CN111681453A - Automobile safety artificial intelligence housekeeper system based on big data and operation mode thereof - Google Patents
Automobile safety artificial intelligence housekeeper system based on big data and operation mode thereof Download PDFInfo
- Publication number
- CN111681453A CN111681453A CN202010401146.2A CN202010401146A CN111681453A CN 111681453 A CN111681453 A CN 111681453A CN 202010401146 A CN202010401146 A CN 202010401146A CN 111681453 A CN111681453 A CN 111681453A
- Authority
- CN
- China
- Prior art keywords
- big data
- module
- vehicle
- visualization
- safety
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
-
- 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
- H04L67/52—Network services specially adapted for the location of the user terminal
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Biomedical Technology (AREA)
- Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses an automobile safety artificial intelligence housekeeping system based on big data and an operation mode thereof, comprising a big data platform, a mode recognition module, a visualization module and an intelligent management module, wherein the big data platform is simultaneously connected to the mode recognition module and the visualization module; the pattern recognition module, the intelligent management module and the visualization module are connected in sequence, and the pattern recognition module is connected to the visualization module. The intelligent vehicle safety management system can automatically acquire the latest data from the big data platform, extract or generate the data required by the intelligent management module through pattern recognition, realize various intelligent vehicle safety management functions based on the big data and by combining artificial intelligence, and interact with users in real time through the visualization module. The invention can be embedded into a mobile phone APP, so that a user can use the mobile phone APP at any time and any place without geographical limitation, the real-time performance is high, the functions are rich, the safety of vehicles is greatly improved, and the driving safety awareness and the traffic security order of the user are favorably improved.
Description
Technical Field
The invention belongs to the technical field of transportation, and particularly relates to an automobile safety artificial intelligence housekeeping system based on big data and an operation mode thereof.
Background
In recent years, the automotive industry has rapidly developed. As a modern main vehicle, the multifunctional bus can provide travel conditions quickly and comfortably, brings convenience to work and life, and is popular with people. However, since the ford T-Model has been scaled up, the car enterprises provide users with standardized and single products, i.e. products before searching for corresponding users, which is one of the features of the industrial revolution: the maximization of the benefit per unit time is sought under the premise of eliminating the personality. However, with the development of computer technology and the improvement of production and consumption level, it is now obvious that customers are no longer satisfied with the same products and services, especially with the development of electric, intelligent, and networking, and the needs of users need to perform digital description and modeling to meet personalized needs, which is the need of digital transformation, in other words, the informatization system provides a better management tool for improving production efficiency.
Meanwhile, with the progress of urbanization and the popularization of vehicles, the traffic safety problem is increasingly serious, the road is crowded, traffic accidents frequently occur, the traffic environment is increasingly worsened, and the safety problem becomes the biggest pain point of the vehicle enterprises and users.
Most of current initiative safety design techniques all are based on hardware passive control, relate to a car crash safety nature simulation analysis optimal design integration system as the patent of authorizing of application number CN201410198600.3, optimal design system drive virtual actuator circulation execution analysis simulation analytic system, virtual actuator feeds back the structure to simulation analytic system through circulation execution analysis, simulation analytic system draws data for virtual sensor automatically, virtual sensor feeds back automatic transmission structure to optimal design system, great promotion car analysis and the overall efficiency of optimization: the existing scheme is based on independent software, data transmission is carried out by adopting files, and a lot of manual operations are needed for extracting results; in the invention, after the virtual actuator (a structural actuator and the like) and the virtual sensor (a deformation sensor, a B-pillar acceleration sensor and the like) related to automobile collision are defined, the CAE analysis and extraction result can be directly driven, and data is transmitted in the system, so that the efficiency is improved. But it is based on a sensor implementation. The patent application with the application number of CN201610558636.7 relates to an intelligent bus safety control system provided with a radar, and the intelligent bus safety control system comprises a vehicle speed measuring sensor, a vehicle speed setting module, a vehicle speed comparison module, a judgment module, a comparison module, a vehicle-mounted radar, a central processing module, a memory and a voice playing device. The invention detects the information of the vehicle in real time through the sensor and intelligently judges the detected information, thereby accurately judging the passing speed and the communication width of the vehicle. The purpose of improving the driving safety of the vehicle is achieved. But it is based on radar waves. The technical schemes of the two patent documents are greatly influenced by geographic environment and weather factors, have poor real-time performance and fewer functions, and cannot completely meet the will of a driver.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention designs a big data-based automobile safety artificial intelligence housekeeping system and an operation mode thereof. The intelligent vehicle safety management system can automatically acquire the latest data from a big data platform, extract or generate data required by an intelligent management module through pattern recognition, realize various intelligent vehicle safety management functions based on the big data and by combining artificial intelligence, and interact with a user in real time through a visualization module. The embedded mobile phone intelligent APP is an embedded mobile phone intelligent APP, a user can use the APP at any time and any place without geographic limitation, the real-time performance is high, the functions are rich, the safety of vehicles is greatly improved, and the driving safety awareness and the traffic security order of the user can be improved.
