Building engineering construction management system based on artificial intelligence

Abstract

The invention discloses a building engineering construction management system based on artificial intelligence, and relates to the technical field of building engineering supervision, and the system comprises a front-end data management module which is used for coordinating pre-connected sensing equipment and a supplier system, and collecting construction associated data of a construction site; the analysis and decision module is used for analyzing and processing the construction associated data based on a preset optimization and adjustment logic and generating an optimization plan and an adjustment suggestion; the visual management module is used for presenting a construction progress, a to-be-optimized point location and a to-be-adjusted point location on the basis of a pre-imported BIM model; the sensing device comprises an environment monitoring sensor, a device operation monitoring sensor, a fixed-point vision module, a mobile vision module and a personal terminal. According to the invention, the construction process of the building engineering can be managed more conveniently.

Description

Technical Field

[0001] The present application relates to the technical field of construction project supervision, and in particular to an artificial intelligence-based construction project management system. Background Art

[0002] During the construction process, construction management has been facing many challenges. Problems such as information opacity, unreasonable resource utilization, and widespread safety hazards have had a serious impact on the efficiency and quality of construction projects.

[0003] Under the traditional construction management model, information opacity is high, and decision makers often cannot obtain timely and accurate project information, resulting in mistakes in decision-making in plan adjustment and resource allocation, which may eventually lead to problems such as project delays and cost overruns. In addition, due to unreasonable resource allocation, resources such as manpower and materials may be wasted, increasing project costs. In addition, safety issues in construction projects have always attracted much attention, but due to the lack of effective and real-time safety monitoring and early warning mechanisms, safety accidents continue to occur.

[0004] Although some existing digital tools, such as Building Information Modeling (BIM) and project management software, have improved these problems to a certain extent, these tools are highly dependent on human operation, making coordination among various units extremely difficult, and are less timely when processing a large amount of complex work. Therefore, this application proposes a new technical solution. Summary of the invention

[0005] In order to manage the construction process of a construction project more conveniently, the present application provides a construction management system based on artificial intelligence.

[0006] This application provides a construction management system based on artificial intelligence, which adopts the following technical solutions:

[0007] An artificial intelligence-based construction management system for building engineering, comprising:

[0008] A front-end data management module, which is used to coordinate pre-connected sensing devices and supplier systems to collect construction-related data at the construction site; wherein the construction-related data includes on-site environment data, material usage data, equipment data, personnel behavior data, and construction progress;

[0009] The analysis and decision-making module is used to analyze and process the construction-related data based on the preset optimization and adjustment logic to generate optimization plans and adjustment suggestions;

[0010] Visual management module, which is used to present the construction progress, points to be optimized and adjusted based on the pre-imported BIM model;

[0011] The sensing device includes an environmental monitoring sensor, an equipment operation monitoring sensor, a fixed-point vision module, a mobile vision module and a personal terminal, and the front-end data management module:

[0012] If the interaction data and / or machine time meet the preset data collection conditions, a request is made to obtain the data collected by the sensing device on the construction site, and the data collection behavior of the sensing device is triggered.

[0013] Optionally, the analysis and decision-making module includes a construction scheduling and resource optimization unit and a mobile visual management unit, and the mobile visual management unit:

[0014] Acquire on-site environmental data and determine whether the current environmental conditions meet the requirements for the mobile vision module to move outdoors. If so, send a wake-up command to the mobile vision module after the mobile vision module receives a request to collect data from the construction site; if not, send a standby command to the mobile vision module.

[0015] Optionally, the mobile vision management unit:

[0016] Obtain the location distribution data and visual validity range data of the fixed-point vision module;

[0017] Generate fixed-point vision distribution data and visual blind spot distribution data based on position distribution data and visual effectiveness range data;

[0018] Obtain the location of the waypoints actively selected by the staff and the location of the standby site of the mobile vision module;

[0019] The data collection path of the mobile vision module is generated based on the visual blind spot distribution data, the path point location and the mobile vision module standby site location.

[0020] Optionally, the mobile vision management unit:

[0021] Visual distribution data and visual blind spot distribution data are presented in the BIM model to obtain a visual inspection model;

[0022] The path point selection information initiated on the visual inspection model is obtained, and the actual space coordinates of the BIM model are converted to obtain the path point position.

[0023] Optionally, the mobile vision management unit: if the visual movement unit is ≥ 2, the path point positions of the data collection path are allocated based on a preset proximity rule.

[0024] Optionally, the mobile vision management unit:

[0025] Get the current endurance data of the visual mobile unit;

[0026] Correct the data collection path allocation results based on the safe return priority rule.

