CN113053111A - Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things - Google Patents
Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things Download PDFInfo
- Publication number
- CN113053111A CN113053111A CN202110258017.7A CN202110258017A CN113053111A CN 113053111 A CN113053111 A CN 113053111A CN 202110258017 A CN202110258017 A CN 202110258017A CN 113053111 A CN113053111 A CN 113053111A
- Authority
- CN
- China
- Prior art keywords
- road
- drainage
- downlink
- road surface
- uplink
- 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.)
- Granted
Links
Images
Classifications
-
- 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
-
- 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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
-
- 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
- G08G1/048—Detecting movement of traffic to be counted or controlled with provision for compensation of environmental or other condition, e.g. snow, vehicle stopped at detector
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
- Y02A30/60—Planning or developing urban green infrastructure
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses an urban traffic municipal road safety online monitoring cloud platform based on machine vision and Internet of things, which comprises an urban interchange road dividing module, a downlink road basic parameter detection module, a downlink road surface evenness detection module, a road drainage parameter detection module, an uplink road leakage detection module, a modeling analysis module, a management cloud platform and a background display terminal, wherein the urban interchange downlink road is subjected to basic parameter detection, road surface evenness detection and drainage parameter detection, and the uplink road is subjected to drainage parameter and leakage detection simultaneously, so that the comprehensive ponding danger coefficient corresponding to the urban interchange downlink road is counted by combining the detection results, the monitoring range of the ponding hidden danger is expanded, the defects of the existing urban interchange downlink road ponding hidden danger monitoring mode are overcome, the reliability of the monitoring results is improved, and the probability of the occurrence of ponding conditions on the downlink road in rainy days is reduced, the running safety of the down road in rainy days is guaranteed.
Description
Technical Field
The invention belongs to the technical field of urban road operation safety monitoring, relates to an urban interchange road operation safety monitoring technology, and particularly relates to an urban traffic and municipal road safety online monitoring cloud platform based on machine vision and the Internet of things.
Background
With the enlargement of urban scale, urban ground traffic is increasingly busy, and urban overpasses gradually become an important way for relieving increasingly severe traffic pressure in cities by virtue of the characteristics of simple traffic organization form, relatively low construction cost, small influence on urban external landscapes and strong practicability. The urban interchange separates traffic flows by utilizing the spatial distribution characteristics of interchange roads, so that the traffic pressure is effectively relieved, but the urban interchange has the spatial distribution characteristics of the roads, so that the descending roads of the urban interchange have terrain height difference of the roads, the descending roads are often local low points of the catchment areas in rainy seasons, rainwater runoff converges to the lower points, and no other roads exit, once the descending roads have water accumulation hidden troubles, the danger of water accumulation on the roads is easily caused, the normal operation of the roads is influenced, traffic accidents are more caused in serious cases, and the life safety of pedestrians is damaged, so that the water accumulation hidden troubles need to be monitored on the descending roads of the urban interchange in order to ensure the operation safety of the descending roads in rainy days.
However, the existing monitoring mode for the potential water accumulation hazard of the urban overpass downlink road is only to detect the terrain height of the downlink road, the road surface evenness, the water discharge amount of a road surface water discharge facility and the like, and the influence of the water accumulation on the downlink road caused by the water discharge condition and the seepage condition of the uplink road of the urban overpass is not considered, and when the uplink road has the conditions of poor water discharge and crack seepage, the water which cannot be discharged and the seepage water inevitably cause the potential water accumulation hazard on the downlink road. Therefore, the method is not in accordance with the actual situation when only the down road is subjected to the water accumulation hidden danger monitoring, and the monitoring has the defects of one-sidedness and singleness, so that the reliability of the monitoring result is poor, and the reliability monitoring requirement on the urban interchange down road water accumulation hidden danger monitoring is difficult to meet.
Disclosure of Invention
In order to solve the problems mentioned in the background art, the invention provides the following technical scheme:
an urban traffic and municipal road safety online monitoring cloud platform based on machine vision and the Internet of things comprises an urban interchange road dividing module, a downlink road basic parameter detection module, a downlink road surface flatness detection module, a road drainage parameter detection module, an uplink road leakage detection module, a modeling analysis module, a management cloud platform and a background display terminal;
the urban interchange road division module is used for dividing the urban interchange into an uplink road and a downlink road according to the spatial position relationship of the roads;
the basic parameter detection module of the downlink is used for detecting basic parameters of the downlink divided by the urban interchange, the basic parameters comprise the width of the downlink, the height from the uplink and the terrain height, and the basic parameters of the detected downlink form a basic parameter set P (P) of the downlinkw,ph,pd)，pw,ph,pdThe basic parameter detection module of the downlink road sends the basic parameter set of the downlink road to the modeling analysis module;
the downgoing road surface flatness detection module is used for carrying out flatness detection on the surface of the downgoing road and sending the detected downgoing road surface flatness to the modeling analysis module, and the specific detection process comprises the following steps:
s1, uniformly distributing a plurality of detection points on the road surface of the descending road, numbering the distributed detection points according to a preset sequence, and marking the detection points as 1,2.. i.. n in sequence;
s2, respectively detecting the height from each detection point to the downgoing road subgrade, wherein the obtained height from each detection point to the downgoing road subgrade forms a detection point-to-subgrade height set H (H1, H2, h.a., hi, hn), and hi is expressed as the height from the ith detection point to the downgoing road subgrade;
s3, comparing the height set of the detection points from the roadbed with the standard height of the downgoing road pavement from the roadbed to obtain a comparison set delta H (delta H1, delta H2, delta hi, delta hn) of the height of the detection points from the roadbed, and counting the flatness of the downgoing road pavement according to the comparison set of the height of the detection points from the roadbed;
the parameter database is used for storing road width ponding danger coefficients corresponding to various road widths, storing height ponding danger coefficients corresponding to various height values between an uplink road and a downlink road, storing terrain ponding danger coefficients corresponding to various terrain heights of the roads, storing road surface flatness ponding danger coefficients corresponding to various road surface flatness, and storing leakage danger coefficients corresponding to various road crack total areas;
