Intelligent management method and system for indoor decoration design construction

Abstract

The invention provides an intelligent management method and system for indoor decoration design construction, and relates to the technical field of construction management. According to the method, the step of obtaining the construction scheme information and constructing the construction process dependency relationship library is combined with the step of inputting the basic information of the construction team and identifying the capability label, so that an accurate and comprehensive data basis is provided for construction of a subsequent task incidence matrix and distribution of risk correlation coefficients; and the step of constructing a task association matrix and distributing risk association coefficients based on the construction process dependency relationship library and the construction team capability labels is fused with the step of setting a dynamic task adjustment mechanism and a trigger condition thereof, so that the task adjustment mechanism can be dynamically set according to scientific and reasonable task association and risk degree. According to the invention, efficient, accurate and dynamic management of indoor decoration design construction tasks is realized, the construction efficiency is effectively improved, the construction risk is reduced, the resource allocation is optimized, and the guarantee of construction progress and quality is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of construction management, and in particular to an intelligent management method and system for interior decoration design and construction. Background Art

[0002] In the field of interior decoration design and construction, traditional management methods mainly rely on manual experience and static plans, and it is difficult to cope with complex and changeable construction environments and dynamically changing resource conditions, resulting in frequent problems such as low construction efficiency, difficult risk control, and unreasonable resource allocation. Specifically, the existing technologies have the following deficiencies:

[0003] Insufficient integration of construction information: In the stage of formulating construction plans, traditional methods often lack systematic integration of information such as construction steps, technological processes, material lists, and construction areas, resulting in poor information transmission during construction, and prone to problems such as improper process connection, insufficient or excessive material supply, etc., affecting construction progress and quality.

[0004] One-sided evaluation of construction team capabilities: The evaluation of construction team capabilities is mostly based on subjective judgments or single-dimensional data (such as the completion of historical projects), lacking a comprehensive and objective ability labeling system, and it is difficult to accurately match construction tasks with construction team capabilities, resulting in unreasonable task allocation and affecting construction efficiency and quality.

[0005] When allocating tasks in the existing technology, the relevance between construction tasks is not fully considered, such as the impact of the delay of a previous task on subsequent tasks, resulting in a lack of flexibility in the construction plan, difficulty in coping with emergencies, and increasing construction risks.

[0006] Lack of dynamic adjustment mechanism: Traditional management methods lack an effective dynamic task adjustment mechanism. When construction progress deviates or resource conditions change, tasks cannot be adjusted in a timely and accurate manner, resulting in construction delays, increased costs, or resource waste.

[0007] Therefore, it is necessary to provide an intelligent management method and system for interior decoration design and construction to solve the above technical problems. Summary of the Invention

[0008] To solve the above technical problems, the present invention provides an intelligent management method and system for interior decoration design and construction to solve the problems of insufficient integration of construction information, one-sided evaluation of construction team capabilities, lack of analysis of task relevance, and lack of dynamic adjustment mechanism in existing decoration construction.

[0009] An intelligent management method for interior decoration design and construction provided by the present invention includes the following steps:

[0010] S1. Obtain construction plan information, extract construction steps, technological processes, material lists, and divided construction areas therefrom, and establish a construction process dependency relationship library;

[0011] S2. Enter the basic information of each construction team and label the ability tags for each construction team. Among them, the basic information of the construction team specifically includes personnel skill data and personnel historical efficiency data;

[0012] S3. Based on the construction process dependency library, construct a task association matrix and assign risk association coefficients. Among them, the task association matrix specifically includes strong association, weak association, and no association;

[0013] S4. Based on the task association matrix and the set risk association, establish a dynamic task adjustment mechanism and set trigger conditions;

[0014] S5. According to the preset cycle, regularly obtain the working status of the current construction team, and adjust the tasks of each construction team according to the trigger conditions and the task adjustment mechanism.

[0015] Preferably, the specific steps of step S1 include:

[0016] S101. Extract the construction steps, construction plan, material list, and construction divided areas of the construction plan information through BIM model or CAD drawing parsing technology;

[0017] S102. Based on the result of the construction divided areas, bind each construction step to the specific spatial position to form a space - process mapping table;

[0018] S103. Use a graph database to construct a construction process dependency library, where nodes represent processes and edges represent the dependency relationships between processes.

[0019] Preferably, the specific steps of step S2 include:

[0020] S201. Obtain the basic information of each construction team, including personnel skill data and personnel historical efficiency data;

[0021] S202. According to the personnel skill data and historical efficiency data, use a clustering algorithm to label the ability tags for the construction team. Among them, the labeled ability tags include skill tags, efficiency tags, and area tags.

[0022] Preferably, the specific steps of step S3 include:

[0023] S301. Based on the construction process dependency library, analyze the association degree between different construction tasks to obtain the association degree between construction tasks;

[0024] S302. According to the association degree between construction tasks, through the preset association degree threshold section, set the task association matrix into three types: strongly associated tasks, weakly associated tasks, and non - associated tasks;

[0025] S303. Assign a risk correlation coefficient to each task in the task correlation matrix according to the impact degree of the task risk. Among them, the values of the risk correlation coefficients are assigned to strongly correlated tasks, weakly correlated tasks, and uncorrelated tasks in descending order.

[0026] Preferably, the specific steps of step S4 include:

[0027] S401. Set up a dynamic task adjustment mechanism, including for strongly correlated tasks, if it is detected that the previous task is delayed, automatically increase the priority of the subsequent dependent tasks and trigger an alarm; for weakly correlated tasks, set a buffer interval and allow parallel tasks to be inserted;

[0028] S402. Set corresponding trigger conditions for the dynamic task adjustment mechanism. The trigger conditions include time threshold trigger or resource exception trigger. Among them, the determination rules for time threshold trigger include that the actual time consumption of strongly correlated task nodes exceeds the planned value by ≥ 2 days, or the task nodes of weakly correlated tasks exceed the planned value by ≥ 3 days; the determination rules for resource exception trigger include that the material inventory is lower than the preset safety threshold or the construction equipment failure has not been repaired for more than 4 hours.

[0029] Preferably, the specific steps of step S5 include:

[0030] S501. According to a preset cycle, use Internet of Things devices to collect construction progress data and equipment usage status in real time, compare the collected construction progress data and equipment usage status with the construction plan, and generate a progress deviation report;

[0031] S502. Based on the progress deviation report, judge whether it meets the trigger conditions. If it is judged to meet the trigger conditions, use the dynamic task adjustment mechanism to dynamically adjust strongly correlated tasks, weakly correlated tasks, and uncorrelated tasks respectively, specifically including: if it is detected that the previous task is delayed, automatically increase the priority of the subsequent dependent tasks and trigger an alarm; for weakly correlated tasks, set a buffer interval and allow parallel tasks to be inserted, if it is detected that the construction team in the area where the uncorrelated task is located is idle, insert a preset task that can be executed in advance;

[0032] S503. Assign the dynamically adjusted strongly correlated tasks, weakly correlated tasks, and uncorrelated tasks to the construction teams with corresponding ability labels.

[0033] An intelligent management system for indoor decoration design and construction, the management system includes:

[0034] An information acquisition module, used to acquire construction plan information, extract construction steps, technological processes, material lists, and construction divided areas from it, and establish a construction process dependency relationship library;

[0035] An information identification module is used to input the basic information of each construction team and label the ability tags for each construction team. Among them, the basic information of the construction team specifically includes personnel skill data and personnel historical efficiency data;

[0036] A task association module is used to construct a task association matrix and assign risk association coefficients based on a construction process dependency library. Among them, the task association matrix specifically includes strong association, weak association, and no association;

[0037] A dynamic adjustment module is used to establish a dynamic task adjustment mechanism and set trigger conditions based on the task association matrix and the set risk association;

[0038] A task generation module is used to regularly obtain the working status of the current construction team at a preset cycle and adjust the tasks of each construction team according to the trigger conditions and the task adjustment mechanism.

[0039] Compared with related technologies, an intelligent management method and system for indoor decoration design and construction provided by the present invention has the following beneficial effects:

[0040] By combining the steps of obtaining construction plan information and constructing a construction process dependency library with the steps of inputting the basic information of the construction team and labeling the ability tags, the present invention provides an accurate and comprehensive data basis for the subsequent construction of the task association matrix and the assignment of risk association coefficients; then, by integrating the steps of constructing a task association matrix and assigning risk association coefficients based on the construction process dependency library and the construction team ability tags with the steps of setting a dynamic task adjustment mechanism and its trigger conditions, the task adjustment mechanism can be dynamically set according to scientific and reasonable task relevance and risk level; finally, by closely associating the steps of obtaining the working status of the construction team at a preset cycle and adjusting tasks according to the trigger conditions and the task adjustment mechanism with the foregoing steps, a closed-loop intelligent management system is formed. The present invention realizes the efficient, accurate, and dynamic management of indoor decoration design and construction tasks, effectively improves the construction efficiency, reduces the construction risk, optimizes the resource allocation, and ensures the dual guarantee of construction progress and quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flowchart of an intelligent management method for indoor decoration design and construction provided in Embodiment 1 of the present invention;

[0042] Figure 2 It is a system block diagram of an intelligent management system for indoor decoration design and construction provided in Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The present invention will be further described below with reference to the drawings and embodiments.

[0044] Embodiment 1

[0045] As Figure 1 shown, an intelligent management method for interior decoration design and construction includes the following steps:

[0046] S1. Obtain the construction plan information, extract the construction steps, technological processes, material lists, and construction-divided areas from it, and establish a construction process dependency relationship library;

[0047] S2. Enter the basic information of each construction team and label the ability tags for each construction team. Among them, the basic information of the construction team specifically includes personnel skill data and personnel historical efficiency data;

[0048] S3. Based on the construction process dependency relationship library and the ability tags labeled for each construction team, construct a task association matrix and assign risk correlation coefficients. Among them, the task association matrix specifically includes strong association, weak association, and no association;

[0049] S4. Based on the task association matrix and the set risk association, establish a dynamic task adjustment mechanism and set trigger conditions;

[0050] S5. According to the preset cycle, regularly obtain the working status of the current construction team, and adjust the tasks of each construction team according to the trigger conditions and the task adjustment mechanism.

[0051] In the specific implementation process, the specific steps of step S1 include:

[0052] S101. Extract the construction steps, construction plans, material lists, and construction-divided areas of the construction plan information through BIM model or CAD drawing parsing technology.

[0053] Specifically, import the BIM model file or CAD drawing file of the interior decoration design into the existing data parsing software, deeply parse the imported model or drawing, identify the geometric feature changes in different construction stages and the annotation descriptions on the drawing. For example, in the stage of water and electricity transformation, it can identify the laying paths and connection methods of water pipes and electric wires, etc., so as to extract specific construction steps such as "water pipe grooving", "electric wire wiring", "pipe connection", etc.; for the construction plan, the software will analyze the time arrangement information of each construction step in the model or drawing, such as "the water pipe grooving plan starts on the 3rd day and lasts for 2 days", etc.; the extraction of the material list is through identifying the material attributes of each component in the model and the material annotations on the drawing. For example, it is identified that "latex paint" is used for the wall and "solid wood floor" is used for the ground, etc., and the quantity of the required materials is counted. The construction-divided areas are based on the spatial division of the model or the area annotations on the drawing, such as "living room area", "bedroom area", etc.; finally, organize the information such as the extracted construction steps, construction plans, material lists, and construction-divided areas, and output it in a structured format, such as an Excel table or a database record, for convenient subsequent processing and use.

[0054] S102. Based on the results of the regions divided by construction, bind each construction step to a specific spatial location to form a space - process mapping table.

[0055] Specifically, according to the construction regions divided in step S101, determine the specific spatial location of each region in the BIM model or CAD drawing. For example, in the CAD drawing, the boundary range of each region can be determined through the coordinate system; in the BIM model, the three - dimensional spatial location of each region can be directly viewed. Match each construction step extracted in step S101 with the corresponding construction region. According to the logical sequence and actual requirements of the construction, determine the execution sequence and location of each construction step within a specific region. For example, in the "living room area", first perform "wall base treatment", and then perform "wall latex painting". Finally, organize the matched construction steps and spatial location information into a space - process mapping table. This table takes the construction regions as rows and the construction steps as columns, and marks the execution sequence and relevant information of the construction steps in the corresponding cells of the region.

[0056] S103. Use a graph database to construct a construction process dependency library, where nodes represent processes and edges represent the dependency relationships between processes.

[0057] Specifically, take each construction step extracted in step S101 as a node in the graph database. Assign a unique identifier and relevant attribute information to each node, such as the construction step name, estimated construction period, required resources, etc. For example, the "water pipe grooving" node contains attributes "Name: Water pipe grooving, Construction period: 2 days, Required resources: Electric drill, Grooving machine, etc.". Analyze the logical sequence and dependency relationships between each construction step. For example, "water pipe installation" can only be carried out after "water pipe grooving" is completed, and "water pressure test" can only be carried out after "water pipe installation" is completed. According to these dependency relationships, determine the edges between the nodes, and mark the type of the edge (such as pre - dependency, post - dependency) and relevant information (such as dependency strength, delay time, etc.); import the created nodes and the determined dependency relationship edges into the database to construct the construction process dependency library, and the dependency library can be queried through the query language (Cypher) of the graph database.

[0058] In the specific implementation process, the specific steps of step S2 include:

[0059] S201. Obtain the basic information of each construction team, including personnel skill data and personnel historical efficiency data.

[0060] Specifically, an online questionnaire survey is organized to let the members of the construction team fill in information, collecting the personal basic information of the construction team members (such as name, age, gender, contact information), work experience (such as the name of the decoration project participated in the past, project scale, role held), and professional skills.

[0061] S202. According to the personnel skill data and historical efficiency data, use the clustering algorithm to label the identification capabilities of the construction teams. Among them, the identification capability labels include skill labels, efficiency labels, and area labels.

[0062] Specifically, according to the basic information of each construction team, extract the skill types (such as electrician, carpenter, bricklayer) and levels (such as senior, intermediate) in the professional skills of the construction team members to generate a skill list, and assign an evaluation coefficient according to the level of the skill type. For the skill label, in this embodiment, the evaluation coefficients assigned to the levels of the skill type are specifically senior = 3 points, intermediate = 2 points, junior = 1 point. Then, according to the assigned evaluation coefficients, calculate the total skill score of each construction team by summing. For the efficiency label, extract the output per unit time of each member in past projects from the personnel historical efficiency data and calculate the average efficiency of each construction team. For the area label, assign an area label to the construction team, such as the construction team is good at the construction of Area A in the divided area. Standardize the features such as the skill scores, average efficiency, and area labels of each construction team to eliminate the dimension difference, and use the K-means clustering algorithm to divide them into 3 categories according to the similarity of the construction team features, specifically including all-round type, efficiency type, and area type. Finally, generate descriptive labels for each clustering category, such as Category 1: All-round construction team, good at the construction of City A, with comprehensive skills and high efficiency.

[0063] In the specific implementation process, the specific steps of step S3 include:

[0064] S301. Based on the construction process dependency library, analyze the correlation degree between different construction tasks to obtain the correlation degree between construction tasks.

[0065] Specifically, by traversing the nodes and edges in the construction process dependency library, obtain the direct pre-process and subsequent process information of each process. Exemplarily, if there is a "pre - dependency" relationship between process A (hydropower installation) and process B (wall plastering), it is recorded as A→B. Then set the calculation rule for task correlation degree, specifically, if process B must wait for process A to complete before it can start, the correlation degree is strongly correlated; if process B needs to start within a certain time (such as within 24 hours) after process A is completed, the correlation degree is weakly correlated; if there is no time or space constraint between process B and process A, the correlation degree is uncorrelated, such as if process A and process B do not need to be constructed in the same area or the same time period.

[0066] S302. According to the correlation degree between construction tasks, through a preset correlation degree threshold section, the task correlation matrix is set into three types: strongly correlated tasks, weakly correlated tasks, and uncorrelated tasks.

[0067] Specifically, in this embodiment, the correlation degree threshold section is divided as follows: strongly correlated tasks: time interval ≤ 1 day or regional overlap degree ≥ 50%; weakly correlated tasks: time interval ≤ 3 days and regional overlap degree < 50%; uncorrelated tasks: time interval > 3 days and no regional overlap; then, based on the correlation degree threshold section, all tasks are further divided to obtain the divided tasks.

[0068] S303. According to the influence degree of task risks, a risk correlation coefficient is assigned to each task in the task correlation matrix, where the values of the risk correlation coefficients are assigned to strongly correlated tasks, weakly correlated tasks, and uncorrelated tasks in descending order.

[0069] Specifically, the divided tasks are evaluated for the degree of risk influence. Specifically, among strongly correlated tasks, if the delay of the preceding task directly causes the subsequent task to be unable to start, it is listed as the highest risk, and the assigned risk correlation coefficient is 0.8; among weakly correlated tasks, tasks with a buffer time allowing a certain delay are listed as medium risk, and the assigned risk correlation coefficient is 0.5; among uncorrelated tasks, tasks with independent construction are listed as the lowest risk, and the assigned risk correlation coefficient is 0.2.

[0070] In the specific implementation process, the specific steps of step S4 include:

[0071] S401. Set a dynamic task adjustment mechanism, including for strongly correlated tasks, if it is detected that the preceding task is delayed, automatically raise the priority of the subsequent dependent tasks and trigger an alarm; for weakly correlated tasks, set a buffer interval and allow parallel tasks to be inserted.

[0072] Specifically, in the strong correlation task adjustment rule, if a previous task (such as process A) is detected to be delayed, the priority of the subsequent dependent task (such as process B) will be automatically increased, and an early warning mechanism will be triggered to notify the project manager and the construction team. Exemplarily, if process A (hydropower installation) was originally planned to take 3 days but actually took 5 days (delayed by 2 days), the priority of process B (wall plastering) will be automatically increased, and process B will be required to reschedule within 24 hours and an early warning will be generated to notify the construction team. In the weak correlation task adjustment rule, a delay buffer time is set for the weak correlation task, such as a buffer time of ±3 days. If the buffer time is exceeded, an adjustment will be triggered. Then, parallel tasks will be inserted. If the previous task (such as process D) of the weak correlation task (such as process C) is completed ahead of schedule, other parallel tasks (such as process E) are allowed to be inserted. In the uncorrelated task adjustment rule, if the construction team in the area where the uncorrelated task is located is idle, preset tasks that can be executed in advance (such as temporary cleaning, material sorting) will be inserted.

[0073] S402. Set corresponding trigger conditions for the dynamic task adjustment mechanism. The trigger conditions include time threshold trigger or resource exception trigger. Among them, the determination rule for time threshold trigger includes that the actual duration of the strong correlation task node exceeds the planned value by ≥2 days, or the weak correlation task node exceeds the planned value by ≥3 days; the determination rule for resource exception trigger includes that the material inventory is lower than the preset safety threshold or the construction equipment failure has not been repaired for more than 4 hours.

[0074] In the specific implementation process, the specific steps of step S5 include:

[0075] S501. According to a preset cycle, use Internet of Things devices to collect construction progress data and equipment usage status in real time, compare the collected construction progress data and equipment usage status with the construction plan, and generate a progress deviation report.

[0076] Specifically, according to a preset cycle, use Internet of Things devices (such as smart bracelets, RFID tags, cameras) to collect the working status of the construction team in real time, including the completion progress of each process (such as process A is 80% completed, process B is suspended) and the distribution of construction team personnel (such as construction team 1 is in area A, construction team 2 is in area B); collect the operation data of construction equipment through equipment sensors, including equipment failure alarms (such as crane failure, drill overheating) or equipment usage duration (such as a certain equipment has been running continuously for 12 hours); material inventory data: obtain the material consumption situation in real time by accessing the warehouse management system; then, compare the collected data with the construction plan, and generate a progress deviation report including: progress deviation: the difference between the actual duration and the planned duration of a certain process (such as process A is planned for 3 days, but actually takes 5 days); resource deviation: whether the material inventory is lower than the preset safety threshold, and whether the equipment has failed and exceeded the time limit for repair.

[0077] S502. Judge whether it meets the trigger condition based on the progress deviation report. If it is judged to meet the trigger condition, dynamically adjust the strongly associated tasks, weakly associated tasks, and unassociated tasks respectively through the dynamic task adjustment mechanism, specifically including: if it is detected that the preceding task is delayed, automatically raise the priority of the subsequent dependent tasks and trigger an alarm; for weakly associated tasks, set a buffer interval and allow parallel tasks to be inserted. If it is detected that the construction team in the area where the unassociated task is located is idle, insert the preset tasks that can be executed in advance.

[0078] S503. Assign the dynamically adjusted strongly associated tasks, weakly associated tasks, and unassociated tasks to the construction teams corresponding to the ability labels.

[0079] Specifically, according to the ability labels of the construction teams (skill label, efficiency label, area label), assign the adjusted tasks to the most suitable construction teams. Specifically, for strongly associated tasks: assign them to the construction teams with high efficiency and high skills in the ability labels; for weakly associated tasks: assign them to the construction teams with the ability of parallel construction; for unassociated tasks: assign them to the currently idle construction teams without task arrangements.

[0080] Embodiment 2

[0081] As Figure 2 shown, an intelligent management system for interior decoration design and construction applied to an intelligent management method for interior decoration design and construction specifically includes:

[0082] An information acquisition module, used to acquire construction plan information, extract construction steps, technological processes, material lists, and construction-divided areas from it, and establish a construction process dependency relationship library;

[0083] An information identification module, used to input the basic information of each construction team and label the ability labels for each construction team. Among them, the basic information of the construction team specifically includes personnel skill data and personnel historical efficiency data;

[0084] A task association module, used to construct a task association matrix and assign risk association coefficients based on the construction process dependency relationship library. Among them, the task association matrix specifically includes strong association, weak association, and no association;

[0085] A dynamic adjustment module, used to establish a dynamic task adjustment mechanism and set trigger conditions based on the task association matrix and the set risk associations;

[0086] A task generation module, used to regularly acquire the working status of the current construction team at a preset cycle, and adjust the tasks of each construction team according to the trigger conditions and the task adjustment mechanism.

[0087] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce means for implementing the functions specified in one flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0088] Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), or other optical disc storage, magnetic disk storage, tape storage, or any other medium that can be used to carry or store data and is computer-readable.

[0089] It should also be noted that the term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "including one..." does not exclude the presence of another identical element in the process, method, article, or apparatus that includes the element.

Claims

1. An intelligent management method for interior decoration design and construction, characterized in that, The described management method includes the following steps: S1. Obtain the construction plan information, extract the construction steps, technological processes, material list, and construction-divided areas from it, and establish a construction process dependency relationship library; S2. Input the basic information of each construction team and label the ability tags for each construction team. Among them, the basic information of the construction team specifically includes personnel skill data and personnel historical efficiency data; S3. Based on the construction process dependency relationship library, construct a task association matrix and assign risk association coefficients. Among them, the task association matrix specifically includes strong association, weak association, and no association; S4. Based on the task association matrix and the set risk associations, establish a dynamic task adjustment mechanism and set trigger conditions; S5. According to a preset cycle, regularly obtain the working status of the current construction team, and adjust the tasks of each construction team according to the trigger conditions and the task adjustment mechanism.

2. The intelligent management method for indoor decoration design and construction according to claim 1, characterized in that, The specific steps of step S1 include: S101. Extract the construction steps, construction plan, material list, and construction-divided areas of the construction plan information through BIM model or CAD drawing parsing technology; S102. Based on the results of the construction-divided areas, bind each construction step to a specific spatial location to form a space-process mapping table; S103. Use a graph database to construct a construction process dependency relationship library, where nodes represent processes and edges represent the dependency relationships between processes.

3. The intelligent management method for indoor decoration design and construction according to claim 2, characterized in that, The specific steps of step S2 include: S201. Obtain the basic information of each construction team, including personnel skill data and personnel historical efficiency data; S202. According to the personnel skill data and historical efficiency data, use a clustering algorithm to label the ability tags for the construction team. Among them, the labeled ability tags include skill tags, efficiency tags, and area tags.

4. An intelligent management method for indoor decoration design and construction according to claim 3, characterized in that The specific steps of step S3 include: S301. Based on the construction process dependency relationship library, analyze the association degree between different construction tasks to obtain the association degree between construction tasks; S302. According to the association degree between construction tasks, through a preset association degree threshold section, set the task association matrix into three types: strongly associated tasks, weakly associated tasks, and non-associated tasks; S303. According to the influence degree of task risks, assign risk association coefficients to each task in the task association matrix. Among them, the values of the risk association coefficients are assigned to strongly associated tasks, weakly associated tasks, and non-associated tasks in order from large to small.

5. The intelligent management method for indoor decoration design and construction according to claim 4, characterized in that, The specific steps of step S4 include: S401. Set a dynamic task adjustment mechanism, including for strongly associated tasks, if it is detected that the preceding task is delayed, automatically raise the priority of the subsequent dependent task and trigger an alarm; for weakly associated tasks, set a buffer interval and allow parallel tasks to be inserted; S402. Set corresponding trigger conditions for the dynamic task adjustment mechanism. The trigger conditions include time threshold trigger or resource exception trigger. Among them, the determination rules for time threshold trigger include that the actual time consumption of strongly associated task nodes exceeds the planned value by ≥ 2 days, or the task nodes of weakly associated tasks exceed the planned value by ≥ 3 days; the determination rules for resource exception trigger include that the material inventory is lower than the preset safety threshold or the construction equipment failure has not been repaired for more than 4 hours.

6. The intelligent management method for interior decoration design and construction according to claim 5, characterized in that, The specific steps of step S5 include: S501. At a preset period, collect construction progress data and equipment usage status in real time through Internet of Things devices, compare the collected construction progress data and equipment usage status with the construction plan, and generate a progress deviation report. S502. Based on the progress deviation report, determine whether it meets the trigger condition. If it is determined that the trigger condition is met, dynamically adjust the strongly associated tasks, weakly associated tasks, and unassociated tasks respectively through the dynamic task adjustment mechanism, specifically including: if it is detected that the previous task is delayed, automatically increase the priority of the subsequent dependent tasks and trigger an alarm; for weakly associated tasks, set a buffer interval and allow parallel tasks to be inserted. If it is detected that the construction team in the area where the unassociated task is located is idle, insert a preset task that can be executed in advance. S503. Assign the dynamically adjusted strongly associated tasks, weakly associated tasks, and unassociated tasks to the construction teams with corresponding ability labels.

7. An intelligent management system for interior decoration design and construction, which is applied to an intelligent management method for interior decoration design and construction according to any one of claims 1-6, characterized in that, The management system includes: An information acquisition module, which is used to acquire construction plan information, extract construction steps, technological processes, material lists, and construction divided areas from it, and establish a construction process dependency relationship library. An information identification module, which is used to input the basic information of each construction team and identify ability labels for each construction team. Among them, the basic information of the construction team specifically includes personnel skill data and personnel historical efficiency data. A task association module, which is used to construct a task association matrix and assign risk association coefficients based on the construction process dependency relationship library. Among them, the task association matrix specifically includes strong association, weak association, and no association. A dynamic adjustment module, which is used to establish a dynamic task adjustment mechanism and set trigger conditions based on the task association matrix and the set risk association. A task generation module, which is used to regularly obtain the working status of the current construction team at a preset period, and adjust the tasks of each construction team according to the trigger condition and the task adjustment mechanism.

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