CN113392903A - Method, system and device for identifying construction site area - Google Patents
Method, system and device for identifying construction site area Download PDFInfo
- Publication number
- CN113392903A CN113392903A CN202110662564.1A CN202110662564A CN113392903A CN 113392903 A CN113392903 A CN 113392903A CN 202110662564 A CN202110662564 A CN 202110662564A CN 113392903 A CN113392903 A CN 113392903A
- Authority
- CN
- China
- Prior art keywords
- clustering
- area
- construction site
- region
- equipment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000010276 construction Methods 0.000 title claims abstract description 100
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000004590 computer program Methods 0.000 claims description 9
- 238000007405 data analysis Methods 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
Landscapes
- Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a method, a system and a device for identifying a construction site area, wherein the method comprises the following steps: acquiring building site information of a known building site in a region to be detected, and determining a target equipment clustering region closest to the known building site from each equipment clustering region according to the building site information; generating a clustering confidence coefficient of a preset clustering standard according to the region of the known construction site and the target equipment clustering region; and if the clustering confidence coefficient does not meet the preset condition, adjusting the preset clustering standard, and clustering the construction site equipment in the area to be detected again based on the adjusted clustering standard so as to determine the area of the unknown construction site in the area to be detected according to the re-clustering result. According to the technical scheme provided by the invention, the efficiency of site identification can be improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method, a system and a device for identifying a construction site area.
Background
In order to improve the safety of the construction of a construction site and to achieve a comprehensive monitoring of the construction site, it is currently necessary to record the presence of the construction site in the area. In practical applications, however, partially non-compliant sites may be in a situation of being under report, resulting in site location and quantity statistics that are not comprehensive, which may lead to a greater safety hazard.
It is considered that if the sites of suspected construction sites are counted manually, a lot of manpower and material resources are consumed, and the counting efficiency is low. Therefore, the suspected site of the construction site can be analyzed based on the positioning information of construction site equipment such as a muck truck. Specifically, in one prior art, the known location and the location of the muck truck may be clustered separately, and whether the location of the muck truck is a known location or an unknown location may be determined by calculating a distance. And if a certain unknown site repeatedly appears for continuous unknown sites, the fact that the muck truck repeatedly reciprocates at the unknown site is indicated, and therefore the unknown site is determined to be the site of the suspected construction site.
However, in the prior art, the muck vehicle and the known location need to be clustered respectively, and the method for screening the suspected site is complicated, so that the efficiency of site identification is low.
Disclosure of Invention
The invention provides a method, a system and a device for identifying a construction site area, which can improve the efficiency of construction site identification.
In order to solve the above problems, the present invention provides a method for identifying a worksite area, which includes clustering, according to a preset clustering standard, worksite devices in a region to be detected to obtain a device clustering region; the method comprises the following steps: acquiring building site information of a known building site in the region to be detected, and determining a target equipment clustering region closest to the known building site from each equipment clustering region according to the building site information; generating a clustering confidence coefficient of the preset clustering standard according to the region of the known construction site and the target equipment clustering region; and if the clustering confidence coefficient does not meet the preset condition, adjusting the preset clustering standard, and clustering the construction site equipment in the area to be detected again based on the adjusted clustering standard so as to determine the area of the unknown construction site in the area to be detected according to the re-clustering result.
In one embodiment, the device cluster region is generated as follows: acquiring positioning information uploaded by the construction site equipment in the area to be detected, clustering the geographical positions represented by the positioning information according to a preset clustering standard, and generating an equipment clustering area corresponding to the construction site equipment in the area to be detected.
In one embodiment, determining the target device cluster region closest to the known worksite comprises: determining a construction site central point in the known construction site, and respectively determining a clustering central point of each equipment clustering area; and calculating the distance between the center point of the construction site and each clustering center point, and taking the equipment clustering region where the clustering center point with the shortest distance is located as the target equipment clustering region closest to the known construction site.
In one embodiment, generating a cluster confidence for the preset clustering criteria comprises: determining a union area and an intersection area of the region of the known worksite and the target device cluster region, and counting a first number of worksite devices contained in the union area and a second number of worksite devices contained in the intersection area; and taking the ratio of the first quantity to the second quantity as the clustering confidence of the preset clustering standard.
In one embodiment, generating a cluster confidence for the preset clustering criteria comprises: and counting the union area and the intersection area of the known construction site and the clustering area of the target equipment, and taking the ratio of the intersection area to the union area as the clustering confidence of the preset clustering standard.
In one embodiment, the preset clustering criterion is one of a plurality of candidate clustering criteria; the clustering confidence coefficient not meeting the preset condition comprises the following steps: the cluster confidence is not the maximum value among the cluster confidence corresponding to each candidate clustering criterion.
In one embodiment, determining the area of the unknown worksite in the area to be detected based on the result of the re-clustering comprises: and calculating the clustering confidence corresponding to the re-clustering result, and if the clustering confidence corresponding to the re-clustering result is the maximum value in the clustering confidence corresponding to each candidate clustering standard, determining the region of the unknown construction site in the region to be detected according to the re-clustering result.
In one embodiment, determining the area of the unknown worksite in the area to be detected based on the result of the re-clustering comprises: determining a clustering contour corresponding to each re-clustering result in the area to be detected, and determining a construction site area based on the clustering contour; taking the area of the work site other than the area of the known work site as the area of the unknown work site in the area to be detected.
In order to solve the above problem, the present invention provides, in another aspect, a system for identifying a worksite area, where the system is provided with an equipment clustering area obtained by clustering worksite equipment in a region to be detected according to a preset clustering standard; the system comprises: the equipment clustering unit is used for acquiring the construction site information of a known construction site in the to-be-detected area, and determining a target equipment clustering area closest to the known construction site from each equipment clustering area according to the construction site information; a confidence generating unit, configured to generate a clustering confidence of the preset clustering standard according to the region of the known worksite and the target device clustering region; and the construction site identification unit is used for adjusting the preset clustering standard if the clustering confidence coefficient does not meet the preset condition, and re-clustering the construction site equipment in the area to be detected based on the adjusted clustering standard so as to determine the area of the unknown construction site in the area to be detected according to the re-clustering result.
In order to solve the above problem, according to another aspect of the present invention, there is provided a device for identifying a worksite area, the device including a memory for storing a computer program, and a processor, wherein the computer program, when executed by the processor, implements the method for identifying a worksite area.
In order to solve the above problem, another aspect of the present invention also provides a computer-readable storage medium for storing a computer program, which when executed by a processor, implements the above-described method for identifying a region of a worksite.
The invention has the following advantages:
according to the technical scheme provided by the embodiment of the application, the building site equipment in the area to be detected can be preliminarily clustered by utilizing the preset clustering standard, and then the closest target equipment clustering area can be determined for the known building site. In theory, it is known that the region of the worksite and the closest target device cluster region should substantially coincide, but the preset cluster criteria may not be selected accurately enough, resulting in the two not coinciding. In view of this, a cluster confidence for the preset clustering criteria may be generated based on the actual area of the known worksite and the target device clustering area. And if the clustering confidence coefficient is not the maximum value in the clustering confidence coefficients corresponding to the candidate clustering standards, indicating that the result obtained by clustering according to the current preset clustering standards is not accurate. Finally, the clustering criteria are continually adjusted according to the clustering confidence, so that the actual region of the known worksite can substantially coincide with the closest target device clustering region. Like this, the clustering region of building site equipment alright in order to approximate the representation building site region, through carrying out the analysis to the clustering result, alright in order to determine the region of unknown building site in waiting to detect the region.
Therefore, the most appropriate clustering standard can be screened out by taking the data of the known construction site as the reference, and the region of the unknown construction site can be accurately identified in the region to be detected through the clustering result generated by the most appropriate clustering standard. According to the technical scheme, the identification efficiency of the unknown construction site can be improved, and the identification accuracy can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 illustrates a schematic block diagram of a system to which a method for identifying a region of a worksite according to one embodiment of the present application may be applied;
FIG. 2 illustrates a schematic representation of a method of identifying a worksite region in another embodiment of the present application;
FIG. 3 illustrates a functional block diagram of an identification system for a worksite area in one embodiment of the present application;
fig. 4 shows a schematic diagram of a device for identifying a region of a work site according to an embodiment of the present application.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The identification method of the construction site area provided by the application can be applied to the system shown in FIG. 1. In the system, worksite equipment and a data analysis server may be included. The construction site equipment can be equipment which is arranged in a construction site for a long time, such as an excavator with a positioning function, a pile driver and the like. In the construction site equipment, besides the positioning module, a data reporting module can be installed. The data reporting module can report the positioning information acquired by the positioning module to the data analysis server. In addition, the data reporting module can also report the working condition information of the construction site equipment to the data analysis server, so that the data analysis server monitors the working state of the construction site equipment based on the received working condition information. The operating condition information may include, for example, information about the operating time, the oil consumption, and the engine water temperature of the construction site equipment.
In an embodiment of the application, after the data analysis server obtains the positioning information reported by the construction site equipment in the area to be detected, the geographical positions represented by the positioning information can be clustered according to a preset clustering standard, so that an equipment clustering area corresponding to the construction site equipment in the area to be detected is generated. Wherein the preset clustering criteria may define a set of parameter values: the cluster radius r and the cluster number minPts, and the geographic location represented by each positioning information can be regarded as a cluster point. If a point P is centered at a distance r (denoted as the r range) that contains at least minPts points (including point P itself), then the point P may be said to be a core point and other points in the r range are all "directly reachable" by the core point.
Having defined the core points and the meaning of "directly reachable," for a path P1, P2, … … Pn consisting of multiple points, if each point can be "directly reachable" by the next previous point, then point Pn can be said to be "reachable" by P1. It will be understood that in the above path, other points than Pn are necessarily core points.
In this embodiment, a point that is not "reachable" by any point may be referred to as an out-of-office point. Points other than core points and outliers may be referred to as non-core points. Thus, by the definition, each construction site device in the area to be detected can be divided into a core point, a non-core point or an out-of-office point according to the geographical position of the construction site device. After the type of each of the worksite devices is ascertained, a device cluster region corresponding to the worksite device may be generated.
In particular, if a worksite device is a core point, that worksite device may be considered a point in a device cluster area with other points that can be "reached" by it. It can be seen that at least one core point is included in one device clustering region, and non-core points may also be included in the device clustering region, except that the non-core points are usually located at the "edge" of the device clustering region, because the non-core points cannot "reach" other points. The local outer points in the area to be detected can be used as discrete points and do not belong to any equipment clustering area.
Through the method, the construction site equipment in the area to be detected can be clustered according to the parameter values defined by the preset clustering standard, so that the corresponding equipment clustering area is generated. It should be noted that if the parameter value changes, the clustering result will also change, so that different clustering criteria will correspond to different clustering results.
Referring to fig. 2, a method for identifying a region of a worksite according to an embodiment of the present application may include the following steps.
S1: and acquiring the building site information of a known building site in the region to be detected, and determining a target equipment clustering region closest to the known building site from each equipment clustering region according to the building site information.
In this embodiment, worksite information for a known worksite in the area to be detected may be obtained in authoritative official data. The worksite information may include, among other things, the footprint of the worksite, the location at which the worksite is located, the worksite equipment registered in the worksite, etc. In practical applications, in order to improve the identification effect of a work site area, a known work site satisfying the following conditions may be selected: 1. the construction site equipment in the construction site is an excavator and a pile machine; 2. the geographical position distribution of the construction site equipment in the construction site is centralized; 3. the number of worksite devices within a worksite is high. Of course, the desired known site can be flexibly selected according to the requirements of the actual application.
In this embodiment, after the site information of the known site is acquired, the target device cluster region closest to the known site may be determined from the device cluster regions. Generally speaking, since the worksite equipment in the known worksite also performs the aforementioned clustering process, if the clustering accuracy is high, the target equipment cluster region closest to the known worksite should substantially coincide with the region of the known worksite. However, since in practical applications the result of clustering based on parameter values defined by preset clustering criteria may not be particularly accurate. Therefore, the target device clustering area needs to be compared with the area of the corresponding known worksite, so that the clustering criteria are continuously optimized.
In particular, the worksite center point may be determined in a known worksite. The area of the known site occupied in the area to be inspected can be represented by an irregular polygon, and then the geometric center of the irregular polygon can be used as the site center point of the known site. After the worksite center point of the known worksite is determined, the cluster center point of each equipment cluster region can be determined respectively. The cluster center point of the device cluster region may be a point represented by the average longitude and latitude of each point in the device cluster region.
After the building site center point and each clustering center point are determined, the distance between the building site center point and each clustering center point can be calculated, and the equipment clustering area where the clustering center point with the shortest distance is located is used as the target equipment clustering area closest to the known building site.
For each known worksite, a respective target device cluster region may be determined in the manner described above.
S3: and generating a clustering confidence coefficient of the preset clustering standard according to the region of the known construction site and the target equipment clustering region.
In this embodiment, by comparing the region of the known worksite with the closest target device clustering region, a clustering confidence of the preset clustering standard may be generated, and the clustering confidence may be used to represent the clustering accuracy of the preset clustering standard.
In practical applications, the cluster confidence may be expressed in various ways. For example, in a specific application example, a union area and an intersection area of an area of a known worksite and a closest target device clustering area may be counted, and a ratio of the intersection area to the union area may be used as a clustering confidence of the preset clustering criterion.
In one embodiment, for each known site, the ratio between the intersection area and the union area may be calculated, so that for a plurality of known sites, a plurality of ratios may be obtained, and the average of the ratios may be used as the clustering confidence of the preset clustering criterion.
In another embodiment, all known construction sites may be taken as a whole, and the determined clustering regions of the target devices may also be taken as a whole, so as to count the intersection area and the union area between the two whole, and thus, the ratio between the intersection area and the union area obtained in this way may be directly used as the clustering confidence of the preset clustering standard.
In the first calculation method, averaging is performed by calculating a plurality of ratios, although the process is somewhat complicated, the accuracy is high. The second calculation is simpler but may be less accurate than the first calculation. In practical application, a corresponding calculation mode can be selected according to specific requirements.
In one embodiment, given that the worksite equipment may not be distributed in every corner of the worksite, the target equipment cluster region determined based on the worksite equipment clustering results may be smaller than the region of the known worksite, which may result in a lower confidence in the determined clusters if calculated according to the area ratio. To improve the accuracy of the cluster confidence, the cluster confidence may be calculated in this embodiment for the number of worksite devices contained therein.
Specifically, the intersection area and the union area of the known worksite and the closest clustering area of the target device may be determined, then a first number of worksite devices included in the intersection area and a second number of worksite devices included in the union area are counted, and by calculating a ratio of the first number and the second number, the ratio may be used as the clustering confidence of the preset clustering standard.
It should be noted that, in practical applications, the statistical manner of the two quantities participating in the ratio operation may be various. For example, in one application scenario, a first number of worksite devices contained in the area of intersection may be counted, and a third number of worksite devices contained in an area of the known worksite may be counted, and then a ratio of the first number to the third number may be used as a cluster confidence for the preset clustering criteria.
S5: and if the clustering confidence coefficient does not meet the preset condition, adjusting the preset clustering standard, and clustering the construction site equipment in the area to be detected again based on the adjusted clustering standard so as to determine the area of the unknown construction site in the area to be detected according to the re-clustering result.
In this embodiment, the higher the clustering confidence, the higher the clustering accuracy of the preset clustering standard. In practical applications, a plurality of candidate clustering criteria may be prepared in advance, and the preset clustering criteria may be one of the candidate clustering criteria. For each candidate clustering criterion, a respective clustering confidence may be determined in the manner described above.
In this embodiment, after the clustering confidence of the preset clustering standard is calculated, it may be determined whether the clustering confidence is the maximum value among the clustering confidence corresponding to each candidate clustering standard, and if not, it indicates that the clustering confidence of the preset clustering standard does not satisfy the preset condition, and the clustering result generated based on the preset clustering standard may not be accurate. In view of this, the preset clustering standard may be adjusted in a manner of resetting a set of parameter values, i.e., a clustering radius and a clustering number, so as to adjust the preset clustering standard to another candidate clustering standard. And according to the adjusted clustering standard, clustering the construction site equipment in the area to be detected again. And if the clustering confidence corresponding to the re-clustering result is the maximum value in the clustering confidence corresponding to each candidate clustering standard, indicating that the clustering result obtained according to the adjusted clustering precision is the most accurate currently. At this time, an area of an unknown worksite may be determined in the area to be detected according to the result of the re-clustering.
In this embodiment, when determining the region of the unknown worksite, a cluster contour corresponding to each re-clustering result may be determined in the region to be detected. For example, for each re-clustered result, a respective circumscribing polygon may be computed. Since the worksite equipment is typically not spread throughout the corners of the worksite, the area of the circumscribed polygon is smaller than the actual area of the worksite. Then a specified distance (e.g., 100 meters) may be expanded outward based on the circumscribed polygon, so that the area defined by the expanded polygon is taken as the actual area occupied by the worksite. In this way, the region of the work site to be detected can be determined on the basis of the cluster contour corresponding to the result of each re-clustering. For the determined work site area, other work site areas than the area of the known work site may be used as the area of the unknown work site in the area to be detected. The areas of the unknown construction sites can be drawn into a map of the area to be detected in a longitude and latitude coordinate mode, and the unknown construction sites can be checked in the field subsequently, so that the supervision strength is improved.
According to the technical scheme provided by each embodiment of the application, the clustering standard can be continuously optimized by taking the construction site information of the known construction site as a reference, the construction site equipment in the area to be detected is finally clustered by adopting the most accurate clustering standard, the actual area of the construction site is represented by the equipment clustering area, and then the area of the unknown construction site can be effectively searched.
Referring to fig. 3, an embodiment of the present application further provides a system for identifying a worksite area, where the system is provided with an equipment clustering area obtained by clustering worksite equipment in an area to be detected according to a preset clustering standard; the system comprises:
the equipment clustering unit is used for acquiring the construction site information of a known construction site in the to-be-detected area, and determining a target equipment clustering area closest to the known construction site from each equipment clustering area according to the construction site information;
a confidence generating unit, configured to generate a clustering confidence of the preset clustering standard according to the region of the known worksite and the target device clustering region;
and the construction site identification unit is used for adjusting the preset clustering standard if the clustering confidence coefficient does not meet the preset condition, and re-clustering the construction site equipment in the area to be detected based on the adjusted clustering standard so as to determine the area of the unknown construction site in the area to be detected according to the re-clustering result.
Referring to fig. 4, an embodiment of the present application further provides a device for identifying a work area, where the device for identifying a work area includes a memory and a processor, the memory is used for storing a computer program, and the computer program is executed by the processor to implement the method for identifying a work area.
The processor may be a Central Processing Unit (CPU). The Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or a combination thereof.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the methods of the embodiments of the present invention. The processor executes various functional applications and data processing of the processor by executing non-transitory software programs, instructions and modules stored in the memory, that is, the method in the above method embodiment is realized.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and such remote memory may be coupled to the processor via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
An embodiment of the present application also provides a computer-readable storage medium for storing a computer program, which when executed by a processor, implements the above-mentioned method for identifying a worksite region.
According to the technical scheme provided by the embodiment of the application, the building site equipment in the area to be detected can be preliminarily clustered by utilizing the preset clustering standard, and then the closest target equipment clustering area can be determined for the known building site. In theory, it is known that the region of the worksite and the closest target device cluster region should substantially coincide, but the preset cluster criteria may not be selected accurately enough, resulting in the two not coinciding. In view of this, a cluster confidence for the preset clustering criteria may be generated based on the actual area of the known worksite and the target device clustering area. And if the clustering confidence coefficient is not the maximum value in the clustering confidence coefficients corresponding to the candidate clustering standards, indicating that the result obtained by clustering according to the current preset clustering standards is not accurate. Finally, the clustering criteria are continually adjusted according to the clustering confidence, so that the actual region of the known worksite can substantially coincide with the closest target device clustering region. Like this, the clustering region of building site equipment alright in order to approximate the representation building site region, through carrying out the analysis to the clustering result, alright in order to determine the region of unknown building site in waiting to detect the region.
Therefore, the most appropriate clustering standard can be screened out by taking the data of the known construction site as the reference, and the region of the unknown construction site can be accurately identified in the region to be detected through the clustering result generated by the most appropriate clustering standard. According to the technical scheme, the identification efficiency of the unknown construction site can be improved, and the identification accuracy can be improved.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (11)
1. A method for identifying a construction site area is characterized in that an equipment clustering area obtained by clustering construction site equipment in a to-be-detected area according to a preset clustering standard is provided; the method comprises the following steps:
acquiring building site information of a known building site in the region to be detected, and determining a target equipment clustering region closest to the known building site from each equipment clustering region according to the building site information;
generating a clustering confidence coefficient of the preset clustering standard according to the region of the known construction site and the target equipment clustering region;
and if the clustering confidence coefficient does not meet the preset condition, adjusting the preset clustering standard, and clustering the construction site equipment in the area to be detected again based on the adjusted clustering standard so as to determine the area of the unknown construction site in the area to be detected according to the re-clustering result.
2. The method of claim 1, wherein the device cluster region is generated as follows:
acquiring positioning information uploaded by the construction site equipment in the area to be detected, clustering the geographical positions represented by the positioning information according to a preset clustering standard, and generating an equipment clustering area corresponding to the construction site equipment in the area to be detected.
3. The method of claim 1, wherein determining a target device cluster region closest to the known worksite comprises:
determining a construction site central point in the known construction site, and respectively determining a clustering central point of each equipment clustering area;
and calculating the distance between the center point of the construction site and each clustering center point, and taking the equipment clustering region where the clustering center point with the shortest distance is located as the target equipment clustering region closest to the known construction site.
4. The method of claim 1, wherein generating a cluster confidence for the preset clustering criteria comprises:
determining a union area and an intersection area of the region of the known worksite and the target device cluster region, and counting a first number of worksite devices contained in the intersection area and a second number of worksite devices contained in the union area;
and taking the ratio of the first quantity to the second quantity as the clustering confidence of the preset clustering standard.
5. The method of claim 1, wherein generating a cluster confidence for the preset clustering criteria comprises:
and counting the union area and the intersection area of the known construction site and the clustering area of the target equipment, and taking the ratio of the intersection area to the union area as the clustering confidence of the preset clustering standard.
6. The method of claim 1, wherein the preset clustering criterion is one of a plurality of candidate clustering criteria;
the clustering confidence coefficient not meeting the preset condition comprises the following steps: the cluster confidence is not the maximum value among the cluster confidence corresponding to each candidate clustering criterion.
7. The method of claim 6, wherein determining the area of the unknown worksite in the area to be detected based on the re-clustering results comprises:
and if the clustering confidence corresponding to the re-clustering result is the maximum value in the clustering confidence corresponding to each candidate clustering standard, determining the region of the unknown construction site in the region to be detected according to the re-clustering result.
8. The method according to claim 1 or 7, wherein determining the area of the unknown worksite in the area to be detected from the result of the re-clustering comprises:
determining a clustering contour corresponding to each re-clustering result in the area to be detected, and determining a construction site area based on the clustering contour;
taking the area of the work site other than the area of the known work site as the area of the unknown work site in the area to be detected.
9. A system for identifying a construction site area is characterized in that the system is provided with an equipment clustering area obtained by clustering construction site equipment in a to-be-detected area according to a preset clustering standard; the system comprises:
the equipment clustering unit is used for acquiring the construction site information of a known construction site in the to-be-detected area, and determining a target equipment clustering area closest to the known construction site from each equipment clustering area according to the construction site information;
a confidence generating unit, configured to generate a clustering confidence of the preset clustering standard according to the region of the known worksite and the target device clustering region;
and the construction site identification unit is used for adjusting the preset clustering standard if the clustering confidence coefficient does not meet the preset condition, and re-clustering the construction site equipment in the area to be detected based on the adjusted clustering standard so as to determine the area of the unknown construction site in the area to be detected according to the re-clustering result.
10. An apparatus for identifying a worksite area, comprising a memory for storing a computer program and a processor, the computer program, when executed by the processor, implementing the method of any one of claims 1 to 8.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium is used to store a computer program which, when executed by a processor, implements the method of any one of claims 1 to 8.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110662564.1A CN113392903A (en) | 2021-06-15 | 2021-06-15 | Method, system and device for identifying construction site area |
| PCT/CN2022/096947 WO2022262595A1 (en) | 2021-06-15 | 2022-06-02 | Method, system, and apparatus for identifying worksite region, and computer-readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110662564.1A CN113392903A (en) | 2021-06-15 | 2021-06-15 | Method, system and device for identifying construction site area |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113392903A true CN113392903A (en) | 2021-09-14 |
Family
ID=77621212
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110662564.1A Pending CN113392903A (en) | 2021-06-15 | 2021-06-15 | Method, system and device for identifying construction site area |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN113392903A (en) |
| WO (1) | WO2022262595A1 (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114333039A (en) * | 2022-03-03 | 2022-04-12 | 济南博观智能科技有限公司 | Portrait clustering method, device and medium |
| WO2022262595A1 (en) * | 2021-06-15 | 2022-12-22 | 上海华兴数字科技有限公司 | Method, system, and apparatus for identifying worksite region, and computer-readable storage medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130108180A1 (en) * | 2011-10-26 | 2013-05-02 | Sony Corporation | Information processing device, information processing method, and program |
| CN105844283A (en) * | 2015-01-16 | 2016-08-10 | 阿里巴巴集团控股有限公司 | Method for identifying category of image, image search method and image search device |
| CN110659600A (en) * | 2019-09-19 | 2020-01-07 | 北京百度网讯科技有限公司 | Object detection method, device and equipment |
| CN111488417A (en) * | 2019-01-28 | 2020-08-04 | 阿里巴巴集团控股有限公司 | Information processing method, system, device, equipment and computer storage medium |
| CN111523786A (en) * | 2020-04-17 | 2020-08-11 | 上海华兴数字科技有限公司 | Electronic fence adjusting method and device and electronic equipment |
| US20200327707A1 (en) * | 2019-04-10 | 2020-10-15 | Safemine Ag | Gnss-based map generation |
| CN112035454A (en) * | 2020-08-28 | 2020-12-04 | 江苏徐工信息技术股份有限公司 | Black-work land detection algorithm based on cluster integration |
| CN112348091A (en) * | 2020-11-10 | 2021-02-09 | 成都福立盟环保大数据有限公司 | Dual-clustering blackwork site identification algorithm based on GPS (global positioning system) of muck truck |
| CN112508989A (en) * | 2020-11-20 | 2021-03-16 | 腾讯科技（深圳）有限公司 | Image processing method, device, server and medium |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10631129B1 (en) * | 2018-10-01 | 2020-04-21 | International Business Machines Corporation | First responder feedback-based emergency response floor identification |
| CN113392903A (en) * | 2021-06-15 | 2021-09-14 | 上海华兴数字科技有限公司 | Method, system and device for identifying construction site area |
-
2021
- 2021-06-15 CN CN202110662564.1A patent/CN113392903A/en active Pending
-
2022
- 2022-06-02 WO PCT/CN2022/096947 patent/WO2022262595A1/en active Application Filing
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130108180A1 (en) * | 2011-10-26 | 2013-05-02 | Sony Corporation | Information processing device, information processing method, and program |
| CN105844283A (en) * | 2015-01-16 | 2016-08-10 | 阿里巴巴集团控股有限公司 | Method for identifying category of image, image search method and image search device |
| CN111488417A (en) * | 2019-01-28 | 2020-08-04 | 阿里巴巴集团控股有限公司 | Information processing method, system, device, equipment and computer storage medium |
| US20200327707A1 (en) * | 2019-04-10 | 2020-10-15 | Safemine Ag | Gnss-based map generation |
| CN110659600A (en) * | 2019-09-19 | 2020-01-07 | 北京百度网讯科技有限公司 | Object detection method, device and equipment |
| CN111523786A (en) * | 2020-04-17 | 2020-08-11 | 上海华兴数字科技有限公司 | Electronic fence adjusting method and device and electronic equipment |
| CN112035454A (en) * | 2020-08-28 | 2020-12-04 | 江苏徐工信息技术股份有限公司 | Black-work land detection algorithm based on cluster integration |
| CN112348091A (en) * | 2020-11-10 | 2021-02-09 | 成都福立盟环保大数据有限公司 | Dual-clustering blackwork site identification algorithm based on GPS (global positioning system) of muck truck |
| CN112508989A (en) * | 2020-11-20 | 2021-03-16 | 腾讯科技（深圳）有限公司 | Image processing method, device, server and medium |
Non-Patent Citations (1)
| Title |
|---|
| 韦鹏程等: "基于人工智能算法的研究与应用", 31 May 2021, pages: 36 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022262595A1 (en) * | 2021-06-15 | 2022-12-22 | 上海华兴数字科技有限公司 | Method, system, and apparatus for identifying worksite region, and computer-readable storage medium |
| CN114333039A (en) * | 2022-03-03 | 2022-04-12 | 济南博观智能科技有限公司 | Portrait clustering method, device and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022262595A1 (en) | 2022-12-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20210021956A1 (en) | System and Method for Determining a Location Area of a Mobile User | |
| US10139471B2 (en) | Supporting a collaborative collection of data | |
| WO2022262595A1 (en) | Method, system, and apparatus for identifying worksite region, and computer-readable storage medium | |
| EP3242144B1 (en) | Improving a positioning performance | |
| CN108124267B (en) | Automatic planning method and device for base station | |
| CN104702432B (en) | The method and server alerted based on band of position division | |
| CN111935820B (en) | Positioning implementation method based on wireless network and related equipment | |
| US20220342024A1 (en) | Reconfiguration of a radio positioning support system | |
| WO2019200139A1 (en) | Wireless network service assessment | |
| CN114374449A (en) | Interference source determination method, device, equipment and medium | |
| CN118171035B (en) | Method and device for early warning of people stream heating power, electronic equipment and storage medium | |
| CN111475746B (en) | Point-of-interest mining method, device, computer equipment and storage medium | |
| CN112199453A (en) | Traffic hot spot clustering method, device, equipment and computer storage medium | |
| CN109246728B (en) | Method and device for identifying coverage abnormal cell | |
| CN109947819B (en) | Suspected cheating area mining method and device, computer equipment and storage medium | |
| CN114838704A (en) | Height detection method and device and computer readable storage medium | |
| US20180167779A1 (en) | Detection of infrastructure changes in opportunity signal data | |
| CN114117121A (en) | Data acquisition method for smart city | |
| CN115146007A (en) | Map data processing method and device | |
| CN113807125A (en) | Emergency lane occupation detection method and device, computer equipment and storage medium | |
| CN107182066B (en) | Method and device for checking whole-network station work parameters based on periodic measurement data | |
| CN111988807A (en) | Network problem positioning method and device based on big data and computing equipment | |
| CN116170814B (en) | Resource allocation method, device, equipment and storage medium | |
| CN115327497B (en) | Radar detection range determining method, radar detection range determining device, electronic equipment and readable medium | |
| CN112584313B (en) | Weak coverage area positioning method, device, equipment and computer storage medium |
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 |