CN113206883A - Automobile information acquisition method based on Internet of things - Google Patents
Automobile information acquisition method based on Internet of things Download PDFInfo
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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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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0965—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages responding to signals from another vehicle, e.g. emergency vehicle
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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]
- H04W4/48—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for in-vehicle communication
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Abstract
The invention discloses an automobile information acquisition method based on the Internet of things, and relates to the technical field of Internet of vehicles. The invention comprises the following steps: s1: the Beidou positioning module is used for acquiring the position information of the vehicle in real time, and the information acquisition module is used for acquiring the driving behavior of a driver, the environment inside the vehicle, the environment outside the vehicle and the vehicle running parameter data in real time; s2: the acquired data are transmitted to the vehicle-mounted T-BOX module, and the vehicle-mounted T-BOX module transmits the data to the remote monitoring center through the LTE wireless communication module. According to the invention, the vehicle is positioned in real time through the Beidou positioning module, the real-time information of the vehicle is comprehensively acquired through the information acquisition module, potential safety hazards are eliminated based on driving behaviors, the environment inside the vehicle, the environment outside the vehicle and vehicle running parameter data and the technology of Internet of things, the road utilization rate is improved, the driving safety factor of a vehicle owner is improved, and the problems that the comprehensiveness of the acquisition of the existing vehicle information acquisition method is insufficient, the function is single, and the driving safety is difficult to guarantee are solved.
Description
Technical Field
The invention belongs to the technical field of Internet of things, and particularly relates to an automobile information acquisition method based on the Internet of things.
Background
The connotation of the Internet of vehicles mainly refers to: the vehicle-mounted equipment on the vehicle effectively utilizes all vehicle dynamic information in the information network platform through a wireless communication technology, provides different functional services in the running process of the vehicle, and can find that the internet of vehicles shows the following characteristics: the Internet of vehicles can provide guarantee for the distance between the vehicles, and the probability of collision accidents of the vehicles is reduced; the Internet of vehicles can help the vehicle owner to navigate in real time, and the efficiency of traffic operation is improved through communication with other vehicles and a network system.
The system comprises an automobile information monitoring system and a method based on the Internet of things, wherein the automobile information monitoring system comprises an automobile information acquisition terminal and a server, the automobile information acquisition terminal comprises a processor, a three-axis acceleration sensor, a positioning device and a network communication unit, and the three-axis acceleration sensor, the positioning device and the network communication unit are respectively and electrically connected with the processor; the automobile information acquisition terminal further comprises a rechargeable power supply. According to the automobile information monitoring system based on the Internet of things, provided by the invention, when an automobile encounters a sudden disaster in the driving process, the automobile information acquisition terminal can automatically send alarm information carrying position information to the server, so that the problem that when a driver encounters a sudden disaster in the automobile driving process, the driver cannot send the alarm information immediately, and great inconvenience is brought to the driver is solved.
The patent has the following disadvantages:
1. the automobile information monitoring method is difficult to improve the driving safety factor of an automobile owner, the practicability is poor, and the Internet of things connection among vehicles is not tight enough;
2. the automobile information monitoring method is single in function, and the use parameters of the automobile are difficult to reasonably adjust based on the acquired automobile information data.
Therefore, the existing automobile information monitoring method cannot meet the requirements in practical use, so that an improved technology is urgently needed in the market to solve the problems.
Disclosure of Invention
The invention aims to provide an automobile information acquisition method based on the Internet of things, which is characterized in that a vehicle is positioned in real time through a Beidou positioning module, real-time information of the vehicle is comprehensively acquired through an information acquisition module, potential safety hazards are eliminated based on driving behaviors, the environment inside the vehicle, the environment outside the vehicle and vehicle running parameter data, the driving safety factor of a vehicle owner is improved based on the Internet of things technology, and the problems that the comprehensiveness of the acquisition of the existing automobile information acquisition method is insufficient, the function is single, and the driving safety is difficult to guarantee are solved.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention relates to an automobile information acquisition method based on the Internet of things, which comprises the following steps:
s1: the Beidou positioning module is used for acquiring the position information of the vehicle in real time, and the information acquisition module is used for acquiring the driving behavior of a driver, the environment inside the vehicle, the environment outside the vehicle and the vehicle running parameter data in real time;
s2: the acquired data are transmitted to the vehicle-mounted T-BOX module, and the vehicle-mounted T-BOX module transmits the data to the remote monitoring center through the LTE wireless communication module;
s3: the computer of the remote monitoring center analyzes the acquired data based on the big data module, and obtains the best vehicle running suggestion and potential danger possibly caused by comprehensively analyzing the driving behavior, the environment in the vehicle, the environment outside the vehicle and the vehicle running parameter data;
s4: the remote monitoring center feeds back vehicle running suggestions through the optimization suggestion module, the warning module feeds back warning information, the vehicle running suggestion information and the warning information are displayed through the vehicle-mounted intelligent multimedia host, and a driver can check the vehicle information at any time through the intelligent mobile equipment.
Further, the information acquisition module is including driving action acquisition unit, in-vehicle environment acquisition unit, outer environment acquisition unit and the vehicle parameter acquisition unit that traveles, driving action acquisition unit passes through on-vehicle camera and gathers driver upper limbs action information, gathers driver low limbs action information through throttle opening sensor, brake sensor, gathers driver eye movement condition information through miniature camera, in-vehicle environment acquisition unit passes through temperature and humidity sensor and gathers the humiture information in the car, and the air quality information in gathering the car through air quality detection sensor, outer environment acquisition unit gathers road surface and the other information in road through outside camera, vehicle parameter acquisition unit that traveles gathers vehicle parameter information through BCM automobile body control module.
Furthermore, the computer of the remote monitoring center analyzes the data acquired by the driving behavior acquisition unit based on the big data module, judges whether the driver is in fatigue driving or not and whether abnormal driving behaviors exist or not by analyzing the driving behavior data, if the driver is in fatigue driving, namely the micro camera acquires the eyeball movement condition information of the driver, and detects that the eyes of the driver are closed or in a fatigue state, the remote monitoring center sends out fatigue warning information through the warning module to remind the driver to pay attention, so as to achieve the intelligent management and monitoring of the vehicle safety, if the driver has abnormal driving behaviors of stepping on the brake suddenly, the vehicle is positioned through the Beidou positioning module, and when the drivers of a plurality of vehicles at the front step on the brake suddenly at the same time, the remote monitoring center sends out deceleration warning information to the vehicle at the rear through the warning module, and the driver is reminded to decelerate in time.
Furthermore, the computer of the remote monitoring center analyzes the data acquired by the in-vehicle environment acquisition unit based on the big data module, and judges whether the in-vehicle environment is suitable for long-term driving of a driver by analyzing the in-vehicle environment data, and if the in-vehicle environment is poor, the remote monitoring center sends out in-vehicle environment warning information through the warning module to remind the driver of paying attention.
Further, remote monitoring center's computer is based on the data that big data module analysis external environment collection unit gathered, through carrying out the analysis to external environment data, judge road conditions, the latent danger that road surface characteristic arouses, if road conditions, when road surface characteristic has latent danger, the position of latent danger is fixed a position through big dipper orientation module, and in saving the latent dangerous position to big data module, when other vehicles are close to the latent dangerous position, remote monitoring center sends road surface danger alarm information through warning module, remind the driver to notice, and guide the vehicle to rationally dodge.
Further, the computer of the remote monitoring center analyzes data collected by the vehicle driving parameter collecting unit based on the big data module, whether the vehicle is normal or not is judged by analyzing the vehicle driving parameter data, if the vehicle is abnormal, the remote monitoring center sends rescue information to the rescue center on one hand, and on the other hand, informs other nearby vehicles to remind the other nearby vehicles of timely rescue.
Further, the intelligent mobile device comprises a mobile phone, a tablet and an intelligent wearable device.
Furthermore, the alarm module alarms in a sound and light mode to remind a driver in time.
Furthermore, the optimization suggestion module comprises personalized maintenance suggestions, personalized vehicle running environment suggestions and optimal road condition route suggestions, the remote monitoring center summarizes the driving style characteristics of the vehicle owner based on the collected driving behavior data and driving environment data of the driver, sends out the personalized vehicle maintenance suggestions, provides optimal running parameter setting suggestions, provides the optimal road condition route suggestions and ensures that the vehicle is in the optimal state.
The invention has the following beneficial effects:
1. according to the intelligent traffic management system, the Beidou positioning module, the information acquisition module, the LTE wireless communication module and the remote monitoring center are arranged, the vehicle is positioned in real time through the Beidou positioning module, the real-time information of the vehicle is comprehensively acquired through the information acquisition module, the vehicle, the remote monitoring center and the vehicle are linked based on the internet of things technology, intelligent traffic management is carried out, traffic jam is relieved, the road utilization rate is improved, and the driving safety factor of a vehicle owner is improved.
2. The driving behavior acquisition unit is arranged, fatigue driving and possible driving hidden dangers are eliminated based on the driving behaviors of the driver, the safety of the driver is improved, and if the driver of a plurality of vehicles in front of the vehicle suddenly steps on the brake at the same time, the remote monitoring center can send deceleration alarm information to the vehicle through the alarm module, so that the driver is reminded of decelerating in time, and the driver is prevented from getting ill.
3. According to the invention, the in-vehicle environment acquisition unit and the vehicle driving parameter acquisition unit are arranged, so that the vehicle is ensured to be in a normal state when driving, the driver is prevented from being subjected to potential safety hazards, and the optimization suggestion module provides the best suggestion based on the acquired driving behavior data and driving environment data of the driver, so that the vehicle is ensured to be in an optimal state.
4. According to the invention, the external environment acquisition unit is arranged, potential danger is eliminated based on road conditions and road surface characteristics, the safety of a driver is improved, when the road conditions and the road surface characteristics have potential danger, such as a large pit is formed on the road surface, the position of the large pit is positioned through the Beidou positioning module, the position of the large pit is stored in the large data module, and when the vehicle approaches the position of the large pit, the remote monitoring center sends out road surface danger alarm information through the alarm module, reminds the driver of having the pit and guides the vehicle to reasonably avoid.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic block diagram of the overall architecture of the present invention;
fig. 2 is a schematic structural diagram of an information acquisition module according to the present invention.
In the drawings, the components represented by the respective reference numerals are listed below:
1. a Beidou positioning module; 2. an information acquisition module; 3. an onboard T-BOX module; 4. an LTE wireless communication module; 5. an intelligent mobile device; 6. a remote monitoring center; 7. a big data module; 8. an on-vehicle intelligent multimedia host; 9. an alarm module; 10. an optimization suggestion module; 201. a driving behavior acquisition unit; 202. an in-vehicle environment acquisition unit; 203. an external environment acquisition unit; 204. vehicle driving parameter acquisition unit.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Referring to fig. 1, the invention relates to an automobile information acquisition method based on the internet of things, which comprises the following steps:
s1: the Beidou positioning module 1 is used for acquiring the position information of the vehicle in real time, and the information acquisition module 2 is used for acquiring the driving behavior of a driver, the environment inside the vehicle, the environment outside the vehicle and the vehicle running parameter data in real time;
s2: the acquired data are transmitted to the vehicle-mounted T-BOX module 3, and the vehicle-mounted T-BOX module 3 transmits the data to the remote monitoring center 6 through the LTE wireless communication module 4;
s3: the computer of the remote monitoring center 6 analyzes the acquired data based on the big data module 7, and obtains the best vehicle driving suggestion and potential danger possibly caused by comprehensively analyzing the driving behavior, the environment in the vehicle, the environment outside the vehicle and the vehicle driving parameter data, wherein the big data module 7 can improve the accuracy of data acquisition and eliminate unreasonable data;
s4: remote monitoring center 6 feeds back the vehicle suggestion of traveling through optimizing suggestion module 10, feedback alarm information through warning module 9, vehicle suggestion information of traveling and alarm information show through on-vehicle intelligent multimedia host 8, and driver accessible intelligent mobile device 5 looks over vehicle information at any time, wherein, intelligent mobile device 5 includes the cell-phone, dull and stereotyped and intelligent wearing equipment, cell-phone APP, little letter applet, a plurality of interactive equipment such as intelligent wearing equipment, greatly improve user's the experience of using the car, warning module 9 adopts sound, the dual mode of light is reported an emergency and asked for help or increased vigilance, in time remind the driver.
As shown in fig. 2, the information collection module 2 includes a driving behavior collection unit 201, an in-vehicle environment collection unit 202, an out-vehicle environment collection unit 203 and a vehicle driving parameter collection unit 204, the driving behavior collection unit 201 collects upper limb movement information of a driver through a vehicle-mounted camera, the lower limb movement information of the driver is collected through an accelerator opening sensor and a brake sensor, eyeball movement condition information of the driver is collected through a micro camera, the in-vehicle environment collection unit 202 collects temperature and humidity information in a vehicle through a temperature and humidity sensor, air quality information in the vehicle is collected through an air quality detection sensor, the out-vehicle environment collection unit 203 collects information of a road surface and two sides of the road through an external camera, and the vehicle driving parameter collection unit 204 collects vehicle driving parameter information through a BCM vehicle body control module.
The computer of the remote monitoring center 6 analyzes the data collected by the driving behavior collecting unit 201 based on the big data module 7, and analyzes the driving behavior data to judge whether the driver is tired and drives or not, and whether abnormal driving behaviors exist or not, if the driver is tired and drives, the remote monitoring center 6 sends out fatigue warning information through the warning module 9 to remind the driver to pay attention, if the driver has abnormal driving behaviors of violently stepping on the brake, the vehicle is positioned through the Beidou positioning module 1, when the drivers of the previous vehicles simultaneously and violently step on the brake, the remote monitoring center 6 sends out deceleration warning information to the vehicle at the rear through the warning module 9 to timely remind the driver of deceleration.
The computer of the remote monitoring center 6 analyzes the data collected by the in-vehicle environment collecting unit 202 based on the big data module 7, and judges whether the in-vehicle environment is suitable for the long-term driving of the driver by analyzing the in-vehicle environment data, if the in-vehicle environment is poor, the remote monitoring center 6 sends out in-vehicle environment warning information through the warning module 9 to remind the driver of paying attention.
The computer of remote monitoring center 6 analyzes the data that external environment acquisition unit 203 of car gathered based on big data module 7, through analyzing external environment data, judge road conditions, the latent danger that road surface characteristic arouses, if road conditions, when road surface characteristic has the latent danger, if the road surface has big hole, the big hole position of latent danger is fixed a position through big dipper orientation module 1, and with the big hole position storage of latent danger to big data module 7, when other vehicles are close the big hole position of latent danger, remote monitoring center 6 sends the dangerous warning information in road surface through warning module 9, remind the driver to notice, and guide the vehicle rationally to dodge big hole.
The computer of the remote monitoring center 6 analyzes the data acquired by the vehicle driving parameter acquisition unit 204 based on the big data module 7, and judges whether the vehicle is normal or not by analyzing the vehicle driving parameter data, if the vehicle is abnormal, the remote monitoring center 6 sends rescue information to the rescue center on one hand, and informs other vehicles nearby on the other hand to remind other vehicles nearby of timely rescue.
The optimization suggestion module 10 includes personalized maintenance suggestions, personalized vehicle operation environment suggestions and optimal road condition route suggestions, and the remote monitoring center 6 summarizes the driving style characteristics of the vehicle owner based on the collected driving behavior data and driving environment data of the driver, sends out the personalized vehicle maintenance suggestions, provides the optimal operation parameter setting suggestions, provides the optimal road condition route suggestions, and ensures that the vehicle is in the optimal state.
The above are only preferred embodiments of the present invention, and the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made to the technical solutions described in the above embodiments, and to some of the technical features thereof, are included in the scope of the present invention.
Claims (9)
1. An automobile information acquisition method based on the Internet of things is characterized in that: the method comprises the following steps:
s1: the Beidou positioning module (1) is used for acquiring the position information of the vehicle in real time, and the information acquisition module (2) is used for acquiring the driving behavior of a driver, the environment inside the vehicle, the environment outside the vehicle and the vehicle running parameter data in real time;
s2: the acquired data are transmitted to a vehicle-mounted T-BOX module (3), and the vehicle-mounted T-BOX module (3) transmits the data to a remote monitoring center (6) through an LTE wireless communication module (4);
s3: the computer of the remote monitoring center (6) analyzes the acquired data based on the big data module (7), and obtains the optimal vehicle driving suggestion and potential danger possibly caused by comprehensively analyzing the driving behavior, the environment in the vehicle, the environment outside the vehicle and the vehicle driving parameter data;
s4: the remote monitoring center (6) feeds back vehicle running suggestions through the optimization suggestion module (10), and feeds back warning information through the warning module (9), the vehicle running suggestion information and the warning information are displayed through the vehicle-mounted intelligent multimedia host (8), and a driver can check the vehicle information at any time through the intelligent mobile device (5).
2. The internet of things-based automobile information acquisition method according to claim 1, wherein the information acquisition module (2) comprises a driving behavior acquisition unit (201), an in-vehicle environment acquisition unit (202), an out-vehicle environment acquisition unit (203) and a vehicle driving parameter acquisition unit (204), the driving behavior acquisition unit (201) acquires upper limb action information of a driver through a vehicle-mounted camera, acquires lower limb action information of the driver through an accelerator opening sensor and a brake sensor, acquires eyeball movement condition information of the driver through a miniature camera, the in-vehicle environment acquisition unit (202) acquires temperature and humidity information in a vehicle through a temperature and humidity sensor, acquires air quality information in the vehicle through an air quality detection sensor, and the out-vehicle environment acquisition unit (203) acquires information on a road surface and on two sides of the road through an external camera, the vehicle running parameter acquisition unit (204) acquires vehicle running parameter information through a BCM vehicle body control module.
3. The Internet of things-based automobile information acquisition method according to claim 2, the computer of the remote monitoring center (6) analyzes the data collected by the driving behavior collecting unit (201) based on the big data module (7), by analyzing the driving behavior data, whether the driver is in fatigue driving or not and whether abnormal driving behavior exists or not are judged, if the driver is in fatigue driving, the remote monitoring center (6) sends out fatigue alarm information through the alarm module (9) to remind the driver to pay attention, if the driver has abnormal driving behavior of stepping on the brake suddenly, when the Beidou positioning module (1) is used for positioning the vehicles and the drivers of a plurality of vehicles in the front simultaneously and violently step on the brakes, the remote monitoring center (6) sends deceleration alarm information to a vehicle behind through the alarm module (9) to prompt a driver to decelerate in time.
4. The internet of things-based automobile information acquisition method according to claim 2, wherein a computer of the remote monitoring center (6) analyzes data acquired by the in-vehicle environment acquisition unit (202) based on the big data module (7), and judges whether the in-vehicle environment is suitable for long-term driving of a driver by analyzing the in-vehicle environment data, and if the in-vehicle environment is poor, the remote monitoring center (6) sends out in-vehicle environment alarm information through the alarm module (9) to remind the driver of paying attention.
5. The automobile information acquisition method based on the Internet of things of claim 2, wherein a computer of the remote monitoring center (6) analyzes data acquired by the external environment acquisition unit (203) based on the big data module (7), potential dangers caused by road conditions and road surface characteristics are judged by analyzing the external environment data, if the road conditions and the road surface characteristics have the potential dangers, the position of the potential danger is positioned through the Beidou positioning module (1), the potential danger position is stored into the big data module (7), and when other vehicles approach the potential danger position, the remote monitoring center (6) sends out road surface danger warning information through the warning module (9), reminds a driver to pay attention to and guides the vehicles to reasonably avoid.
6. The internet of things-based automobile information collection method according to claim 2, wherein a computer of the remote monitoring center (6) analyzes data collected by the vehicle driving parameter collection unit (204) based on the big data module (7), judges whether the vehicle is normal or not by analyzing the vehicle driving parameter data, and if the vehicle is abnormal, the remote monitoring center (6) sends rescue information to the rescue center on one hand and notifies other nearby vehicles on the other hand to remind the other nearby vehicles of timely rescue.
7. The Internet of things-based automobile information acquisition method according to claim 1, wherein the smart mobile device (5) comprises a mobile phone, a tablet and a smart wearable device.
8. The Internet of things-based automobile information acquisition method according to claim 1, wherein the alarm module (9) alarms in a sound and light mode to remind a driver in time.
9. The internet of things-based automobile information acquisition method according to claim 1, wherein the optimization suggestion module (10) comprises personalized maintenance suggestions, personalized vehicle operation environment suggestions and optimal road condition route suggestions, and the remote monitoring center (6) summarizes the driving style characteristics of the owner of the automobile based on the acquired driving behavior data and driving environment data of the driver, sends out personalized vehicle maintenance suggestions, provides optimal operation parameter setting suggestions, provides optimal road condition route suggestions and ensures that the vehicle is in an optimal state.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113761363A (en) * | 2021-08-04 | 2021-12-07 | 南斗六星系统集成有限公司 | Internet of vehicles big data analysis system |
| CN115442397A (en) * | 2022-08-09 | 2022-12-06 | 广州小鹏汽车科技有限公司 | Data transmission method, system and device and vehicle |
| CN118553107A (en) * | 2024-07-26 | 2024-08-27 | 云盾智慧安全科技有限公司 | Network-connected automobile data safety warning method and system based on data analysis |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103793787A (en) * | 2014-01-23 | 2014-05-14 | 南京邮电大学 | Car networking processing system and method |
| CN108099601A (en) * | 2018-01-30 | 2018-06-01 | 成都四海万联科技有限公司 | A kind of detecting system for improving drive safety |
| CN109823346A (en) * | 2019-01-23 | 2019-05-31 | 广州德晟人工智能科技有限公司 | Based on big data active safety early warning system and method |
| CN111176259A (en) * | 2020-01-06 | 2020-05-19 | 中卫物联成都科技有限公司 | Internet of things road transport vehicle active safety intelligent prevention and control system |
-
2021
- 2021-05-06 CN CN202110490828.XA patent/CN113206883A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103793787A (en) * | 2014-01-23 | 2014-05-14 | 南京邮电大学 | Car networking processing system and method |
| CN108099601A (en) * | 2018-01-30 | 2018-06-01 | 成都四海万联科技有限公司 | A kind of detecting system for improving drive safety |
| CN109823346A (en) * | 2019-01-23 | 2019-05-31 | 广州德晟人工智能科技有限公司 | Based on big data active safety early warning system and method |
| CN111176259A (en) * | 2020-01-06 | 2020-05-19 | 中卫物联成都科技有限公司 | Internet of things road transport vehicle active safety intelligent prevention and control system |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113761363A (en) * | 2021-08-04 | 2021-12-07 | 南斗六星系统集成有限公司 | Internet of vehicles big data analysis system |
| CN115442397A (en) * | 2022-08-09 | 2022-12-06 | 广州小鹏汽车科技有限公司 | Data transmission method, system and device and vehicle |
| CN118553107A (en) * | 2024-07-26 | 2024-08-27 | 云盾智慧安全科技有限公司 | Network-connected automobile data safety warning method and system based on data analysis |
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Application publication date: 20210803 |