Road construction management system based on cloud computing

Abstract

The invention relates to the technical field of construction management, in particular to a road construction management system based on cloud computing, which comprises a cloud density sensing module, a construction task disassembling module, an equipment scheduling conflict identification module, a resource throttling rate matching module and a dynamic risk early warning defining module. According to the method, the aggregation tasks are disassembled and the priorities are adjusted by identifying and labeling the high-load construction area and combining the process dependence degree, the task organization sequence of the high-density area is effectively optimized, and the equipment resource use conflicts are identified through cross judgment of the scheduling time periods among the processes; whether scheduling overrun exists or not is judged in combination with the equipment utilization rate and the resource scheduling rate, standby equipment is matched in time or speed limiting regulation is implemented, an early warning boundary is established through included angle change rate and path intersection judgment, and forward risk prompt and path boundary calibration of personnel and equipment intersection points are achieved; and the organization efficiency, the resource collaboration and the safety control precision in a high-density working environment are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of construction management, and particularly relates to a road construction management system based on cloud computing. BACKGROUND

[0002] The technical field of construction management involves the overall organization, coordination and control of construction projects during the construction phase, covering aspects such as construction progress management, cost control, quality assurance, safety production, material and equipment scheduling, human resource allocation, etc. This field emphasizes dynamic scheduling and optimized decision-making based on actual engineering processes and resource status, in order to improve construction efficiency, shorten construction period and reduce costs. Modern construction management technology also integrates information technology, using tools such as engineering management software, BIM, GIS, sensor monitoring systems, etc. to achieve data integration and smooth information flow in the construction site, ensuring controllability and transparency of the construction process, and supporting fine, systematic and intelligent management of construction projects.

[0003] Among them, the road construction management system is an information management system for construction activities in road construction projects, used to coordinate the scheduling, coordination and execution of various construction links and resources. Its purposes include unified management and monitoring of road construction progress, construction tasks, human and equipment allocation, construction quality and site safety, etc.; achieving construction site data collection and analysis to assist decision-making; improving construction organization efficiency, reducing management costs, and enhancing overall project execution and transparency. The system can be widely used in highway, municipal road, bridge construction and other projects.

[0004] Traditional management systems cannot accurately identify human overload units in high-density work scenarios, and lack hierarchical judgment ability for process dependency relationships and task aggregation levels, resulting in blindness in task execution order, and unable to effectively analyze resource conflicts caused by multi-process cross-scheduling in the equipment scheduling process. In the process of resource calling, the actual equipment utilization efficiency and resource input intensity are not considered, causing resource allocation blind spots and redundant losses, and the running vector trend change is not established in the personnel and equipment coordination area, making it difficult to form early warning control boundaries, and when the work density is improved or the construction area is complicated, it is easy to produce safety blind area and reduce the overall organization efficiency. SUMMARY

[0005] The purpose of the present application is to solve the shortcomings in the prior art, and to provide a road construction management system based on cloud computing.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme: a road construction management system based on cloud computing, the system comprises: The cloud density perception module obtains the cloud-synchronized road construction site work unit number, daily work manpower input quantity, and construction area of each unit, calls the manpower value and construction area value to calculate the man-hour density, screens the number set whose density exceeds the reference value, and generates a high-density work unit label set; The construction task decomposition module calls the high-density work unit label set, screens the work whose dependent items are higher than the set threshold as an aggregated task node, performs sequence rearrangement on the front process number, uploads the rearranged sequence task to the cloud scheduling area, and generates a high-density priority process link set; The equipment scheduling conflict identification module calls the equipment number and pre-arranged scheduling time period of the corresponding process based on the high-density priority process link set, screens the time period overlapping equipment combination, and generates an equipment conflict mapping group list; The resource throttling rate matching module calls the mechanical utilization rate level setting value and resource input rate execution interval based on the equipment conflict mapping group list, judges whether the set resource scheduling rate threshold is exceeded, calls the standby equipment list or limited speed value, and generates a throttling resource allocation strategy set.

[0007] As a further scheme of the application, the high-density work unit label set includes a work unit unique number for cloud identification, a unit area daily man-hour input value identifier, and a man-hour density over-limit judgment label, the high-density priority process link set is specifically a reorganized process number sequence, a dependent mapping path between structure nodes, and a work priority level identifier, the equipment conflict mapping group list includes an equipment scheduling conflict corresponding table, a process overlap identifier group, and a time period overlapping number set, and the throttling resource allocation strategy set specifically refers to a resource input frequency adjustment instruction, a standby resource call sequence number list, and a limited scheduling strategy parameter.

[0008] As a further scheme of the application, the cloud density perception module includes: The unit information extraction submodule obtains the cloud-synchronized road construction site work unit number, daily work manpower input quantity, and construction area of each unit, extracts the area value and manpower value of each unit respectively, and performs number corresponding identification on the extraction results, establishes a unit-level data index table, and obtains work unit structured data index; The work intensity calculation submodule calls the work unit structured data index, calculates the man-hour density deviation value of each work unit according to the daily manpower input quantity and construction area data corresponding to the work unit number, screens the number set whose deviation value exceeds the man-hour density reference value, and generates a man-hour density abnormal unit number set; The tag generation and upload submodule generates a unique identification code for each number item based on the human-time density anomaly unit number set and attaches an anomaly level identifier. The identification code is then bound one by one with the corresponding unit in the construction task scheduling information. At the same time, the identifier data is synchronously uploaded to the cloud and archived in the identification tag library to establish a high-density operation unit tag set.

[0009] As a further aspect of the present invention, the formula for calculating the man-hour density deviation value of each work unit is specifically as follows: ; in, Indicates the first The deviation value of man-hour density in each work unit Indicates the first The normalized value of the daily human labor hours input for each work unit. Indicates the first The normalized value of the auxiliary man-hour allocation for each work unit. Indicates the first The normalized value of the construction area of ​​each work unit. Indicates the first The distribution ratio of work procedures in each work unit Indicates the first The first work unit in the The task complexity value in the assignment task. Indicates the first The number of tasks contained in each work unit.

[0010] As a further aspect of the present invention, the construction task breakdown module includes: The process dependency extraction submodule calls the high-density work unit tag set, extracts the structural node number in the work item and matches it with the corresponding process dependency quantity according to the work unit's corresponding work process list and structural node data, establishes a structural association mapping matrix for each work item, and obtains process dependency structural matching information. The aggregation node filtering submodule reads the number of matched process dependencies in each work item based on the process dependency structure matching information, performs a size judgment on the number and the set process dependency number threshold, filters work items with dependency number exceeding the threshold as aggregation task nodes, records the corresponding work unit number and structure node number, and establishes a set of work node aggregation intensity values. The sequence link reordering submodule calls the set of aggregation intensity values ​​of the job nodes, extracts the set of preceding process numbers corresponding to the structure node numbers, adjusts the positions according to the process execution order, renumbers and sorts the adjusted links and adds priority identifiers, uploads the structure to the cloud scheduling area, and establishes a high-density priority process link set.