In order to solve the problems, the invention adopts the technical scheme that:
an automobile safety artificial intelligence housekeeping system based on big data, comprising: the system comprises a big data platform, a pattern recognition module, a visualization module and an intelligent management module; the big data platform is connected to the pattern recognition module and the visualization module at the same time; the pattern recognition module, the intelligent management module and the visualization module are connected in sequence, and the pattern recognition module is connected to the visualization module.
In the automobile safety artificial intelligence housekeeping system based on the big data, the big data platform crawls relevant basic information of the vehicle from a public department traffic safety comprehensive service management platform, a 4S shop brand part platform and an automobile relevant forum and leads the basic information into a vehicle information database.
In the automobile safety artificial intelligence housekeeper system based on big data, the pattern recognition module performs data mining from the vehicle information database to obtain a training set (a data set used by an estimation model) as the input of a subsequent deep neural network, performs pattern recognition, and realizes the extraction processing of data;
according to the automobile safety artificial intelligence housekeeping system based on the big data, the visualization module comprises the visualization of the driving record of the automobile, the visualization of the automobile safety components and the visualization of the information (price and brand) of the automobile.
In the automobile safety artificial intelligence housekeeping system based on the big data, the automobile safety construction visualization is based on the big data processing of the 4S shop maintenance records, the personalized analysis is carried out on the user vehicle, and the integrated modeling and adjustment are carried out by means of the strong modeling capability, namely, the JIETUSOFT-VR roaming master software is selected and used. And the parts are innovatively modeled, and the parts are dynamically marked, so that the personalized function of the vehicle is realized.
In the automobile safety artificial intelligence housekeeper system based on the big data, the intelligent management module is used for managing the functions of preventing drunk driving, automatically braking, realizing online social contact and realizing bionic energy absorption. The bionic energy absorption box has the advantages that the drunk driving prevention and automatic braking functions can avoid traffic accidents as much as possible, and the passive safety function of the bionic energy absorption box can reduce the damage degree after the collision accidents to the maximum extent. And the online social function enables the car owner to enjoy a pleasant driving experience. The bionic energy absorption box with the bionic energy absorption function of the front wing of the beetle (application number: 201610903362.0) is used as a passive safety function of the bionic energy absorption box, and the bionic energy absorption box is an automobile energy absorption device with high energy consumption and stable deformation mode.
Compared with the prior art, the method has the following advantages:
1. most of the existing active safety design technologies are based on hardware passive control, such as based on sensors and radar waves, are greatly influenced by geographic environment and weather factors, and the quality of acquired data is poor.
2. The risk estimation can be carried out on each automobile individual by combining artificial intelligence and applying pattern recognition, so that the simulation of real-time traffic safety is realized, the safety weaknesses of different brands and different vehicle types are accurately mastered, and the cross analysis of common problems and individual problems is realized.
3. The function is abundant, through intelligent management module, and the subjective initiative of full play car owner realizes taking precautions against wine and drives and the automatic brake function, avoids the emergence of traffic accident as far as possible, and the damage degree after the emergence of collision accident is reduced to the driven safety function furthest of bionical energy-absorbing box.
4. Besides the safety management function, the system also provides an online social function, so that a car owner can enjoy a pleasant driving experience.
