CN114332170B - Novel capital construction site safety monitoring system - Google Patents
Novel capital construction site safety monitoring system Download PDFInfo
- Publication number
- CN114332170B CN114332170B CN202111602577.6A CN202111602577A CN114332170B CN 114332170 B CN114332170 B CN 114332170B CN 202111602577 A CN202111602577 A CN 202111602577A CN 114332170 B CN114332170 B CN 114332170B
- Authority
- CN
- China
- Prior art keywords
- cluster
- nodes
- target object
- safety
- new
- 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.)
- Active
Links
Images
Landscapes
- Alarm Systems (AREA)
Abstract
New capital construction site safety monitoring system, relate to safety monitoring technical field, because people can not timely discovery accident and can not be effectual withdraw to the safety zone when the accident takes place among the prior art, the problem of evacuation inefficiency, this application monitors new capital construction project object at first, new capital construction project object takes place the displacement, and the displacement exceeds safe threshold, then carry out the clustering with people, this application can be effectual when new capital construction project object collapses, the personnel of going on of safety are evacuated, when having avoided taking place the incident, evacuation speed is slow, the problem of easy emergence stepping on the incident, and this application can assemble people, unified evacuation, personnel's falling single has been avoided, take place danger, evacuation efficiency is high, this application is through carrying out the first selection of cluster in the region that crowd density is high at last, crowd's flow has been reduced, indirect gathering speed has been increased, thereby evacuation efficiency has been improved.
Description
Technical Field
The invention relates to the technical field of safety monitoring, in particular to a novel capital construction on-site safety monitoring system.
Background
The new infrastructure is the national infrastructure and infrastructure construction of a modern economic system by carrying out new development concepts in the intelligent economic era, absorbing the achievements of new technological revolution, realizing the ecological, digital, intelligent, high-speed, new and old kinetic energy conversion and the symmetrical state of an economic structure.
The novel infrastructure construction (called as new infrastructure for short) mainly comprises seven fields of 5G base station construction, extra-high voltage, inter-city high-speed railways, urban rail transit, new energy automobile charging piles, large data centers, artificial intelligence and industrial internet, relates to a plurality of industrial chains, takes new development as an idea, takes technical innovation as drive, takes an information network as a basis, and provides an infrastructure system with services of digital transformation, intelligent upgrading, fusion innovation and the like for the high-quality development needs.
At present, accidents of new capital construction safety production in China occur frequently, the number of casualties is high every year, and according to investigation and statistics of past accident cases, 90% of accidents are caused by the fact that people cannot find the accidents timely and can not evacuate to a safety area when the accidents occur, and evacuation efficiency is low.
Disclosure of Invention
The purpose of the invention is: aiming at the problems that in the prior art, people cannot find an accident in time and cannot be evacuated to a safety area effectively when the accident happens, and the evacuation efficiency is low, a new infrastructure field safety monitoring system is provided.
The technical scheme adopted by the invention to solve the technical problems is as follows:
the new capital construction site safety monitoring system comprises a site monitoring module and an evacuation module,
the on-site monitoring module specifically executes the following steps:
the method comprises the following steps: monitoring the new infrastructure project target object, and monitoring the displacement of the new infrastructure project target object if the new infrastructure project target object is displaced;
the first step is: obtaining a displacement safety threshold of the new capital construction project target object according to the new capital construction safety standard data and the stress characteristics of the new capital construction project target object;
step one, three: when the displacement of the new basic construction project target reaches the displacement safety threshold of the new basic construction project target, alarming and sending a signal to the evacuation module;
after the evacuation module receives the signal sent by the monitoring module, the evacuation module executes evacuation steps, wherein the evacuation steps are as follows:
step two is as follows: determining a safety warning area according to the size information of the new infrastructure project target object;
step two: recording each member in the safety warning area as a node;
step two and step three: acquiring a plan view of an area where a new infrastructure project target object is located, and determining a safety area in the plan view;
step two: clustering all nodes, determining cluster heads, and finally establishing communication among members in the clusters.
Further, the second step and the fourth step specifically comprise the following steps:
firstly, taking a node closest to each safety region as a cluster, determining a plurality of central nodes by using K-mediads for each cluster, then calculating the average distance from other nodes in the cluster to each central node, taking the central node with the minimum average distance from other nodes as a final cluster head, then establishing communication between members in the cluster, and sending a route map of each node in the cluster to the nearest safety region to each node.
