Intelligent construction project intelligent level evaluation method based on human-intelligent cooperation ternary theory

Abstract

The invention provides an intelligent level evaluation method for an intelligent construction project based on a human-intelligent cooperation ternary theory. The method comprises the following steps: acquiring target project data and traditional equipment intelligent correction parameters of each stage; according to the target project data, determining a total manual proportion, a traditional equipment proportion, a man-machine cooperation proportion and an intelligent equipment participation proportion in man-machine cooperation of each stage; according to a human-intelligent cooperation ternary theory, taking the proportions and the corresponding intelligent correction parameters of the traditional equipment as evaluation parameters, and obtaining the intelligent degree of each stage; and obtaining the intelligent degree of the whole life cycle according to the intelligent degree of each stage and the predetermined weight of each stage. According to the invention, from the perspective of non-intelligence, the dynamic proportion of tasks independently completed by manpower, traditional equipment, man-machine cooperation and intelligent equipment in the construction process is analyzed, the globality and coordination of intelligent implementation are ensured, and scientific support is provided for efficient management and implementation of intelligent construction projects.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent level assessment, and specifically relates to an intelligent level assessment method for intelligent construction projects based on the human-intelligence synergy ternary theory. Background Art

[0002] The degree of intelligence refers to the comprehensive contribution of intelligent equipment, automation technology and human-machine collaboration to construction efficiency and resource optimization during the implementation of engineering projects. The level of intelligence throughout the life cycle reflects the effect of the overall intelligent transformation of the project by integrating the degree of intelligence at each stage. With the rapid development of intelligent construction technology, the widespread application of intelligent equipment, automation tools and artificial intelligence technology has gradually become the mainstream of the industry. Using these technologies to improve construction efficiency and resource utilization has become an industry trend. However, in the process of gradually transitioning from traditional construction mode to intelligent construction, how to scientifically measure the degree of intelligence and dynamically optimize resource allocation and construction paths is still a key issue that needs to be solved urgently.

[0003] The core of intelligent construction lies in the accurate assessment and dynamic optimization of the degree of intelligence. However, the current intelligent technology is changing rapidly, and the technical form and application level vary greatly at different stages, making it challenging to conduct quantitative analysis only from the perspective of intelligence. Existing technologies often evaluate the degree of intelligence based on the goal of intelligence, ignoring the basic characteristics of traditional construction modes, and failing to fully measure the actual role of manual tasks and traditional equipment in the process of intelligent transformation. At the same time, with the rapid development of intelligent equipment and digital platforms, their complexity and diversity make it difficult for existing evaluation methods to fully adapt to the needs of rapid technology iteration and diversified application scenarios. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a method and device for evaluating the intelligence level of intelligent construction projects based on the human-intelligence synergy ternary theory, so as to meet the demand for effectively evaluating the intelligence level of intelligent construction.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] According to the first aspect, the present invention provides a method for evaluating the intelligence level of intelligent construction projects based on the human-intelligence collaboration ternary theory, including: obtaining target project data of intelligent construction projects and intelligent correction parameters of traditional equipment at each stage; determining the total labor ratio, traditional equipment ratio, human-machine cooperation ratio and intelligent equipment participation ratio in human-machine cooperation at each stage of the project according to the target project data; according to the human-intelligence collaboration ternary theory, taking the total labor ratio, traditional equipment ratio, human-machine cooperation ratio, intelligent equipment participation ratio in human-machine cooperation ratio and corresponding traditional equipment intelligent correction parameters at each stage of the project as evaluation parameters to obtain the degree of intelligence at each stage; according to the degree of intelligence at each stage and the predetermined weights of each stage, the degree of intelligence throughout the life cycle is obtained.

[0007] Optionally, according to the ternary theory of human-intelligence collaboration, the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, intelligent equipment participation ratio in human-machine collaboration ratio and corresponding traditional equipment intelligent correction parameters of each stage of the project are used as evaluation parameters to obtain the degree of intelligence of each stage, including: dividing the tasks completed in each stage into three categories according to independent completion by manual labor, completion by human-machine collaboration and independent completion by intelligent equipment to obtain constraints, among which human-machine collaboration includes completion by human and traditional equipment and completion by human and intelligent equipment; determining the total proportion of human-machine collaboration and manual independent completion based on the constraints and the total labor ratio and the traditional equipment ratio; determining the intelligent contribution value of traditional equipment based on the human-machine collaboration ratio, the intelligent equipment participation ratio in human-machine collaboration and the intelligent correction parameters of traditional equipment; determining the degree of intelligence of each stage based on the total proportion of human-machine collaboration and manual independent completion and the intelligent contribution value of traditional equipment.

