A method, system and device for identifying construction site areas

Abstract

The present application provides a method, system and device for identifying a construction site area, wherein the method includes: obtaining construction site information of a known construction site in an area to be detected, and determining a target equipment clustering area closest to the known construction site from various equipment clustering areas based on the construction site information; generating a clustering confidence of a preset clustering standard based on the area of ​​the known construction site and the target equipment clustering area; if the clustering confidence does not meet a preset condition, adjusting the preset clustering standard, 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 based on the re-clustering result. The technical solution provided by the present invention can improve the efficiency of construction site identification.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method, system and device for identifying a construction site area. Background Art

[0002] In order to improve the safety of construction sites and realize comprehensive monitoring of construction sites, it is currently necessary to record the construction sites in the area. However, in actual applications, some informal construction sites may be concealed, resulting in incomplete statistics on the location and number of construction sites, which will bring greater safety hazards.

[0003] Considering that if the locations of suspected construction sites are counted manually, it will consume a lot of manpower and material resources, and the statistical efficiency is relatively low. Therefore, the locations of suspected construction sites can be analyzed based on the positioning information of construction site equipment such as dump trucks. Specifically, one method in the prior art can cluster the locations of known locations and dump trucks respectively, and determine whether the location of the dump truck is a known location or an unknown location by calculating the distance. For continuous unknown locations, if an unknown location appears repeatedly, it means that the dump truck repeatedly goes back and forth at the unknown location, thereby determining that the unknown location is the location of a suspected construction site.

[0004] However, this method in the prior art requires that the muck trucks and known locations be clustered separately, and the method of screening the locations of suspected construction sites is also relatively cumbersome, resulting in low construction site identification efficiency. Summary of the invention

[0005] The present invention provides a method, system and device for identifying a construction site area, which can improve the efficiency of construction site identification.

[0006] In order to solve the above problems, the present invention provides a method for identifying a construction site area, and provides an equipment clustering area obtained by clustering the construction site equipment in the area to be detected according to a preset clustering standard; the method includes: obtaining construction site information of a known construction site in the area to be detected, and determining a target equipment clustering area closest to the known construction site from each of the equipment clustering areas based on the construction site information; generating a clustering confidence of the preset clustering standard based on the area of ​​the known construction site and the target equipment clustering area; if the clustering confidence does not meet the preset conditions, adjusting the preset clustering standard, 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 based on the result of the re-clustering.

[0007] In one embodiment, the equipment clustering area is generated in the following manner: the positioning information uploaded by the construction site equipment in the area to be detected is obtained, and the geographical locations represented by the positioning information are clustered according to a preset clustering standard to generate the equipment clustering area corresponding to the construction site equipment in the area to be detected.

[0008] In one embodiment, determining the target equipment clustering area that is closest to the known construction site includes: determining the construction site center point in the known construction site, and respectively determining the cluster center points of each of the equipment clustering areas; calculating the distance between the construction site center point and each of the cluster center points, and taking the equipment clustering area where the cluster center point with the shortest distance is located as the target equipment clustering area closest to the known construction site.

[0009] In one embodiment, generating the clustering confidence of the preset clustering standard includes: determining the union area and the intersection area of ​​the area of ​​the known construction site and the target equipment clustering area, and counting the first number of construction site equipment contained in the union area and the second number of construction site equipment contained in the intersection area; and using the ratio of the first number to the second number as the clustering confidence of the preset clustering standard.

[0010] In one embodiment, generating the clustering confidence of the preset clustering standard includes: counting the union area and intersection area of ​​the known construction site area and the target equipment cluster area, and taking the ratio of the intersection area to the union area as the clustering confidence of the preset clustering standard.

[0011] In one embodiment, the preset clustering standard is one of a plurality of candidate clustering standards; the clustering confidence not satisfying the preset condition includes: the clustering confidence is not the maximum value among the clustering confidences corresponding to the candidate clustering standards.

[0012] In one embodiment, determining the area of ​​the unknown construction site in the area to be detected based on the result of re-clustering includes: calculating the clustering confidence corresponding to the result of re-clustering; if the clustering confidence corresponding to the result of re-clustering is the maximum value among the clustering confidences corresponding to each candidate clustering standard, determining the area of ​​the unknown construction site in the area to be detected based on the result of re-clustering.