Overall, the system of the invention can be embedded into a mobile phone and other mobile terminals, users can use the system at any time and any place without geographical limitation, the real-time performance is high, the functions are rich, the safety of vehicles is greatly improved, and the system is beneficial to improving the driving safety awareness and traffic peace order of users.
Drawings
FIG. 1 is a schematic diagram of the system components of the present invention;
FIG. 2 is a diagram of the big data platform working principle;
FIG. 3 is a schematic diagram of a pattern recognition operation;
FIG. 4 is a visual diagram of the safety member of the automobile according to embodiment 2;
FIG. 5 is a example 3 vehicle information (price, brand) visualization;
fig. 6 is a high alcohol warning diagram for preventing drunk driving in embodiment 4.
Detailed Description
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
The automobile safety artificial intelligence housekeeping system based on big data shown in figure 1 comprises a big data platform, a mode recognition module, a visualization module and an intelligent management module. The big data platform is connected to the pattern recognition module and the visualization module at the same time, and data support is provided for the pattern recognition module and the visualization module. The intelligent management system comprises a pattern recognition module, an intelligent management module and a visualization module which are sequentially connected, and the pattern recognition module is connected to the visualization module.
In the above four modules, aiming at the implementation requirement of a specific scene, the visualization module and the intelligent management module are modules which are directly oriented to the user and embody the practical functions of the invention. In view of this feature, the following 4 embodiments are listed as functional explanations and supplements.
FIG. 2 is a diagram of the big data platform operating principle. The work flow of the system mainly comprises four stages:
stage one, data import: and the big data platform crawls relevant basic information of the vehicle from a public department traffic safety comprehensive service management platform, a 4S shop brand part platform and an automobile relevant forum and imports the basic information into a vehicle information database.
The big data platform imports specific objects, specific time and places and specific illegal contents of traffic violation from a traffic safety comprehensive service management platform of the department of public transportation; importing part transaction records of each large automobile maintenance center from a 4S shop brand part platform; from the hot spot tracking and the flow analysis of the automobile-related forum, the official data, the merchant data and the user data are organically combined, and the maximization of data authenticity is realized. Supplementing the records of the violation and the records of the part transaction.
Stage two, data processing
Fig. 3 is a schematic diagram of the operation of pattern recognition. The pattern recognition module performs data mining from a vehicle information database, acquires a huge neural network training set, is used for building a deep learning neural network, and performs data extraction processing through pattern recognition. Wherein the discriminant ability of the learner on new samples is tested using a neural network training set, and then the test error is used as an approximation of the generalization error.
When researching and comparing generalization performances of different algorithms, the pattern recognition module estimates generalization capability of the model in actual use by using discrimination effect of the test set, divides training data into a verification set additionally, and selects and adjusts parameters of the model based on performances on the verification set, such as an optimizer and a loss activation function.
And finally, pattern recognition is carried out through the trained neural network model, and risk prediction is carried out on each automobile individual, so that real-time traffic safety simulation is realized, the safety weaknesses of different brands and different automobile types are accurately mastered, and the cross analysis of common problems and individual problems is realized.
Stage three, visual display
The visualization module includes three aspects: the vehicle driving record is visualized, and the automobile safety component and maintenance guidance and the vehicle information (price and brand) are visualized.
1. Vehicle driving record visualization
By researching interactive vision of abstract data, aiming at vehicle violation records collected in a comprehensive traffic safety service management platform of a database of the ministry of public security, danger grades are divided by taking a vehicle owner as a unit, and the records are marked in a real-time geographic positioning system, so that information visualization of the front end is realized. The abstract data is replaced with a visual image to enhance user perception.
2. Visualization and maintenance guidance for automotive safety components
Based on the big data processing of the 4S shop maintenance records, personalized analysis is performed on the user vehicle. And with the help of powerful modeling ability, the vehicle personalized function has been realized. That is, when the user performs maintenance or care in the 4S shop, the developed love car security APP can display a three-dimensional model of the love car of the user and display information of each component on the model. We take the "Benz mini type" as an example to briefly describe the implementation process of our technique. Firstly, collecting and acquiring a 3DSMAX model of the gallo mini, and then selecting and using JIETUSOFT-VR roaming master software to perform overall modeling and adjustment. And innovatively modeling in a subsection mode, dynamically marking parts and components, and finally realizing visualization of the parts and components.