[0008] Optionally, the degree of intelligence at each stage is determined based on the total proportion of work completed by human-machine collaboration and work completed independently by humans, as well as the intelligent contribution value of traditional equipment, including:

[0009] S i =1-(a i +b i )+x i ·d t,λ b i ;

[0010] Among them, S i represents the degree of intelligence at stage i, a i represents the pure manual labor ratio in stage i, a i +b i represents the total proportion of human-machine collaboration and manual independent completion, b i represents the proportion of human-machine collaboration, x i represents the proportion of intelligent devices involved in human-machine collaboration in stage i, dt,λ represents the intelligent correction parameter of traditional equipment, x i ·d t,λ b i Represents the intelligent contribution value of traditional equipment in stage i.

[0011] Optionally, according to the intelligence level of each stage and the predetermined weight of each stage, the intelligence level of the entire life cycle is obtained, including:

[0012]

[0013] Among them, S total Indicates the degree of intelligence in the entire life cycle, S i represents the intelligence level of stage i, ω i represents the weight of stage i, and n represents the number of stages.

[0014] Optionally, the process of determining the intelligent correction parameters of traditional equipment includes: obtaining the service life of the traditional equipment, the type of traditional equipment and the original intelligence level; determining the attenuation coefficient according to the type of traditional equipment; determining the intelligent correction parameters of the traditional equipment according to the service life, the original intelligence level and the attenuation coefficient.

[0015] Optionally, according to the service life, the original intelligence level and the attenuation coefficient, the intelligent correction parameter of the traditional equipment is determined, including: substituting the service life, the original intelligence level and the attenuation coefficient into the following formula:

[0016] d t,λ =S raw ·e -λt ;

[0017] Among them, d t,λ represents the intelligent correction parameter of traditional equipment, S raw It represents the original intelligence level of the equipment, λ represents the attenuation coefficient, and t represents the service life of the equipment.

[0018] According to the second aspect, an embodiment of the present invention provides an intelligent construction project intelligence level assessment device based on the human-intelligence collaboration ternary theory, including: a data acquisition module, used to acquire target project data of intelligent construction projects and intelligent correction parameters of traditional equipment at each stage; a proportion determination module, used to determine the total labor proportion, traditional equipment proportion, human-machine cooperation proportion and intelligent equipment participation proportion in human-machine cooperation at each stage of the project according to the target project data; a staged intelligence degree determination module, used to use the total labor proportion, traditional equipment proportion, human-machine cooperation proportion, intelligent equipment participation proportion in human-machine cooperation proportion and corresponding traditional equipment intelligent correction parameters at each stage of the project as evaluation parameters according to the human-intelligence collaboration ternary theory, to obtain the intelligence degree of each stage; a full life cycle intelligence degree determination module, used to obtain the intelligence degree of the whole life cycle according to the intelligence degree of each stage and the predetermined weights of each stage.

[0019] According to the third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of the method for evaluating the intelligence level of an intelligent construction project based on the human-intelligence collaboration ternary theory as described in the first aspect or any implementation scheme of the first aspect.

[0020] According to the fourth aspect, an embodiment of the present invention provides a computer storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the method for evaluating the intelligence level of intelligent construction projects based on the human-intelligence collaboration ternary theory as described in the first aspect or any embodiment of the first aspect.