[0027] Optionally, it also includes a quality and safety monitoring module, wherein:

[0028] Recognize images acquired through fixed-point vision modules and mobile vision modules;

[0029] Based on the image recognition results, potential quality problems and construction risks are determined, and the determination results are output as prompts.

[0030] Optionally, the quality and safety monitoring module:

[0031] Obtain identity information of workers at the construction site;

[0032] If the behavior corresponding to a certain staff member is determined to be a construction risk, the preset personnel information database is searched according to the identity information to obtain the pre-stored identification information of the personal terminal, and a prompt is sent to the matching personal terminal according to the identification information.

[0033] In summary, this application includes the following beneficial technical effects:

[0034] 1. Collect information on the construction site in real time, continuously monitor changes on the construction site for analysis and resolution by the analysis and decision-making module, automatically generate optimization plans and adjustment suggestions, reduce manual dependence and improve the accuracy and efficiency of decision-making;

[0035] 2. Combined with BIM technology, construction-related information is visualized through 3D models, allowing project managers and team members to intuitively view construction progress, identify problem areas, and evaluate the effectiveness of resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a structural diagram of this system;

[0037] Figure 2 It is a schematic diagram of the visual layout of this system and the moving path of the mobile visual module. DETAILED DESCRIPTION

[0038] The following is combined with Figure 1-2 This application is described in further detail.

[0039] The embodiment of the present application discloses a construction management system for a building project based on artificial intelligence.

[0040] Reference Figure 1The construction management system based on artificial intelligence includes a front-end data management module, an analysis and decision-making module, and a visualization module. Because the system is implemented by a corresponding computer loading a corresponding computer program, the above modules are program function modules, which are explained in detail below.

[0041] A front-end data management module is used to coordinate pre-connected sensing devices and supplier systems to collect construction-related data at the construction site; and it:

[0042] The interaction data and / or machine time meet the preset data collection conditions. For example, when a staff member initiates a request and the current time is the preset sampling start time point, a request is made to obtain the data collected by the sensing device on the construction site and trigger the data collection behavior of the sensing device.

[0043] The above-mentioned sensing devices include environmental monitoring sensors, such as: rain sensors, anemometers, and temperature sensors installed at the construction site; equipment operation monitoring sensors, such as: intelligent gateways whose data is connected to the control system of the on-site construction equipment, current / voltage sensors or acceleration sensors installed on low-automation equipment, and sensors equipped with data transmission modules to upload data; fixed-point visual modules, such as: cameras installed at various locations on the construction site, preferably with night vision and rotatable lenses; mobile visual modules include drones and mobile carts with cameras, preferably drones; personal terminals, such as: mobile phones. The above-mentioned sensing devices are all connected to a computer loaded with a front-end data management module through a communication network to automatically collect front-end data.

[0044] The above-mentioned supplier systems, for example: procurement systems corresponding to concrete mixing plants, scaffolding suppliers, steel bar accessories suppliers, water and electricity pipe fittings suppliers, etc.

[0045] On the premise of setting up the above-mentioned sensing equipment, construction-related data include on-site environmental data, such as: rain or shine, wind speed, and temperature, so as to evaluate whether it is suitable for carrying out construction work; material usage data, such as: material entry and exit usage records actively uploaded by staff through mobile phones, material types, entry and exit records, and material order records obtained through image recognition taken by fixed-point vision modules and mobile vision modules; equipment data, such as: the category, start and stop information, fault information, and power of each equipment; personnel behavior data, such as: operating behaviors and other behaviors obtained through image recognition taken by fixed-point vision modules and mobile vision modules; construction progress, such as: project progress actively uploaded by staff through mobile phones, and project progress obtained through image recognition taken by fixed-point vision modules and mobile vision modules.

[0046] The analysis and decision-making module is used to analyze and process construction-related data based on the preset optimization and adjustment logic, and generate optimization plans and adjustment suggestions.

[0047] Example of optimization and adjustment logic: Project A, designed concrete consumption is 15,000 cubic meters, the current construction progress is 80%, and the intermediate process construction adjustment consumes 800 cubic meters more in each stage, a total of 6 stages, then timely generate adjustment suggestions: add 6*800 cubic meters, and estimate the increased budget based on the unit price of the supplier system. Project B, originally planned for 25 months, the 3rd stage was completed in the 19th month, and there are two more stages after that, one stage designed for 6 months, and the other stage designed for 2 months, and it is expected to exceed the deadline by 2 months, then generate an optimization plan: the original working hours are 8 am-5:30 pm, and the shift system will be used from the next week, and the second shift will be from 5:30 pm-9 pm, which will last for 4 months. For optimization and adjustment logic, models with machine learning capabilities such as neural network models are preferred to better analyze and interpret the collected data in depth.

[0048] The visualization management module is used to present the construction progress, points to be optimized and adjusted based on the pre-imported BIM model. For example, if the second floor slab is poured, the building model with the second floor slab will be displayed; if two additional fire wells need to be dug in the third phase of the project, the locations of the fire wells expected to be dug in the third phase in the model will be displayed separately.

[0049] Based on the above, this system:

[0050] 1. Collect information on the construction site in real time, continuously monitor changes on the construction site for analysis and resolution by the analysis and decision-making module, automatically generate optimization plans and adjustment suggestions, reduce manual dependence and improve the accuracy and efficiency of decision-making;

[0051] 2. Combined with BIM technology, construction-related information is visualized through 3D models, allowing project managers and team members to intuitively view construction progress, identify problem areas, and evaluate the effectiveness of resource allocation.

[0052] In another embodiment of the system, the analysis and decision module includes a construction scheduling and resource optimization unit and a mobile visual management unit, wherein the construction scheduling and resource optimization unit can be used to implement the example shown in the previous embodiment. Mobile visual management unit:

[0053] Acquire on-site environmental data and determine whether the current environmental conditions meet the requirements for the mobile vision module to move outdoors. If so, send a wake-up command to the mobile vision module after the mobile vision module receives a request to collect data from the construction site; if not, send a standby command to the mobile vision module.

[0054] Taking the mobile vision module as an example of a drone, according to the performance of the drone, if the wind speed and rainfall in the on-site environment exceed the design flight standards, if the drone is forcibly released, it will cause the drone to malfunction or be damaged. Therefore, this system manages the movement of the mobile vision module based on the environmental data obtained by the front end.

[0055] In one embodiment of the system, the path of the drone when taking off to collect information at the construction site is not manually controlled, but automatically generated. Specifically:

[0056] Obtain the position distribution data of the fixed-point vision module (i.e., each camera) and the visual effectiveness range data (i.e., the effective distance and angle of the camera); the two data here need to be actively uploaded by the staff.

[0057] Generate fixed-point visual distribution data and visual blind spot distribution data based on position distribution data and visual effectiveness range data; Figure 2 ,Example: a1, a2... in the figure represent the cameras of the fixed-point vision module. The circle drawn by a1, a2... is the corresponding visual effectiveness range, and the other areas outside the circle are the visual blind spots.

[0058] Obtain the path point locations actively selected by the staff and the mobile vision module standby site locations; the two data are actively uploaded by the staff.

[0059] The data collection path of the mobile vision module is generated based on the visual blind spot distribution data, the path point location and the mobile vision module standby site location.

[0060] like Figure 2 As shown, for example: in the figure, b1, b2... represent the path points actively selected by the staff, c1 and c2 represent the stations, and the generated data collection path requires connecting c1 with b1, b2... and passing through the visual blind spot; or, connecting c2 with b1, b2... and passing through the visual blind spot.

[0061] According to the above settings, the system's dependence on manual labor is further reduced, which can effectively reduce the impact of information lag caused by untimely operations.

[0062] Further, the mobile visual management unit:

[0063] Visual distribution data and visual blind spot distribution data are presented in the BIM model. For example, the above Figure 2 , and according to the installation height of the camera, the flight height of the drone, the three-dimensional path and range, the visual inspection model is obtained;

[0064] Get the path point selection information initiated on the visual inspection model (such as the position of the mouse double-click after turning on the path point selection function), and convert the actual space coordinates of the BIM model to obtain the path point position (that is, the coordinate conversion is performed based on the scale calculated by the model size and the actual size).

[0065] According to the above settings, workers can check the coverage of visual acquisition on the construction site more intuitively and it is relatively easier to find omissions.

[0066] It should be noted that for mobile visual management units: if the visual mobile unit (i.e., drone) is ≥ 2, the path point position of the data collection path is assigned based on the preset proximity rule. For example: there are two path point positions b1 and b2, site c1 is 120m away from b1, and site c1 is 80m away from b2, and b2 is assigned to c1.

[0067] The above settings can improve the efficiency of visual data collection, make full use of each site, and make the flight path of the drone more reasonable.

[0068] Due to the current limitations of battery technology, although the station can be used to charge the drone, the battery degradation, whether it is charged correctly, and the charging time will change the drone's endurance. Therefore, the mobile vision management unit:

[0069] Get the current endurance data of the visual mobile unit;

[0070] The data collection path allocation result is corrected based on the safety return priority rule. For example, if the remaining battery life is 17 minutes, and the current collection path length / drone flight speed = 26 minutes, then based on the principle of proximity, several points far from the site are eliminated until the calculated time is within 13 minutes to ensure that the drone can return smoothly.

[0071] In another embodiment of the system, it also includes a quality and safety monitoring module, the quality and safety monitoring module:

[0072] Recognize images acquired through fixed-point vision modules and mobile vision modules;

[0073] Based on the image recognition results, potential quality problems and construction risks are determined, and the determination results are output as prompts. For example: workers are working directly under the lifting object of the tower crane, workers are walking on the construction site without wearing safety helmets, and the diameter of the steel bars used in the floor slab pouring does not match the design specifications.

[0074] According to the above settings, this system can improve the safety and quality standards of the project and effectively prevent the occurrence of project accidents and quality problems.

[0075] Furthermore, the above prompts are generally output to project managers and back-end, who may not be able to notify specific personnel on site in a timely manner. Therefore, the quality and safety monitoring module:

[0076] Obtain the identity information of the staff at the construction site (e.g., obtaining the name through face recognition);

[0077] If the behavior corresponding to a certain staff member is judged as a construction risk, the preset personnel information database is searched according to the identity information to obtain the pre-stored identification information (mobile phone number) of the personal terminal (mobile phone), and a prompt is sent to the matching personal terminal according to the identification information. The prompt can be a mobile phone text message or an alarm sound of a pre-developed functional App.

[0078] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A construction management system based on artificial intelligence, characterized in that: include: A front-end data management module, which is used to coordinate pre-connected sensing devices and supplier systems to collect construction-related data at the construction site; wherein the construction-related data includes on-site environment data, material usage data, equipment data, personnel behavior data, and construction progress; The analysis and decision-making module is used to analyze and process the construction-related data based on the preset optimization and adjustment logic to generate optimization plans and adjustment suggestions; Visual management module, which is used to present the construction progress, points to be optimized and adjusted based on the pre-imported BIM model; The sensing device includes an environmental monitoring sensor, an equipment operation monitoring sensor, a fixed-point vision module, a mobile vision module and a personal terminal; the front-end data management module: If the interaction data and / or machine time meet the preset data collection conditions, a request is made to obtain the data collected by the sensing device on the construction site, and the data collection behavior of the sensing device is triggered.

2. The construction management system based on artificial intelligence according to claim 1 is characterized by: The analysis and decision-making module includes a construction scheduling and resource optimization unit and a mobile visual management unit. The mobile visual management unit: Acquire on-site environmental data and determine whether the current environmental conditions meet the requirements for the mobile vision module to move outdoors. If so, send a wake-up command to the mobile vision module after the mobile vision module receives a request to collect data from the construction site; if not, send a standby command to the mobile vision module.

3. The construction management system based on artificial intelligence according to claim 2 is characterized in that: The mobile vision management unit: Obtain the location distribution data and visual validity range data of the fixed-point vision module; Generate fixed-point vision distribution data and visual blind spot distribution data based on position distribution data and visual effectiveness range data; Obtain the location of the waypoints actively selected by the staff and the location of the standby site of the mobile vision module; The data collection path of the mobile vision module is generated based on the visual blind spot distribution data, the path point location and the mobile vision module standby site location.

4. The construction management system based on artificial intelligence according to claim 3 is characterized in that: The mobile vision management unit: Visual distribution data and visual blind spot distribution data are presented in the BIM model to obtain a visual inspection model; The path point selection information initiated on the visual inspection model is obtained, and the actual space coordinates of the BIM model are converted to obtain the path point position.

5. The construction management system based on artificial intelligence according to claim 2 is characterized in that: The mobile vision management unit: if the visual movement unit is ≥ 2, the path point position of the data collection path is allocated based on a preset proximity rule.

6. The construction management system based on artificial intelligence according to claim 5 is characterized in that: The mobile vision management unit: Get the current endurance data of the visual mobile unit; Correct the data collection path allocation results based on the safe return priority rule.

7. The construction management system based on artificial intelligence according to claim 1 is characterized in that: It also includes a quality and safety monitoring module, wherein: Recognize images acquired through fixed-point vision modules and mobile vision modules; Based on the image recognition results, potential quality problems and construction risks are determined, and the determination results are output as prompts.

8. The construction management system based on artificial intelligence according to claim 7 is characterized in that: The quality and safety monitoring module: Obtain identity information of workers at the construction site; If the behavior corresponding to a certain staff member is determined to be a construction risk, the preset personnel information database is searched according to the identity information to obtain the pre-stored identification information of the personal terminal, and a prompt is sent to the matching personal terminal according to the identification information.

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