Further, the specific steps of the K-mediads are as follows:
step two, four and one: acquiring the position information of all member nodes in a cluster;
step two, step four and step two: uniformly dividing the areas where all the member nodes are located to obtain the average density value of each divided area;
step two, step four and step three: selecting an area with density larger than the average density as a central point set;
step two, step four: and obtaining a plurality of central nodes by using the K-mediads.
Further, the second, fourth and second steps are as follows:
step two, four, two and one: intercepting the minimum circumscribed rectangular area where all members in the cluster are located according to the node coordinates;
step two, four, two: marking the position information of member nodes in the cluster in the intercepted rectangular area;
step two, four, two and three: carrying out uniform grid division on the marked rectangular area;
step two, step four, step two and step four: and obtaining the density value in each grid according to the number of members in each cluster in each grid, thereby obtaining the average density value of the nodes in each cluster in each grid.
Further, the specific steps of monitoring the new capital construction project target object in the steps one by one are as follows:
step 1: acquiring new capital construction project target object video data;
and 2, step: extracting a video frame of a target object at the current moment from the video data, comparing the extracted video frame of the target object at the current moment with a video frame of the target object extracted at the next moment, if deviation occurs, executing a first step three, and if deviation does not occur, taking the video frame of the target object extracted at the next moment as the video frame of the target object at the current moment, and continuously comparing the video frame of the target object with the video frame of the target object at the next moment;
and step 3: calibrating a camera by using a camera with a fixed focal length to obtain an internal reference matrix and a distortion coefficient of the camera;
and 4, step 4: acquiring a displacement video of a target object of a new construction project by using a camera with fixed frequency;
and 5: correcting the displacement video acquired by the camera through a distortion coefficient;
step 6: extracting a video frame of the new basic building project target object in a static state from the corrected video data, and establishing a three-dimensional coordinate system according to the size information of the new basic building project target object;
and 7: selecting a target point on the new infrastructure project target object, determining the coordinate of the target point in a three-dimensional coordinate system, tracking the displacement information of a pixel point corresponding to the target point in a video frame by using a target tracking algorithm, and obtaining the position of the characteristic point after displacement by using the displacement information.
Further, the target tracking algorithm is a template matching algorithm, a feature point matching algorithm or an optical flow estimation algorithm.
Further, the camera in the first step is a fixed-focus camera or a zoom camera, and the focal length and the field angle parameters of the zoom camera are fixed.
Further, the alarm is performed through an audible and visual alarm and a smoke alarm.
Further, the second and fourth steps are specifically as follows:
step A: taking the node closest to each safe area as a cluster, comparing the number of the members in the cluster with the maximum number of the members in the safe area, executing the step C if the number of the members in the cluster is less than the maximum number of the members in the safe area, and executing the step B if the number of the members in the cluster is more than the maximum number of the members in the safe area;
and B, step B: according to the maximum number of the accommodated people in the safe area, sorting the nodes in the cluster from near to far away from the safe area, dividing the nodes with the ranking sequence number larger than the maximum number of the accommodated people in the safe area into the cluster of the safe area closest to the nodes except the safe area, comparing the number of the members in the cluster with the maximum number of the accommodated people in the safe area, if the number of the members in the cluster is smaller than the maximum number of the accommodated people in the safe area, executing the step C, and if the number of the members in the cluster is larger than the maximum number of the accommodated people in the safe area, repeatedly executing the step until all the nodes are distributed;
and C: and determining a plurality of central nodes by using K-media for each cluster, then calculating the average distance from other nodes in the cluster to each central node, taking the central node with the minimum average distance from other nodes as a final cluster head, then establishing communication between members in the cluster, and sending a route map of a safety region with each node in the cluster closest to each node.
Further, before the step B, the following steps are also included:
judging whether the total number of the nodes is larger than the maximum number of persons accommodated in all the safety regions or not, if so, expanding the maximum number of persons accommodated in all the safety regions in proportion to enable the total number of the nodes to be equal to the maximum number of persons accommodated in all the safety regions, and then executing the step B;
and B, if the total number of the nodes is not more than the maximum number of persons accommodated in all the safety areas, executing the step B.