The function can enable a user to know the structure of the favorite vehicle like a person, and the user can know the use and safety conditions of each part in real time according to part marks, such as a manufacturer, a 4S shop address for maintenance, installation time and use time. Meanwhile, by means of the function, a guide for maintaining the love car can be formed in real time. For example, if the tire is judged to have been used for two years, the user is prompted to perform maintenance, repair and replacement.
3. Vehicle information (price, brand) visualization
The prices of vehicle owners around the user's ride are graded ("premium, low-grade") to be displayed on a map platform similar to a GPS to prevent scratching onto premium vehicles.
When a user drives, the APP displays the price brand information of nearby vehicles in real time through big data analysis, the information is combined with the vehicle danger index information, and the multi-directional and all-angle implementation vehicle condition analysis of the user is provided, so that the vehicle safety and the accuracy of user pre-judgment are improved. For example, as shown in fig. 5, when car lover indicates that a high-grade car with a high risk index exists near the user, the user can quickly recognize that the driving safety of the user is threatened, and the user needs to prevent the high-grade car from being scratched. Stage four, intelligent management function
The intelligent management module has the functions of preventing drunk driving and automatic braking to avoid traffic accidents as much as possible, and the passive safety function of the bionic energy absorption box furthest reduces the damage degree after the collision accidents. Besides the safety management function, the invention also provides an online social function, so that a car owner can enjoy a pleasant driving experience.
1. Prevent wine from driving
Drunk driving is one of the important causes of traffic accidents, particularly for some malignant traffic accidents. The existing drunk driving prevention safety technology is based on sensors, such as alcohol detection. This requires expensive hardware equipment to achieve higher accuracy. The drunk driving recording data is analyzed, a model is built, the real-time possibility of drunk driving of the user is calculated, real-time reminding of the user is achieved on the APP, and the subjective initiative of the user is fully played from the user.
2. Safety distance and automatic brake
The existing active safety design technologies such as safety distance and automatic braking are based on passive control of hardware such as sensors and radar waves (as mentioned in the two patent documents in the background art). The automatic braking function of the invention calls the relevant information of the traffic driving record vehicle in the database through the idea of internet and big data and transmits the information to the user through the APP, thereby achieving the purpose of avoiding the collision risk subjectively.
3. Online social interactions, car-friend interactions
The interaction of the car owner is realized through three sub-functional modules, namely a personal center, a community and a dynamic state. The vehicle owner information can be displayed, friends can be made with nearby vehicle owners, the dynamic states of the vehicle owners are dynamically displayed, online chatting is supported, the establishment of a social network is realized, and the vehicle owner information can be communicated and interacted with other vehicle owners on a platform.
4. Bionic energy absorption box
As a supplementary function of the safety system, the passive safety part of the automobile is structurally optimized, the bionic energy absorption box with the beetle front wing is an automobile energy absorption device with high energy consumption and stable deformation mode, the APP can effectively reduce the accident probability, and meanwhile, the damage degree after the collision accident occurs can be reduced to the maximum extent through the part modification of the novel bionic energy absorption box.
Example 1: vehicle driving record visualization
Through big data platform and pattern recognition, the dangerous grade is divided by taking the car owner as a unit according to the collected and disclosed vehicle violation record in the database of the ministry of public security, and the dangerous grade is marked in a real-time geographical positioning system. During driving, the APP map page carried on the vehicle can visually read the driving safety level of the surrounding vehicle, and the APP can automatically perform voice reminding on the surrounding vehicle with bad driving records, so that the driving safety of a vehicle owner is improved.
Example 2: vehicle safety component visualization
As shown in fig. 4, when the vehicle needs to be maintained and maintained, the user can see the three-dimensional model of the vehicle through the APP interface, and meanwhile, according to different maintenance and maintenance requirements, the user can learn each part and each component of the vehicle in a gradually detailed manner, and component parameters, price information, working principles and the like can be displayed on the component model which is consulted by the user in 3D. In combination with an 'intelligent management' module, the function can be expanded into a personalized vehicle maintenance guide, and scientific guidance of vehicle maintenance is provided on the basis that a user provides vehicle component replacement records.