[0011] As a further scheme of the present application, the device scheduling conflict identification module comprises: The scheduling information extraction submodule calls the construction section number and the associated device number corresponding to each process based on the high-density priority process link set, extracts the pre-arranged scheduling start and end time bound to the device number, constructs a structure comparison set of scheduling time periods and device numbers, and establishes device scheduling time comparison information; The time section discrimination submodule calls the device scheduling time comparison information, performs start and end value overlap judgment on the device scheduling time period, filters the device number combination with intersection and overlap relationship, extracts the corresponding intersection and overlap section number and time span value, and establishes an intersection and overlap device combination record value set; The process device mapping submodule extracts the corresponding process number of each device participating in the intersection and overlap combination according to the intersection and overlap device combination record value set, constructs a one-to-one mapping relationship between the device and the process, and writes the mapping data into the cloud conflict identification record area to generate a device conflict mapping group list.

[0012] As a further scheme of the present application, the resource throttling rate matching module comprises: The utilization section acquisition submodule acquires the job area number of the associated device of the process based on the device conflict mapping group list, extracts the daily working time and the available total time of each device in the corresponding job area, calculates the daily mechanical utilization rate of the device, forms a corresponding record with the actual resource input frequency of the device, and generates device resource input relationship value information; The rate threshold judgment submodule calls the device resource input relationship value information, extracts the resource input rate value and the corresponding mechanical utilization rate value under the device number, performs deviation judgment on the resource input rate value and the resource scheduling rate threshold, calculates the resource input pressure value of each device, marks the number whose pressure value exceeds the resource pressure tolerance threshold as a speed adjustment object, and obtains a speed adjustment device identification number set; The deployment strategy generation submodule obtains the standby resource identifier and the shortest job supply cycle of the device corresponding to the identification number according to the speed adjustment device identification number set, constructs a resource supply index with the identifier and the cycle, and writes the number, index and rate correction value into the scheduling interface to establish a throttling resource deployment strategy set.

[0013] As a further scheme of the present application, the formula for calculating the resource input pressure value of each device is specifically: ; Wherein, represents the resource input pressure value, represents the resource input rate normalization value of the device, represents the set resource scheduling rate threshold normalization value, a unit area task density value representing a work area where the equipment is located, a task execution order index value, an energy consumption utilization efficiency normalized value, a device work duration to standard construction cycle ratio value.

[0014] As a further scheme of the present application, the system further comprises: The dynamic risk early warning definition module obtains the trajectory vector and displacement trend of the corresponding work personnel based on the throttling resource allocation strategy set, calculates the change rate of the included angle between the work personnel and the equipment travel vector, judges whether the included angle is less than a set intersection included angle threshold, and detects whether the equipment braking distance and the personnel path intersect, if both conditions are met, the corresponding intersection point is calibrated and the forward path is set as the early warning boundary, and the personnel-equipment intersection early warning boundary value set is recorded and synchronized to the cloud early warning interface, and the personnel-equipment intersection early warning boundary value set is generated; The personnel-equipment intersection early warning boundary value set includes an early warning boundary coordinate set, an equipment braking critical region label, and a work personnel dynamic risk point label.

[0015] As a further scheme of the present application, the dynamic risk early warning definition module comprises: The vector relationship extraction submodule extracts the travel vector data, load state, and path coordinate information corresponding to each equipment number based on the throttling resource allocation strategy set, combines the trajectory vector data and displacement change trend generated by each work personnel positioning device, constructs a two-way dynamic trajectory relationship structure between the equipment and the personnel, and generates a device-personnel trajectory vector coupling set; The critical included angle identification submodule calls the device-personnel trajectory vector coupling set, detects the change rate of the included angle between the equipment motion vector and the personnel trajectory vector, judges the size of the change rate and the set intersection included angle threshold, calculates the corresponding braking distance of the equipment under the current load at the same time, performs a Boolean judgment on the intersection result of the distance and the personnel predicted path, screens the trajectory combinations that meet the two conditions, and establishes an included angle path overlap confirmation value group; The boundary range calibration submodule extracts the intersection point coordinates based on the included angle path overlap confirmation value group according to the device-personnel combination that has been judged as a risk intersection, extends the equipment travel direction path from the intersection point as the starting point, sets the path target range as the boundary section and marks the coordinate range, records the calibrated boundary and writes it into the cloud early warning data interface, and establishes the personnel-equipment intersection early warning boundary value set.

[0016] Compared with the prior art, the present application has the advantages and positive effects that: In the present application, by carrying out density calculation on the manpower input in the work unit and the construction area data and establishing a high-density label, the identification and labeling of high-load construction areas can be realized, the aggregated tasks are disassembled and the priority is adjusted according to the process dependence, the task organization sequence of the high-density area is effectively optimized, the device resource use conflict is identified by cross-discrimination of the scheduling time period between processes in the device scheduling, whether there is scheduling overrun is judged according to the device utilization and the resource adjustment rate, and standby devices or speed limiting control are matched in time, on this basis, the intersection risk between the device running path and the work personnel trajectory is analyzed synchronously, the early warning boundary is established by the angle change rate and the path intersection discrimination, the forward risk prompt and path boundary demarcation of the personnel and device intersection point are realized, and the organization efficiency, resource collaboration and safety control precision in the high-density work environment are improved. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Figure 1 The system flowchart of the present application; Figure 2 The system framework schematic diagram of the present application; Figure 3 The flowchart of the cloud density perception module of the present application; Figure 4 The flowchart of the construction task disassembly module of the present application; Figure 5 The flowchart of the device scheduling conflict identification module of the present application; Figure 6 The flowchart of the resource throttling rate matching module of the present application; Figure 7 The flowchart of the dynamic risk early warning definition module of the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the present application will be described below in combination with the drawings.

[0020] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0021] In the embodiments of the present application, "image" and "picture" can be used interchangeably, and it should be pointed out that their meanings are consistent when their differences are not emphasized.

[0022] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings are consistent when their differences are not emphasized.

[0023] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, specific embodiments will be described in detail below with reference to the drawings.

[0024] Please refer to Figure 1 , the road construction management system based on cloud computing, the system includes a cloud density perception module, a construction task decomposition module, a device scheduling conflict identification module, a resource throttling rate matching module and a dynamic risk early warning definition module; The cloud density perception module obtains the cloud-synchronized road construction site unit number, daily work manpower input quantity and construction area of each unit, calls the manpower value and construction area value to calculate the man-hour density, sorts the calculation results according to the unit number, judges whether the unit in the front row exceeds the set man-hour density benchmark value in unit time, selects the number set whose density exceeds the benchmark value, uploads the corresponding number to the cloud and establishes a callable identification tag, and generates a high-density work unit tag set; The construction task decomposition module calls the high-density work unit tag set, extracts the work procedure list and structure node data of each unit, compares the structure node number and procedure dependency number of the work item, selects the work whose dependency number is higher than the set threshold as the aggregation task node, executes sequence rearrangement on the front process number, adjusts the priority, uploads the rearranged sequence task to the cloud scheduling area, and generates a high-density priority process link set; The procedure dependency number refers to the number of pre-task required by a single work item, which is a structured parameter determined by the process sequence in the standard construction process, and is commonly used in BIM process or WBS structure coding table; The device scheduling conflict identification module calls the device number and pre-arranged scheduling time period of the corresponding process based on the high-density priority process link set, obtains the start and end values of the time period and performs intersection interval judgment, selects the device combination with overlapping time periods, constructs a mapping pair of the device number and the corresponding process, and writes the mapping result into the conflict query record to generate a device conflict mapping group list; The resource throttling rate matching module obtains the job area number, mechanical utilization rate level and real-time input resource rate of each process associated device based on the device conflict mapping group list, calls the mechanical utilization rate level setting value and resource input rate execution interval judgment, judges whether it exceeds the set resource scheduling rate threshold, if it exceeds the limit, calls the standby device list or limited speed value, writes the control strategy into the cloud device deployment interface, and generates a set of throttling resource deployment strategies; The mechanical utilization rate level is the ratio of the daily operation time length of the construction machinery to the available working time length, expressed in percentage, used to measure the equipment operation intensity; the resource scheduling rate threshold is the upper and lower limits of the frequency of a certain type of construction resource entering a certain construction section per unit time, which can be set based on resource deployment specifications or site logistics efficiency model; The dynamic risk early warning definition module extracts the adjusted device number and travel vector data, load state, path coordinates based on the set of throttling resource deployment strategies, obtains the trajectory vector and displacement trend of the corresponding workers, calculates the angle change rate between the travel vectors of the workers and the equipment, judges whether the angle is less than the set intersection angle threshold, and detects whether the equipment braking distance and the personnel path intersect, if both conditions are met, the corresponding intersection point is marked and the forward path is set as the early warning boundary, and the record is synchronized to the cloud early warning interface, generating a set of personnel-equipment intersection early warning boundary values; The travel vector data refers to the displacement direction and distance information of the construction machinery per unit time, which comes from GNSS or inertial navigation device; the intersection angle threshold can be set to 25°, which is used to represent the trend strength of the personnel and equipment moving towards or intersecting; the braking distance is the moving distance required from the equipment to recognize the stop command to completely stop, which is related to the type of equipment, load and speed; The high-density work unit tag set includes a unique work unit number for cloud identification, a daily man-hour input value per unit area identifier, and a man-hour density overrun judgment tag. The high-density priority process link set specifically includes the reorganized process number sequence, the dependent mapping path between structure nodes, and the work priority level identifier. The device conflict mapping group list includes a device scheduling conflict corresponding table, a process overlap identifier group, and a time section overlap number set. The throttling resource deployment strategy set specifically refers to the resource input frequency adjustment instruction, the standby resource call sequence number list, and the limited scheduling strategy parameter. The personnel-equipment intersection early warning boundary value set includes a set of early warning boundary coordinates, a device braking critical region tag, and a work personnel dynamic risk point marker.

[0025] Please refer to Figure 2 and Figure 3 , the cloud density perception module includes a unit information extraction submodule, a work intensity calculation submodule, and a tag generation and upload submodule; The unit information extraction submodule obtains the cloud-synchronized road construction site work unit number, daily work manpower input quantity, and construction area of each unit, extracts the area value and manpower value of each unit respectively, and numbers and corresponds the extraction results for identification, establishes a unit-level data index table, and obtains structured data index of the work unit; To obtain the work unit number, daily work manpower input quantity, and corresponding construction area data of the road construction site, first, the number of workers and the corresponding time length of each work unit are extracted from the daily task assignment record in the construction scheduling system, for example, the number of workers marked in the record of work unit U1 on June 12, 2025 is 20, and each worker works for 6 hours, so the total working hours are 120 hours, which is marked as , the auxiliary working hour allocation is 30 hours obtained from the regional scheduling log, i.e. , the construction area is read as 200 square meters through the BIM platform drawing export model data, i.e. , which needs to be normalized, and the maximum unit area in the region is set to 250 square meters, so the normalized value is , for the work procedure distribution ratio , 3 work procedures involved in U1 work unit are extracted from the engineering list, and if the total work procedure of the project is 10, the unit ratio is , the task complexity value needs to be set manually, for example, U1 involves 3 tasks, and the corresponding level scores are 6, 5, and 7, and the average is , which is put into the subsequent formula for unified calculation, and the number is bound with each parameter through the number mapping table to form a structured data index set, i.e. work unit structured data index.

[0026] The work intensity calculation submodule calls the work unit structured data index, calculates the man-hour density deviation value of each work unit according to the daily manpower input quantity and construction area data corresponding to the work unit number, screens the number set whose deviation value exceeds the man-hour density reference value, and generates a man-hour density abnormal unit number set; The formula for calculating the man-hour density deviation value of each work unit is as follows: ; Among them, represents the man-hour density deviation value of the th work unit, represents the normalized value of the daily man-hour input of the th work unit, and the normalization method is the ratio of the man-hour input in the unit to the total manpower input on the day, represents the The normalized value of auxiliary man-hour allocation for each work unit, normalized by the ratio of allocated man-hours to the average allocated man-hours within the region. Indicates the first The normalized value of the construction area of ​​each work unit, normalized by the ratio of the unit area to the largest area of ​​all work units. Indicates the first The distribution ratio of work procedures in a work unit is defined as the ratio of the total number of procedures involved in that unit to the total number of construction procedures. Indicates the first The first work unit in the The task complexity value in each assignment is quantified using a unitless rank rating system. Indicates the first The number of tasks contained in each work unit; The following formula is used to calculate the work unit's structured data index, which includes the work unit number, manual labor hours, auxiliary labor hours, construction area, process ratio, and task complexity score: ; Taking U1 as an example, , , Then the left term is In the right item, , The average value is 6, therefore The final result is If the deviation value is found to be less than the baseline value of 0.8 when compared with the human time density baseline value, then U1 will not enter the screening set. If the calculation result of a certain unit is 1.2, and the deviation is greater than the baseline value of 0.8, then it will enter the numbered screening result set, and finally form the human time density abnormal unit number set.

[0027] The benchmark value for man-hour density is set based on the upper limit standard of man-hour density per unit area listed in the construction organization design, and with reference to the maximum daily manpower load of 0.75 person-hours / m² in the standard operation process of municipal roads. 2 Up to 0.85 people·h / m 2 Therefore, the benchmark value is set at 0.8, which is in the middle of the standard range and has strong adaptability. This value shows a stable trend as the area of ​​the construction unit increases, but in areas with concentrated manpower input, the screening action will be triggered because the upper limit is close to the limit.

[0028] The formula structure and logic are explained as follows: left-hand term of formula The right-hand item reflects the actual man-hour input density per unit area, representing the actual work intensity within the work unit. This indicates how task complexity and process distribution structure modulate the theoretical strength. Measuring the clustering of multiple processes, This represents the average task intensity level, which is generally positively correlated. The square root expression is used to smooth the complexity value and prevent excessive fluctuations in the result due to individual scores. The overall formula uses absolute value calculations to ensure that the deviation is quantified as a non-negative result, facilitating subsequent comparisons with the benchmark value. The final calculation result... This represents the deviation of the man-hour density in the work unit. If this value exceeds the benchmark value, it indicates that there may be uneven construction intensity or overload of task allocation in the work unit. As shown in Table 1, U3 has the following properties in the calculation of human-time density: The area is normalized to 1.0, and the complexity of the right term is O(n). The left term is 1.0, and the final deviation value is If the value is less than the baseline of 0.8, and the U3 labor hours are increased to 280 hours, then the left-hand term will be... The deviation is Similarly, it did not reach the selection boundary, but if the task complexity score increases to 8, the right-hand item becomes... The deviation is The value is close to the baseline. If the working hours are increased to 320, the left term will be 1.28, and the deviation will be... It has not yet crossed the boundary, but if the structure becomes more complex, it is easy to fall into the screening range, thus verifying the rationality and sensitivity of the benchmark value setting logic.

[0029] The tag generation and upload submodule generates a unique identification code for each number item based on the abnormal unit number set of human-time density and attaches an abnormality level label. The identification code is then bound to the corresponding unit in the construction task scheduling information one by one. At the same time, the label data is uploaded to the cloud and archived in the identification tag library to establish a high-density operation unit tag set. Based on the set of abnormal unit numbers for human-time density, the selected numbers are sequentially mapped to generate unique identification codes. These codes can be generated using the format "HD + timestamp + unit number". For example, if the selection time for number U2 is 20250716, the identification code would be "HD20250716U2". The anomaly level can be tiered based on the difference between the deviation value and the benchmark value. A deviation value greater than 1.5 is set to a red level, corresponding to a significant overload risk. A deviation value between 1.2 and 1.5 is set to an orange level, indicating a tight work configuration. A deviation value less than 1.2 is a yellow warning level, corresponding to three warning levels in construction scheduling. For example, if U2 has a deviation value of 1.35 and a benchmark value of 0.8, the calculated ratio is 1.6875, which falls under the red level. This identifier is then bound to the U2 work unit in the construction task system and synchronized to the cloud tag library, forming a high-density work unit tag set.

[0030] Please see Figure 2 and Figure 4 The construction task decomposition module includes a process dependency extraction submodule, an aggregation node filtering submodule, and a sequence link rearrangement submodule. The process dependency extraction submodule calls the high-density work unit tag set, compiles the corresponding work process list and structural node data according to the work unit, extracts the structural node number in the work item and matches it one by one with the corresponding process dependency quantity, establishes the structural association mapping matrix of each work item, and obtains the process dependency structure matching information. The system calls the work unit numbers from the high-density work unit tag set. First, it extracts the process list data corresponding to each unit in the construction task platform based on the number item, and simultaneously retrieves the structural node number information already marked in the BIM structural model. Taking work unit U12 as an example, its structural node numbers are N1203, N1204, and N1205, and the process list items are rebar tying, formwork installation, and concrete pouring. For each process, it records the number of its preceding dependent processes and marks the number of dependencies. For example, formwork installation depends on rebar tying, which is 1 dependency, and concrete pouring depends on the first two, which is 2 dependencies. Therefore, the three process items in U12 are marked with dependency numbers of 0, 1, and 2 respectively, forming a mapping item between nodes and dependency numbers. In actual system operation, the position mapping is performed through structural node codes and process list numbers, and the data is registered in the mapping table to form a two-dimensional structure, where the horizontal axis is the structural node number, the vertical axis is the process item, and the intersection is filled with the corresponding dependency value. The following matrix is ​​generated as described above: Blank items in Table 2 indicate no corresponding operation. The dependency count can be further used for subsequent filtering operations. After the construction is completed, it is recorded in the process structure index module of the scheduling system. During the formation of the data structure, if there are multiple processes with duplicate numbers under a certain node, a uniqueness check must be performed and similar items must be merged. The dependency count is used as an integer parameter in subsequent judgment operations. After all numbers are processed in batches, the process dependency structure matching information is compiled and summarized.

[0031] The aggregation node filtering submodule reads the number of matched process dependencies in each work item based on the process dependency structure matching information, performs a size judgment on the number and the set process dependency number threshold, filters work items with dependency number exceeding the threshold as aggregation task nodes, records the corresponding work unit number and structure node number, and establishes a set of work node aggregation intensity values. Based on the process dependency structure matching information, the number of process dependencies recorded in each work item is read item by item and compared with a set dependency number threshold. The threshold is set to 2. According to the standard for determining multi-process synchronous collaboration nodes as dependency points in the construction organization, if the number of dependencies is greater than or equal to 2, it is considered a dependency cluster node. For example, the concrete pouring process in U12 depends on two items, which meets the condition. Its node number is recorded as N1205, and the work unit is U12. It is then included in the result set. In this process, the dependency value of each process needs to be converted into a numerical variable through numerical extraction first, and then the comparison function is called to perform the comparison between the dependency number and the threshold. If a threshold is set... If the threshold is 2, then if a certain process has a dependency quantity of 3, the condition is met; if the dependency quantity is 1, the condition is not met. All work items that meet the condition constitute an aggregate node set. The reason for setting this threshold is that 1 dependency is the standard linear work logic, and 2 or more dependencies usually indicate that there are intersections, convergences, or waiting signals, which need to be specially marked. For example, if the threshold for the dependency quantity is set to 2, then processes with a dependency quantity of 0 or 1 will not enter the screening, while processes with a dependency quantity of 2, 3, or 4 will enter the result set. After screening, the concrete pouring items under work unit U12 meet the conditions and are recorded in the aggregate node. The structural node number and work unit number are also recorded, and the output is organized into a set of aggregate strength values ​​for work nodes.

[0032] The sequence link reordering submodule calls the job node aggregation intensity value set, extracts the set of preceding process numbers corresponding to the structure node number, and adjusts the position according to the process execution order. The adjusted links are renumbered and sorted and priority identifiers are added. The structure is uploaded to the cloud scheduling area to establish a high-density priority process link set. The system retrieves the structural node numbers from the aggregated strength value set of the work nodes. For each structural node, it extracts the set of process numbers bound to it and sorts them in ascending order according to the planned start time of the process in the scheduling system. For example, if the process bound to node N1205 is rebar tying, formwork installation, and concrete pouring, and its start time is 8:00, 9:00, and 11:00 respectively, the sorting result remains unchanged. If the order is concrete pouring, rebar tying, and formwork installation, it needs to be rearranged according to the time value to rebar tying, formwork installation, and concrete pouring, and the process number sequence is updated. Then, a priority identifier is added to each process in the new order, with the priority set from 1 to n, where 1 is the earliest and increases sequentially. The recorded result is: rebar tying priority is 1, formwork installation is 2, and concrete pouring is 3. The priority data type is an integer. After all process nodes are sorted, the result list is archived in the scheduling module according to the work unit dimension and the node number dimension, and then uploaded to the cloud task platform, thus forming a high-density priority process link set.

[0033] Please see Figure 2 and Figure 5The equipment scheduling conflict identification module includes a scheduling information extraction submodule, a time segment discrimination submodule, and a process equipment mapping submodule; The scheduling information extraction submodule is based on a high-density priority process link set. It calls the construction section number and associated equipment number corresponding to each process, extracts the pre-scheduled start and end times bound to the equipment number, constructs a structured comparison set between the scheduling time period and the equipment number, and establishes equipment scheduling time comparison information. Based on a high-density priority process link set, the process number information recorded within it is called sequentially. The construction section number assigned to each process is retrieved, and a list of all mechanical equipment numbers within that section is retrieved from the construction scheduling system. For example, if the construction section number corresponding to process number W302 is Z07, the system returns the equipment numbers D018, D021, and D034 registered within Z07. Further, the pre-scheduled time slots for each piece of equipment are extracted from the equipment ledger. The scheduling time for D018 is 7:30 to 10:00, for D021 it is 8:00 to 10:30, and for D034 it is 10:30 to 13:00. This is achieved by constructing... The combination table of equipment number and its corresponding start and end time periods completes the structured record, forming the time distribution relationship between the section and the equipment. The start and end times are represented in the standard 24-hour format, accurate to the minute, and are compared and unified using timestamps. If a piece of equipment has scheduling requirements in two processes, it needs to be marked as a reused piece of equipment, and multiple scheduling records for it should be registered. All scheduling entries are organized into a structured comparison item, with content fields including construction section number, equipment number, scheduling start time, scheduling end time, and scheduling sequence number. A standard index is established to facilitate subsequent matching and judgment, and finally, equipment scheduling time comparison information is generated.

[0034] The time segment discrimination submodule calls the equipment scheduling time comparison information, performs start and end value overlap judgment on the equipment scheduling time period, filters the equipment number combinations with overlapping relationships, and extracts the corresponding overlapping segment number and time span value to establish an overlapping equipment combination record value set; The equipment scheduling time comparison information is retrieved and grouped by construction section number. For each group, the start and end times of the equipment are checked for overlapping time intervals. This is done by comparing the start and end times of two pieces of equipment pairwise. If the start time of equipment A is earlier than the end time of equipment B, and the start time of equipment B is earlier than the end time of equipment A, then there is an overlap in time periods. For example, if the scheduling time for equipment D018 is 7:30 to 10:00 and the scheduling time for equipment D021 is 8:00 to 10:30, both conditions are met, and the equipment is identified as an overlapping combination. The combination is recorded as (D018...). (D021), and extract the overlapping section number Z07, calculate the time span value of the overlapping time period, that is, take the difference between the minimum end time and the maximum start time of the two, which is 10:00 minus 8:00 to get 2 hours, construct the overlapping combination record value items: combination number, overlapping section, overlapping start time, overlapping end time, overlapping duration, and collect all the equipment combinations that meet the conditions in a structured record format to form the overlapping equipment combination record value set. In the judgment process, it is necessary to exclude the boundary cases where the start and end times are equal, and ensure that the equipment numbers are not repeatedly paired to avoid generating mirror entries.

[0035] The process equipment mapping submodule extracts the process number corresponding to each piece of equipment participating in the cross-load combination based on the cross-load equipment combination record value set, constructs a one-to-one mapping relationship between equipment and process, and writes the mapping data into the cloud conflict identification record area to generate a list of equipment conflict mapping groups. Based on the record set of equipment combination data, extract the process number information corresponding to the equipment number in each combination. The equipment usage plan needs to be retrieved in reverse through the process task scheduling list. For example, in combination (D018, D021), D018 is used for process W302 and D021 is used for process W305, thus forming a mapping relationship D018→W302, D021→W305. The above mapping entries are merged according to the construction section number and uniformly coded, and the fields are constructed as: equipment number, process number, mapping time period, and equipment combination type identifier. If there are more than two equipment mappings in a certain process, the primary and secondary priorities of the equipment need to be set and the priority identifier field needs to be recorded. After the mapping relationship is established, the mapping data is submitted to the data recording interface of the cloud conflict identification module. A standard structure record item is formed inside the interface for subsequent conflict analysis and scheduling optimization. Finally, a unified list of equipment conflict mapping groups is generated.

[0036] Please see Figure 2 and Figure 6 The resource throttling rate matching module includes a utilization rate segment acquisition submodule, a rate threshold judgment submodule, and an allocation strategy generation submodule. The utilization rate segment acquisition submodule obtains the work area number of the equipment associated with the process based on the equipment conflict mapping group list, extracts the daily working time and total available time of each equipment in the corresponding work area, calculates the daily mechanical utilization rate of the equipment, forms a corresponding record with the actual resource transfer frequency of the equipment, and generates equipment resource transfer relationship value information. Based on the equipment conflict mapping group list, the equipment numbers corresponding to each process are extracted sequentially, and their corresponding work area numbers in the construction organization plan are located. Using a combined index of equipment number and area number, the daily records of equipment runtime and total available time in the area are retrieved. For example, if equipment D021 is located in work area Z07, its working time on July 5, 2025 is 6 hours, and its total available time is 8 hours, then its utilization rate is calculated as 6 divided by 8, which equals 0.75. Recording these daily, a sequence of daily mechanical utilization rates for equipment numbers and work areas is constructed. Subsequently, the daily resource transfer frequency data for the same equipment in the corresponding area is obtained. For example, if D021 has 4 resource transfers in area Z07 on July 5, 2025, then the data structure items are: equipment number, work area number, utilization rate value, and resource transfer frequency. This data is organized into a key-value pair set according to the equipment number, forming a one-to-one correspondence record between equipment and transferred resource intensity. This is then interfaced with the scheduling management platform to uniformly output equipment resource transfer relationship value information.

[0037] The rate threshold judgment submodule calls the equipment resource loading relationship value information, extracts the resource loading rate value and the corresponding mechanical utilization value under the equipment number, performs deviation judgment on the resource loading rate value and the resource scheduling rate threshold, calculates and obtains the resource loading pressure value of each equipment, and marks the number of the pressure value that exceeds the resource pressure tolerance threshold as the speed regulation object, thus obtaining the speed regulation equipment identification number set. The specific formula for calculating the resource load pressure value for each device is as follows: ; in, This indicates the pressure value for resource allocation. This represents the normalized value of the resource inbound rate of the device. This represents the normalized value of the set resource scheduling rate threshold. This represents the task density per unit area of ​​the work area where the equipment is located. This represents the task execution order index, which is the ratio of the current process position of the device to its corresponding task chain. This represents the normalized value of energy consumption efficiency, calculated as the operational output efficiency per unit of resource input. This represents the speed regulation excitation term between task execution and energy consumption intensity. This represents the ratio of equipment operation duration to the standard construction cycle. The system retrieves the resource loading relationship information of each device, extracts the resource loading rate value and corresponding mechanical utilization rate value recorded for each device, and uses the normalized loading rate as a parameter. Resource scheduling rate threshold The setting benchmark is the task density level in the current construction organization plan. Specifically, the level is determined based on the average daily task quantity per unit area of ​​the construction section. For example, a task density value of less than or equal to 0.6 is defined as Level I, with a threshold of 0.65; values ​​between 0.6 and 1.0 are defined as Level II, with a threshold of 0.75; and values ​​above 1.0 are defined as Level III, with a threshold of 0.85. This classification is based on the verification of the linear relationship between resource scheduling load and task backlog rate. Furthermore, as the task density per unit area increases, the resource scheduling tension intensifies; therefore, the threshold needs to be adjusted according to the level. The calculation method is to divide the total number of work processes on that day by the area. Taking Z07 as an example, there are 15 work processes performed, with a total area of ​​250 square meters. Task execution order index Defined as the execution order of the process number within its chain divided by the total number of tasks. For example, if process W302 is the 3rd process in the chain, with a total of 6 tasks, then... Energy efficiency The effective output is determined by the amount of resources transferred per unit. If a certain piece of equipment generates an effective output of 15 for every 10 units of resources transferred, then... ; Operational continuity ratio The setting is the daily operating time of the equipment divided by the standard construction cycle. For example, the daily operating time of equipment D021 is 6 hours, and the standard cycle is 8 hours. Substitute into the formula: ; The resource pressure tolerance threshold is set to 0.35, which is based on the daily energy consumption load capacity of the construction area. This value is equal to the arithmetic mean of the Z values ​​of the resource transfer rate of each equipment in the previous 5 days plus 0.1 as a safety margin. The purpose of setting this threshold is to limit the frequency of equipment resource transfer to exceed the high load warning line, which would cause the scheduling system to become disordered. If the Z value is greater than 0.35, it is marked as a speed regulation object, its number is recorded, and a set of speed regulation equipment identification numbers is constructed according to the screening results.

[0038] Explanation of formula calculation logic: In the formula This indicates the degree of deviation in resource rate, with the denominator reflecting the impact of task density. This is the speed regulation effect term resulting from the coupling of task urgency and energy consumption intensity; the entire bracket is multiplied by... The incoming pressure is scaled proportionally to the duration of the operation, ultimately forming a comprehensive resource incoming pressure value, which reflects whether the equipment exceeds the current resource scheduling capacity.

[0039] Parameter meaning explanation: Among them, This indicates the pressure value for resource allocation. This is the normalized value of the resource inflow rate. This is the normalized value of the scheduling rate threshold. This represents the task density value per unit area. This is the task execution order index value. This is the normalized value of energy consumption utilization efficiency. This is the ratio of the operation duration to the standard cycle time. See Table 3, which shows the resource allocation parameters and calculated pressure values ​​for different equipment in their respective work areas.

[0040] The allocation strategy generation submodule obtains the spare resource identifier and shortest operation replenishment cycle of the equipment corresponding to the identification number based on the set of speed regulation equipment identification numbers, constructs a resource replenishment index with the identifier and cycle, and writes the number, index and rate correction value into the scheduling interface to establish a set of throttling resource allocation strategies.

[0041] Based on the set of speed control equipment identification numbers, the standby resource identifier and shortest replenishment cycle data of each identified equipment are retrieved item by item. For example, the standby resource identifier corresponding to equipment D021 is R018, and the shortest replenishment cycle is 4 hours. This resource identifier is bound to the equipment number, and the original rate record and its calculated pressure value are read. The magnitude of the pressure value exceeding the threshold is used as the rate correction factor. If the original rate of D021 is 0.78, the pressure value is 0.3783, and the threshold is 0.35, then the correction magnitude is 0.0283. The fields are constructed as equipment number, standby resource number, replenishment cycle, and correction rate value. At the same time, a resource replenishment index is generated and uniformly coded. All index items, along with the equipment number and correction rate, are written to the speed control interface of the scheduling platform. The interface pushes the strategy to the resource management subsystem according to the field, and finally establishes a set of resource throttling and allocation strategies.

[0042] Please see Figure 2 and Figure 7 The dynamic risk warning and definition module includes a vector relationship extraction submodule, a critical angle identification submodule, and a boundary range calibration submodule; The vector relationship extraction submodule is based on the resource allocation strategy set and extracts the driving vector data, load status and path coordinate information corresponding to each equipment number. Combined with the trajectory vector data and displacement change trend generated by the positioning device of each operator, it constructs a two-way dynamic trajectory relationship structure between equipment and personnel and generates a coupled set of equipment and personnel trajectory vectors. Based on the equipment numbers recorded in the resource-saving allocation strategy set, the configured travel vector data, current load status, and work path coordinates are extracted for each equipment number. The travel vector is determined by the direction of position change of the equipment at two consecutive time points. For example, if the coordinates of equipment D011 at time T1 are (35.2, 21.6) and at time T2 are (37.8, 24.1), then the travel vector is a two-dimensional vector (2.6, 2.5) composed of the coordinate difference between the two points. The load status is retrieved from the equipment's IoT monitoring interface, and the path coordinates are read from the geographic information collection system. Simultaneously, the data uploaded by the positioning devices worn by the operators is also read. The trajectory vector data analyzes the displacement direction of the trajectory data at continuous time points and constructs the displacement change trend based on the displacement difference sequence within the time period. For example, if the displacement change of personnel P203 at five consecutive sampling points shows a northeastward shift trend, then its trajectory vector tends to the corresponding angular direction. Subsequently, using the equipment number and personnel number as dual index keys, all vector sequences of equipment and personnel are aligned by timestamp, and a dynamic interaction structure between the equipment vector sequence and the personnel vector sequence is constructed to record their respective vector directions, change rates, current path position coordinates, and corresponding times. Finally, a coupled set of equipment and personnel trajectory vectors is generated.

[0043] The critical angle recognition submodule calls the coupling set of equipment and personnel trajectory vectors, detects the rate of change of the angle between the equipment motion vector and the personnel trajectory vector, judges the magnitude of the rate of change and the set intersection angle threshold, calculates the braking distance corresponding to the current load of the equipment, performs a Boolean judgment on the intersection result of the distance and the predicted path of the personnel, filters the trajectory combinations that meet the two conditions, and establishes the angle path overlap confirmation value group. The system calls upon all vector pairs in the equipment and personnel trajectory vector coupling set to perform angle change rate detection between the equipment vector and the personnel trajectory vector. The angle change rate is defined as the ratio of the angle difference over time. When the angle between the equipment and personnel changes from 35° to 20° within 1.5 seconds, the rate of change is (35°-20°) / 1.5 = 10° / s. The threshold for the intersection angle is set at 15°, based on the average visual approach reaction angle at the construction site. Within a 3-5 meter intersection distance, an angle less than 15° indicates a convergence of movement trends and a potential intersection. This value is adjusted according to equipment speed fluctuations; as speed increases, the threshold is appropriately widened to 20°, and the rate of change is used to check if the current angle is less than this threshold. Simultaneously, the braking distance of the equipment under load is calculated. If the equipment mass is 5.2 tons, the current speed is 2.8 m / s, and the ground friction coefficient is 0.65, the braking distance is calculated using the formula... Calculate and substitute to get The distance is measured in meters. The intersection of this distance with the position coordinate sequence in the personnel path trajectory is determined. The point set projection method is used to verify whether there is an intersection. If the intersection angle is less than 15° and there is a coordinate intersection between the braking distance path and the predicted personnel trajectory, the trajectory combination is marked as an intersection event that meets the conditions. The equipment number, personnel number, included angle value and intersection position are recorded and uniformly organized into an included angle path overlap confirmation value group.

[0044] The boundary range calibration submodule is based on the angle path overlap confirmation value group. According to the combination of equipment and personnel that has been identified as risk intersection, it extracts the coordinates of the intersection point, extends the equipment travel direction path with the intersection point as the starting point, sets the target range of the path as the boundary segment and marks the coordinate range, records the calibration boundary and writes it into the cloud early warning data interface, and establishes the personnel and equipment intersection early warning boundary value set. Based on all records in the intersection confirmation value group of the included path, the intersection point coordinates of each equipment and personnel number combination are extracted. For example, D011 and P203 intersect at coordinates (42.5, 30.8). These coordinates are used as the boundary calibration starting point. The path direction unit vector is calculated by combining the current travel direction vector of the equipment (2.6, 2.5). The boundary end point is obtained by extending it by 10 meters proportionally. The boundary line segment is formed from the starting point to the end point. A rectangular area is formed in the two-dimensional coordinate system to cover the forward path segment. The coordinates of the four vertices of the path segment are recorded as the boundary area coordinate set. If the current direction of the equipment changes slightly, the boundary direction is dynamically adjusted in real time according to the vector recalculation result. All generated boundary area record data includes fields such as starting point coordinates, ending point coordinates, corresponding equipment number, personnel number, and intersection time point. These are uniformly pushed to the cloud early warning interface and archived in the early warning boundary storage area to generate a personnel and equipment intersection early warning boundary value set.

[0045] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0046] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0047] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0048] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0049] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0050] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0051] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0052] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0053] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0054] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A cloud-based road construction management system, characterized in that, The system includes: The cloud-based density perception module obtains the road construction site work unit number, daily manpower input, and construction area of ​​each unit synchronized with the cloud. It then uses the manpower value and construction area value to calculate man-hour density, filters out the set of numbers with density exceeding the benchmark value, and generates a high-density work unit tag set. The construction task decomposition module calls the high-density operation unit tag set, filters the operations with more than a set threshold of dependencies as aggregated task nodes, performs sequence rearrangement on the preceding process number, uploads the rearranged sequence tasks to the cloud scheduling area, and generates a high-density priority process link set. The equipment scheduling conflict identification module, based on the high-density priority process link set, calls the equipment number and pre-scheduled time period of the construction section occupied by the corresponding process, filters the equipment combinations with overlapping time periods, and generates a list of equipment conflict mapping groups. Based on the equipment conflict mapping group list, the resource throttling rate matching module calls the mechanical utilization rate level setting value and the resource input rate to perform range judgment. If it is determined whether the set resource scheduling rate threshold is exceeded, the module calls the standby equipment list or the speed adjustment value to generate a set of throttling resource allocation strategies.

2. The cloud-based road construction management system according to claim 1, characterized in that, The high-density work unit tag set includes a unique work unit number for cloud identification, a daily man-hour input value per unit area identifier, and a man-hour density exceeding limit judgment tag. The high-density priority process link set specifically includes a reorganized process number sequence, a dependency mapping path between structural nodes, and a work priority level identifier. The equipment conflict mapping group list includes an equipment scheduling conflict correspondence table, a process overlap identifier group, and a time segment overlap number set. The resource throttling allocation strategy set specifically refers to resource transfer frequency adjustment instructions, a spare resource call sequence number list, and restriction scheduling strategy parameters.

3. The cloud-based road construction management system according to claim 2, characterized in that, The cloud-based density sensing module includes: The unit information extraction submodule obtains the road construction site operation unit number, daily manpower input, and construction area of ​​each unit synchronized in the cloud. It extracts the area and manpower values ​​for each unit, assigns corresponding numbers to the extraction results, establishes a unit-level data index table, and obtains the structured data index of the operation unit. The work intensity calculation submodule calls the structured data index of the work unit, calculates the man-hour density deviation value of each work unit based on the daily manpower input and construction area data corresponding to the work unit number, filters the set of numbers whose deviation value exceeds the man-hour density benchmark value, and generates a set of man-hour density abnormal unit numbers. The tag generation and upload submodule generates a unique identification code for each number item based on the human-time density anomaly unit number set and attaches an anomaly level identifier. The identification code is then bound one by one with the corresponding unit in the construction task scheduling information. At the same time, the identifier data is synchronously uploaded to the cloud and archived in the identification tag library to establish a high-density operation unit tag set.

4. The cloud-based road construction management system according to claim 3, characterized in that, The formula for obtaining the man-hour density deviation value of each work unit is as follows: ； in, Indicates the first The deviation value of man-hour density in each work unit Indicates the first The normalized value of the daily human labor hours input for each work unit. Indicates the first The normalized value of the auxiliary man-hour allocation for each work unit. Indicates the first The normalized value of the construction area of ​​each work unit. Indicates the first The distribution ratio of work procedures in each work unit Indicates the first The first work unit in the The task complexity value in the assignment task. Indicates the first The number of tasks contained in each work unit.

5. The cloud-based road construction management system according to claim 4, characterized in that, The construction task breakdown module includes: The process dependency extraction submodule calls the high-density work unit tag set, extracts the structural node number in the work item and matches it with the corresponding process dependency quantity according to the work unit's corresponding work process list and structural node data, establishes a structural association mapping matrix for each work item, and obtains process dependency structural matching information. The aggregation node filtering submodule reads the number of matched process dependencies in each work item based on the process dependency structure matching information, performs a size judgment on the number and the set process dependency number threshold, filters work items with dependency number exceeding the threshold as aggregation task nodes, records the corresponding work unit number and structure node number, and establishes a set of work node aggregation intensity values. The sequence link reordering submodule calls the set of aggregation intensity values ​​of the job nodes, extracts the set of preceding process numbers corresponding to the structure node numbers, adjusts the positions according to the process execution order, renumbers and sorts the adjusted links and adds priority identifiers, uploads the structure to the cloud scheduling area, and establishes a high-density priority process link set.

6. The cloud-based road construction management system according to claim 5, characterized in that, The equipment scheduling conflict identification module includes: The scheduling information extraction submodule, based on the high-density priority process link set, calls the construction section number and associated equipment number corresponding to each process, extracts the pre-scheduled start and end times bound to the equipment number, constructs a structured comparison set between the scheduling time period and the equipment number, and establishes equipment scheduling time comparison information. The time segment discrimination submodule calls the equipment scheduling time comparison information, performs start and end value overlap judgment on the equipment scheduling time period, filters the equipment number combinations with overlapping relationships, and extracts the corresponding overlapping segment number and time span value to establish an overlapping equipment combination record value set; The process equipment mapping submodule extracts the process number corresponding to each piece of equipment participating in the cross-load combination based on the cross-load equipment combination record value set, constructs a one-to-one mapping relationship between equipment and process, writes the mapping data into the cloud conflict identification record area, and generates a list of equipment conflict mapping groups.

7. The cloud-based road construction management system according to claim 6, characterized in that, The resource throttling rate matching module includes: The utilization rate segment acquisition submodule obtains the work area number of the equipment associated with the process based on the equipment conflict mapping group list, extracts the daily working time and total available time of each equipment in the corresponding work area, calculates the daily mechanical utilization rate of the equipment, forms a corresponding record with the actual resource transfer frequency of the equipment, and generates equipment resource transfer relationship value information. The rate threshold judgment submodule calls the equipment resource transfer relationship value information, extracts the resource transfer rate value and the corresponding mechanical utilization value under the equipment number, performs deviation judgment on the resource transfer rate value and the resource scheduling rate threshold, calculates and obtains the resource transfer pressure value of each equipment, marks the number of the pressure value exceeding the resource pressure tolerance threshold as the speed regulation object, and obtains the speed regulation equipment identification number set. The allocation strategy generation submodule obtains the spare resource identifier and the shortest operation replenishment cycle of the equipment corresponding to the identification number based on the set of speed regulation equipment identification numbers, constructs a resource replenishment index with the identifier and cycle, and writes the number, index and rate correction value into the scheduling interface to establish a set of throttling resource allocation strategies.

8. The cloud-based road construction management system according to claim 7, characterized in that, The specific formula for calculating the resource allocation pressure value of each device is as follows: ； in, This indicates the pressure value for resource allocation. This represents the normalized value of the resource inbound rate of the device. This represents the normalized value of the set resource scheduling rate threshold. This represents the task density value per unit area of ​​the work area where the equipment is located. This represents the task execution order index value. This represents the normalized value of energy consumption efficiency. This indicates the ratio of equipment operation duration to the standard construction cycle.

9. The cloud-based road construction management system according to claim 8, characterized in that, The system also includes: The dynamic risk warning and definition module, based on the resource-saving allocation strategy set, obtains the trajectory vector and displacement trend of the corresponding operator, calculates the rate of change of the angle between the operator and the equipment travel vector, determines whether the angle is less than the set intersection angle threshold, and detects whether the equipment braking distance and the personnel path intersect. If both conditions are met, the corresponding intersection point is marked and the forward path is set as the warning boundary. The warning is recorded and synchronized to the cloud warning interface to generate a set of personnel and equipment intersection warning boundary values. The personnel and equipment intersection early warning boundary value set includes an early warning boundary coordinate set, equipment braking critical area labels, and dynamic risk point markers for operators.

10. The cloud-based road construction management system according to claim 9, characterized in that, The dynamic risk warning and definition module includes: The vector relationship extraction submodule extracts the driving vector data, load status and path coordinate information corresponding to each equipment number based on the resource allocation strategy set. Combined with the trajectory vector data and displacement change trend generated by the positioning device of each operator, it constructs a two-way dynamic trajectory relationship structure between equipment and personnel, and generates a coupled set of equipment and personnel trajectory vectors. The critical angle recognition submodule calls the coupled set of equipment and personnel trajectory vectors to detect the rate of change of the angle between the equipment motion vector and the personnel trajectory vector. It judges the magnitude of the rate of change and the set intersection angle threshold, and calculates the braking distance corresponding to the current load of the equipment. It performs a Boolean judgment on the intersection result of the distance and the predicted path of the personnel, filters the trajectory combinations that meet the two conditions, and establishes the angle path overlap confirmation value group. The boundary range calibration submodule, based on the overlapping confirmation value group of the included path, extracts the coordinates of the intersection point according to the combination of equipment and personnel that has been determined to be at risk of intersection, extends the path of the equipment's travel direction with the intersection point as the starting point, sets the target range of the path as the boundary segment and marks the coordinate range, records the calibration boundary and writes it into the cloud early warning data interface, and establishes a personnel and equipment intersection early warning boundary value set.

Images