The invention has the beneficial effects that:
this application at first monitors new capital construction project object, new capital construction project object takes place the displacement, and the displacement exceeds safe threshold, then carry out the clustering with people, this application can be effectual when new capital construction project object takes place to collapse, the safe personnel of carrying on evacuate, when having avoided taking place emergency, evacuation speed is slow, the problem of stepping on the incident easily takes place, and this application can assemble people, unified evacuation, personnel's falling list has been avoided, take place danger, evacuation efficiency is high, this application is selected through clustering in the region that crowd density is high at last, crowd's flow has been reduced, the gathering speed has been increased indirectly, thereby evacuation efficiency has been improved.
Drawings
Fig. 1 is a block diagram of the present application.
Detailed Description
It should be noted that, in the present invention, the embodiments disclosed in the present application may be combined with each other without conflict.
The first embodiment is as follows: referring to fig. 1, the new basic site safety monitoring system according to the embodiment is characterized by comprising a site monitoring module and an evacuation module,
the monitoring module specifically executes the following steps:
the method comprises the following steps: monitoring the new basic construction project target object, and monitoring the displacement of the new basic construction project target object if the new basic construction project target object is displaced;
the first step is: obtaining a displacement safety threshold of the new capital construction project target object according to the new capital construction safety standard data and the stress characteristics of the new capital construction project target object;
step one is three: when the displacement of the new basic construction project target object reaches the displacement safety threshold of the new basic construction project target object, alarming and sending a signal to the evacuation module;
after the evacuation module receives the signal sent by the monitoring module, the evacuation module executes evacuation steps, wherein the evacuation steps are as follows:
step two, firstly: determining a security alert area according to the size information of the new infrastructure item target object;
step two: recording each member in the safety warning area as a node;
step two and step three: acquiring a plan view of an area where a new infrastructure project target object is located, and determining a safety area in the plan view;
step two: and taking the node closest to each safety region as a cluster, determining a plurality of central nodes by using K-mediads for each cluster, and then calculating the average distance from other nodes in the cluster to each central node, wherein the central node with the minimum average distance from other nodes is the final cluster head.
The method aims at solving the problem that in the prior art, people cannot find an accident in time and cannot evacuate to a safe area effectively when the accident happens, and evacuation efficiency is low.
This application is through calculating average density, chooses the crowd that is higher than average density to carry out the cluster head selection, can reduce personnel's flow like this, if directly select the cluster head in the member in the cluster, crowd intensive and crowd not intensive colony all need remove, this application carries out the cluster head selection in crowd intensive colony, reduces intensive crowd's removal, and then increases the gathering speed of the member in the cluster to accelerate evacuation speed, improve evacuation efficiency.
The second embodiment is as follows: this embodiment is a further description of the first embodiment, and the difference between this embodiment and the first embodiment is that the specific steps of the second step and the fourth step are:
firstly, taking a node closest to each safety region as a cluster, determining a plurality of central nodes by using K-media for each cluster, then calculating the average distance from other nodes in the cluster to each central node, taking the central node with the minimum average distance from other nodes as a final cluster head, then establishing communication between members in the cluster, and sending a route map of each node in the cluster to the nearest safety region to each node.
Each node goes to a safe area according to the route map.
The third concrete implementation mode: this embodiment is a further description of a second embodiment, and the difference between this embodiment and the second embodiment is that the specific steps of the K-intermediates are as follows:
step two, four and one: acquiring the position information of all member nodes in a cluster;
step two, step four, step two: uniformly dividing the areas where all the member nodes are located to obtain the average density value of each divided area;
step two, step four and step three: selecting an area with the density larger than the average density as a central point set;
step two, step four: and obtaining a plurality of central nodes by using the K-mediads.
The fourth concrete implementation mode: this embodiment is a further description of a third embodiment, and is different from the third embodiment in that the second and fourth steps are as follows:
step two, four, two and one: intercepting the minimum circumscribed rectangular area where all members in the cluster are located according to the node coordinates;
step two, four, two: marking the position information of member nodes in the cluster in the intercepted rectangular area;
step two, four, two and three: carrying out uniform grid division on the marked rectangular area;
step two, step four, step two and step four: and obtaining the density value in each grid according to the number of members in each cluster in each grid, thereby obtaining the average density value of the nodes in each cluster in each grid.