the road drainage parameter detection module is used for counting the number of drainage facilities on the uplink road surface and the downlink road surface, numbering the counted drainage facilities on the uplink road surface and respectively marking the counted drainage facilities as 1,2.. a.. z, numbering the counted drainage facilities on the downlink road surface and respectively marking the counted drainage facilities as 1,2.. b.. y, so as to respectively count the drainage quantity of the drainage facilities on the uplink road surface and the drainage facilities on the downlink road surface, and the obtained drainage quantity corresponding to the drainage facilities on the uplink road surface forms an uplink road drainage quantity set QOn the upper part(QOn the upper part1,QOn the upper part2,...,QOn the upper parta,...,QOn the upper partz) the obtained drainage amounts corresponding to the drainage facilities on the road surface of the downlink form a downlink drainage amount set QLower part(QLower part1,QLower part2,...,QLower partb,...,QLower party), thereby respectively counting the average drainage quantity of the drainage facilities of the uplink and the average drainage quantity of the drainage facilities of the downlink according to the drainage quantity set of the uplink and the drainage quantity set of the downlink, and simultaneously respectively carrying out the average distance counting between two adjacent drainage facilities on each drainage facility existing on the road surface of the uplink and each drainage facility existing on the road surface of the downlink, wherein the road drainage parameter detection module sends the counted average drainage quantity of the drainage facility corresponding to the road surface of the uplink, the average distance between two adjacent drainage facilities, the average drainage quantity of the drainage facility corresponding to the road surface of the downlink and the average distance between two adjacent drainage facilities to the modeling analysis module;
the ascending road leakage detection module is used for carrying out image acquisition on an ascending road bottom area, comparing the acquired ascending road bottom area image with a normal road bottom area image to obtain the position of a crack of the ascending road bottom area, counting the number of cracks existing in the ascending road bottom area at the moment, numbering the counted cracks, sequentially marking the number of the counted cracks as 1,2.. j.. m, focusing the area of the crack on the ascending road bottom area image respectively, extracting the contour line of each crack to obtain the area corresponding to each crack, and forming an ascending road bottom crack area set S (S1, S2...., sj.,. sm.) and sending the ascending road bottom crack area set to the modeling analysis module by the ascending road leakage detection module;
the modeling analysis module receives the basic parameter set of the downlink road sent by the basic parameter detection module of the road, compares the width of the downlink road in the basic parameter set of the downlink road with road width ponding danger coefficients corresponding to various road widths in the parameter database, screens out the road width ponding danger coefficient corresponding to the downlink road, compares the height of the downlink road in the basic parameter set of the downlink road from the uplink road with the height ponding danger coefficients corresponding to various height values between the uplink road and the downlink road in the parameter database, screens out the height ponding danger coefficient corresponding to the downlink road, compares the terrain height of the downlink road in the basic parameter set of the downlink road with the terrain ponding danger coefficients corresponding to various terrain heights of the road in the parameter database, screens out the terrain ponding danger coefficient corresponding to the downlink road, the modeling analysis module is used for calculating a basic parameter ponding risk coefficient corresponding to the downlink road by combining the road width ponding risk coefficient, the height ponding risk coefficient and the terrain ponding risk coefficient corresponding to the downlink road, and sending the basic parameter ponding risk coefficient to the management cloud platform;
the modeling analysis module receives the flatness of the downlink road surface sent by the downlink road surface flatness detection module, compares the received flatness of the downlink road surface with road surface flatness water accumulation danger coefficients corresponding to various road surface flatness in the parameter database to obtain the road surface flatness water accumulation danger coefficients corresponding to the downlink road surface, and sends the road surface flatness water accumulation danger coefficients to the management cloud platform;
the modeling analysis module receives the average drainage quantity of the drainage facility corresponding to the uplink road surface and the average distance between two adjacent drainage facilities, and the average drainage quantity of the drainage facility corresponding to the downlink road surface and the average distance between two adjacent drainage facilities, which are sent by the road drainage parameter detection module, so that the drainage risk index of the uplink road surface to the downlink road is counted according to the average drainage quantity of the drainage facility corresponding to the uplink road surface and the average distance between two adjacent drainage facilities, the total drainage risk coefficient of the downlink road surface is counted according to the drainage risk index of the uplink road surface to the downlink road, the average drainage quantity of the drainage facility corresponding to the downlink road surface and the average distance between two adjacent drainage facilities, and the total drainage risk coefficient is sent to the management cloud platform;
the modeling analysis module receives the uplink road bottom crack area set sent by the uplink road leakage detection module, sums the areas of all cracks according to the uplink road bottom crack area set to obtain the total crack area corresponding to the bottom of the uplink road, compares the total crack area with leakage danger coefficients corresponding to the total crack areas of all roads in the parameter database to obtain the leakage danger coefficients of the uplink road to the downlink road, and sends the leakage danger coefficients to the management cloud platform;
the management cloud platform receives the basic parameter accumulated water danger coefficient, the road surface flatness accumulated water danger coefficient, the total drainage danger coefficient and the leakage danger coefficient of the descending road of the urban interchange, which are sent by the modeling analysis module and correspond to the descending road, counts the comprehensive accumulated water danger coefficient corresponding to the descending road of the urban interchange, and sends the comprehensive accumulated water danger coefficient to the background display terminal;
and the background display terminal receives the comprehensive ponding danger coefficient corresponding to the urban interchange downlink road sent by the management cloud platform and performs background display.
In an implementation manner, the specific layout method for uniformly laying a plurality of detection points on the road surface of the downlink road comprises the following steps:
t1, acquiring the length and width of the road surface of the downlink;
t2, evenly dividing the length and the width of the road surface of the descending road respectively to obtain equal division points of the length and the width, and evenly dividing the road surface of the descending road into sub areas of each road surface;
and T3, respectively arranging a single detection point at the central position of each divided pavement sub-area, thereby obtaining a plurality of arranged detection points.
