and the access permission coefficient corresponding to the second level access level is larger than the access permission coefficient corresponding to the third level access level;
step S4: acquiring the request times of the secondary access terminal for sending the data access request, and marking the request times as QCu; obtaining access time of the secondary access terminal for accessing the Internet of things server each time, and obtaining access average time JFtu of the secondary access terminal by adding and summing the access time of the Internet of things server each time and dividing the access time by the request times;
step S5: by the formulaCalculating to obtain an access value FWu of the secondary access terminal; wherein, c1 and c2 are fixed values of the proportionality coefficient, and the values of c1 and c2 are larger than zero;
step S6: if the access value FWu of the secondary access terminal is greater than or equal to Y2, marking the secondary access terminal as an active access terminal;
if the access value FWu of the secondary access terminal is greater than or equal to Y1 and less than Y2, marking the secondary access terminal as a medium access terminal;
if the access value FWu of the secondary access terminal is smaller than Y1, marking the secondary access terminal as a cold access terminal; wherein Y1 and Y2 are access thresholds, and Y1 is less than Y2;
the fusion scheduling module feeds back an active access terminal, a medium access terminal, a cold access terminal or a first access terminal to an Internet of things server, and the Internet of things server sets access rights for a mobile police terminal according to the active access terminal, the medium access terminal, the cold access terminal or the first access terminal;
the access authority of the first access terminal is browsing of business data of the Internet of things;
the access authority of the cold access terminal is browsing and downloading of business data of the Internet of things;
the access authority of the medium access terminal is browsing, downloading and uploading of the business data of the Internet of things;
the access authority of the active access terminal is browsing, downloading, uploading and deleting of the business data of the Internet of things;
the alarm module is used for alarming dangerous driving behaviors of the vehicle; the vehicle-mounted internet of things terminal is used for transmitting the driving data of the vehicle to an internet of things server, and the internet of things server is used for transmitting the driving data of the vehicle to a deviation early warning module and a speed monitoring module respectively;
the specific explanation is as follows: the driving data of the vehicle are specifically a vehicle driving route, a vehicle driving lane, a real-time vehicle speed, a vehicle distance and the like;
in the implementation, the vehicle runs on a road with two lanes in two directions, and the vehicle is located on a left lane, but the vehicle is not limited to the two lanes, the departure warning module is connected with a timing unit, the timing unit is used for timing the departure time of the vehicle and sending timing data to the departure warning module, and the departure warning module is used for carrying out departure warning on a driving lane of the vehicle, and the working process is as follows:
step P1: the method comprises the steps that a vehicle preset running route is obtained through a data acquisition module, a lane of the vehicle preset running route is obtained, a plurality of first deviation detection points are set at equal intervals on the left limit of the lane, and a plurality of second deviation detection points are set at equal intervals on the left limit of the lane;
step P2: when the vehicle runs on a preset running route, the first deviation detection point is always positioned at the left side of the vehicle, and the second deviation detection point is always positioned at the right side of the vehicle; the method comprises the steps of dotting four groups of tires of a vehicle, connecting two points of a left front wheel and a left rear wheel, extending front and back to form a left side deviation early warning line, connecting two points of a right front wheel and a right rear wheel, and extending front and back to form a right side deviation early warning line;
step P3: when the vehicle is in a running process, if the first deviation detection point is positioned at the left side of the left deviation early warning line and the second deviation detection point is positioned at the right side of the right deviation early warning line, judging that the vehicle is in a normal running state, and generating no signal;
step P4: if the first deviation detection point is positioned on the right side of the left deviation early warning line or the second deviation detection point is positioned on the left side of the right deviation early warning line, acquiring driving time of the vehicle in an abnormal driving state through a timing unit, and marking the driving time as Tp;
if Tp is less than or equal to Ty, judging that the vehicle is in a overtaking state, and generating no signal;
if Tp is more than Ty, judging that the vehicle is in an abnormal running state, and generating a lane departure signal; wherein Ty is a time threshold;
step P5: acquiring a first deviation detection point and a second deviation detection point of an adjacent lane, judging that the vehicle changes the lane state if the first deviation detection point of the adjacent lane is positioned at the left side of a left deviation early warning line and the second deviation detection point of the adjacent lane is positioned at the right side of a right deviation early warning line, and generating no signal;
the lane departure warning module sends lane departure signals to the Internet of things server, the Internet of things server feeds the lane departure signals back to the vehicle-mounted Internet of things terminal, the vehicle-mounted Internet of things terminal converts the lane departure signals into warning signals, the vehicle-mounted Internet of things terminal loads the warning signals to the warning module, and the warning module sounds a warning;
in specific implementation, the vehicle is on an urban straight line road, but not limited thereto, and the speed monitoring module is used for safely monitoring the abnormal running speed of the vehicle, and the safety monitoring steps are as follows:
step one: marking the vehicle as i, i=1, 2, … …, z, z being a positive integer; acquiring a running route of a vehicle, and acquiring real-time vehicle flow CLi on the running route through the running route;
step two: acquiring the front vehicle distance between the vehicle and the front vehicle, and marking the front vehicle distance as QCi; acquiring the rear vehicle distance between the vehicle and the rear vehicle, and marking the rear vehicle distance as HCi; the front vehicle distance and the rear vehicle distance are both provided with a safety distance, and if the front vehicle distance and the rear vehicle distance exceed the safety distance, the values of QCi and HCi are zero;
step three: acquiring the real-time speed of the vehicle, and marking the real-time speed as CSI;
step four: the abnormal speed value YCi of the vehicle is calculated by combining a formula, and the formula is specifically as follows:
wherein a1 and a2 are fixed values of a proportionality coefficient, the values of a1 and a2 are larger than zero, and e is a natural constant;
step five: if YCi is less than X1, judging that the real-time speed of the vehicle is in a normal state, and generating no signal;
step six: if X1 is less than or equal to YCi and less than X2, judging that the real-time speed of the vehicle is in an abnormal state, and generating a cautious driving signal;
step seven: if X2 is less than or equal to YCi, judging that the real-time speed of the vehicle is in a dangerous state, and generating a dangerous driving signal; wherein X1 and X2 are both vehicle speed thresholds, and X1 is less than X2;
the speed monitoring module sends a cautious driving signal or a dangerous driving signal to the Internet of things server, the Internet of things server feeds the cautious driving signal or the dangerous driving signal back to the vehicle-mounted Internet of things terminal, the vehicle-mounted Internet of things terminal sends the dangerous driving signal to the alarm module, the alarm module sends out alarm sound after receiving the dangerous driving signal, and the Internet of things server displays the cautious driving signal on a vehicle-mounted central control screen of the vehicle;
meanwhile, the Internet of things server records dangerous driving behaviors of the vehicle, integrates the recorded dangerous driving behaviors into driving data, and sends the driving data of the vehicle to the mobile police terminal through the data connection module.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (7)
1. The intelligent vehicle monitoring and early warning system based on the mobile police Internet of things is characterized by comprising a mobile police terminal, an Internet of things server and a vehicle-mounted Internet of things terminal, wherein the Internet of things server comprises a deviation early warning module, a speed monitoring module and a fusion scheduling module, the Internet of things server is connected with the vehicle-mounted Internet of things terminal, the Internet of things server is connected with the fusion scheduling module, the fusion scheduling module is connected with the mobile police terminal, and the Internet of things server is in data connection with the mobile police terminal through the fusion scheduling module;
the mobile police terminal is used for sending a data access request by police personnel and sending the data access request to the fusion scheduling module; after the converged scheduling module receives a data access request sent by the mobile police terminal, the converged scheduling module is used for performing access scheduling between the mobile police terminal and the Internet of things server, and the working process is as follows:
step S1: the IP address of the mobile police terminal is obtained, and the mobile police terminal is marked as a first access terminal and a second access terminal through IP address comparison;
step S2: the secondary access terminal is marked as u, u=1, 2, … …, x, x is a positive integer; acquiring generation time of a data access request sent by a secondary access terminal, and marking the generation time as TSu;
step S3: obtaining an access level of a secondary access terminal, and obtaining an access authority coefficient FQxu corresponding to the secondary access terminal through the access level;
step S4: acquiring the request times of the secondary access terminal for sending the data access request, and marking the request times as QCu; obtaining access time of the secondary access terminal for accessing the Internet of things server each time, and obtaining access average time JFtu of the secondary access terminal by adding and summing the access time of the Internet of things server each time and dividing the access time by the request times;
step S5: by the formulaCalculating to obtain an access value FWu of the secondary access terminal; wherein, c1 and c2 are fixed values of the proportionality coefficient, and the values of c1 and c2 are larger than zero;
step S6: if the access value FWu of the secondary access terminal is greater than or equal to Y2, marking the secondary access terminal as an active access terminal;
if the access value FWu of the secondary access terminal is greater than or equal to Y1 and less than Y2, marking the secondary access terminal as a medium access terminal;
if the access value FWu of the secondary access terminal is smaller than Y1, marking the secondary access terminal as a cold access terminal; wherein Y1 and Y2 are access thresholds, and Y1 is less than Y2;
the fusion scheduling module feeds back an active access terminal, a medium access terminal, a cold access terminal or a first access terminal to an Internet of things server, and the Internet of things server sets access rights for a mobile police terminal according to the active access terminal, the medium access terminal, the cold access terminal or the first access terminal;
the vehicle-mounted internet of things terminal is connected with a data acquisition module and an alarm module, and the alarm module is used for alarming dangerous driving behaviors of a vehicle; the vehicle-mounted internet of things terminal is used for transmitting the driving data of the vehicle to an internet of things server, and the internet of things server is used for transmitting the driving data of the vehicle to a deviation early warning module and a speed monitoring module respectively;
the deviation early-warning module is connected with a timing unit, the timing unit is used for timing the deviation time of the vehicle and sending timing data to the deviation early-warning module, the deviation early-warning module is used for carrying out deviation early warning on a driving lane of the vehicle, if the vehicle is in a normal driving state, a overtaking state or a lane changing state, no signal is generated, and if the vehicle is judged to be in an abnormal driving state, a lane deviation signal is generated;
the lane departure warning module sends lane departure signals to the Internet of things server, the Internet of things server feeds the lane departure signals back to the vehicle-mounted Internet of things terminal, the vehicle-mounted Internet of things terminal converts the lane departure signals into warning signals, the vehicle-mounted Internet of things terminal loads the warning signals to the warning module, and the warning module sounds a warning;
the speed monitoring module is used for safely monitoring the abnormal running speed of the vehicle, generating no signal if the real-time speed of the vehicle is in a normal state, generating a cautious driving signal if the real-time speed of the vehicle is in an abnormal state, and generating a dangerous driving signal if the real-time speed of the vehicle is in a dangerous state;
the speed monitoring module sends a cautious driving signal or a dangerous driving signal to the Internet of things server, the Internet of things server feeds the cautious driving signal or the dangerous driving signal back to the vehicle-mounted Internet of things terminal, the vehicle-mounted Internet of things terminal sends the dangerous driving signal to the alarm module, the alarm module sends out alarm sound after receiving the dangerous driving signal, and the Internet of things server displays the cautious driving signal on a vehicle-mounted central control screen of the vehicle;
the Internet of things server records dangerous driving behaviors of the vehicle, integrates the recorded dangerous driving behaviors into driving data, and sends the driving data of the vehicle to the mobile police terminal through the data connection module.
2. The intelligent vehicle monitoring and early warning system based on the mobile police Internet of things according to claim 1, wherein the Internet of things server is connected with a vehicle-mounted Internet of things terminal, the Internet of things server is connected with a data connection module, the data connection module is connected with the mobile police terminal, and the Internet of things server is in data connection with the mobile police terminal through the data connection module.
3. The intelligent vehicle monitoring and early warning system based on the mobile police internet of things according to claim 1, wherein the working process of the deviation early warning module is specifically as follows:
step P1: the method comprises the steps that a vehicle preset running route is obtained through a data acquisition module, a lane of the vehicle preset running route is obtained, a plurality of first deviation detection points are set at equal intervals on the left limit of the lane, and a plurality of second deviation detection points are set at equal intervals on the left limit of the lane;
step P2: when the vehicle runs on a preset running route, the first deviation detection point is always positioned at the left side of the vehicle, and the second deviation detection point is always positioned at the right side of the vehicle; the method comprises the steps of dotting four groups of tires of a vehicle, connecting two points of a left front wheel and a left rear wheel, extending front and back to form a left side deviation early warning line, connecting two points of a right front wheel and a right rear wheel, and extending front and back to form a right side deviation early warning line;
step P3: when the vehicle is in a running process, if the first deviation detection point is positioned at the left side of the left deviation early warning line and the second deviation detection point is positioned at the right side of the right deviation early warning line, judging that the vehicle is in a normal running state, and generating no signal;
step P4: if the first deviation detection point is positioned on the right side of the left deviation early warning line or the second deviation detection point is positioned on the left side of the right deviation early warning line, acquiring driving time of the vehicle in an abnormal driving state through a timing unit, and marking the driving time as Tp;
if Tp is less than or equal to Ty, judging that the vehicle is in a overtaking state, and generating no signal;
if Tp is more than Ty, judging that the vehicle is in an abnormal running state, and generating a lane departure signal; wherein Ty is a time threshold;
step P5: acquiring a first deviation detection point and a second deviation detection point of an adjacent lane, and judging that the vehicle changes the lane state if the first deviation detection point of the adjacent lane is positioned at the left side of the left deviation early warning line and the second deviation detection point of the adjacent lane is positioned at the right side of the right deviation early warning line, and generating no signal.