[0021] The embodiment of the present invention provides an intelligent construction project intelligence level evaluation method based on the human-intelligence collaboration ternary theory. Based on the staged and full life cycle intelligence degree quantitative evaluation system, from a non-intelligent perspective, it analyzes the dynamic proportion of manual tasks, traditional equipment participation, human-machine collaboration, and intelligent equipment independently completing tasks during the construction process, and scientifically measures the intelligence level of each stage. At the same time, through the human-intelligence collaboration ternary theory, the proportion of work independently completed by intelligent equipment is reversed, overcoming the difficulties in directly calculating the proportion of intelligent equipment due to the various participation modes of intelligent equipment, and the problem that the existing method cannot effectively reflect the proportion level of intelligent equipment. By introducing the traditional equipment depreciation correction parameters and dynamic adjustment formulas, the intelligence degree is calculated in stages, and the weighted average method is used to integrate the stage results to quantify the comprehensive intelligence level of the whole life cycle. At the same time, combined with real-time data collection and dynamic analysis mechanisms, the distribution of construction tasks and the changing trends in the process of intelligent implementation are dynamically captured, providing quantitative support for optimizing resource allocation and construction paths, and ensuring the dynamic coordination of intelligent implementation and project goals. At the same time, the present invention overcomes the limitations of static analysis of the prior art, and significantly improves the real-time and accuracy of intelligent degree assessment through dynamic data collection and real-time monitoring; comprehensively considers the actual contribution of manual tasks and traditional equipment participation in traditional construction modes to intelligent implementation, and provides a more scientific and comprehensive quantitative basis for intelligent transformation; ultimately ensures the globality and coordination of intelligent implementation, and provides scientific support for the efficient management and implementation of intelligent construction projects.

[0022] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art may be taught from the practice of the present invention. The objectives and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0024] Figure 1 It is a specific example flow chart of a method for evaluating the intelligent level of an intelligent construction project based on the human-intelligence synergy ternary theory in the present invention;

[0025] Figure 2 A theoretical schematic diagram of the human intelligence ternary synergy theory in a method for evaluating the intelligent level of an intelligent construction project based on the human intelligence ternary synergy theory of the present invention;

[0026] Figure 3 It is a specific structural schematic diagram of an intelligent construction project intelligent level assessment device based on the human-intelligence synergy ternary theory of the present invention;

[0027] Figure 4 It is a principle block diagram of a specific example of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can also be the internal connection of two components, it can be a wireless connection, or it can be a wired connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0030] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0031] This embodiment takes the construction industry as an example. With the gradual introduction of intelligent equipment (such as robots, drones, automated construction machinery, etc.) and information technology (such as building information model BIM, Internet of Things, etc.) into the construction industry, the intelligentization process of construction projects has been accelerated. However, in the process of intelligent application, there are still some problems:

[0032] First, the assessment of the level of intelligence is not accurate; existing intelligent assessment methods are mostly qualitative assessment or quantitative analysis, which cannot accurately quantify the level of intelligence at different stages of a construction project.

[0033] Second, the proportion of smart devices cannot be directly measured; due to the diverse participation modes of smart devices, it is difficult to directly calculate the proportion of smart devices, and the existing methods cannot effectively reflect the level of smart device proportion.

[0034] Third, human-machine collaboration has not been fully optimized. In construction projects, the collaboration between manual labor, traditional equipment and intelligent equipment is often not systematically quantified, resulting in irrational resource allocation and affecting the intelligent effect of the project.

[0035] Therefore, there is an urgent need for a new method that can accurately quantify the proportion of people, the proportion of people and traditional equipment, and derive the proportion of intelligent equipment from a non-intelligent perspective, so as to achieve a dynamic and accurate evaluation of the intelligent level of construction projects. The ternary theory based on human-intelligence collaboration proposed in this invention provides a scientific theoretical framework and calculation basis for the quantitative analysis of the intelligent level, and can provide systematic and operational decision support for the intelligent process of construction projects. The following is the specific process:

[0036] The embodiment of the present invention provides a method for evaluating the intelligent level of intelligent construction projects based on the human-intelligence synergy ternary theory. Figure 1 As shown, including:

[0037] S101, obtaining target project data of the intelligent construction project and intelligent correction parameters of traditional equipment at each stage;

[0038] S102, determining the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, and intelligent equipment participation ratio in human-machine collaboration at each stage of the project based on the target project data;

[0039] S103, according to the tri-element theory of human-intelligence collaboration, the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, intelligent equipment participation ratio in human-machine collaboration ratio, and corresponding traditional equipment intelligent correction parameters of each stage of the project are used as evaluation parameters to obtain the degree of intelligence at each stage;

[0040] S104, obtaining the intelligence level of the entire life cycle according to the intelligence level of each stage and the predetermined weight of each stage.

[0041] For example, this embodiment provides a theoretical schematic diagram of the triadic synergy theory of human intelligence, such as Figure 2 As shown, the entire construction project is divided into three parts: one is the proportion of tasks completed independently by humans, one is the proportion of tasks completed by humans and machines in cooperation, and the last is the proportion of tasks completed independently by intelligent devices. The proportion of tasks completed by humans and machines in the second part includes the proportion completed by humans and traditional devices and the proportion completed by humans and intelligent devices. The constraint relationship between the three is as follows:

[0042] a i +b i +c i =1;(1)

[0043] Among them, a i represents the proportion of tasks completed independently by humans, b i Indicates the proportion of work completed by human and machine collaboration, c i Indicates the proportion of tasks completed independently by smart devices.

[0044] Since the intelligence level is closely related to the proportion of tasks independently completed by intelligent devices, it is difficult to directly calculate the proportion of tasks independently completed by intelligent devices in actual practice. In this embodiment, based on the above-mentioned human intelligence ternary synergy theory, the proportion of tasks independently completed by intelligent devices can be indirectly obtained. The specific implementation process is as follows:

[0045] First, obtain the target project data in the construction project. The target project data can be project duration data and / or project cost data. The project duration data can be obtained from the project management system or the construction progress system. The project cost data can be obtained from the budget management system, the cost accounting system, and the construction progress relationship system. The project cost data includes the labor and equipment costs of key processes in each stage, such as the foundation stage and the main structure stage. Labor costs include labor costs (worker wages, labor volume) and labor-related expenses. Traditional equipment costs include equipment depreciation costs, maintenance costs, hours of use, etc.

[0046] Then, the intelligent correction parameters of traditional equipment are obtained. The intelligent correction parameters of traditional equipment are used to dynamically adjust the impact of traditional equipment on the intelligence level to ensure that the evaluation results accurately reflect the actual use status of the equipment. It is usually closely related to the service life, working status and functional degradation rate of the equipment. For the intelligent correction parameters of traditional equipment, an exponential decay model can be used to describe the situation in which the intelligence level of the equipment gradually decreases with the increase of service life. Specifically, it can be calculated by the service life of the traditional equipment and the original intelligence level. As an optional implementation method, the process of determining the intelligent correction parameters of traditional equipment includes: obtaining the service life of the traditional equipment, the type of traditional equipment and the original intelligence level; determining the attenuation coefficient according to the type of traditional equipment; determining the intelligent correction parameters of the traditional equipment according to the service life, the original intelligence level and the attenuation coefficient.

[0047] Substitute the age, original intelligence level, and attenuation coefficient into the following formula:

[0048] d t,λ =S raw ·e -λt ; (2)

[0049] Among them, d t,λ represents the intelligent correction parameter of traditional equipment, S raw It represents the original intelligence level of the equipment, λ represents the attenuation coefficient, and t represents the service life of the equipment.

[0050] Assuming that the intelligence level of traditional equipment decreases with the service life t, its depreciation correction coefficient d t,λ The exponential decay model is used for calculation:

[0051] d t,λ=S raw C(t)=S raw ·e -λt ; (3)

[0052] Where C(t) represents the depreciation correction coefficient of the equipment at age t (the value range is [0,1]), which indicates the degree of reduction in the intelligence level of the equipment as the equipment ages; t represents the service life of the equipment (unit: year); λ represents the attenuation coefficient, which indicates the speed at which the intelligence of the equipment decays; d t,λ Indicates the intelligent correction parameters of traditional equipment.

[0053] The attenuation coefficient depends on the type of equipment, speed of technology update, maintenance frequency, etc. Generally speaking, the attenuation coefficient is usually between 0.05 and 0.2. A lower attenuation coefficient (such as 0.05) is suitable for situations where the equipment is updated quickly, maintained well, and the level of intelligence declines slowly. A higher attenuation coefficient (such as 0.15 or 0.2) is suitable for situations where the level of intelligence of the equipment declines quickly, usually equipment that ages quickly or has not been maintained for a long time.

[0054] Intelligent correction parameters of traditional equipment t,λ The steps to determine are as follows:

[0055] Step 1: Determine the age of your equipment

[0056] The service life of the equipment is determined by the difference between the equipment purchase time and the current time. For example, if the equipment has been purchased for 8 years, then t = 8 years.

[0057] Step 2: Choose the appropriate attenuation factor

[0058] Select the appropriate attenuation coefficient based on the type of equipment and the speed of decline in intelligence level:

[0059] For newer equipment or equipment with a higher level of intelligence, a smaller attenuation coefficient can be selected, such as λ=0.05.

[0060] For older, improperly maintained or less intelligent equipment, a larger attenuation coefficient can be selected, such as λ=0.1 or λ=0.2.

[0061] Step 3: Calculate the depreciation correction factor C(t)

[0062] Use formula (4) to calculate the depreciation correction factor of the equipment at the service life t. For example, assuming that the service life of the equipment is 8 years and the attenuation coefficient is λ=0.1, the depreciation correction factor is:

[0063] C(8)=e -0.1*8 =e -0.8 ≈0.449; (4)

[0064] Step 4: Apply the Correction Factor

[0065] Use the depreciation correction factor C(t) to adjust the intelligence level of the equipment. For example, if the original intelligence level of the equipment is S raw =0.8, then the intelligence level after depreciation correction is:

[0066] d t,λ =S raw ·C(t)=0.8*0.449≈0.359; (5)

[0067] Through the above steps, the intelligent correction coefficient d of the traditional equipment can be calculated according to the service life t of the equipment and the attenuation coefficient λ t,λ , thereby adjusting the intelligence level of the equipment. This embodiment combines factors such as depreciation of traditional equipment and task complexity to flexibly adjust the intelligent evaluation model to ensure that the evaluation results of the intelligence level reflect the changes in equipment status and the actual situation during project execution in real time.

[0068] Next, based on the target project data, determine the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, and intelligent device participation ratio in human-machine collaboration at each stage of the project. Specifically, the ratio can be calculated based on the following two dimensions:

[0069] The first dimension is to estimate the proportion of labor and traditional equipment through the construction period. At each stage, the completion time distribution and construction period arrangement of the task can help estimate the degree of participation of labor and traditional equipment. For example, if there are multiple subtasks in a certain stage, the proportion of labor participation can be estimated by analyzing the construction period distribution of each subtask.

[0070] The second dimension is to calculate the proportion of labor and traditional equipment through cost estimation. The cost can more directly reflect the resource consumption of labor and traditional equipment. For example, the proportion of labor cost is calculated by calculating the proportion of labor cost to total cost in a certain stage (for example, the main structure stage). Similarly, the proportion of traditional equipment cost in this stage is calculated. For specific tasks, the proportion of labor and traditional equipment in specific tasks is calculated, and detailed analysis is carried out for specific tasks in combination with construction period and cost.

[0071] Through the above two methods, we can get the total labor ratio and traditional equipment ratio of each stage of the project. In addition, we also need to get the human-machine cooperation ratio and the intelligent equipment participation ratio in the human-machine cooperation ratio. Taking the target project data as cost data as an example, the human-machine cooperation ratio is the labor cost ratio of human and traditional equipment collaboration when completing a task, the labor cost ratio when people and intelligent equipment collaborate, the traditional equipment cost ratio when people and traditional equipment collaborate, and the intelligent equipment cost ratio when people and intelligent equipment collaborate. The intelligent equipment participation ratio in the human-machine cooperation ratio can be obtained by counting the total cost of human-machine cooperation and the cost of intelligent equipment in human-machine cooperation.

[0072] After determining the total labor ratio, traditional equipment ratio, intelligent equipment ratio in human-machine collaboration, and the corresponding intelligent correction parameters of traditional equipment at each stage of the project, the degree of intelligence at each stage is determined through the human-intelligence collaboration ternary theory. Specifically, formula (1) can be transformed into:

[0073] a i +(b i1 +b i2 +b i3 +b i4 )+c i =1; (6)

[0074] Among them, a i Indicates the proportion of the cost of completing a task independently by humans, b i1 , b i2 , b i3 , b i4 They represent the labor cost ratio of human-machine collaboration when completing a task, the labor cost ratio of human-machine collaboration when humans and traditional equipment collaborate, the labor cost ratio of human-machine collaboration when humans and intelligent equipment collaborate, the traditional equipment cost ratio of human-machine collaboration when humans and traditional equipment collaborate, and the intelligent equipment cost ratio of human-machine collaboration when humans and intelligent equipment collaborate. i It indicates the cost ratio of a smart device to complete a task independently.

[0075] According to formula (6), the known parameters include the proportion of traditional equipment b i3 , total labor ratio z i :

[0076] z i =a i +b i1 +b i2 ; (7)

[0077] Human-machine collaboration ratio i :

[0078] b i =b i1 +b i2+b i3 +b i4 ; (8)

[0079] Proportion of intelligent devices involved in human-machine collaboration x i :

[0080]

[0081] Based on the constraints established by formulas (7)-(9) corresponding to the known parameters, the total proportion of tasks completed by human-machine collaboration and tasks completed independently can be obtained:

[0082] γ i =z i +b i3 +x i b i =a i +(b i1 +b i2 +b i3 +b i4 )=a i +b i ; (10)

[0083] Then, according to the proportion of human-machine cooperation, the proportion of intelligent equipment in human-machine cooperation, and the intelligent correction parameters of traditional equipment, the intelligent contribution value of traditional equipment is determined. The specific formula can be:

[0084]

[0085] in, represents the intelligent contribution value of traditional equipment, x i represents the proportion of intelligent devices involved in human-machine collaboration, d t,λ represents the intelligent correction parameter of traditional equipment, b i Indicates the proportion of human-machine collaboration.

[0086] According to formulas (10) and (11), the total proportion of human-machine collaboration and manual independent work and the intelligent contribution value of traditional equipment are used to determine the degree of intelligence at each stage:

[0087] S i =1-(a i +b i )+x i ·d t,λ b i ; (12)

[0088] Among them, S i represents the degree of intelligence at stage i, a i represents the pure manual labor ratio in stage i, a i +b irepresents the total proportion of human-machine collaboration and manual independent completion, b i represents the proportion of human-machine collaboration, x i represents the proportion of intelligent devices involved in human-machine collaboration in stage i, d t,λ represents the intelligent correction parameter of traditional equipment, x i ·d t,λ b i Represents the intelligent contribution value of traditional equipment in stage i.

[0089] As an optional implementation, the intelligence level of the entire life cycle is obtained according to the intelligence level of each stage and the predetermined weight of each stage, including:

[0090]

[0091] Among them, S total Indicates the degree of intelligence in the entire life cycle, S i represents the intelligence level of stage i, ω i represents the weight of stage i, n represents the number of stages, and weight ω i The weights may be obtained in advance based on expert opinions, and this embodiment does not limit the method for determining the weights.

[0092] The embodiment of the present invention provides an intelligent construction project intelligence level evaluation method based on the human-intelligence synergy ternary theory. Based on the staged and full life cycle intelligence degree quantitative evaluation system, from a non-intelligent perspective, the dynamic proportion of manual tasks, traditional equipment participation, human-machine collaboration and intelligent equipment independently completing tasks in the construction process is analyzed to scientifically measure the intelligence level of each stage. At the same time, through the human-intelligence synergy ternary theory, the proportion of work independently completed by intelligent equipment is reversed, overcoming the difficulties in directly calculating the proportion of intelligent equipment independently completed due to the various participation modes of intelligent equipment, and the problem that the existing method cannot effectively reflect the proportion level of intelligent equipment. By introducing the traditional equipment depreciation correction parameters and dynamic adjustment formulas, the intelligence degree is calculated in stages, and the weighted average method is used to integrate the stage results to quantify the comprehensive intelligence level of the whole life cycle. At the same time, combined with real-time data collection and dynamic analysis mechanisms, the distribution of construction tasks and the changing trends in the process of intelligent implementation are dynamically captured to provide quantitative support for optimizing resource allocation and construction paths, and to ensure the dynamic coordination of intelligent implementation and project goals.

[0093] At the same time, the present invention overcomes the limitations of static analysis of the prior art, and significantly improves the real-time and accuracy of intelligent degree assessment through dynamic data collection and real-time monitoring; comprehensively considers the actual contribution of manual tasks and traditional equipment participation in traditional construction modes to intelligent implementation, and provides a more scientific and comprehensive quantitative basis for intelligent transformation; ultimately ensures the globality and coordination of intelligent implementation, and provides scientific support for the efficient management and implementation of intelligent construction projects.

[0094] The present invention provides an intelligent construction project intelligence level assessment device based on the human-intelligence synergy ternary theory, such as Figure 3 As shown, including:

[0095] The data acquisition module 201 is used to acquire the target project data of the intelligent construction project and the intelligent correction parameters of the traditional equipment at each stage;

[0096] The proportion determination module 202 is used to determine the total labor proportion, traditional equipment proportion, human-machine cooperation proportion, and intelligent equipment participation proportion in human-machine cooperation at each stage of the project according to the target project data;

[0097] The module 203 for determining the degree of intelligence at each stage is used to obtain the degree of intelligence at each stage by taking the total labor ratio, traditional equipment ratio, human-machine cooperation ratio, intelligent equipment participation ratio in the human-machine cooperation ratio, and the corresponding traditional equipment intelligence correction parameters as evaluation parameters according to the human-intelligence synergy ternary theory;

[0098] The whole life cycle intelligence level determination module 204 is used to obtain the intelligence level of the whole life cycle according to the intelligence level of each stage and the predetermined weight of each stage.

[0099] The present application also provides an electronic device, such as Figure 4 As shown, a processor 501 and a memory 502, wherein the processor 501 and the memory 502 may be connected via a bus or other means.

[0100] The processor 501 may be a central processing unit (CPU). The processor 501 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0101] The memory 502 is a non-transient computer-readable storage medium that can be used to store non-transient software programs, non-transient computer executable programs and modules, such as program instructions / modules corresponding to the intelligent level assessment method of intelligent construction projects based on the human-intelligence synergy ternary theory in the embodiment of the present invention. The processor executes various functional applications and data processing of the processor by running the non-transient software programs, instructions and modules stored in the memory.

[0102] The memory 502 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 502 may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0103] The one or more modules are stored in the memory 502, and when executed by the processor 501, the following is performed: Figure 1 The illustrated embodiment is a method for evaluating the intelligence level of an intelligent construction project based on the human-intelligence synergy ternary theory.

[0104] For details of the above electronic equipment, please refer to Figure 1 The corresponding related descriptions and effects in the illustrated embodiments can be understood and will not be repeated here.

[0105] This embodiment also provides a computer storage medium, which stores computer executable instructions, and the computer executable instructions can execute the intelligent level assessment method of intelligent construction projects based on the human-intelligence synergy ternary theory in any of the above method embodiments. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above types of memory.

[0106] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A method for evaluating the intelligent level of intelligent construction projects based on the triadic theory of human-intelligence collaboration, characterized in that: include: Obtain target project data for smart construction projects and intelligent correction parameters for traditional equipment at each stage; According to the target project data, determine the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, and intelligent equipment participation ratio in human-machine collaboration at each stage of the project; According to the tri-element theory of human-intelligence collaboration, the proportion of total labor, the proportion of traditional equipment, the proportion of human-machine collaboration, the proportion of intelligent equipment in the proportion of human-machine collaboration, and the corresponding intelligent correction parameters of traditional equipment in each stage of the project are used as evaluation parameters to obtain the degree of intelligence in each stage; According to the intelligence level of each stage and the predetermined weight of each stage, the intelligence level of the entire life cycle is obtained.

2. The intelligent level assessment method for intelligent construction projects based on the human-intelligence synergy triad theory according to claim 1 is characterized in that: According to the tri-element theory of human-intelligence collaboration, the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, intelligent equipment ratio in human-machine collaboration ratio, and corresponding traditional equipment intelligent correction parameters of each stage of the project are used as evaluation parameters to obtain the degree of intelligence at each stage, including: The tasks completed at each stage are divided into three categories according to whether they are completed independently by humans, completed by human-machine collaboration, and completed by intelligent devices independently, and the constraints are obtained. Among them, the tasks completed by human-machine collaboration include the tasks completed by humans and traditional devices in collaboration, and the tasks completed by humans and intelligent devices in collaboration. According to the constraints, the total labor ratio and the traditional equipment ratio, determine the total ratio of human-machine collaboration and manual independent work; Determine the intelligent contribution value of traditional equipment based on the proportion of human-machine collaboration, the proportion of intelligent equipment involved in human-machine collaboration, and the intelligent correction parameters of traditional equipment; The degree of intelligence at each stage is determined based on the total proportion of work completed by human-machine collaboration and manual independent work, as well as the intelligent contribution value of traditional equipment.

3. The intelligent level assessment method for intelligent construction projects based on the human-intelligence synergy triad theory according to claim 2 is characterized in that: The degree of intelligence at each stage is determined based on the total proportion of work completed by human-machine collaboration and work completed independently by humans, as well as the intelligent contribution value of traditional equipment, including: S i =1-(a i +b i )+x i ·d t,λ ·b i ; Among them, S i represents the degree of intelligence at stage i, a i represents the pure manual labor ratio in stage i, a i +b i represents the total proportion of human-machine collaboration and manual independent completion, b i represents the proportion of human-machine collaboration, x i represents the proportion of intelligent devices involved in human-machine collaboration in stage i, d t,λ represents the intelligent correction parameter of traditional equipment, x i ·d t,λ b i Represents the intelligent contribution value of traditional equipment in stage i.

4. The intelligent level assessment method for intelligent construction projects based on the human-intelligence synergy triad theory according to claim 1 is characterized in that: According to the intelligence level of each stage and the predetermined weight of each stage, the intelligence level of the whole life cycle is obtained, including: Among them, S total Indicates the degree of intelligence in the entire life cycle, S i represents the intelligence level of stage i, ω i represents the weight of stage i, and n represents the number of stages.

5. The intelligent level assessment method for intelligent construction projects based on the human-intelligence synergy ternary theory according to any one of claims 1 to 4, characterized in that: The process of determining the intelligent correction parameters of traditional equipment includes: Obtain the age, type and original intelligence level of traditional equipment; Determine the attenuation coefficient based on the type of traditional equipment; Determine the intelligent correction parameters of traditional equipment based on its service life, original intelligence level and attenuation coefficient.

6. The intelligent level assessment method for intelligent construction projects based on the human-intelligence synergy triad theory according to claim 5 is characterized in that: According to the service life, original intelligence level and attenuation coefficient, the intelligent correction parameters of traditional equipment are determined, including: Substitute the age, original intelligence level, and attenuation coefficient into the following formula: d t,λ =S raw ·e -λt ; Among them, d t,λ represents the intelligent correction parameter of traditional equipment, S raw It represents the original intelligence level of the equipment, λ represents the attenuation coefficient, and t represents the service life of the equipment.

7. An intelligent construction project intelligence level assessment device based on the human-intelligence synergy triad theory, characterized in that: include: A data acquisition module is used to obtain target project data of smart construction projects and intelligent correction parameters of traditional equipment at each stage; The proportion determination module is used to determine the total labor proportion, traditional equipment proportion, human-machine cooperation proportion, and intelligent equipment participation proportion in human-machine cooperation at each stage of the project based on the target project data; The module for determining the degree of intelligence at each stage is used to obtain the degree of intelligence at each stage by taking the total labor ratio, traditional equipment ratio, human-machine cooperation ratio, intelligent equipment participation ratio in human-machine cooperation ratio and corresponding traditional equipment intelligent correction parameters as evaluation parameters according to the ternary theory of human-intelligence collaboration at each stage of the project; The module for determining the degree of intelligence in the entire life cycle is used to obtain the degree of intelligence in the entire life cycle according to the degree of intelligence in each stage and the predetermined weights of each stage.

8. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the steps of the method for evaluating the intelligent level of an intelligent construction project based on the human-intelligence collaboration ternary theory as described in any one of claims 1 to 6.

9. A computer storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by the processor, the steps of the method for evaluating the intelligent level of intelligent construction projects based on the human-intelligence collaboration ternary theory as described in any one of claims 1-6 are implemented.

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