In an implementation manner, the calculation formula of the flatness of the downlink road surface is
h0Expressed as the standard height of the road surface of the downgoing road from the road bed.
In one implementation, the calculation formula of the average water discharge of the ascending road drainage facility is
Expressed as the average displacement of the upstream drainage facility and the average displacement of the downstream drainage facility as
Expressed as the average displacement of the downgoing road drainage facility.
In one implementation, the average distance between two adjacent drainage facilities is counted for each drainage facility on the ascending road surface and each drainage facility on the descending road surface, and the specific statistical method is as follows:
g1, making statistics of the distance between two adjacent drainage facilities for each drainage facility on the surface of the ascending road, wherein the obtained distance between two adjacent drainage facilities on the surface of the ascending road forms an interval set X of the adjacent drainage facilities on the surface of the ascending roadOn the upper part[xOn the upper part1,xOn the upper part2,...,xOn the upper parta,...,xOn the upper part(z-1)],xOn the upper parta represents the distance between the a-th drainage facility and the a + 1-th drainage facility on the pavement of the ascending road;
g2 statistics of the flatness between two adjacent drainage facilities on the road surface of the ascending road according to the set of the distances between the adjacent drainage facilities on the road surface of the ascending roadAverage distance, which is calculated by the formula
G3 calculating the distance between two adjacent drainage facilities for each drainage facility on the down road surface, wherein the obtained distance between two adjacent drainage facilities on the down road surface forms a set X of the distance between two adjacent drainage facilities on the down road surfaceLower part[xLower part1,xLower part2,...,xLower partb,...,xLower part(y-1)],xLower partb represents the distance between the b-th drainage facility and the b + 1-th drainage facility on the pavement of the downlink road;
g4 calculating the average distance between two adjacent drainage facilities on the road surface of the descending road according to the distance set of the adjacent drainage facilities on the road surface of the descending road, wherein the calculation formula is
In an implementation mode, the calculation formula of the basic parameter ponding danger coefficient corresponding to the downlink is
Alpha, beta and epsilon are respectively expressed as road width ponding danger coefficient, height ponding danger coefficient and terrain ponding danger coefficient corresponding to the downlink road.
In one implementation, the calculation formula of the drainage risk influence index of the ascending road surface to the descending road surface is
Sigma is expressed as the drainage danger influence index of an ascending road surface to a descending road surface, and the total drainage danger coefficient of the descending road surface is calculated by the formula
In a realizable manner, the comprehensive ponding danger system corresponding to the descending road of the urban interchangeThe calculation formula of the number is
The comprehensive accumulated water danger coefficient corresponding to the descending road of the urban interchange is represented, xi, mu, psi and lambda are respectively represented as a basic parameter accumulated water danger coefficient, a road surface flatness accumulated water danger coefficient, a total drainage danger coefficient and a leakage danger coefficient of the descending road corresponding to the descending road, k1, k2, k3 and k4 are respectively represented as weight influence coefficients corresponding to the basic parameter, the road surface flatness, the drainage and the leakage, and k1+ k2+ k3+ k4 is 1.
The invention has the following beneficial effects:
(1) the invention carries out basic parameter detection, road surface evenness detection and drainage parameter detection on the descending road of the urban interchange, and simultaneously carries out drainage parameter detection and leakage detection on the ascending road, thereby counting the basic parameter water accumulation danger coefficient, the road surface evenness water accumulation danger coefficient, the total drainage danger coefficient and the leakage danger coefficient of the ascending road to the descending road corresponding to the descending road of the urban interchange according to the detection result, further integrating the comprehensive water accumulation danger coefficient corresponding to the descending road of the urban interchange, realizing the comprehensive monitoring on the water accumulation hidden danger of the descending road of the urban interchange, expanding the monitoring range of the water accumulation hidden danger, making up the one-sidedness and simplification defects existing in the monitoring mode of the water accumulation hidden danger of the descending road of the urban interchange, improving the reliability of the monitoring result, greatly reducing the probability of the water accumulation condition of the descending road in rainy days, and furthermore, the occurrence rate of traffic jam and traffic accidents caused by water accumulation of the downlink road is reduced, and the running safety of the downlink road in rainy days is guaranteed.
(2) In the process of detecting the road surface evenness of the downgoing road, the detection points are distributed on the downgoing road surface, the height of each detection point from the downgoing road subgrade is detected, and then the road surface evenness is obtained.
(3) When the drainage detection of the urban interchange up-road and down-road is carried out, the invention not only detects the average drainage quantity of the drainage facilities of the up-road and the down-road, but also detects the average distance between adjacent drainage facilities, thereby avoiding the influence on the accuracy of the later statistics of the drainage danger index of the up-road to the down-road caused by the detection of the drainage quantity of the drainage facilities.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a schematic diagram of the module connection 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.
Referring to fig. 1, an urban traffic town road safety on-line monitoring cloud platform based on machine vision and internet of things comprises an urban interchange road dividing module, a downlink road basic parameter detection module, a downlink road surface evenness detection module, a road drainage parameter detection module, an uplink road leakage detection module, a modeling analysis module, a management cloud platform and a background display terminal, wherein the urban interchange road dividing module is respectively connected with the downlink road basic parameter detection module, the downlink road surface evenness detection module, the road drainage parameter detection module and the uplink road leakage detection module, the downlink road basic parameter detection module, the downlink road surface evenness detection module, the road drainage parameter detection module and the uplink road leakage detection module are all connected with the modeling analysis module, and the modeling analysis module is connected with the management cloud platform, the management cloud platform is connected with the background display terminal.
The urban interchange road division module is used for dividing the urban interchange into an uplink road and a downlink road according to the spatial position relationship of the roads.