[0013] In one embodiment, determining the area of ​​unknown construction sites in the area to be detected based on the results of re-clustering includes: determining the cluster outlines corresponding to the results of each re-clustering in the area to be detected, and determining the construction site area based on the cluster outlines; and treating other construction site areas except the areas of the known construction sites as the areas of unknown construction sites in the area to be detected.

[0014] In order to solve the above problems, the present invention further provides a construction site area identification system on the other hand, the system provides an equipment clustering area obtained by clustering the construction site equipment in the area to be detected according to a preset clustering standard; the system includes: an equipment clustering unit, used to obtain the construction site information of the known construction sites in the area to be detected, and determine the target equipment clustering area closest to the known construction site from each of the equipment clustering areas based on the construction site information; a confidence generation unit, used to generate the clustering confidence of the preset clustering standard based on the area of ​​the known construction sites and the target equipment clustering area; a construction site identification unit, used to adjust the preset clustering standard if the clustering confidence does not meet the preset conditions, and re-cluster 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.

[0015] In order to solve the above problems, the present invention further provides a device for identifying a construction site area on the other hand. The device for identifying a construction site area includes a memory and a processor. The memory is used to store a computer program. When the computer program is executed by the processor, the above-mentioned method for identifying a construction site area is implemented.

[0016] In order to solve the above problem, the present invention further provides a computer-readable storage medium on the other hand, wherein the computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the above-mentioned method for identifying a construction site area is implemented.

[0017] The present invention has the following advantages:

[0018] The technical solution provided by the above-mentioned embodiment of the present application can use the preset clustering standard to preliminarily cluster the construction site equipment in the area to be detected, and then determine the closest target equipment clustering area for the known construction site. Theoretically, the area of ​​the known construction site and the closest target equipment clustering area should basically overlap, but because the selection of the preset clustering standard may not be accurate enough, the two will not overlap. In view of this, the clustering confidence of the preset clustering standard can be generated according to the actual area of ​​the known construction site and the target equipment clustering area. If the clustering confidence is not the maximum value among the clustering confidences corresponding to the candidate clustering standards, it indicates that the result obtained by clustering according to the current preset clustering standard is not accurate. Finally, the clustering standard is continuously adjusted according to the clustering confidence, so that the actual area of ​​the known construction site can basically overlap with the closest target equipment clustering area. In this way, the clustering area of ​​the construction site equipment can approximately represent the construction site area, and by analyzing the clustering results, the area of ​​the unknown construction site can be determined in the area to be detected.

[0019] As can be seen from the above, by using the data of known construction sites as a reference, the most appropriate clustering standard can be screened out, and the clustering results generated by the most appropriate clustering standard can accurately identify the area of ​​the unknown construction site in the area to be detected. The technical solution provided in the implementation mode of the present application can not only improve the recognition efficiency of the unknown construction site, but also improve the recognition accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 A schematic diagram of the structure of a system used in a method for identifying a construction site area in one embodiment of the present application is shown;

[0022] Figure 2 A schematic diagram showing a method for identifying a construction site area in another embodiment of the present application is shown;

[0023] Figure 3 A schematic diagram showing the functional modules of a construction site area recognition system in one embodiment of the present application is shown;

[0024] Figure 4 A schematic structural diagram of a construction site area identification device in one embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0027] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0028] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0029] The method for identifying a construction site area provided in this application can be applied to Figure 1 In the system shown. In the system, construction site equipment and a data analysis server may be included. Among them, the construction site equipment may be equipment such as excavators and pile drivers with positioning functions that are in the construction site for a long time. In the construction site equipment, in addition to installing a positioning module, a data reporting module may also be installed. The data reporting module may report the positioning information collected by the positioning module to the data analysis server. In addition, the data reporting module may also report the working condition information of the construction site equipment to the data analysis server, so that the data analysis server can monitor the working status of the construction site equipment based on the received working condition information. Among them, the working condition information may, for example, include information such as the working time, fuel consumption, and engine water temperature of the construction site equipment.