Example 3: vehicle information (price, brand) visualization
As shown in fig. 5, by means of a big data platform, surrounding vehicle information is displayed in an APP map page loaded on a vehicle, and by combining with the safety level of the vehicle, a reminder item of "high-grade and high-risk vehicles" is added, so that the scratch and rub probability of vehicle owners on the vehicles is subjectively reduced.
Example 4: prevent wine from driving
Through record and analysis to car owner's trip habit, combine the statistics law that big data system collected, calculate the possibility that the car owner drove wine in the real-time geographical position, when this possibility exceeded 70%, APP carried out pronunciation warning automatically. For example, after ten nights on a holiday, the vehicle owner starts the vehicle near a hotel, and at this time, the APP automatically estimates that the vehicle owner has a high drunk driving risk, and reminds the vehicle owner of the high drunk driving risk by voice, so that the safe driving awareness of the vehicle owner is improved.
Claims (7)
1. The utility model provides a car safety artificial intelligence butler system based on big data which characterized in that includes: the system comprises a big data platform, a pattern recognition module, a visualization module and an intelligent management module; the big data platform is connected to the pattern recognition module and the visualization module at the same time; the pattern recognition module, the intelligent management module and the visualization module are connected in sequence, and the pattern recognition module is connected to the visualization module.
2. The artificial intelligent housekeeping system for automobile safety based on big data of claim 1, wherein the big data platform crawls basic information of relevant vehicles from a comprehensive service management platform for public department of transportation safety, a brand part platform of 4S stores and an automobile-related forum and imports the basic information into a vehicle information database.
3. The automobile safety artificial intelligence housekeeping system based on big data according to claim 1, characterized in that the pattern recognition module performs data mining from a vehicle information database to obtain a training set as an input of a subsequent deep neural network for pattern recognition to realize data extraction processing.
4. The big data based automobile safety artificial intelligence housekeeping system according to claim 1, wherein the visualization module comprises vehicle driving record visualization, automobile safety component visualization and vehicle information visualization.
5. The artificial intelligent housekeeping system for automobile safety based on big data as claimed in claim 3, wherein the visualization of automobile safety construction is based on big data processing of 4S shop maintenance records, and after personalized analysis of user' S vehicle, the whole modeling, adjustment or partial modeling is performed by means of JIETUSOFT-VR roaming master software, and parts are dynamically marked, so as to realize the personalized function of vehicle.
6. The big-data-based automobile safety artificial intelligence housekeeper system according to claim 1, wherein the intelligent management module manages drunk driving prevention, an automatic braking function, online social contact and a bionic energy absorption function.
7. The operation mode of the artificial intelligent housekeeping system for automobile safety based on big data as claimed in claim 1, wherein the big data platform crawls basic information of relevant vehicles from a traffic safety comprehensive service management platform of the department of public transportation, a brand part platform of a 4S store and a related forum of automobiles, and imports the basic information into a vehicle information database;
the pattern recognition module performs data mining from a vehicle information database to obtain a training set, and the training set is used as the input of a subsequent deep neural network to perform pattern recognition so as to realize data extraction processing;
based on the big data processing of the maintenance records of the 4S shop, the integrated modeling, the adjustment or the fractional modeling are carried out by means of JIETUSOFT-VR roaming master software after the personalized analysis of the vehicle of the user, and the dynamic marking is carried out on the parts, so that the personalized function of the vehicle is realized; the intelligent management function is based on the vehicle information database to realize functions and interacts with a user in real time through a visualization module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010401146.2A CN111681453A (en) | 2020-05-13 | 2020-05-13 | Automobile safety artificial intelligence housekeeper system based on big data and operation mode thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010401146.2A CN111681453A (en) | 2020-05-13 | 2020-05-13 | Automobile safety artificial intelligence housekeeper system based on big data and operation mode thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111681453A true CN111681453A (en) | 2020-09-18 |