The fifth concrete implementation mode: the embodiment is a further description of a fourth specific embodiment, and the difference between the embodiment and the fourth specific embodiment is that the specific steps of monitoring a new infrastructure project target object in the steps one by one are as follows:
step 1: acquiring video data of a target object of a new infrastructure project;
step 2: extracting a video frame of a target object at the current moment from the video data, comparing the extracted video frame of the target object at the current moment with an extracted video frame of the target object at the next moment, if the extracted video frame of the target object at the current moment is deviated, executing a third step, and if the extracted video frame of the target object at the next moment is not deviated, taking the extracted video frame of the target object at the current moment as the video frame of the target object at the current moment and continuously comparing the extracted video frame of the target object at the next moment with the video frame of the target object at the next moment;
and 3, step 3: calibrating a camera by using a camera with a fixed focal length to obtain an internal reference matrix and a distortion coefficient of the camera;
and 4, step 4: acquiring a displacement video of a target object of a new construction project by using a camera with fixed frequency;
and 5: correcting the displacement video acquired by the camera through a distortion coefficient;
step 6: extracting a video frame of a new basic building project object in a static state from the corrected video data, and establishing a three-dimensional coordinate system according to the size information of the new basic building project object;
and 7: selecting a target point on the new infrastructure project target object, determining the coordinate of the target point in a three-dimensional coordinate system, tracking the displacement information of a pixel point corresponding to the target point in a video frame by using a target tracking algorithm, and obtaining the position of the feature point after displacement by using the displacement information.
The sixth specific implementation mode is as follows: the fifth embodiment is a further description of the fifth embodiment, and the difference between the fifth embodiment and the fifth embodiment is that the target tracking algorithm is a template matching algorithm, a feature point matching algorithm, or an optical flow estimation algorithm.
The seventh embodiment: this embodiment is further described with respect to a sixth embodiment, and the difference between this embodiment and the sixth embodiment is that in the first step, the camera is a fixed-focus camera or a zoom camera, and the focal length and the angle of view parameters of the zoom camera are fixed.
The specific implementation mode is eight: the seventh embodiment is further described, and the difference between the seventh embodiment and the seventh embodiment is that the alarm is performed by an audible and visual alarm and a smoke alarm.
The specific implementation method nine: this embodiment is a further description of an eighth embodiment, and the difference between this embodiment and the eighth embodiment is that the specific steps of the second step and the fourth step are:
step A: taking the node closest to each safe area as a cluster, comparing the number of the members in the cluster with the maximum number of the members in the safe area, executing the step C if the number of the members in the cluster is less than the maximum number of the members in the safe area, and executing the step B if the number of the members in the cluster is more than the maximum number of the members in the safe area;
and B: according to the maximum number of the accommodated people in the safe area, sorting the nodes in the cluster from near to far away from the safe area, dividing the nodes with the ranking sequence number larger than the maximum number of the accommodated people in the safe area into the cluster of the safe area closest to the nodes except the safe area, comparing the number of the members in the cluster with the maximum number of the accommodated people in the safe area, if the number of the members in the cluster is smaller than the maximum number of the accommodated people in the safe area, executing the step C, and if the number of the members in the cluster is larger than the maximum number of the accommodated people in the safe area, repeatedly executing the step until all the nodes are distributed;
and C: and determining a plurality of central nodes by using K-mediads aiming at each cluster, then calculating the average distance from other nodes in the cluster to each central node, taking the central node with the minimum average distance from other nodes as a final cluster head, then establishing communication between members in the cluster, and sending a route map of a safety region with each node in the cluster closest to each node.
The detailed implementation mode is ten: this embodiment is further described with respect to a ninth embodiment, and the difference between this embodiment and the ninth embodiment is that the following steps are further included before step B:
judging whether the total number of the nodes is larger than the maximum accommodating number of all the safety regions, if so, expanding the maximum accommodating number of all the safety regions in proportion to enable the total number of the nodes to be equal to the maximum accommodating number of all the safety regions, and then executing a step B;
and B, if the total number of the nodes is not more than the maximum number of persons accommodated in all the safety areas, executing the step B.