The descending road basic parameter detection module is used for detecting basic parameters of a descending road divided by the urban interchange, wherein the basic parameters comprise the width of the descending road, the height from the ascending road and the terrain height, and the basic parameters of the descending road obtained through detection form a descending road basic parameter set P (P)w,ph,pd)，pw,ph,pdThe basic parameter detection module of the downlink road sends the basic parameter set of the downlink road to the modeling analysis module.
The downlink road surface flatness detection module is used for detecting the flatness of the downlink road surface and sending the detected downlink road surface flatness to the modeling analysis module, and the specific detection process comprises the following steps:
s1, uniformly arranging a plurality of detection points on the road surface of the downlink road, wherein the specific arrangement method comprises the following steps:
t1, acquiring the length and width of the road surface of the downlink;
t2, evenly dividing the length and the width of the road surface of the descending road respectively to obtain equal division points of the length and the width, and evenly dividing the road surface of the descending road into sub areas of each road surface;
t3, respectively laying a single detection point at the center position of each divided pavement sub-area to obtain a plurality of laid detection points, numbering the laid detection points according to a preset sequence, and marking the detection points as 1,2.. i.. n in sequence;
s2, respectively detecting the height from each detection point to the downgoing road subgrade, wherein the obtained height from each detection point to the downgoing road subgrade forms a detection point-to-subgrade height set H (H1, H2, h.a., hi, hn), and hi is expressed as the height from the ith detection point to the downgoing road subgrade;
s3, comparing the height set of the detection points from the roadbed with the standard height of the downgoing road pavement from the roadbed to obtain a comparison set delta H (delta H1, delta H2, delta hi, delta H, delta hn) of the height of the detection points from the roadbed, and counting the flatness of the downgoing road pavement according to the comparison set of the height of the detection points from the roadbed
h0Expressed as the standard height of the road surface of the downgoing road from the road bed.
In the process of detecting the road surface evenness of the downgoing road, the detection points are arranged on the downgoing road surface, the height of each detection point from the downgoing road subgrade is detected, and then the road surface evenness is obtained.
The parameter database is used for storing road width ponding danger coefficients corresponding to various road widths, storing height ponding danger coefficients corresponding to various height values between an uplink road and a downlink road, storing terrain ponding danger coefficients corresponding to various terrain heights of the roads, storing road surface flatness ponding danger coefficients corresponding to various road surface flatness, and storing leakage danger coefficients corresponding to various road crack total areas.
The road drainage parameter detection module is used for counting the number of drainage facilities on the uplink road surface and the downlink road surface, wherein the drainage facilities comprise drainage pipes, drainage ditches, drainage channels and the like, numbering the counted drainage facilities on the uplink road surface and marking the numbered drainage facilities as 1,2Facilities are numbered and respectively marked as 1,2.. b.. y, so that the water discharge amount statistics is respectively carried out on each water discharge facility existing on the uplink road surface and each water discharge facility existing on the downlink road surface, and the obtained water discharge amount corresponding to each water discharge facility on the uplink road surface forms an uplink road water discharge amount set QOn the upper part(QOn the upper part1,QOn the upper part2,...,QOn the upper parta,...,QOn the upper partz) the obtained drainage amounts corresponding to the drainage facilities on the road surface of the downlink form a downlink drainage amount set QLower part(QLower part1,QLower part2,...,QLower partb,...,QLower party) to thereby count the average displacement of the up-link drainage facility from the up-link drainage volume set and the down-link drainage volume set, respectively
Expressed as the average displacement of the drainage facility of the ascending road and the average displacement of the drainage facility of the descending road
The average water discharge quantity of the downstream road water drainage facilities is expressed, and meanwhile, the average distance between two adjacent water drainage facilities is counted for each water drainage facility existing on the upstream road surface and each water drainage facility existing on the downstream road surface respectively, and the specific statistical method is as follows:
g1, making statistics of the distance between two adjacent drainage facilities for each drainage facility on the surface of the ascending road, wherein the obtained distance between two adjacent drainage facilities on the surface of the ascending road forms an interval set X of the adjacent drainage facilities on the surface of the ascending roadOn the upper part[xOn the upper part1,xOn the upper part2,...,xOn the upper parta,...,xOn the upper part(z-1)],xOn the upper parta represents the distance between the a-th drainage facility and the a + 1-th drainage facility on the pavement of the ascending road;
g2 calculating the average distance between two adjacent drainage facilities on the road surface according to the distance set of the adjacent drainage facilities on the road surface, wherein the calculation formula is
G3 calculating the distance between two adjacent drainage facilities for each drainage facility on the down road surface, wherein the obtained distance between two adjacent drainage facilities on the down road surface forms a set X of the distance between two adjacent drainage facilities on the down road surfaceLower part[xLower part1,xLower part2,...,xLower partb,...,xLower part(y-1)],xLower partb represents the distance between the b-th drainage facility and the b + 1-th drainage facility on the pavement of the downlink road;
g4 calculating the average distance between two adjacent drainage facilities on the road surface of the descending road according to the distance set of the adjacent drainage facilities on the road surface of the descending road, wherein the calculation formula is
The road drainage parameter detection module sends the calculated average drainage quantity of the drainage facility corresponding to the uplink road surface, the calculated average distance between two adjacent drainage facilities, the calculated average drainage quantity of the drainage facility corresponding to the downlink road surface and the calculated average distance between two adjacent drainage facilities to the modeling analysis module.
When the drainage detection of the urban interchange uplink and downlink is carried out, the average drainage quantity of the drainage facilities of the uplink and downlink and the average distance between adjacent drainage facilities are detected, and the influence on the accuracy of counting the drainage danger index of the uplink to the downlink by the later detection due to the detection of the drainage quantity of the drainage facilities is avoided.