Family
ID=72433507
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010401146.2A Pending CN111681453A (en) | 2020-05-13 | 2020-05-13 | Automobile safety artificial intelligence housekeeper system based on big data and operation mode thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111681453A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107221196A (en) * | 2017-05-26 | 2017-09-29 | 广东中星电子有限公司 | Vehicle drive methods of risk assessment, device, system and readable storage medium storing program for executing |
| CN107316487A (en) * | 2017-07-11 | 2017-11-03 | 东莞市信瑞智能科技有限公司 | Car networking Intelligent vehicle-carried information terminal and information interacting method |
| US20180130229A1 (en) * | 2016-11-08 | 2018-05-10 | Nec Laboratories America, Inc. | Surveillance system with landmark localization on objects in images using convolutional neural networks |
| CN108091156A (en) * | 2017-12-14 | 2018-05-29 | 合肥寰景信息技术有限公司 | Travel safety ensuring system based on big data platform |
| CN108806297A (en) * | 2018-07-24 | 2018-11-13 | 四川数字灯塔科技有限公司 | Traffic accident prevention system based on fusion big data analysis |
-
2020
- 2020-05-13 CN CN202010401146.2A patent/CN111681453A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180130229A1 (en) * | 2016-11-08 | 2018-05-10 | Nec Laboratories America, Inc. | Surveillance system with landmark localization on objects in images using convolutional neural networks |
| CN107221196A (en) * | 2017-05-26 | 2017-09-29 | 广东中星电子有限公司 | Vehicle drive methods of risk assessment, device, system and readable storage medium storing program for executing |
| CN107316487A (en) * | 2017-07-11 | 2017-11-03 | 东莞市信瑞智能科技有限公司 | Car networking Intelligent vehicle-carried information terminal and information interacting method |
| CN108091156A (en) * | 2017-12-14 | 2018-05-29 | 合肥寰景信息技术有限公司 | Travel safety ensuring system based on big data platform |
| CN108806297A (en) * | 2018-07-24 | 2018-11-13 | 四川数字灯塔科技有限公司 | Traffic accident prevention system based on fusion big data analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9747730B2 (en) | Driver measurement and incentive system for improving fuel-efficiency | |
| US10504188B2 (en) | Systems and methods using a mobile device to collect data for insurance premiums | |
| CN103359123B (en) | A kind of intelligent vehicle speed Control management system and implementation method | |
| CN107784587B (en) | Driving behavior evaluation system | |
| US10915964B1 (en) | System and method for providing vehicle services based on driving behaviors | |
| JP2021064395A (en) | Information processing device, information processing method, and program | |
| US10958701B1 (en) | Systems and methods for modulating advertisement frequencies in streaming signals based on vehicle operation data | |
| US20130046510A1 (en) | Systems and Methods for Controlling the Collection of Vehicle Use Data Using a Mobile Device | |
| CN108989541A (en) | Session initiation device, system, vehicle and method based on situation | |
| CN106293032A (en) | Portable terminal device and control method thereof and device | |
| CN107226025A (en) | A kind of system and method for real-time monitoring driving behavior | |
| CN201268230Y (en) | Speed limit sign information vehicle auxiliary drive system based on computer vision | |
| CN109278758A (en) | A kind of intelligent vehicle personalized driving learning system based on smart phone | |
| CN110793537A (en) | Navigation path recommendation method, vehicle machine and vehicle | |
| CA2805439C (en) | Systems and methods using a mobile device to collect data for insurance premiums | |
| CN111009137A (en) | Interval speed measurement prompting method and system based on camera and navigation data fusion and automobile | |
| CN110956483A (en) | Advertisement information pushing method, system, server and vehicle | |
| CN112215093A (en) | Method and device for evaluating vehicle driving ability level | |
| CA3099982C (en) | Content output systems using vehicle-based data | |
| CN106651133B (en) | Method for achieving user driving behavior scoring based on ADAS by using mobile phone | |
| McGarva et al. | Effects of driver cell-phone use on driver aggression | |
| CN111681453A (en) | Automobile safety artificial intelligence housekeeper system based on big data and operation mode thereof | |
| EP2725556A2 (en) | Systems and methods for controlling the collection of vehicle use data using a mobile device | |
| CN115476862A (en) | Driving behavior scoring method, driving behavior reward and punishment method, driving behavior scoring device and driving behavior storage medium | |
| CA2805995A1 (en) | Systems and methods for controlling the collection of vehicle use data using a mobile device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200918 |