[0030] In one embodiment of the present application, after the data analysis server obtains the positioning information reported by the construction site equipment in the area to be detected, the geographical locations represented by these positioning information can be clustered according to the preset clustering standard, thereby generating an equipment clustering area corresponding to the construction site equipment in the area to be detected. Among them, the preset clustering standard can define a set of parameter values: cluster radius r and cluster number minPts, and each geographical location represented by the positioning information can be regarded as a cluster point. If a point P is taken as the center, and there are at least minPts points (including point P itself) within a range of distance r (denoted as r range), then the point P can be called a core point, and the other points within the r range are "directly reachable" from the core point.

[0031] After defining the meaning of core points and "directly reachable", for a path consisting of multiple points P1, P2, ... Pn, if each point can be "directly reachable" from the adjacent previous point, then point Pn can be said to be "reachable" from P1. It is not difficult to understand that in the above path, except for Pn, all other points must be core points.

[0032] In this embodiment, any point that cannot be "reached" by any other point can be called an outlier point. All other points except core points and outliers can be called non-core points. In this way, through the above definition, each construction site equipment in the area to be detected can be divided into core points, non-core points or outliers according to their geographical location. After clarifying the type of each construction site equipment, the equipment clustering area corresponding to the construction site equipment can be generated.

[0033] Specifically, if a certain construction site equipment is a core point, then the construction site equipment and other points that can be "reached" by it can be regarded as points in a device clustering area. It can be seen that in a device clustering area, there will be at least one core point, and non-core points can also be included in the device clustering area, but non-core points are usually located at the "edge" of the device clustering area because non-core points cannot "reach" other points. Outliers in the area to be detected can be regarded as discrete points that do not belong to any device clustering area.

[0034] In the above manner, the construction site equipment in the detection area can be clustered according to the parameter values ​​defined by the preset clustering standard, thereby generating the corresponding equipment clustering area. It should be noted that if the parameter value changes, the clustering result will usually change as well. Therefore, different clustering standards will correspond to different clustering results.

[0035] See also Figure 2 A method for identifying a construction site area provided in one embodiment of the present application may include the following steps.

[0036] S1: Acquire construction site information of known construction sites in the area to be detected, and determine a target equipment clustering area closest to the known construction site from each of the equipment clustering areas based on the construction site information.

[0037] In this embodiment, the construction site information of the known construction sites in the area to be detected can be obtained from the authoritative official data. The construction site information may include information such as the area occupied by the construction site, the location of the construction site, and the construction site equipment registered in the construction site. In practical applications, in order to improve the recognition effect of the construction site area, known construction sites that meet the following conditions can be selected: 1. The construction site equipment in the construction site is an excavator and a pile driver; 2. The geographical location distribution of the construction site equipment in the construction site is relatively concentrated; 3. The number of construction site equipment in the construction site is relatively large. Of course, according to the needs of the actual application, the required known construction site can be flexibly selected.

[0038] In this embodiment, after the construction site information of a known construction site is obtained, the target equipment clustering area that is closest to the known construction site can be determined from the aforementioned equipment clustering areas. Generally speaking, since the construction site equipment in the known construction site has also undergone the aforementioned clustering process, if the clustering accuracy is high, the target equipment clustering area that is closest to the known construction site should basically overlap with the area of ​​the known construction site. However, in actual applications, the results of clustering based on the parameter values ​​defined by the preset clustering criteria may not be particularly accurate. Therefore, it is necessary to compare the target equipment clustering area with the corresponding area of ​​the known construction site, so as to continuously optimize the clustering criteria.

[0039] Specifically, the construction site center point can be determined in the known construction site. The area occupied by the known construction site in the area to be detected can be represented by an irregular polygon, and then the geometric center of the irregular polygon can be used as the construction site center point of the known construction site. After determining the construction site center point of the known construction site, the cluster center points of each of the above-mentioned equipment clustering areas can be determined respectively. Among them, the cluster center point of the equipment clustering area can be a point represented by the average longitude and latitude of each point in the equipment clustering area.

[0040] After determining the above-mentioned construction site center point and each cluster center point, the distance between the construction site center point and each cluster center point can be calculated, and the equipment cluster area where the cluster center point with the shortest distance is located is used as the target equipment cluster area closest to the known construction site.

[0041] For each known construction site, the respective target equipment clustering area can be determined by the above method.

[0042] S3: Generate a clustering confidence of the preset clustering standard according to the area of ​​the known construction site and the target equipment clustering area.

[0043] In this embodiment, by comparing the area of ​​the known construction site with the closest target equipment clustering area, a clustering confidence of a preset clustering standard can be generated, and the clustering confidence can be used to characterize the clustering accuracy of the preset clustering standard.

[0044] In practical applications, the clustering confidence can be expressed in a variety of ways. For example, in a specific application example, the union area and intersection area of ​​the known construction site area and the closest target equipment cluster area can be counted, and the ratio of the intersection area to the union area is used as the clustering confidence of the preset clustering standard.

[0045] In one embodiment, for each known construction site, the ratio between the intersection area and the union area can be calculated. In this way, for multiple known construction sites, multiple ratios can be obtained, and the average value of these ratios can be used as the clustering confidence of the preset clustering standard.

[0046] In another embodiment, all known construction sites can be taken as a whole, and the determined target equipment clustering areas can also be taken as a whole, so as to count the intersection area and union area between the two wholes. In this way, the ratio between the intersection area and the union area can be directly used as the clustering confidence of the preset clustering standard.

[0047] The first calculation method mentioned above calculates multiple ratios and then averages them. Although the process is slightly cumbersome, it has higher accuracy. The second calculation method is relatively simple, but the accuracy may be slightly worse than the first calculation method. In practical applications, the corresponding calculation method can be selected according to specific needs.

[0048] In one embodiment, considering that the construction site equipment may not be distributed in every corner of the construction site, the target equipment clustering area determined based on the clustering result of the construction site equipment may be smaller than the area of ​​the known construction site. If the area ratio is calculated in the above manner, the clustering confidence may be smaller. In order to improve the accuracy of the clustering confidence, in this embodiment, the clustering confidence may be calculated based on the number of construction site equipment contained therein.

[0049] Specifically, the intersection area and union area of ​​the known construction site area and the closest target equipment clustering area can be determined first, and then the first number of construction site equipment contained in the intersection area and the second number of construction site equipment contained in the union area can be counted. By calculating the ratio of the first number to the second number, the ratio can be used as the clustering confidence of the preset clustering standard.

[0050] It should be noted that in practical applications, the two quantities involved in the ratio calculation can be counted in various ways. For example, in one application scenario, the first quantity of construction site equipment contained in the intersection area can be counted, and the third quantity of construction site equipment contained in the area of ​​the known construction site can be counted, and then the ratio of the first quantity to the third quantity is used as the clustering confidence of the preset clustering standard.

[0051] S5: If the clustering confidence does not meet the preset conditions, the preset clustering standard is adjusted, and the construction site equipment in the area to be detected is re-clustered based on the adjusted clustering standard to determine the area of ​​the unknown construction site in the area to be detected according to the re-clustering result.

[0052] In this embodiment, the higher the clustering confidence, the higher the clustering accuracy of the preset clustering standard. In practical applications, multiple candidate clustering standards can be prepared in advance, and the above-mentioned preset clustering standard can be one of the candidate clustering standards. For each candidate clustering standard, the respective clustering confidence can be determined in the above-mentioned manner.

[0053] In this embodiment, after calculating the clustering confidence of the preset clustering standard, it can be determined whether the clustering confidence is the maximum value among the clustering confidences corresponding to the candidate clustering standards. If it is not the maximum value, it indicates that the clustering confidence of the preset clustering standard does not meet the preset conditions, and the clustering result generated based on the preset clustering standard may not be accurate. In view of this, the preset clustering standard can be adjusted, and the adjustment method can be to reset the clustering radius and the number of clusters. This group of parameter values ​​adjusts the preset clustering standard to another candidate clustering standard. According to the adjusted clustering standard, the construction site equipment in the area to be detected can be re-clustered. If the clustering confidence corresponding to the result of the re-clustering is the maximum value among the clustering confidences corresponding to the candidate clustering standards, it indicates that the clustering result obtained according to the adjusted clustering accuracy is currently the most accurate. At this time, the area of ​​the unknown construction site can be determined in the area to be detected based on the result of the re-clustering.