And if the total number of the nodes is larger than the maximum number of the redundant nodes in all the safety regions, expanding the maximum number of the redundant nodes in the safety regions in proportion.
It should be noted that the detailed description is only for explaining and explaining the technical solution of the present invention, and the scope of protection of the claims is not limited thereby. It is intended that all such modifications and variations that fall within the spirit and scope of the invention be limited only by the claims and the description.
Claims (8)
1. The new capital construction site safety monitoring system is characterized in that: comprises an on-site monitoring module and an evacuation module,
the on-site monitoring module specifically executes the following steps:
the method comprises the following steps: monitoring the new infrastructure project target object, and monitoring the displacement of the new infrastructure project target object if the new infrastructure project target object is displaced;
the first step is: obtaining a displacement safety threshold of the new capital construction project target object according to the new capital construction safety standard data and the stress characteristics of the new capital construction project target object;
step one, three: when the displacement of the new basic construction project target reaches the displacement safety threshold of the new basic construction project target, alarming and sending a signal to the evacuation module;
after the evacuation module receives the signal sent by the monitoring module, the evacuation module executes evacuation steps, wherein the evacuation steps are as follows:
step two, firstly: determining a security alert area according to the size information of the new infrastructure item target object;
step two: recording each member in the security alert area as a node;
step two and step three: acquiring a plan view of an area where a new infrastructure project target object is located, and determining a safety area in the plan view;
step two: clustering all nodes, determining cluster heads, and finally establishing communication among members in the clusters;
the second and fourth steps are as follows:
step A: taking the node closest to each safety zone as a cluster, comparing the number of the members in the cluster with the maximum number of the members in the safety zone, executing a step C if the number of the members in the cluster is less than the maximum number of the members in the safety zone, and executing a step B if the number of the members in the cluster is greater than the maximum number of the members in the safety zone;
and B: according to the maximum number of the accommodated people in the safe area, sorting the nodes in the cluster from near to far away from the safe area, dividing the nodes with the ranking sequence number larger than the maximum number of the accommodated people in the safe area into the cluster of the safe area closest to the nodes except the safe area, comparing the number of the members in the cluster with the maximum number of the accommodated people in the safe area, if the number of the members in the cluster is smaller than the maximum number of the accommodated people in the safe area, executing the step C, and if the number of the members in the cluster is larger than the maximum number of the accommodated people in the safe area, repeatedly executing the step until all the nodes are distributed;
step C: aiming at each cluster, determining a plurality of central nodes by using K-media, then calculating the average distance from other nodes in the cluster to each central node, taking the central node with the minimum average distance from other nodes as a final cluster head, then establishing communication between members in the cluster, and sending a route map of a safety region with each node in the cluster closest to each node;
the step B also comprises the following steps before:
judging whether the total number of the nodes is larger than the maximum number of persons accommodated in all the safety regions or not, if so, expanding the maximum number of persons accommodated in all the safety regions in proportion to enable the total number of the nodes to be equal to the maximum number of persons accommodated in all the safety regions, and then executing the step B;
and C, if the total number of the nodes is not more than the maximum accommodating number of all the safety areas, executing the step B.
2. The new construction site safety monitoring system according to claim 1, wherein the specific steps of the second step and the fourth step are as follows:
firstly, taking a node closest to each safety region as a cluster, determining a plurality of central nodes by using K-media for each cluster, then calculating the average distance from other nodes in the cluster to each central node, taking the central node with the minimum average distance from other nodes as a final cluster head, then establishing communication between members in the cluster, and sending a route map of each node in the cluster to the nearest safety region to each node.
3. The new capital construction site safety monitoring system according to claim 2, characterized in that the K-mediads comprises the following specific steps:
step two, four and one: acquiring the position information of all member nodes in a cluster;
step two, step four and step two: uniformly dividing the areas where all the member nodes are located to obtain the average density value of each divided area;
step two, step four and step three: selecting an area with the density larger than the average density as a central point set;
step two, step four: and obtaining a plurality of central nodes by using the K-mediads.
4. The new construction site safety monitoring system according to claim 3, wherein the specific steps of the second step, the second step and the second step are as follows:
step two, four, two and one: intercepting the minimum circumscribed rectangular area where all members in the cluster are located according to the node coordinates;
step two, four, two: marking the position information of member nodes in the cluster in the intercepted rectangular area;
step two, four, two and three: carrying out uniform grid division on the marked rectangular area;
step two, four, two and four: and obtaining the density value in each grid according to the number of members in each cluster in each grid, thereby obtaining the average density value of the nodes in each cluster in each grid.
5. The new construction site safety monitoring system according to claim 4, wherein the specific steps of monitoring the new construction project target object in the steps one by one are as follows:
step 1: acquiring video data of a target object of a new infrastructure project;
step 2: extracting a video frame of a target object at the current moment from the video data, comparing the extracted video frame of the target object at the current moment with an extracted video frame of the target object at the next moment, if the extracted video frame of the target object at the current moment is deviated, executing a third step, and if the extracted video frame of the target object at the next moment is not deviated, taking the extracted video frame of the target object at the current moment as the video frame of the target object at the current moment and continuously comparing the extracted video frame of the target object at the next moment with the video frame of the target object at the next moment;
and step 3: calibrating a camera by using a camera with a fixed focal length to obtain an internal reference matrix and a distortion coefficient of the camera;
and 4, step 4: acquiring a displacement video of a target object of a new construction project by using a camera with fixed frequency;
and 5: correcting the displacement video acquired by the camera through a distortion coefficient;
step 6: extracting a video frame of a new basic building project object in a static state from the corrected video data, and establishing a three-dimensional coordinate system according to the size information of the new basic building project object;
and 7: selecting a target point on the new infrastructure project target object, determining the coordinate of the target point in a three-dimensional coordinate system, tracking the displacement information of a pixel point corresponding to the target point in a video frame by using a target tracking algorithm, and obtaining the position of the characteristic point after displacement by using the displacement information.
6. The new construction site safety monitoring system according to claim 5, characterized in that the target tracking algorithm is a template matching algorithm, a feature point matching algorithm or an optical flow estimation algorithm.
7. The system of claim 6, wherein the camera in step one is a fixed-focus camera or a zoom camera, and the parameters of focal length and field angle of the zoom camera are fixed.
8. The new capital construction site safety monitoring system according to claim 7, characterized in that the alarm is performed by an audible and visual alarm and a smoke alarm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111602577.6A CN114332170B (en) | 2021-12-24 | 2021-12-24 | Novel capital construction site safety monitoring system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111602577.6A CN114332170B (en) | 2021-12-24 | 2021-12-24 | Novel capital construction site safety monitoring system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114332170A CN114332170A (en) | 2022-04-12 |
| CN114332170B true CN114332170B (en) | 2022-11-18 |
Family
ID=81013332
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111602577.6A Active CN114332170B (en) | 2021-12-24 | 2021-12-24 | Novel capital construction site safety monitoring system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114332170B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1996053A (en) * | 2006-11-23 | 2007-07-11 | 浙江工业大学 | Debris flow disaster detector based on omnibearing visual range |
| CN103279800A (en) * | 2013-01-10 | 2013-09-04 | 吉林大学 | Game theory-based optimal escape route generating method for large-scale crowd evacuation |
| CN109242183A (en) * | 2018-09-05 | 2019-01-18 | 山东师范大学 | Crowd simulation evacuation method and device based on artificial fish-swarm algorithm and target detection |
| CN109670270A (en) * | 2019-01-11 | 2019-04-23 | 山东师范大学 | Crowd evacuation emulation method and system based on the study of multiple agent deeply |
| CN110136374A (en) * | 2019-05-22 | 2019-08-16 | 微云（武汉）科技有限公司 | A kind of generation method, device and the storage medium of building evacuation route |
| CN110648025A (en) * | 2019-09-25 | 2020-01-03 | 赵娜 | Emergency evacuation scheduling method |
| CN111400963A (en) * | 2020-03-04 | 2020-07-10 | 山东师范大学 | Crowd evacuation simulation method and system based on chicken swarm algorithm and social force model |
| CN113076883A (en) * | 2021-04-08 | 2021-07-06 | 西南石油大学 | Blowout gas flow velocity measuring method based on image feature recognition |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113128473A (en) * | 2021-05-17 | 2021-07-16 | 哈尔滨商业大学 | Underground comprehensive pipe gallery-oriented inspection system, method, equipment and storage medium |
-
2021
- 2021-12-24 CN CN202111602577.6A patent/CN114332170B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1996053A (en) * | 2006-11-23 | 2007-07-11 | 浙江工业大学 | Debris flow disaster detector based on omnibearing visual range |
| CN103279800A (en) * | 2013-01-10 | 2013-09-04 | 吉林大学 | Game theory-based optimal escape route generating method for large-scale crowd evacuation |
| CN109242183A (en) * | 2018-09-05 | 2019-01-18 | 山东师范大学 | Crowd simulation evacuation method and device based on artificial fish-swarm algorithm and target detection |
| CN109670270A (en) * | 2019-01-11 | 2019-04-23 | 山东师范大学 | Crowd evacuation emulation method and system based on the study of multiple agent deeply |
| CN110136374A (en) * | 2019-05-22 | 2019-08-16 | 微云（武汉）科技有限公司 | A kind of generation method, device and the storage medium of building evacuation route |
| CN110648025A (en) * | 2019-09-25 | 2020-01-03 | 赵娜 | Emergency evacuation scheduling method |
| CN111400963A (en) * | 2020-03-04 | 2020-07-10 | 山东师范大学 | Crowd evacuation simulation method and system based on chicken swarm algorithm and social force model |
| CN113076883A (en) * | 2021-04-08 | 2021-07-06 | 西南石油大学 | Blowout gas flow velocity measuring method based on image feature recognition |
Non-Patent Citations (1)
| Title |
|---|
| "基于计算机视觉的无标靶结构振动信号提取方法研究";莫康;《中国优秀硕士学位论文全文数据库》;20210115;第12、20-21、39-40、54-59页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114332170A (en) | 2022-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| AU2020100946A4 (en) | Multi-source traffic information sensing roadside device for smart highway | |
| CN106251578B (en) | Stream of people's early warning analysis method and system based on probe | |
| CN111178598A (en) | Passenger flow prediction method and system for railway passenger station, electronic device and storage medium | |
| CN211237137U (en) | Multi-source information fusion bridge ship-collision prevention monitoring and early warning system | |
| CN103338349A (en) | Intelligent mass video signal screening and display access method based on VW and system based on VW | |
| CN102098495A (en) | Intelligent monitoring device and method for landslide based on image recognition technology | |
| CN110164145A (en) | A kind of high-speed road conditions intelligence warning system and its working method | |
| CN113642403B (en) | Crowd abnormal intelligent safety detection system based on edge calculation | |
| CN105354542A (en) | Method for detecting abnormal video event in crowded scene | |
| CN114332170B (en) | Novel capital construction site safety monitoring system | |
| CN101076174A (en) | Method for processing warn windstorm | |
| CN116192459A (en) | Edge node network security threat monitoring method based on edge-to-edge cooperation | |
| CN110348329B (en) | Pedestrian detection method based on video sequence interframe information | |
| CN106331615A (en) | Intelligent traffic information acquisition system and static information acquisition method thereof | |
| CN112950929B (en) | All-weather real-time traffic information monitoring and QOS hierarchical control system and method | |
| CN105069710A (en) | Data processing method and system for intelligent power grid | |
| CN114779794B (en) | Street obstacle identification method based on unmanned patrol vehicle system in typhoon scene | |
| CN114025375B (en) | 5G tracking area anomaly detection method and system based on cellular distribution recognition technology | |
| CN103093579B (en) | Debris flow or landslide alarm system based on videos | |
| CN102075990B (en) | Large-area base station out-of-service alarm monitoring method and system | |
| CN114563796B (en) | Power line identification method and device based on unmanned aerial vehicle laser radar detection data | |
| CN111245833A (en) | Vehicle intrusion detection method and device | |
| CN110223506A (en) | A kind of novel traffic intersection pedestrian's rale violation warnings system and method | |
| CN115393900A (en) | Intelligent construction site safety supervision method and system based on Internet of things | |
| CN113115051A (en) | Data transmission and storage device for lossless compression coding and decoding of high-definition video |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |