CN111524356A - Intelligent highway management system based on Internet of things communication and management method thereof - Google Patents
Intelligent highway management system based on Internet of things communication and management method thereof Download PDFInfo
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- CN111524356A CN111524356A CN202010362362.0A CN202010362362A CN111524356A CN 111524356 A CN111524356 A CN 111524356A CN 202010362362 A CN202010362362 A CN 202010362362A CN 111524356 A CN111524356 A CN 111524356A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/005—General purpose rendering architectures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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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
Abstract
The invention discloses an intelligent road management system based on Internet of things communication and a management method thereof, belonging to the technical field of application of the Internet of things communication in traffic management, wherein an information acquisition module comprises an image acquisition device for acquiring scene, a wireless communication module comprises a wireless transmission module and a wireless signal terminal, the wireless transmission module transmits scene image data acquired by the image acquisition device to a system terminal through the wireless signal terminal, and the wireless signal terminal can access data, an information storage module and the system terminal module in a cloud server of the Internet of things in real time and carry out internal data labeling on the processed image. The invention can timely collect images and other information on the accident road and feed the images and other information back to the system terminal, and the system terminal feeds the images and other information back to each department terminal and the scene after three-dimensional modeling, thereby improving the efficiency of later rescue.
Description
Technical Field
The invention relates to the technical field of application of communication of the Internet of things in traffic management, in particular to an intelligent road management system based on communication of the Internet of things and a management method thereof.
Background
The intelligent traffic management system mainly completes implementation, traffic information acquisition and traffic guidance work, and the acquisition and processing of traffic information and vehicle information on roads are the core contents of the research; the acquisition of information must accomplish that the information volume is big and accurate reliable, and traditional traffic information acquisition mode such as based on speed measuring radar, microwave detector, ultrasonic detector, annular induction coil and video detect etc. all has its limitation, can not satisfy intelligent transportation system's demand well.
The construction and operation safety of the highway, which is an important component for connecting urban roads and high speed in various regions, become important in the development of traffic planning. Most of highways in western regions are constructed around mountains, weather is changeable, natural disasters easily occur to highways, such as landslide and debris flow, and damage to highway traffic is caused.
Disclosure of Invention
Therefore, the invention aims to provide an intelligent road management system based on communication of the internet of things and a management method thereof, which can timely collect images and other information on an accident road and feed the images and other information back to a system terminal, and the system terminal feeds the images and other information back to each department terminal and a site after three-dimensional modeling, so that the later rescue efficiency is improved.
The intelligent road management system based on the communication of the Internet of things comprises an information acquisition module, a wireless communication module, an information storage module and a system terminal module;
the information acquisition module comprises an image collector for collecting scene on site;
the wireless communication module comprises a wireless transmission module and a wireless signal terminal, the wireless transmission module transmits field image data acquired by the image acquisition device to the system terminal through the wireless signal terminal, and the wireless signal terminal can access data in the cloud server of the Internet of things in real time;
the information storage module is used for uploading field image data subjected to modeling processing on the system terminal to the Internet of things cloud server;
the system terminal module is used for carrying out three-dimensional modeling and rendering processing on the image data acquired on site and carrying out internal data annotation on the processed image.
Preferably, the image collector comprises an unmanned aerial vehicle, a camera installed below the unmanned aerial vehicle, a controller installed inside the unmanned aerial vehicle in an embedded mode, and a processor, wherein a Beidou positioning module connected with a Beidou satellite navigation system, a wireless transmission module in data connection with a system terminal module in a ground control station, and an air pressure altimeter used for measuring real-time road section information are arranged in the processor.
Preferably, the data acquisition time interval is 30-180 minutes.
Preferably, the system terminal module utilizes the image data information transmitted by the CPU storage and management information acquisition module, the CPU transmits the image data information to the GPU to dynamically process the image data information by the GPU, and the processed image data information is directly cached in the GPU and backed up to be uploaded to the information storage module.
Preferably, the information storage module is an internet of things cloud server provided with a system terminal module, and transmits modeling data to each department terminal through an internet of things service provided in the internet of things cloud server.
Preferably, the method comprises the following steps:
step 1: utilizing an unmanned aerial vehicle to reach a road section with natural disasters;
step 2: the method comprises the steps that an image collector is used for carrying out omnibearing data collection on the site, and a wireless transmission module is used for transmitting all collected data to a system terminal module in a ground control station;
and step 3: the system terminal module carries out three-dimensional modeling on the image data acquired on site and carries out rendering processing to form a three-dimensional colored modeling structure of an accident road section, and marks the processed structural image data;
and 4, step 4: and directly caching the modeled structural image data in a GPU, backing up and uploading the structural image data to an information storage module, and transmitting the processed image data to each department terminal by the information storage module in real time.
Preferably, the data acquisition in step 2 includes performing surrounding image acquisition on the site by using a camera, locating a specific geographic position of the site by using a Beidou positioning module, and recording the barometric pressure and altitude of the road section by using a barometric altimeter.
Preferably, the three-dimensional modeling and rendering processing in step 3 includes the following steps:
step 3.1: preliminarily creating a polygon for rendering the accident road section;
step 3.2: the method comprises the steps that images transmitted back by a plurality of image collectors are used for conducting superposition of multilayer two-dimensional and three-dimensional seamless Perlin noise, Worley noise and curl noise to conduct low-resolution volume rendering, and the low-resolution volume rendering is used for forming a modeling structure of a three-dimensional volume;
step 3.3: taking the modeling structure of the three-dimensional body formed in the step 3.2 as a base map, writing different shader programs for area structures in different base maps, and performing shading rendering processing;
step 3.4: and performing anti-aliasing processing by using the temporal anti-aliasing, and finally rendering the processed image to a polygon to form a high-resolution image.
Preferably, the shader program is a terrain rendering shader program.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention utilizes the information acquisition module to acquire the image information and other geographic information of the accident road in real time in different time intervals, so that the working personnel can conveniently master the information of the field change in real time, and the rescue management can be conveniently carried out on the commanding accident road on the field;
(2) the environment of the incident road site can be restored and the site information data can be marked by utilizing three-dimensional modeling and rendering processing, so that the incident road site is more intuitive and easier to observe compared with the traditional video or image;
(3) the coloring of the terrain information after modeling is realized by using a coloring device, coloring marks of different colors are carried out according to the disaster-suffered condition of the road section, and the highlight is carried out on the road section with serious disaster or the road section with dense vehicle distribution and more disaster-suffered people, so that rescue workers are warned to rescue the road section preferentially, the real-time editing and updating of the super-large-scale terrain can be met, and the method is suitable for the road section with multiple natural disasters.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a block diagram illustrating an intelligent road management system and a management method thereof based on internet of things communication according to the present invention;
fig. 2 is a flowchart of an implementation of the intelligent road management system based on communication of internet of things and the management method thereof according to the present invention.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.
Referring to fig. 1, an intelligent road management system based on communication of internet of things includes an information acquisition module, a wireless communication module, an information storage module, and a system terminal module;
the information acquisition module comprises an image acquisition device for acquiring scene on site;
the wireless communication module comprises an RF24L01 remote wireless transmission module and a wireless signal terminal, the wireless transmission module transmits field image data acquired by the image acquisition device to the system terminal through the wireless signal terminal, and the wireless signal terminal can access data in the Internet of things cloud server in real time;
the information storage module is used for uploading field image data subjected to modeling processing on the system terminal to the Internet of things cloud server;
the system terminal module is used for carrying out three-dimensional modeling on the image data acquired on site, carrying out rendering processing and carrying out internal data annotation on the processed image.
The image collector comprises an unmanned aerial vehicle, a CCD camera arranged below the unmanned aerial vehicle, a controller arranged in the unmanned aerial vehicle in an embedded mode and an ARMCortex-M series processor, wherein a Beidou positioning module connected with a Beidou satellite navigation system, a wireless transmission module in data connection with a system terminal module in a ground control station and an air pressure altimeter used for measuring real-time road section information are arranged in the processor.
