CN111209327A - Multi-sensor distributed sensing interconnection and edge fusion processing system and method - Google Patents
Multi-sensor distributed sensing interconnection and edge fusion processing system and method Download PDFInfo
- Publication number
- CN111209327A CN111209327A CN202010037813.3A CN202010037813A CN111209327A CN 111209327 A CN111209327 A CN 111209327A CN 202010037813 A CN202010037813 A CN 202010037813A CN 111209327 A CN111209327 A CN 111209327A
- Authority
- CN
- China
- Prior art keywords
- data
- module
- sensor
- edge fusion
- vehicle
- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/251—Fusion techniques of input or preprocessed data
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Computational Biology (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Traffic Control Systems (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a multi-sensor distributed perception interconnection and edge fusion processing system and a method, wherein the perception interconnection and edge fusion processing system comprises a plurality of sensors for acquiring data, a data association module for associating the sensor data, a data fusion module for fusing the associated data, a vehicle-mounted sensor for acquiring the front vehicle data, a data uploading module for uploading the vehicle-mounted sensor data to a cloud-end database, and an edge fusion processing module for performing final data edge fusion.
Description
Technical Field
The invention relates to the technical field of perception interconnection and edge fusion, in particular to a multi-sensor distributed perception interconnection and edge fusion processing system and method.
Background
With the continuous development of society, the mode of going on a journey also gradually develops to drive private cars, take subways, high-speed rails and the like from walking, and with the continuous increase of the number of the private cars, the crowding condition of roads is continuously aggravated, and particularly when vehicle collision and major traffic accidents occur, the vehicle congestion is more serious.
When a vehicle collision or a major traffic accident occurs, a traffic police generally inquires the accident scene about the passing of the accident, then takes a picture and obtains evidence, and when the clear accident passing cannot be known from a party, the video shot by a camera and the video recorded by an on-board recorder need to be taken, and then the passing of the accident is judged according to the video.
When the situation of the accident is known, if the situation of the accident cannot be rapidly known, more serious road congestion is caused, and a great amount of time is wasted in the process of calling the video.
Therefore, a system and a method for processing distributed sensing interconnection and edge fusion of multiple sensors are needed to solve the above problems.
Disclosure of Invention
The invention aims to provide a multi-sensor distributed sensing interconnection and edge fusion processing system and method to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a multisensor distributed perception interconnection and edge fuse processing system, this perception interconnection and edge fuse processing system include a plurality of sensors of data acquisition, carry out the data correlation module of sensor data correlation, carry out the data fusion module that fuses to the data after the correlation, carry out the on-vehicle sensor of gathering to the front truck data, upload the data of on-vehicle sensor to the cloud end database and upload the module, carry out the edge of last data edge fusion processing module that fuses, its characterized in that: the data association module is connected with the sensor, the data association module is connected with the data fusion module, the data uploading module is connected with the vehicle-mounted sensor, the data uploading module uploads the data monitored by the vehicle-mounted sensor to the cloud database, and the edge fusion processing module carries out edge fusion processing on the data in the data fusion module and the cloud database and restores the process of accidents.
As a preferred technical scheme, the sensors are respectively a sensor 1 and a sensor 2 … …, the sensors collect data of vehicles on a road and transmit the collected data to a data association module, the data association module classifies and combines the data transmitted by the sensors, data sets belonging to the same data source are combined together, tracking is performed to realize motion parameter estimation of a motion entity, the associated data are transmitted to a data fusion module, the data fusion module performs data fusion on the data processed by the data association module, and time-space alignment is performed on multi-source observation data which are asynchronous in time domain and belong to different coordinate systems in space domain, so that the multi-source data are contained in a unified reference frame to lay a cushion for the work of a later edge fusion processing module.
As an optimal technical scheme, the vehicle-mounted sensor monitors the data of the front vehicle and transmits the monitored data to the data uploading module, the data uploading module uploads the data monitored by the vehicle-mounted sensor to the cloud database, and the cloud database sums up and stores the uploaded data of the same data source and lays a cushion for the work of the later edge fusion processing module.
As a preferred technical solution, the edge fusion processing module performs edge fusion processing on data in the data fusion module to fuse overlapped parts in the data into a unified data, the data processed by the edge fusion module in the data fusion module is referred to as data a, the edge fusion processing module extracts data in the cloud database at the same time and in the same space, performs edge fusion processing on the data in the cloud database to fuse the overlapped parts in the data into a unified data, the data processed by the edge fusion module in the cloud database is referred to as data b, and the edge fusion module performs edge fusion processing on the data a and the data b again to fuse the data a and the data b into a new data c, where the data c is a reduced image through which an accident passes.
As a preferred technical scheme, before the data uploading module transmits the data monitored by the vehicle-mounted sensor to the cloud database, the data uploading module classifies and combines the data transmitted by the vehicle-mounted sensor, combines data sets belonging to the same data source together, tracks the data sets for realizing motion parameter estimation of the motion entity, and transmits the processed data to the cloud database.
A multi-sensor distributed sensing interconnection and edge fusion processing method comprises the following steps: 1) collecting vehicle data, correlating the data, and fusing the correlated data; 2) collecting data of the vehicle-mounted sensor, correlating the data, and uploading the data to a cloud database; 3) the vehicle data and the vehicle-mounted sensor data are subjected to edge fusion processing to form new data (i.e., a passing picture of an accident).
The method comprises the following specific steps of ①, wherein the sensors are sensor 1 and sensor 2 … …, sensor N, the sensors collect data of vehicles on a road and transmit the collected data to a data association module, ② the data association module classifies and combines the data transmitted by the sensors, combines data sets belonging to the same data source together, tracks the data to estimate motion parameters of a motion entity and transmits the associated data to a data fusion module, ③ the data fusion module performs data fusion on the data processed by the data association module, performs space-time alignment on multi-source observation data which are asynchronous in time domain and belong to different coordinate systems in space domain, and accordingly brings the multi-source observation data into a unified reference frame to be padded for the work of a later edge fusion processing module.
As a preferable technical scheme, the specific steps of the step 2) include ① that the vehicle-mounted sensor monitors the data of the front vehicle and transmits the monitored data to the data uploading module, ② that the data uploading module uploads the data monitored by the vehicle-mounted sensor to the cloud database, and ③ that the cloud database summarizes and stores the uploaded data of the same data source and lays a cushion for the later work of the edge fusion processing module.
The specific step of the step 3) includes ① performing edge fusion processing on data in the data fusion module by the edge fusion processing module to fuse overlapped parts of the data into a unified data, wherein the data processed by the edge fusion module in the data fusion module is called data a, ② performing edge fusion processing on the data in the cloud database at the same time and in the same space, performing edge fusion processing on the data in the cloud database to fuse the overlapped parts of the data into a unified data, and the data processed by the edge fusion module in the cloud database is called data b, ③ performing edge fusion processing on the data a and the data b again to fuse the data a and the data b into a new data c, and the data c is a reduced image through which an accident passes.
As a preferred technical solution, the specific steps of step ② include that the data uploading module classifies and combines data transmitted by the vehicle-mounted sensors, combines data sets belonging to the same data source, tracks the data sets to realize motion parameter estimation of the motion entity, and transmits the processed data to the cloud database.
Compared with the prior art, the invention has the beneficial effects that: through the collection of front-end data, the association of the data and the edge fusion processing of the data, the video of an accident scene is quickly synthesized and restored, police officers are helped to quickly know the passing of the accident, the accident processing time is shortened, and the accident processing efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of a module connection of a multi-sensor distributed sensing interconnection and edge blending processing system according to the present invention;
fig. 2 is a schematic diagram of a road simulation of the multi-sensor distributed sensing interconnection and edge fusion processing system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b): as shown in fig. 1-2, a distributed sensing interconnection and edge fusion processing system for multiple sensors includes a plurality of sensors for collecting data, a data association module for associating the sensor data, a data fusion module for fusing the associated data, a vehicle-mounted sensor for collecting the data of a vehicle ahead, a data upload module for uploading the data of the vehicle-mounted sensor to a cloud database, and an edge fusion processing module for edge fusion of the last data, wherein the data association module is connected with the sensors, the data association module is connected with the data fusion module, the data upload module is connected with the vehicle-mounted sensor, the data upload module uploads the data monitored by the vehicle-mounted sensor to the cloud database, the edge fusion processing module performs edge fusion processing on the data in the data fusion module and the cloud database and restores the passing of an accident, the sensors involved in the present system may be radar sensors, laser sensors, or other sensors used for road data monitoring.
The sensors are respectively a sensor 1 and a sensor 2 … …, the sensors acquire data of vehicles on a road and transmit the acquired data to the data association module, the data association module classifies and combines the data transmitted by the sensors, data sets belonging to the same data source are combined together, tracking is used for realizing motion parameter estimation of a motion entity, the associated data are transmitted to the data fusion module, the data fusion module performs data fusion on the data processed by the data association module and performs space-time alignment on multisource observation data which are asynchronous in time domain and belong to different coordinate systems in space domain, so that the multisource data are brought into a unified reference frame and are laid for the work of a later edge fusion processing module.
The vehicle-mounted sensor monitors the data of the front vehicle, the vehicle can shift in position in the driving process, the vehicle-mounted sensor can monitor multiple groups of data of the same vehicle, the multiple groups of data monitored by the vehicle-mounted sensor are transmitted to the data uploading module, the data uploading module uploads the data monitored by the vehicle-mounted sensor to the cloud database, the cloud database sums up and stores the uploaded data of the same data source, and the data are paved for the work of the edge fusion processing module in the later period.
Before the data uploading module transmits the data monitored by the vehicle-mounted sensor to the cloud database, the data uploading module classifies and combines the data transmitted by the vehicle-mounted sensor, combines data sets belonging to the same data source together, tracks the data sets to realize motion parameter estimation of a motion entity, and transmits the processed data to the cloud database.
The edge fusion processing module carries out edge fusion processing on data in the data fusion module to enable overlapped parts in the data to be fused into unified data, the data processed by the edge fusion module in the data fusion module is called data a, the edge fusion processing module extracts data in the same time and the same space in the cloud database and carries out edge fusion processing on the data in the cloud database to enable the overlapped parts in the data to be fused into the unified data, the data processed by the edge fusion module in the cloud database is called data b, the edge fusion module carries out edge fusion processing on the data a and the data b again to enable the data a and the data b to be fused into new data c, and the data c is a reduced image through which an accident passes.
A multi-sensor distributed sensing interconnection and edge fusion processing method comprises the following steps: 1) collecting vehicle data, correlating the data, and fusing the correlated data; 2) collecting data of the vehicle-mounted sensor, correlating the data, and uploading the data to a cloud database; 3) the vehicle data and the vehicle-mounted sensor data are subjected to edge fusion processing to form new data (i.e., a passing picture of an accident).
The specific steps of the step 1) include ① that a plurality of sensors are respectively a sensor 1 and a sensor 2 … … sensor N, the sensors collect data of vehicles on a road and transmit the collected data to a data association module, ② the data association module classifies and combines the data transmitted by the sensors, combines data sets belonging to the same data source together, tracks the data to realize motion parameter estimation of a motion entity and transmits the associated data to a data fusion module, and ③ the data fusion module performs data fusion on the data processed by the data association module and performs space-time alignment on multi-source observation data which are asynchronous in a time domain and belong to different coordinate systems in a space domain, so that the multi-source data are incorporated into a unified reference frame and are laid for the work of a later edge fusion processing module.
The specific steps of the step 2) include that ① vehicle-mounted sensors monitor the data of the front vehicle and transmit the monitored data to a data uploading module, ② the data uploading module uploads the data monitored by the vehicle-mounted sensors to a cloud database, and ③ the cloud database summarizes and stores the uploaded data of the same data source, so that the operation of the edge fusion processing module at the later stage is padded.
The specific step of step ② in step 2 includes that the data uploading module classifies and combines the data transmitted by the vehicle-mounted sensors, combines data sets belonging to the same data source together, tracks the data sets for realizing motion parameter estimation of the motion entity, and transmits the processed data to the cloud database.
The specific steps of the step 3) include ① that the edge fusion processing module carries out edge fusion processing on data in the data fusion module to enable overlapped parts in the data to be fused into uniform data, the data processed by the edge fusion module in the data fusion module is called data a, ② that the edge fusion processing module extracts data in the same time and in the same space in the cloud database and carries out edge fusion processing on the data in the cloud database to enable the overlapped parts in the data to be fused into uniform data, the data processed by the edge fusion module in the cloud database is called data b, and ③ that the edge fusion module carries out edge fusion processing on the data a and the data b again to enable the data a and the data b to be fused into new data c, wherein the data c is a reduced image through which an accident passes.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. The utility model provides a multisensor distributed perception interconnection and edge fuse processing system, this perception interconnection and edge fuse processing system include a plurality of sensors of data acquisition, carry out the data correlation module of sensor data correlation, carry out the data fusion module that fuses to the data after the correlation, carry out the on-vehicle sensor of gathering to the front truck data, upload the data of on-vehicle sensor to the cloud end database and upload the module, carry out the edge of last data edge fusion processing module that fuses, its characterized in that: the data association module is connected with the sensor, the data association module is connected with the data fusion module, the data uploading module is connected with the vehicle-mounted sensor, the data uploading module uploads the data monitored by the vehicle-mounted sensor to the cloud database, and the edge fusion processing module carries out edge fusion processing on the data in the data fusion module and the cloud database and restores the process of accidents.
2. The multi-sensor distributed sensing interconnection and edge fusion processing system according to claim 1, wherein: the sensors are respectively a sensor 1 and a sensor 2 … …, the sensors acquire data of vehicles on a road and transmit the acquired data to the data association module, the data association module classifies and combines the data transmitted by the sensors, data sets belonging to the same data source are combined together, tracking is used for realizing motion parameter estimation of a motion entity, the associated data are transmitted to the data fusion module, the data fusion module performs data fusion on the data processed by the data association module and performs space-time alignment on multisource observation data which are asynchronous in time domain and belong to different coordinate systems in space domain, so that the multisource data are brought into a unified reference frame and are laid for the work of a later edge fusion processing module.
3. The multi-sensor distributed sensing interconnection and edge fusion processing system according to claim 1, wherein: the vehicle-mounted sensor monitors the data of the front vehicle and transmits the monitored data to the data uploading module, the data uploading module uploads the monitored data of the vehicle-mounted sensor to the cloud database, and the cloud database sums up and stores the uploaded data of the same data source and lays a cushion for the later work of the edge fusion processing module.
4. The multi-sensor distributed sensing interconnection and edge blending processing system according to claim 2 or 3, wherein: the edge fusion processing module carries out edge fusion processing on data in the data fusion module to enable overlapped parts in the data to be fused into unified data, the data processed by the edge fusion module in the data fusion module is called data a, the edge fusion processing module extracts data in the same time and the same space in the cloud database and carries out edge fusion processing on the data in the cloud database to enable the overlapped parts in the data to be fused into the unified data, the data processed by the edge fusion module in the cloud database is called data b, the edge fusion module carries out edge fusion processing on the data a and the data b again to enable the data a and the data b to be fused into new data c, and the data c is a reduced image through which an accident passes.
5. The multi-sensor distributed sensing interconnection and edge blending processing system according to claim 3, wherein: before the data uploading module transmits the data monitored by the vehicle-mounted sensor to the cloud database, the data uploading module classifies and combines the data transmitted by the vehicle-mounted sensor, combines data sets belonging to the same data source together, tracks the data sets to realize motion parameter estimation of the motion entity, and transmits the processed data to the cloud database.
6. A multi-sensor distributed sensing interconnection and edge fusion processing method is characterized by comprising the following steps: the processing method for perception interconnection and edge fusion comprises the following steps: 1) collecting vehicle data, correlating the data, and fusing the correlated data; 2) collecting data of the vehicle-mounted sensor, correlating the data, and uploading the data to a cloud database; 3) the vehicle data and the vehicle-mounted sensor data are subjected to edge fusion processing to form new data (i.e., a passing picture of an accident).
7. The multi-sensor distributed sensing interconnection and edge fusion processing method of claim 6, wherein the specific steps of the step 1) include ① that the sensors are sensor 1 and sensor 2 … …, respectively, the sensors collect data of vehicles on a road and transmit the collected data to a data association module, ② that the data association module classifies and combines the data transmitted by the sensors, combines data sets belonging to the same data source together, tracks the data to estimate motion parameters of a motion entity, and transmits the correlated data to a data fusion module, and ③ that the data fusion module performs data fusion on the data processed by the data association module, performs time-space alignment on multi-source observation data belonging to different coordinate systems in time domain and space domain, and thus incorporates the multi-source data into a unified reference frame and lays a cushion for the work of a later edge fusion processing module.
8. The multi-sensor distributed sensing interconnection and edge fusion processing method according to claim 6, wherein the specific steps of the step 2) include ① that the vehicle-mounted sensor monitors the data of the front vehicle and transmits the monitored data to the data uploading module, ② that the data uploading module uploads the data monitored by the vehicle-mounted sensor to a cloud database, and ③ that the cloud database summarizes and stores the uploaded data of the same data source and lays a cushion for the later work of the edge fusion processing module.
9. The method for the distributed sensing interconnection and edge fusion processing of the multiple sensors according to claim 6, wherein the specific steps of the step 3) include ① performing edge fusion processing on data in the data fusion module by the edge fusion processing module to fuse overlapped parts of the data into a unified data, wherein the data processed by the edge fusion module in the data fusion module is called data a, ② performing edge fusion processing on the data in the same time and space in the cloud database, performing edge fusion processing on the data in the cloud database to fuse the overlapped parts of the data into a unified data, and the data processed by the edge fusion module in the cloud database is called data b, and ③ performing edge fusion processing on the data a and the data b again to fuse the data a and the data b into a new data c, wherein the data c is a reduced image through which an accident passes.
10. The method of claim 8, wherein the step ② comprises classifying and combining data transmitted by vehicle-mounted sensors by a data uploading module, combining data sets belonging to the same data source, tracking to estimate motion parameters of a moving entity, and transmitting the processed data to a cloud database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010037813.3A CN111209327A (en) | 2020-01-14 | 2020-01-14 | Multi-sensor distributed sensing interconnection and edge fusion processing system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010037813.3A CN111209327A (en) | 2020-01-14 | 2020-01-14 | Multi-sensor distributed sensing interconnection and edge fusion processing system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111209327A true CN111209327A (en) | 2020-05-29 |
Family
ID=70789668
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010037813.3A Pending CN111209327A (en) | 2020-01-14 | 2020-01-14 | Multi-sensor distributed sensing interconnection and edge fusion processing system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111209327A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114978977A (en) * | 2022-06-02 | 2022-08-30 | 星河互联网络(深圳)有限公司 | Edge computing gateway with multi-data fusion processing |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105741546A (en) * | 2016-03-18 | 2016-07-06 | 重庆邮电大学 | Intelligent vehicle target tracking system through integration of road side equipment and vehicle sensor and method thereof |
| CN106408940A (en) * | 2016-11-02 | 2017-02-15 | 南京慧尔视智能科技有限公司 | Microwave and video data fusion-based traffic detection method and device |
| CN108762245A (en) * | 2018-03-20 | 2018-11-06 | 华为技术有限公司 | Data fusion method and relevant device |
| CN109118732A (en) * | 2018-08-27 | 2019-01-01 | 中国科学院上海微***与信息技术研究所 | Sensor perception event judgement and alarm system and method based on marginal information |
| US10365355B1 (en) * | 2016-04-21 | 2019-07-30 | Hunter Engineering Company | Method for collective calibration of multiple vehicle safety system sensors |
-
2020
- 2020-01-14 CN CN202010037813.3A patent/CN111209327A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105741546A (en) * | 2016-03-18 | 2016-07-06 | 重庆邮电大学 | Intelligent vehicle target tracking system through integration of road side equipment and vehicle sensor and method thereof |
| US10365355B1 (en) * | 2016-04-21 | 2019-07-30 | Hunter Engineering Company | Method for collective calibration of multiple vehicle safety system sensors |
| CN106408940A (en) * | 2016-11-02 | 2017-02-15 | 南京慧尔视智能科技有限公司 | Microwave and video data fusion-based traffic detection method and device |
| CN108762245A (en) * | 2018-03-20 | 2018-11-06 | 华为技术有限公司 | Data fusion method and relevant device |
| CN109118732A (en) * | 2018-08-27 | 2019-01-01 | 中国科学院上海微***与信息技术研究所 | Sensor perception event judgement and alarm system and method based on marginal information |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114978977A (en) * | 2022-06-02 | 2022-08-30 | 星河互联网络(深圳)有限公司 | Edge computing gateway with multi-data fusion processing |
| CN114978977B (en) * | 2022-06-02 | 2023-10-03 | 星河互联网络(深圳)有限公司 | Edge computing gateway with multivariate data fusion processing |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN211124362U (en) | Multisource traffic information perception roadside equipment towards wisdom highway | |
| CN109816811B (en) | Natural driving data acquisition device | |
| CN112789619B (en) | Simulation scene construction method, simulation method and device | |
| CN103295396B (en) | Speedy ex-situ evidence collection of traffic accident method and system | |
| CN202071799U (en) | Intelligent automobile safety warning device | |
| CN203134149U (en) | Vehicle auxiliary driving system based on different wave band imaging fusion image processing | |
| CN105291984A (en) | Pedestrian and vehicle detecting method and system based on multi-vehicle cooperation | |
| DE102011122297A1 (en) | Method for generating and using traffic-relevant information by vehicles of a vehicle pool | |
| CN103593884B (en) | A kind of drive recorder and control method thereof | |
| CN106056697A (en) | Event monitoring method, device and system | |
| DE102021131844A1 (en) | SYSTEMS AND METHODS FOR IMPLEMENTING COVERAGE PRESENTATIONS OVER ROAD FEATURES | |
| CN112633120A (en) | Intelligent roadside sensing system based on semi-supervised learning and model training method | |
| CN111311942A (en) | Road condition display method and system based on V2X technology, V2X terminal and V2X server | |
| CN109874099B (en) | Networking vehicle-mounted equipment flow control system | |
| CN114492679A (en) | Vehicle data processing method and device, electronic equipment and medium | |
| CN111209327A (en) | Multi-sensor distributed sensing interconnection and edge fusion processing system and method | |
| DE102023111485A1 (en) | TRACKING SEGMENT CLEANUP OF TRACKED OBJECTS | |
| CN115775378A (en) | Vehicle-road cooperative target detection method based on multi-sensor fusion | |
| CN113470359A (en) | 5G-V2X-based road large-scale congestion warning method and system | |
| CN111260935B (en) | Vehicle passing method and device | |
| Zhang et al. | Smart-rain: A degradation evaluation dataset for autonomous driving in rain | |
| CN111243290B (en) | Driving behavior data acquisition and analysis method and system | |
| CN102514531A (en) | Vehicle-mounted real-time panorama monitoring and recording system | |
| CN107766833A (en) | A kind of harvester and method of monocular vision ADAS systematic samples | |
| CN203116856U (en) | System of lens automatically zooming along with vehicle speed |
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 |