[0054] In this embodiment, when determining the area of ​​the unknown construction site, the cluster outline corresponding to each re-clustering result can be determined in the area to be detected. For example, for each re-clustering result, a respective circumscribed polygon can be calculated. Since the construction site equipment is usually not spread all over the corners of the construction site, the area of ​​the circumscribed polygon is smaller than the actual area of ​​the construction site. Then, based on the circumscribed polygon, a specified distance (for example, 100 meters) can be expanded outward, so that the area defined by the expanded polygon is used as the actual area occupied by the construction site. In this way, based on the cluster outline corresponding to each re-clustering result, the construction site area in the area to be detected can be determined. For the determined construction site area, other construction site areas except the known construction site areas can be used as the unknown construction site areas in the area to be detected. The areas of these unknown construction sites can be drawn into the map of the area to be detected in the form of longitude and latitude coordinates, and these unknown construction sites can be subsequently checked on the spot, thereby improving the supervision efforts.

[0055] The technical solutions provided by the above-mentioned various embodiments of the present application can continuously optimize the clustering standards by taking the construction site information of known construction sites as a reference, and finally adopt the most accurate clustering standards to cluster the construction site equipment in the detection area, and characterize the actual area of ​​the construction site through the equipment clustering area, thereby effectively screening out the area of ​​unknown construction sites.

[0056] See also Figure 3 One embodiment of the present application further provides a construction site area recognition system, the system providing an equipment clustering area obtained by clustering construction site equipment in a detection area according to a preset clustering standard; the system comprising:

[0057] An equipment clustering unit, used for acquiring construction site information of known construction sites in the area to be detected, and determining a target equipment clustering area closest to the known construction site from each of the equipment clustering areas according to the construction site information;

[0058] A confidence generating unit, configured to generate a clustering confidence of the preset clustering standard according to the area of ​​the known construction site and the target equipment clustering area;

[0059] The construction site identification unit is used to adjust the preset clustering standard if the clustering confidence does not meet the preset conditions, and re-cluster 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.

[0060] See also Figure 4 One embodiment of the present application further provides a construction site area identification device, the construction site area identification device comprising a memory and a processor, the memory is used to store a computer program, and when the computer program is executed by the processor, the above-mentioned construction site area identification method is implemented.

[0061] The processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0062] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the method in the embodiment of the present invention. The processor executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory, that is, implementing the method in the above method embodiment.

[0063] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0064] One embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the above-mentioned method for identifying a construction site area is implemented.

[0065] The technical solution provided by the above-mentioned embodiment of the present application can use the preset clustering standard to preliminarily cluster the construction site equipment in the area to be detected, and then determine the closest target equipment clustering area for the known construction site. Theoretically, the area of ​​the known construction site and the closest target equipment clustering area should basically overlap, but because the selection of the preset clustering standard may not be accurate enough, the two will not overlap. In view of this, the clustering confidence of the preset clustering standard can be generated according to the actual area of ​​the known construction site and the target equipment clustering area. If the clustering confidence is not the maximum value among the clustering confidences corresponding to the candidate clustering standards, it indicates that the result obtained by clustering according to the current preset clustering standard is not accurate. Finally, the clustering standard is continuously adjusted according to the clustering confidence, so that the actual area of ​​the known construction site can basically overlap with the closest target equipment clustering area. In this way, the clustering area of ​​the construction site equipment can approximately represent the construction site area, and by analyzing the clustering results, the area of ​​the unknown construction site can be determined in the area to be detected.

[0066] As can be seen from the above, by using the data of known construction sites as a reference, the most appropriate clustering standard can be screened out, and the clustering results generated by the most appropriate clustering standard can accurately identify the area of ​​the unknown construction site in the area to be detected. The technical solution provided in the implementation mode of the present application can not only improve the recognition efficiency of the unknown construction site, but also improve the recognition accuracy.

[0067] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A method for identifying a construction site area, characterized in that: An equipment clustering area is provided, which is obtained by clustering the construction site equipment in the area to be detected according to a preset clustering standard; the method comprises: Acquire construction site information of known construction sites in the area to be detected, and determine, from each of the equipment clustering areas, a target equipment clustering area closest to the known construction site based on the construction site information; Generating a clustering confidence of the preset clustering standard according to the area of ​​the known construction site and the target equipment clustering area; If the clustering confidence does not meet the preset condition, the preset clustering standard is adjusted, and the construction site equipment in the to-be-detected area is re-clustered based on the adjusted clustering standard, so as to determine the area of ​​the unknown construction site in the to-be-detected area according to the re-clustering result; the preset clustering standard is one of multiple candidate clustering standards; the clustering confidence does not meet the preset condition including: the clustering confidence is not the maximum value among the clustering confidences corresponding to each candidate clustering standard; The step of generating the clustering confidence of the preset clustering standard includes: Determine a union area and an intersection area of ​​the known construction site area and the target equipment cluster area, and count a first number of construction site equipment included in the intersection area and a second number of construction site equipment included in the union area; Using the ratio of the first number to the second number as the clustering confidence of the preset clustering standard; The area of ​​the unknown construction site determined in the to-be-detected area according to the re-clustering result includes: Determine the clustering outlines corresponding to the results of each re-clustering in the area to be detected, and determine the construction site area based on the clustering outlines; Other construction site areas except the known construction site area are regarded as unknown construction site areas in the area to be detected.

2. The method according to claim 1, characterized in that The device clustering area is generated in the following manner: The positioning information uploaded by the construction site equipment in the area to be detected is obtained, and the geographical locations represented by the positioning information are clustered according to a preset clustering standard to generate equipment clustering areas corresponding to the construction site equipment in the area to be detected.

3. The method according to claim 1, characterized in that Determining the target equipment cluster area closest to the known construction site includes: Determine a construction site center point in the known construction site, and respectively determine cluster center points of each of the equipment clustering areas; The distances between the construction site center point and each of the cluster center points are calculated, and the equipment cluster area where the cluster center point with the shortest distance is located is used as the target equipment cluster area closest to the known construction site.

4. The method according to claim 1, characterized in that: Generating the clustering confidence of the preset clustering standard includes: The union area and the intersection area of ​​the known construction site area and the target equipment cluster area are counted, and the ratio of the intersection area to the union area is used as the clustering confidence of the preset clustering standard.

5. The method according to claim 1, characterized in that The area of ​​the unknown construction site determined in the to-be-detected area according to the re-clustering result includes: If the clustering confidence corresponding to the re-clustering result is the maximum value among the clustering confidences corresponding to the candidate clustering standards, the area of ​​the unknown construction site is determined in the area to be detected according to the re-clustering result.

6. A construction site area identification system, characterized in that: The system provides an equipment clustering area obtained by clustering the construction site equipment in the detection area according to a preset clustering standard; the system comprises: An equipment clustering unit, used for acquiring construction site information of known construction sites in the area to be detected, and determining a target equipment clustering area closest to the known construction site from each of the equipment clustering areas according to the construction site information; The confidence generating unit is used to generate the clustering confidence of the preset clustering standard according to the area of ​​the known construction site and the target equipment clustering area, specifically comprising: determining the union area and the intersection area of ​​the area of ​​the known construction site and the target equipment clustering area, and counting the first number of construction site equipment contained in the intersection area and the second number of construction site equipment contained in the union area; and taking the ratio of the first number to the second number as the clustering confidence of the preset clustering standard; A construction site identification unit is used to adjust the preset clustering standard if the clustering confidence does not meet the preset conditions, and re-cluster 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, specifically including: determining the clustering outline corresponding to each re-clustering result in the area to be detected, and determining the construction site area based on the clustering outline; taking other construction site areas except the area of ​​the known construction site as the area of ​​the unknown construction site in the area to be detected; the preset clustering standard is one of a plurality of candidate clustering standards; the clustering confidence does not meet the preset conditions including: the clustering confidence is not the maximum value among the clustering confidences corresponding to each candidate clustering standard.

7. A construction site area identification device, characterized in that: The device for identifying a construction site area comprises a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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