The data acquisition time interval is 30-180 minutes, the acquired data are transmitted to the system terminal module by repeating the steps, and the system terminal module carries out modeling and color rendering, so that scene rescuers and rear commanders can observe the change data of the accident scene in real time, and the rescue or reconstruction scheme can be effectively changed according to the real-time data.
The system terminal module comprises a CPU and a GPU, the CPU is used for storing and managing image data information transmitted by the information acquisition module, the CPU transmits the image data information to the GPU and dynamically processes the image data information through the GPU, and the processed image data information is directly cached in the GPU and is backed up and uploaded to the information storage module.
The information storage module is an internet of things cloud server provided with a system terminal module, and transmits modeling data to each department terminal through internet of things services provided in the internet of things cloud server.
Referring to fig. 2, the steps are included as follows:
step 1: utilizing an unmanned aerial vehicle to reach a road section with natural disasters;
step 2: the method comprises the steps that an image collector is used for carrying out omnibearing data collection on the site, and a wireless transmission module is used for transmitting all collected data to a system terminal module in a ground control station;
and step 3: the system terminal module carries out three-dimensional modeling on the image data acquired on site and carries out rendering processing to form a three-dimensional colored modeling structure of an accident road section, and marks the processed structural image data;
and 4, step 4: and directly caching the modeled structural image data in a GPU, backing up and uploading the structural image data to an information storage module, and transmitting the processed image data to each department terminal by the information storage module in real time.
The data acquisition in the step 2 comprises the steps of utilizing a camera to perform surrounding image acquisition on the site, positioning the specific geographic position of the site through a Beidou positioning module, and recording the air pressure and the altitude of a road section through an air pressure altimeter;
the image acquisition data acquisition function is that the rendering modeling in the step 3 is used for supporting the image, the Beidou positioning module and the barometric altimeter acquire three-dimensional coordinates of longitude, latitude and altitude of an incident road section, so that the three-dimensional modeling structure formed in the step 3 is conveniently subjected to spatial marking, similarly, the barometric altimeter is used for recording the air pressure of the road section and can also be marked in the three-dimensional image data, the expansion of rescue work is often influenced by the change of the air pressure in a plateau environment, the three-dimensional image data of the modeled incident road section is more visualized by the data marking, and workers on site can observe a plurality of items of data of the incident road and command rescue by combining the real-time data of the incident road section.
The three-dimensional modeling and rendering processing in the step 3 comprises the following steps:
step 3.1: preliminarily creating a polygon for rendering the accident road section;
step 3.2: the method comprises the steps that images transmitted back by a plurality of image collectors are used for conducting superposition of multilayer two-dimensional and three-dimensional seamless Perlin noise, Worley noise and curl noise in a GPU to conduct low-resolution volume rendering, and the low-resolution volume rendering is used for forming a modeling structure of a three-dimensional volume;
road terrain resources are dynamically processed through the GPU, and the processed resources are directly cached in the GPU to be used for subsequent operations, so that the parallel computing capability of the GPU can be fully utilized, the execution efficiency of a computing-intensive resource processing algorithm is greatly improved, reliable performance guarantee is provided for large-scale road terrain rendering, meanwhile, delay caused by data transmission is reduced through a GPU video memory caching technology, and the rendering performance is further improved.
Step 3.3: taking the modeling structure of the three-dimensional body formed in the step 3.2 as a base map, writing different shader programs for area structures in different base maps, and performing shading rendering processing;
step 3.4: and performing anti-aliasing processing by using the temporal anti-aliasing, and finally rendering the processed image to a polygon to form a high-resolution image.
The shader program is a shader program for terrain rendering, a shader is written for the rendering of the road terrain, and the shader mainly realizes an illumination algorithm for terrain shading. Meanwhile, the method for mapping the logical coordinates (x, y, l) to the resource cache position is realized, so that the resources in the cache can be obtained. Because the processing of the resources is realized in the shader, the real-time editing and updating of the resources become simple and efficient, and the real-time editing and updating of ultra-large-scale terrains such as roads can be met.
Example 1:
when debris flow occurs on a road, inputting an area to be shot by an upper computer of a ground control station, calculating the flight path of an unmanned aerial vehicle by the upper computer, leading the flight path into a flight controller through a serial port, receiving navigation information of a Beidou navigation system by a Beidou positioning module on the unmanned aerial vehicle, correcting the flight path of the unmanned aerial vehicle in real time, operating by an operator to reach the upper space of a target to be inspected, hovering the unmanned aerial vehicle above the target, tracking and shooting or recording the target area by a high-definition camera on the unmanned aerial vehicle, positioning the specific geographic position by the Beidou positioning module by the unmanned aerial vehicle, and recording the air pressure and the altitude of a road section by an air pressure altimeter, transmitting the air pressure and the altitude to a system terminal module in the ground control station through a 5.8GHz wireless transmission module, and transmitting data of images which change in real time every 30 minutes by the unmanned aerial vehicle to the system terminal module in the ground control station, the system terminal module carries out three-dimensional modeling on image data acquired on site and carries out rendering processing to form a three-dimensional colored modeling structure of an accident road section, the processed structure image data are labeled, the modeled structure image data are directly cached in a GPU and are backed up and uploaded to an Internet of things cloud server, the Internet of things cloud server transmits the processed image data to each department terminal in real time, workers in the department can carry out expansion analysis on the modeled site structure according to the real-time updated modeling data structure, the workers in the site can access data in the Internet of things cloud server in real time through a wireless signal terminal, and rescue management is carried out on the accident road commanded on site in time.
The invention utilizes the information acquisition module to acquire the image information and other geographic information of the incident road in real time in different time intervals, facilitates the working personnel to master the information of the field change in real time so as to command the incident road to rescue and manage the scene, utilizes the three-dimensional modeling and rendering processing to restore the scene environment of the incident road and label the scene information data, is more visual and easy to observe compared with the traditional camera device, not only enables the rear system terminal and the working personnel of the scene to visually, quickly and detailedly know the real-time information of the incident road section through the wireless signal terminal after the three-dimensional modeling and rendering processing is carried out on the scene road section, utilizes the coloring device to realize the coloring of the terrain information after modeling, carries out the coloring marking of different colors according to the disaster situation of the road section, and highlights the road section with serious disaster or the dense vehicle distribution, The highway section with more disaster-stricken people can be used for warning rescue workers to rescue the highway section preferentially, real-time editing and updating of super-large-scale terrain can be met, and the highway section is suitable for highway sections with multiple natural disasters.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (9)
1. The utility model provides an wisdom highway management system based on thing networking communication which characterized in that: the system comprises an information acquisition module, a wireless communication module, an information storage module and a system terminal module;
the information acquisition module comprises an image collector for collecting scene on site;
the wireless communication module comprises a wireless transmission module and a wireless signal terminal, the wireless transmission module transmits field image data acquired by the image acquisition device to the system terminal through the wireless signal terminal, and the wireless signal terminal can access data in the cloud server of the Internet of things in real time;
the information storage module is used for uploading field image data subjected to modeling processing of the system terminal to the cloud server of the Internet of things;
the system terminal module is used for carrying out three-dimensional modeling and rendering processing on the image data acquired on site and carrying out internal data annotation on the processed image.
2. The intelligent road management system based on internet of things communication of claim 1, wherein: the image collector comprises an unmanned aerial vehicle, a camera arranged below the unmanned aerial vehicle, a controller arranged in the unmanned aerial vehicle in an embedded mode and a processor, wherein a Beidou positioning module connected with a Beidou satellite navigation system, a wireless transmission module in data connection with a system terminal module in a ground control station and an air pressure altimeter used for measuring real-time road section information are arranged in the processor.
3. The intelligent road management system based on internet of things communication of claim 1, wherein: the system terminal module utilizes the image data information transmitted by the CPU storage and management information acquisition module, the CPU transmits the image data information to the GPU, the image data information is dynamically processed by the GPU, and the processed image data information is directly cached in the GPU and is backed up and uploaded to the information storage module.
4. The intelligent road management system based on internet of things communication of claim 1, wherein: the information storage module is an internet of things cloud server and transmits modeling data to each department terminal through internet of things services provided in the internet of things cloud server.
5. The management method of the intelligent road management system based on communication of internet of things according to any one of claims 1 to 4, wherein: the method comprises the following steps:
step 1: utilizing an unmanned aerial vehicle to reach a road section with natural disasters;
step 2: the method comprises the steps that an image collector is used for carrying out omnibearing data collection on the site, and a wireless transmission module is used for transmitting all collected data to a system terminal module in a ground control station;
and step 3: the system terminal module carries out three-dimensional modeling on the image data acquired on site and carries out rendering processing to form a three-dimensional colored modeling structure of an accident road section, and marks the processed structural image data;
and 4, step 4: and directly caching the modeled structural image data in a GPU, backing up and uploading the structural image data to an information storage module, and transmitting the processed image data to each department terminal by the information storage module in real time.
6. The intelligent road management method based on internet of things communication of claim 5, wherein: the data acquisition in the step 2 comprises the steps of utilizing a camera to acquire surrounding images of a site, positioning the specific geographic position of the site through a Beidou positioning module, and recording the air pressure and the altitude of a road section through an air pressure altimeter.
7. The intelligent road management method based on internet of things communication of claim 6, wherein: the data acquisition time interval is 30-180 minutes.
8. The intelligent road management method based on internet of things communication of claim 5, wherein: the three-dimensional modeling and rendering processing in the step 3 comprises the following steps:
step 3.1: preliminarily creating a polygon for rendering the accident road section;
step 3.2: the method comprises the steps that images transmitted back by a plurality of image collectors are used for conducting superposition of multilayer two-dimensional and three-dimensional seamless Perlin noise, Worley noise and curl noise to conduct low-resolution volume rendering, and the low-resolution volume rendering is used for forming a modeling structure of a three-dimensional volume;
step 3.3: taking the modeling structure of the three-dimensional body formed in the step 3.2 as a base map, writing different shader programs for area structures in different base maps, and performing shading rendering processing;
step 3.4: and performing anti-aliasing processing by using the temporal anti-aliasing, and finally rendering the processed image to a polygon to form a high-resolution image.
9. The intelligent road management method based on internet of things communication of claim 8, wherein: the shader program is a shader program for terrain rendering.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011072467A1 (en) * | 2009-12-18 | 2011-06-23 | 湖南城市学院 | Method and system for monitoring of wetlands resource and ecological environment |
| CN105592305A (en) * | 2015-12-23 | 2016-05-18 | 重庆邮电大学 | Three-dimensional video emergency communication system based on multi-rotor unmanned plane |
| CN206757406U (en) * | 2016-10-27 | 2017-12-15 | 昆明理工大学 | The four rotor wing unmanned aerial vehicle mountain highway mud-rock flow cruising inspection systems based on Big Dipper positioning |
| CN109215168A (en) * | 2018-09-27 | 2019-01-15 | 南京感动科技有限公司 | A kind of highway accident method for tracing based on cloud computing |
| CN109767488A (en) * | 2019-01-23 | 2019-05-17 | 广东康云科技有限公司 | Three-dimensional modeling method and system based on artificial intelligence |
-
2020
- 2020-04-30 CN CN202010362362.0A patent/CN111524356A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011072467A1 (en) * | 2009-12-18 | 2011-06-23 | 湖南城市学院 | Method and system for monitoring of wetlands resource and ecological environment |
| CN105592305A (en) * | 2015-12-23 | 2016-05-18 | 重庆邮电大学 | Three-dimensional video emergency communication system based on multi-rotor unmanned plane |
| CN206757406U (en) * | 2016-10-27 | 2017-12-15 | 昆明理工大学 | The four rotor wing unmanned aerial vehicle mountain highway mud-rock flow cruising inspection systems based on Big Dipper positioning |
| CN109215168A (en) * | 2018-09-27 | 2019-01-15 | 南京感动科技有限公司 | A kind of highway accident method for tracing based on cloud computing |
| CN109767488A (en) * | 2019-01-23 | 2019-05-17 | 广东康云科技有限公司 | Three-dimensional modeling method and system based on artificial intelligence |
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Application publication date: 20200811 |