4. The intelligent vehicle monitoring and early warning system based on the mobile police internet of things according to claim 1, wherein the safety monitoring step of the speed monitoring module is specifically as follows:
step one: marking the vehicle as i, i=1, 2, … …, z, z being a positive integer; acquiring a running route of a vehicle, and acquiring real-time vehicle flow CLi on the running route through the running route;
step two: acquiring the front vehicle distance between the vehicle and the front vehicle, and marking the front vehicle distance as QCi; acquiring the rear vehicle distance between the vehicle and the rear vehicle, and marking the rear vehicle distance as HCi; the front vehicle distance and the rear vehicle distance are both provided with a safety distance, and if the front vehicle distance and the rear vehicle distance exceed the safety distance, the values of QCi and HCi are zero;
step three: acquiring the real-time speed of the vehicle, and marking the real-time speed as CSI;
step four: the abnormal speed value YCi of the vehicle is calculated by combining a formula, and the formula is specifically as follows:
wherein a1 and a2 are fixed values of a proportionality coefficient, the values of a1 and a2 are larger than zero, and e is a natural constant;
step five: if YCi is less than X1, judging that the real-time speed of the vehicle is in a normal state, and generating no signal;
step six: if X1 is less than or equal to YCi and less than X2, judging that the real-time speed of the vehicle is in an abnormal state, and generating a cautious driving signal;
step seven: if X2 is less than or equal to YCi, judging that the real-time speed of the vehicle is in a dangerous state, and generating a dangerous driving signal; wherein X1 and X2 are both vehicle speed thresholds, and X1 is less than X2.
5. The intelligent vehicle monitoring and early warning system based on the mobile police internet of things according to claim 1, wherein the data acquisition module is a vehicle-mounted camera, a GPS, a speed sensor, an alarm device and a range finder.
6. The intelligent vehicle monitoring and early warning system based on the mobile police internet of things according to claim 1, wherein dangerous driving behaviors specifically comprise:
a1, lane departure early warning: the driving speed is greater than the threshold speed, and the vehicle is provided with an early warning when one side of the vehicle passes through a lane line and a turn signal is not turned on;
a2, forward collision early warning: early warning when the driving speed is greater than the threshold speed and the expected time of collision with the front vehicle at the relative speed is smaller than the threshold value;
a3, alarming in sharp turning: abnormal sharp turn warning in driving process
A4, overspeed alarm: abnormal overspeed warning in the driving process;
a5, alarming in a rapid acceleration mode: abnormal rapid acceleration warning in the driving process;
a6, alarming when the speed is suddenly reduced: and alarming when the vehicle is in abnormal rapid deceleration.
7. The intelligent vehicle monitoring and early warning system based on the mobile police internet of things according to claim 1, wherein the access level of the secondary access terminal is divided into: the access permission coefficient corresponding to the first level access level is larger than the access permission coefficient corresponding to the second level access level, and the access permission coefficient corresponding to the second level access level is larger than the access permission coefficient corresponding to the third level access level;
the access authority of the first access terminal is browsing of business data of the Internet of things;
the access authority of the cold access terminal is browsing and downloading of business data of the Internet of things;
the access authority of the medium access terminal is browsing, downloading and uploading of the business data of the Internet of things;
the access authority of the active access terminal is browsing, downloading, uploading and deleting of the business data of the Internet of things.
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| CN106303962A (en) * | 2016-08-17 | 2017-01-04 | 公安部道路交通安全研究中心 | A kind of method and system realizing people's car information association |
| WO2018076559A1 (en) * | 2016-10-26 | 2018-05-03 | 深圳市元征科技股份有限公司 | Safe driving early warning method and device |
| CN112187920A (en) * | 2020-09-28 | 2021-01-05 | 杭州宣迅电子科技有限公司 | Vehicle driving safety intelligent monitoring and early warning management system based on big data |
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| JP6662828B2 (en) * | 2017-09-08 | 2020-03-11 | 本田技研工業株式会社 | Driving support system, driving support device, and driving support method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106303962A (en) * | 2016-08-17 | 2017-01-04 | 公安部道路交通安全研究中心 | A kind of method and system realizing people's car information association |
| WO2018076559A1 (en) * | 2016-10-26 | 2018-05-03 | 深圳市元征科技股份有限公司 | Safe driving early warning method and device |
| CN112187920A (en) * | 2020-09-28 | 2021-01-05 | 杭州宣迅电子科技有限公司 | Vehicle driving safety intelligent monitoring and early warning management system based on big data |
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