The up road leakage detection module is used for collecting images of the bottom area of the up road and comparing the collected images of the bottom area of the up road with the images of the bottom area of the normal road, wherein the normal road bottom area image is the road bottom area image without cracks, so as to obtain the positions of the cracks in the uplink road bottom area, at the moment, the number of the cracks in the uplink road bottom area is counted, simultaneously numbering the counted cracks, sequentially marking the cracks as 1,2.. j.. m, then respectively focusing on the region where each crack is located on the image of the bottom region of the ascending road, thereby extracting the contour line of each crack, and therefore, the areas corresponding to all cracks are obtained, an ascending road bottom crack area set S is formed (S1, S2.., sj.., sm), and the ascending road leakage detection module sends the ascending road bottom crack area set to the modeling analysis module.
In the embodiment, the crack area of the ground of the uplink is obtained by carrying out image acquisition on the bottom area of the uplink and adopting a machine vision processing technology, and the leakage condition of the bottom area of the uplink is visually reflected by the constructed crack area set of the bottom of the uplink, so that a foundation is laid for later statistics of the leakage risk coefficient of the uplink to the downlink.
The modeling analysis module receives the downgoing road basic parameter set sent by the road basic parameter detection module, compares the width of the downgoing road in the downgoing road basic parameter set with road width ponding danger coefficients corresponding to various road widths in the parameter database, screens out the road width ponding danger coefficient corresponding to the downgoing road, compares the height of the downgoing road in the downgoing road basic parameter set from the upgoing road with height ponding danger coefficients corresponding to various height values between the downgoing road and the downgoing road in the parameter database, screens out the height ponding danger coefficient corresponding to the downgoing road, compares the terrain height of the downgoing road in the downgoing road basic parameter set with the terrain ponding danger coefficients corresponding to various terrain heights of the road in the parameter database, screens out the terrain ponding danger coefficient corresponding to the downgoing road, and combines the road width ponding danger coefficients corresponding to the downgoing road, Calculating the corresponding basic parameter ponding danger coefficient of the downlink by the height ponding danger coefficient and the terrain ponding danger coefficient
α、βAnd epsilon is respectively expressed as a road width water accumulation risk coefficient, a height water accumulation risk coefficient and a terrain water accumulation risk coefficient corresponding to the downlink road and is sent to the management cloud platform;
the modeling analysis module receives the flatness of the downlink road surface sent by the downlink road surface flatness detection module, compares the received flatness of the downlink road surface with road surface flatness water accumulation danger coefficients corresponding to various road surface flatness in the parameter database to obtain the road surface flatness water accumulation danger coefficients corresponding to the downlink road surface, and sends the road surface flatness water accumulation danger coefficients to the management cloud platform;
the modeling analysis module receives the average displacement of the drainage facilities corresponding to the uplink road surface and the average distance between two adjacent drainage facilities, and the average displacement of the drainage facilities corresponding to the downlink road surface and the average distance between two adjacent drainage facilities, which are sent by the road drainage parameter detection module, so that the drainage risk index of the uplink road surface to the downlink road is counted according to the average displacement of the drainage facilities corresponding to the uplink road surface and the average distance between two adjacent drainage facilities
Thus, the total drainage danger coefficient of the downlink road surface is counted according to the drainage danger index of the uplink road surface to the downlink road surface, the average drainage quantity of the drainage facilities corresponding to the downlink road surface and the average distance between two adjacent drainage facilities
And sending the data to a management cloud platform;
the total drainage risk coefficient of the down road surface counted by the embodiment integrates the drainage influence condition of the up road on the down road and the drainage condition of the down road, well fits the actual condition, and provides a relevant coefficient of drainage risk for counting the comprehensive ponding risk coefficient corresponding to the down road of the urban interchange at the back.
The modeling analysis module receives the uplink road bottom crack area set sent by the uplink road leakage detection module, sums the areas of all cracks according to the uplink road bottom crack area set to obtain the total crack area corresponding to the bottom of the uplink road, compares the total crack area with leakage danger coefficients corresponding to the total crack areas of all roads in the parameter database to obtain the leakage danger coefficients of the uplink road to the downlink road, and sends the leakage danger coefficients to the management cloud platform.
The management cloud platform receives the basic parameter ponding danger coefficient, the road surface flatness ponding danger coefficient, the total drainage danger coefficient and the leakage danger coefficient of the descending road of the urban interchange, which are sent by the modeling analysis module and correspond to the descending road, and counts the comprehensive ponding danger coefficient corresponding to the descending road of the urban interchange
The comprehensive accumulated water danger coefficient corresponding to the descending road of the urban interchange is represented, xi, mu, psi and lambda are respectively represented as a basic parameter accumulated water danger coefficient, a road surface flatness accumulated water danger coefficient, a total drainage danger coefficient and a leakage danger coefficient of the descending road corresponding to the descending road, k1, k2, k3 and k4 are respectively represented as weight influence coefficients corresponding to the basic parameter, the road surface flatness, the drainage and the leakage, and k1+ k2+ k3+ k4 is 1 and is sent to a background display terminal.
The comprehensive monitoring method of the urban interchange downlink road water accumulation hidden danger comprises the steps of counting the comprehensive water accumulation danger coefficient corresponding to the urban interchange downlink road by combining the basic parameter water accumulation danger coefficient corresponding to the downlink road, the road surface flatness water accumulation danger coefficient, the total drainage danger coefficient and the leakage danger coefficient of the uplink road to the downlink road, realizing the comprehensive monitoring of the urban interchange downlink road water accumulation hidden danger, expanding the monitoring range of the water accumulation hidden danger, overcoming the defects of one-piece and simplification existing in the existing urban interchange downlink road water accumulation hidden danger monitoring mode, improving the reliability of the monitoring result, and intuitively reflecting the water accumulation danger degree of the downlink road by the counted comprehensive water accumulation danger coefficient corresponding to the downlink road, facilitating the road management personnel to carry out the maintenance of the downlink road water accumulation hidden danger according to the comprehensive water accumulation danger coefficient, and further greatly reducing the probability of water accumulation on the downlink road in rainy days, the occurrence rate of traffic jam and traffic accidents caused by the water accumulation of the downlink road is reduced, and the running safety of the downlink road in rainy days is guaranteed.
And the background display terminal receives the comprehensive ponding danger coefficient corresponding to the urban interchange downlink road sent by the management cloud platform and performs background display.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (8)
1. The utility model provides an urban traffic town road safety on-line monitoring cloud platform based on machine vision and thing networking which characterized in that: the urban interchange road drainage system comprises an urban interchange road dividing module, a downlink road basic parameter detection module, a downlink road surface flatness detection module, a road drainage parameter detection module, an uplink road leakage detection module, a modeling analysis module, a management cloud platform and a background display terminal;
the urban interchange road division module is used for dividing the urban interchange into an uplink road and a downlink road according to the spatial position relationship of the roads;
the basic parameter detection module of the downlink is used for detecting basic parameters of the downlink divided by the urban interchange, the basic parameters comprise the width of the downlink, the height from the uplink and the terrain height, and the basic parameters of the detected downlink form a basic parameter set P (P) of the downlinkw,ph,pd)，pw,ph,pdThe basic parameter detection module of the downlink road sends the basic parameter set of the downlink road to the modeling analysis module;
the downgoing road surface flatness detection module is used for carrying out flatness detection on the surface of the downgoing road and sending the detected downgoing road surface flatness to the modeling analysis module, and the specific detection process comprises the following steps:
s1, uniformly distributing a plurality of detection points on the road surface of the descending road, numbering the distributed detection points according to a preset sequence, and marking the detection points as 1,2.. i.. n in sequence;
s2, respectively detecting the height from each detection point to the downgoing road subgrade, wherein the obtained height from each detection point to the downgoing road subgrade forms a detection point-to-subgrade height set H (H1, H2, h.a., hi, hn), and hi is expressed as the height from the ith detection point to the downgoing road subgrade;
s3, comparing the height set of the detection points from the roadbed with the standard height of the downgoing road pavement from the roadbed to obtain a comparison set delta H (delta H1, delta H2, delta hi, delta hn) of the height of the detection points from the roadbed, and counting the flatness of the downgoing road pavement according to the comparison set of the height of the detection points from the roadbed;
the parameter database is used for storing road width ponding danger coefficients corresponding to various road widths, storing height ponding danger coefficients corresponding to various height values between an uplink road and a downlink road, storing terrain ponding danger coefficients corresponding to various terrain heights of the roads, storing road surface flatness ponding danger coefficients corresponding to various road surface flatness, and storing leakage danger coefficients corresponding to various road crack total areas;
the road drainage parameter detection module is used for counting the number of drainage facilities on the uplink road surface and the downlink road surface, numbering the counted drainage facilities on the uplink road surface and respectively marking the counted drainage facilities as 1,2.. a.. z, numbering the counted drainage facilities on the downlink road surface and respectively marking the counted drainage facilities as 1,2.. b.. y, so as to respectively count the drainage quantity of the drainage facilities on the uplink road surface and the drainage facilities on the downlink road surface, and the obtained drainage quantity corresponding to the drainage facilities on the uplink road surface forms an uplink road drainage quantity set QOn the upper part(QOn the upper part1,QOn the upper part2,...,QOn the upper parta,...,QOn the upper partz) to obtain a down roadThe water discharge amount corresponding to each drainage facility constitutes a downlink water discharge amount set QLower part(QLower part1,QLower part2,...,QLower partb,...,QLower party), thereby respectively counting the average drainage quantity of the drainage facilities of the uplink and the average drainage quantity of the drainage facilities of the downlink according to the drainage quantity set of the uplink and the drainage quantity set of the downlink, and simultaneously respectively carrying out the average distance counting between two adjacent drainage facilities on each drainage facility existing on the road surface of the uplink and each drainage facility existing on the road surface of the downlink, wherein the road drainage parameter detection module sends the counted average drainage quantity of the drainage facility corresponding to the road surface of the uplink, the average distance between two adjacent drainage facilities, the average drainage quantity of the drainage facility corresponding to the road surface of the downlink and the average distance between two adjacent drainage facilities to the modeling analysis module;
the ascending road leakage detection module is used for carrying out image acquisition on an ascending road bottom area, comparing the acquired ascending road bottom area image with a normal road bottom area image to obtain the position of a crack of the ascending road bottom area, counting the number of cracks existing in the ascending road bottom area at the moment, numbering the counted cracks, sequentially marking the number of the counted cracks as 1,2.. j.. m, focusing the area of the crack on the ascending road bottom area image respectively, extracting the contour line of each crack to obtain the area corresponding to each crack, and forming an ascending road bottom crack area set S (S1, S2...., sj.,. sm.) and sending the ascending road bottom crack area set to the modeling analysis module by the ascending road leakage detection module;
the modeling analysis module receives the basic parameter set of the downlink road sent by the basic parameter detection module of the road, compares the width of the downlink road in the basic parameter set of the downlink road with road width ponding danger coefficients corresponding to various road widths in the parameter database, screens out the road width ponding danger coefficient corresponding to the downlink road, compares the height of the downlink road in the basic parameter set of the downlink road from the uplink road with the height ponding danger coefficients corresponding to various height values between the uplink road and the downlink road in the parameter database, screens out the height ponding danger coefficient corresponding to the downlink road, compares the terrain height of the downlink road in the basic parameter set of the downlink road with the terrain ponding danger coefficients corresponding to various terrain heights of the road in the parameter database, screens out the terrain ponding danger coefficient corresponding to the downlink road, the modeling analysis module is used for calculating a basic parameter ponding risk coefficient corresponding to the downlink road by combining the road width ponding risk coefficient, the height ponding risk coefficient and the terrain ponding risk coefficient corresponding to the downlink road, and sending the basic parameter ponding risk coefficient to the management cloud platform;
the modeling analysis module receives the flatness of the downlink road surface sent by the downlink road surface flatness detection module, compares the received flatness of the downlink road surface with road surface flatness water accumulation danger coefficients corresponding to various road surface flatness in the parameter database to obtain the road surface flatness water accumulation danger coefficients corresponding to the downlink road surface, and sends the road surface flatness water accumulation danger coefficients to the management cloud platform;
the modeling analysis module receives the average drainage quantity of the drainage facility corresponding to the uplink road surface and the average distance between two adjacent drainage facilities, and the average drainage quantity of the drainage facility corresponding to the downlink road surface and the average distance between two adjacent drainage facilities, which are sent by the road drainage parameter detection module, so that the drainage risk index of the uplink road surface to the downlink road is counted according to the average drainage quantity of the drainage facility corresponding to the uplink road surface and the average distance between two adjacent drainage facilities, the total drainage risk coefficient of the downlink road surface is counted according to the drainage risk index of the uplink road surface to the downlink road, the average drainage quantity of the drainage facility corresponding to the downlink road surface and the average distance between two adjacent drainage facilities, and the total drainage risk coefficient is sent to the management cloud platform;
the modeling analysis module receives the uplink road bottom crack area set sent by the uplink road leakage detection module, sums the areas of all cracks according to the uplink road bottom crack area set to obtain the total crack area corresponding to the bottom of the uplink road, compares the total crack area with leakage danger coefficients corresponding to the total crack areas of all roads in the parameter database to obtain the leakage danger coefficients of the uplink road to the downlink road, and sends the leakage danger coefficients to the management cloud platform;
the management cloud platform receives the basic parameter accumulated water danger coefficient, the road surface flatness accumulated water danger coefficient, the total drainage danger coefficient and the leakage danger coefficient of the descending road of the urban interchange, which are sent by the modeling analysis module and correspond to the descending road, counts the comprehensive accumulated water danger coefficient corresponding to the descending road of the urban interchange, and sends the comprehensive accumulated water danger coefficient to the background display terminal;
and the background display terminal receives the comprehensive ponding danger coefficient corresponding to the urban interchange downlink road sent by the management cloud platform and performs background display.
2. The machine vision and internet of things based urban traffic town road safety online monitoring cloud platform according to claim 1, characterized in that: the specific layout method of the detection points uniformly laid on the road surface of the downlink road comprises the following steps:
t1, acquiring the length and width of the road surface of the downlink;
t2, evenly dividing the length and the width of the road surface of the descending road respectively to obtain equal division points of the length and the width, and evenly dividing the road surface of the descending road into sub areas of each road surface;
and T3, respectively arranging a single detection point at the central position of each divided pavement sub-area, thereby obtaining a plurality of arranged detection points.
3. The machine vision and internet of things based urban traffic town road safety online monitoring cloud platform according to claim 1, characterized in that: the calculation formula of the flatness of the down road pavement is
h0Expressed as the standard height of the road surface of the downgoing road from the road bed.
4. The machine vision and Internet of things based urban traffic and municipal road safety online monitoring cloud platform according to claim 1The method is characterized in that: the calculation formula of the average displacement of the uplink road drainage facility is
Expressed as the average displacement of the upstream drainage facility and the average displacement of the downstream drainage facility as
Expressed as the average displacement of the downgoing road drainage facility.
5. The machine vision and internet of things based urban traffic town road safety online monitoring cloud platform according to claim 1, characterized in that: the average distance statistics between two adjacent drainage facilities is respectively carried out on each drainage facility existing on the upper road surface and each drainage facility existing on the lower road surface, and the specific statistical method is as follows:
g1, making statistics of the distance between two adjacent drainage facilities for each drainage facility on the surface of the ascending road, wherein the obtained distance between two adjacent drainage facilities on the surface of the ascending road forms an interval set X of the adjacent drainage facilities on the surface of the ascending roadOn the upper part[xOn the upper part1,xOn the upper part2,...,xOn the upper parta,...,xOn the upper part(z-1)],xOn the upper parta represents the distance between the a-th drainage facility and the a + 1-th drainage facility on the pavement of the ascending road;
g2 calculating the average distance between two adjacent drainage facilities on the road surface according to the distance set of the adjacent drainage facilities on the road surface, wherein the calculation formula is
G3 calculating the distance between two adjacent drainage facilities for each drainage facility on the down road surface, wherein the obtained distance between two adjacent drainage facilities on the down road surface forms a set X of the distance between two adjacent drainage facilities on the down road surfaceLower part[xLower part1,xLower part2,...,xLower partb,...,xLower part(y-1)],xLower partb represents the distance between the b-th drainage facility and the b + 1-th drainage facility on the pavement of the downlink road;
g4 calculating the average distance between two adjacent drainage facilities on the road surface of the descending road according to the distance set of the adjacent drainage facilities on the road surface of the descending road, wherein the calculation formula is
6. The machine vision and internet of things based urban traffic town road safety online monitoring cloud platform according to claim 1, characterized in that: the calculation formula of the basic parameter ponding danger coefficient corresponding to the downlink is
Alpha, beta and epsilon are respectively expressed as road width ponding danger coefficient, height ponding danger coefficient and terrain ponding danger coefficient corresponding to the downlink road.
7. The machine vision and internet of things based urban traffic town road safety online monitoring cloud platform according to claim 1, characterized in that: the calculation formula of the drainage danger influence index of the uplink road surface to the downlink road is
Sigma is expressed as the drainage danger influence index of an ascending road surface to a descending road surface, and the total drainage danger coefficient of the descending road surface is calculated by the formula
8. The machine vision and internet of things based urban traffic town road safety online monitoring cloud platform according to claim 1, characterized in that: the calculation formula of the comprehensive ponding danger coefficient corresponding to the urban interchange downlink road is
The comprehensive accumulated water danger coefficient corresponding to the descending road of the urban interchange is represented, xi, mu, psi and lambda are respectively represented as a basic parameter accumulated water danger coefficient, a road surface flatness accumulated water danger coefficient, a total drainage danger coefficient and a leakage danger coefficient of the descending road corresponding to the descending road, k1, k2, k3 and k4 are respectively represented as weight influence coefficients corresponding to the basic parameter, the road surface flatness, the drainage and the leakage, and k1+ k2+ k3+ k4 is 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110258017.7A CN113053111B (en) | 2021-03-09 | 2021-03-09 | Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110258017.7A CN113053111B (en) | 2021-03-09 | 2021-03-09 | Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113053111A true CN113053111A (en) | 2021-06-29 |
| CN113053111B CN113053111B (en) | 2022-08-12 |
Family
ID=76510723
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110258017.7A Active CN113053111B (en) | 2021-03-09 | 2021-03-09 | Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113053111B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114648249A (en) * | 2022-04-11 | 2022-06-21 | 武汉生凡建筑装饰工程有限公司 | Town road engineering quality safety monitoring management system based on big data analysis |
| CN114413922B (en) * | 2022-01-20 | 2024-04-09 | 北京百度网讯科技有限公司 | Navigation method, device, equipment, medium and product of electronic map |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109544912A (en) * | 2018-11-07 | 2019-03-29 | 北京城市系统工程研究中心 | A kind of city road network ponding trend prediction method based on multisource data fusion |
| CN111815955A (en) * | 2020-09-11 | 2020-10-23 | 深圳市城市交通规划设计研究中心股份有限公司 | Intelligent urban road accumulated water identification method based on traffic flow basic graph |
| CN111896721A (en) * | 2020-08-31 | 2020-11-06 | 杭州宣迅电子科技有限公司 | Municipal road engineering quality intelligent acceptance detection management system based on big data |
| CN112382091A (en) * | 2020-11-11 | 2021-02-19 | 北京世纪高通科技有限公司 | Road water accumulation early warning method and device |
| KR20210020408A (en) * | 2019-08-14 | 2021-02-24 | 권복남 | System for monitoring and processing dangerous situation on road |
-
2021
- 2021-03-09 CN CN202110258017.7A patent/CN113053111B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109544912A (en) * | 2018-11-07 | 2019-03-29 | 北京城市系统工程研究中心 | A kind of city road network ponding trend prediction method based on multisource data fusion |
| KR20210020408A (en) * | 2019-08-14 | 2021-02-24 | 권복남 | System for monitoring and processing dangerous situation on road |
| CN111896721A (en) * | 2020-08-31 | 2020-11-06 | 杭州宣迅电子科技有限公司 | Municipal road engineering quality intelligent acceptance detection management system based on big data |
| CN111815955A (en) * | 2020-09-11 | 2020-10-23 | 深圳市城市交通规划设计研究中心股份有限公司 | Intelligent urban road accumulated water identification method based on traffic flow basic graph |
| CN112382091A (en) * | 2020-11-11 | 2021-02-19 | 北京世纪高通科技有限公司 | Road water accumulation early warning method and device |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114413922B (en) * | 2022-01-20 | 2024-04-09 | 北京百度网讯科技有限公司 | Navigation method, device, equipment, medium and product of electronic map |
| CN114648249A (en) * | 2022-04-11 | 2022-06-21 | 武汉生凡建筑装饰工程有限公司 | Town road engineering quality safety monitoring management system based on big data analysis |
| CN114648249B (en) * | 2022-04-11 | 2023-01-10 | 中咨数据有限公司 | Town road engineering quality safety monitoring management system based on big data analysis |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113053111B (en) | 2022-08-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113053111B (en) | Urban traffic town road safety on-line monitoring cloud platform based on machine vision and Internet of things | |
| CN105869405B (en) | Urban road traffic congestion index calculation method based on bayonet socket data | |
| CN108446464B (en) | Method for constructing large drainage system by using SWMM model | |
| US20200370283A1 (en) | Engineering system for collecting and utilizing regional rainwater and allocation method | |
| CN115081757B (en) | Automatic road disease detection method based on robot technology | |
| CN104484993A (en) | Processing method of cell phone signaling information for dividing traffic zones | |
| CN112579975A (en) | Environmental parameter monitoring management system based on big data visual analysis | |
| CN110543984A (en) | Urban water surface rate planning method based on water safety | |
| CN109308560B (en) | A kind of urban rainstorm waterlogging and the method for prewarning risk of long-pending flood | |
| CN112432665A (en) | Hydraulic engineering dam body safety real-time monitoring and early warning management system based on big data analysis | |
| CN113701060B (en) | Intelligent diagnosis method for urban drainage pipe network based on drainage model | |
| CN116206426B (en) | Mobile water level monitoring alarm system based on Internet of things | |
| CN112801969A (en) | Municipal road construction project supervision quality acceptance analysis processing method based on big data and cloud computing | |
| CN106327485B (en) | A kind of bituminous pavement rainy season light maintenance early warning system and its method | |
| CN105303831A (en) | Method for determining congestion state of highway based on communication data | |
| CN112462035A (en) | Reservoir dam safety on-line monitoring system based on cloud computing informatization | |
| CN115472003A (en) | Urban traffic supervision system and method based on multi-source information | |
| CN107085658A (en) | A kind of mountain flood time of causing disaster determines method | |
| CN109902971A (en) | A kind of road side security risk evaluations and stage division | |
| CN105139670A (en) | Video-based regional self-optimizing signal control method and apparatus | |
| CN111931330A (en) | Generalized calculation method for pipe network drainage process of urban area without pipe network data | |
| CN104966404A (en) | Single-point self-optimization signal control method and device based on array radars | |
| CN107330594A (en) | Urban operating mechanism information management system | |
| CN116737989B (en) | Urban surface hydrologic monitoring network construction method based on video image | |
| CN104750936A (en) | GIS (Geographic Information System)-based urban hydrological run-off calculating method and system |
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 | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20220714 Address after: 200000 room 2002-d, No. 509, Wuning Road, Putuo District, Shanghai Applicant after: Shanghai new front end Yitian Technology Co.,Ltd. Address before: 225000 No.2 Youyi Road, Yangzhou City, Jiangsu Province Applicant before: Zhou Fengying |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |