Intelligent level evaluation method for intelligent construction project based on human intelligence collaborative ternary theory

Abstract

The application provides an intelligent construction project intelligent level evaluation method based on a human intelligence collaborative ternary theory, comprising: obtaining target project data and traditional equipment intelligent correction parameters of each stage; determining total artificial proportion, traditional equipment proportion, human-machine cooperation proportion and intelligent equipment participation proportion in human-machine cooperation of each stage according to the target project data; according to the human intelligence collaborative ternary theory, taking the above proportions and corresponding traditional equipment intelligent correction parameters as evaluation parameters to obtain intelligent degrees of each stage; and obtaining the intelligent degree of the whole life cycle according to the intelligent degrees of each stage and the pre-determined weights of each stage. Through the implementation of the application, the dynamic proportions of artificial, traditional equipment, human-machine cooperation and intelligent equipment independently completing tasks in the construction process are analyzed from the non-intelligent perspective, 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 an engineering project. The overall lifecycle intelligence level, by integrating the intelligence levels of each stage, reflects the effectiveness of the project's overall intelligent transformation. With the rapid development of intelligent construction technology, the widespread application of intelligent equipment, automation tools, and artificial intelligence technologies has gradually become mainstream in the industry. Leveraging these technologies to improve construction efficiency and resource utilization has become an industry trend. However, in the gradual transition from traditional construction models to intelligent construction, how to scientifically measure the degree of intelligence and dynamically optimize resource allocation and construction paths remains a key issue that needs to be addressed.

[0003] The core of intelligent construction lies in the accurate assessment and dynamic optimization of the degree of intelligence. However, current intelligent technologies are evolving rapidly, with significant variations in technology forms and application levels across different stages, making quantitative analysis based solely on intelligence challenging. Existing technologies often assess the degree of intelligence based on intelligence goals, ignoring the fundamental characteristics of traditional construction models and failing to fully measure the actual role of manual tasks and traditional equipment in the intelligent transformation process. Furthermore, the rapid development of intelligent devices and digital platforms has increased their complexity and diversity, making it difficult for existing assessment methods to fully adapt to the demands of rapid technological iteration and diverse 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 collaboration 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 the intelligent construction project and intelligent correction parameters of traditional equipment at each stage; 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; according to the human-intelligence collaboration ternary theory, taking 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 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, obtaining the degree of intelligence throughout the life cycle.

[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, and obtaining constraints, among which human-machine collaboration completion includes completion by human and traditional equipment collaboration and completion by human and intelligent equipment collaboration; determining the total ratio of human-machine collaboration completion and human independent completion according to the constraints and the total labor ratio and traditional equipment ratio; determining the intelligent contribution value of traditional equipment according to 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 according to the total ratio of human-machine collaboration completion and manual independent completion and the intelligent contribution value of traditional equipment.

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

[0009] ;

[0010] in, represents the degree of intelligence at stage i, represents the proportion of manual independent completion in stage i, It represents the total proportion of tasks completed by human-machine collaboration and those completed by humans independently. Indicates the proportion of human-machine collaboration, Indicates the proportion of intelligent devices involved in human-machine collaboration in stage i, Indicates the intelligent correction parameters of traditional equipment, Represents the intelligent contribution value of traditional equipment in stage i.

[0011] Optionally, based on 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] in, Indicates the degree of intelligence throughout the entire life cycle. represents the degree of intelligence at stage 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 based on the type of traditional equipment; and determining the intelligent correction parameters of the traditional equipment based on the service life, the original intelligence level and the attenuation coefficient.

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

[0016] ;

[0017] in, Indicates the intelligent correction parameters of traditional equipment, Indicates the original intelligence level of the device, represents the attenuation coefficient, Indicates the age 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 for acquiring target project data of the intelligent construction project and intelligent correction parameters of traditional equipment at each stage; a proportion determination module for determining 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 level determination module for using 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 level of each stage; a full life cycle intelligence level determination module for obtaining the intelligence level of the full life cycle according to the intelligence level of each stage and the predetermined weights of each stage.

[0019] According to a third aspect, an electronic device is provided, the device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor performing the steps of the method for evaluating the intelligent level of an intelligent construction project based on the theory of human intelligence synergy ternary according to the first aspect or any of the embodiments of the first aspect.

[0020] According to a fourth aspect, a computer storage medium is provided, having stored thereon computer instructions, which, when executed by a processor, implement the steps of the method for evaluating the intelligent level of an intelligent construction project based on the theory of human intelligence synergy ternary according to the first aspect or any of the embodiments of the first aspect.

[0021] The embodiments of the present application provide a method for evaluating the intelligent level of an intelligent construction project based on the theory of human intelligence synergy ternary, which is based on a phased and full life cycle intelligent degree quantitative evaluation system, analyzes the dynamic proportion of manual tasks, traditional equipment participation, human-machine collaboration and intelligent equipment independent task completion in the construction process from the perspective of non-intelligence, scientifically measures the intelligent level of each stage, and inversely calculates the proportion of work completed by intelligent equipment through the theory of human intelligence synergy ternary, thereby overcoming the problem that it is difficult to directly calculate the proportion of intelligent equipment due to various participation modes of intelligent equipment, and existing methods cannot effectively reflect the intelligent equipment proportion level. By introducing a traditional equipment depreciation correction parameter and a dynamic adjustment formula, the intelligent degree is calculated in stages, and the stage results are integrated using a weighted average method to quantify the comprehensive intelligent level of the full life cycle. At the same time, combined with real-time data acquisition and dynamic analysis mechanism, the change trend in the construction task distribution and intelligent implementation process is dynamically captured, providing quantitative support for optimizing resource allocation and construction path, ensuring the dynamic coordination of intelligent implementation and project goals. At the same time, the present application overcomes the limitations of static analysis in the prior art, significantly improves the real-time and accuracy of intelligent degree evaluation through dynamic data acquisition and real-time monitoring, comprehensively considers the actual contribution of manual tasks and traditional equipment participation in intelligent implementation in the traditional construction mode, and provides a more scientific and comprehensive quantitative basis for intelligent transformation. Finally, the globality and coordination of intelligent implementation are ensured, and scientific support is provided for efficient management and implementation of intelligent construction projects.

[0022] Other advantages, objects, and features of the present application will be apparent to those skilled in the art from the following specification, and it is intended to cover by the claims all such modifications as fall within the true spirit and scope of the present application. The present application can be practiced by other than the described embodiments, which are presented for illustration of the present application and not in limitation of the present application as defined in the claims. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to make the purposes, technical solutions and beneficial effects of the present application clearer, the present application provides the following drawings for illustration:

[0024] Figure 1 This 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 This is a theoretical 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 This is a schematic diagram of a specific structure of an intelligent construction project intelligence level assessment device based on the human-intelligence synergy ternary theory of the present invention;

[0027] Figure 4 This 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 clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0029] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components; wireless connections or wired connections. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on 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 example uses the construction industry as an example. With the gradual introduction of intelligent equipment (such as robots, drones, and automated construction machinery) and information technology (such as Building Information Modeling (BIM) and the Internet of Things) into the construction industry, the intelligentization of construction projects has accelerated. However, in the process of intelligent application, some problems still exist:

[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 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, thereby achieving a dynamic and accurate assessment of the level of intelligence in construction projects. The present invention proposes a ternary theory based on human-intelligence collaboration, which provides a scientific theoretical framework and calculation basis for the quantitative analysis of the level of intelligence, and can provide systematic and actionable decision support for the intelligentization process of construction projects. The specific process is as follows:

[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 triad theory. Figure 1 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: 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 based on the target project data;

[0039] S103, based on the tri-element theory of human-intelligence collaboration, uses the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, intelligent equipment ratio within human-machine collaboration ratio, and the corresponding intelligent correction parameters of traditional equipment at each stage of the project 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 diagram of the triadic synergy theory of human intelligence, such as Figure 2 As shown, the entire construction project is divided into three parts: the proportion of tasks completed independently by humans, the proportion of tasks completed by humans and machines in collaboration, and 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, as well as the proportion completed by humans and intelligent devices. The constraints between the three are as follows:

[0042] ; (1)

[0043] in, Indicates the proportion of tasks completed independently by humans, Indicates the proportion of work completed by humans and machines. Indicates the proportion of tasks completed independently by smart devices.

[0044] Since the degree of intelligence 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 practice. In this embodiment, based on the above-mentioned human intelligence triadic 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 for the construction project. This data can be project duration data and / or project cost data. Project duration data can be obtained from a project management system or construction schedule system, while project cost data can be obtained from a budget management system, cost accounting system, and construction schedule relationship system. Project cost data includes labor and equipment costs for key processes in various stages, such as the foundation and main structure stages. Labor costs include labor expenses (worker wages, labor volume) and related labor expenses. Traditional equipment costs include equipment depreciation, maintenance costs, and hours of use.

[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 usage 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 where the intelligence level of the equipment gradually decreases with the increase of service life. Specifically, it can be calculated based on 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] ; (2)

[0049] in, Indicates the intelligent correction parameters of traditional equipment, Indicates the original intelligence level of the device, represents the attenuation coefficient, Indicates the age of the equipment.

[0050] Assume that the intelligence level of traditional equipment increases with the age Decrease, its depreciation correction factor The exponential decay model is used for calculation:

[0051] ; (3)

[0052] in, The depreciation correction factor 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; Indicates the service life of the equipment (unit: year); Represents the attenuation coefficient, which indicates the speed at which the intelligence of the device decays; Indicates the intelligent correction parameters of traditional equipment.

[0053] The attenuation coefficient depends on the device type, rate of technological updates, and maintenance frequency. Generally speaking, it ranges from 0.05 to 0.2. A lower attenuation coefficient (such as 0.05) is suitable for devices with rapid updates, good maintenance, and a slower decline in intelligence. A higher attenuation coefficient (such as 0.15 or 0.2) is suitable for devices with a faster decline in intelligence, typically those that age rapidly or have not been maintained for a long time.

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

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

[0056] Determine the age of the device by taking the difference between the device purchase time and the current time. For example, if the device has been purchased for 8 years, then t = 8 years.

[0057] Step 2: Choose the appropriate attenuation coefficient

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

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

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

[0061] Step 3: Calculate the depreciation correction factor

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

[0063] ; (4)

[0064] Step 4: Apply the correction factor

[0065] Using Depreciation Modification Factors To adjust the intelligence level of the device. For example, if the original intelligence level of the device is , then the intelligence level after depreciation correction is:

[0066] ; (5)

[0067] Through the above steps, you can and attenuation coefficient Calculate the intelligent correction coefficient of traditional equipment This embodiment combines factors such as the depreciation of traditional equipment and task complexity to flexibly adjust the intelligent evaluation model, ensuring that the evaluation results of the intelligent level reflect changes in equipment status and the actual situation during project execution in real time.

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

[0069] The first dimension is to estimate the proportion of labor and traditional equipment by duration. At each stage, the time distribution and duration of tasks can help estimate the degree of labor and traditional equipment involvement. For example, if a stage has multiple subtasks, the proportion of labor involved can be estimated by analyzing the duration distribution of each subtask.

[0070] The second dimension is to calculate the labor and traditional equipment ratios through cost estimation. This allows the cost to more directly reflect the resource consumption of labor and traditional equipment. For example, the labor cost ratio is calculated by calculating the proportion of labor costs to total costs during a specific stage (e.g., the main structure stage). Similarly, the cost ratio of traditional equipment during that stage is calculated. For specific tasks, the labor and traditional equipment ratios are calculated, and combined with the construction period and cost, a detailed analysis of the specific task is conducted.

[0071] Through the above two methods, we can obtain the total labor ratio and traditional equipment ratio of each stage of the project. In addition, we also need to obtain the human-machine cooperation ratio and the proportion of intelligent equipment participation in the human-machine cooperation ratio. Taking the target project data as cost data as an example, the human-machine cooperation ratio is the sum of the labor cost ratio of human and traditional equipment collaboration when completing a task, the labor cost ratio when human and intelligent equipment collaborate, the traditional equipment cost ratio when human and traditional equipment collaborate, and the intelligent equipment cost ratio when human and intelligent equipment collaborate. The proportion of intelligent equipment participation 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 in each stage of the project, the degree of intelligence in each stage can be determined through the human-intelligence collaboration ternary theory. Specifically, formula (1) can be transformed into:

[0073] ; (6)

[0074] in, Indicates the proportion of costs involved in completing a task independently. They represent the proportion of labor costs when humans collaborate with traditional equipment, the proportion of labor costs when humans collaborate with intelligent equipment, the proportion of traditional equipment costs when humans collaborate with traditional equipment, and the proportion of intelligent equipment costs when humans collaborate with intelligent equipment in the human-machine collaboration part when completing a certain task. 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 , the total labor ratio :

[0076] ; (7)

[0077] Proportion of human-machine collaboration :

[0078] ; (8)

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

[0080] ; (9)

[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 manual independent work can be obtained:

[0082] ; (10)

[0083] Then, according to the man-machine cooperation ratio, the intelligent device participation ratio in man-machine cooperation and the traditional device intelligent correction parameter, the intelligent contribution value of the traditional device is determined, and the specific formula can be:

[0084] ; (11)

[0085] Wherein, represents the intelligent contribution value of the traditional device, represents the intelligent device participation ratio in man-machine cooperation, represents the traditional device intelligent correction parameter, represents the man-machine cooperation ratio.

[0086] According to the total ratio of man-machine cooperation and artificial independent completion and the intelligent contribution value of the traditional device according to formula (10) and (11), the formula of the intelligent degree of each stage is as follows:

[0087] ; (12)

[0088] Wherein, represents the intelligent degree of stage i, represents the ratio of artificial independent completion in stage i, represents the total ratio of man-machine cooperation and artificial independent completion, represents the man-machine cooperation ratio, represents the intelligent device participation ratio in man-machine cooperation in stage i, represents the traditional device intelligent correction parameter, represents the intelligent contribution value of the traditional device in stage i.

[0089] As an optional implementation, according to the intelligent degree of each stage and the predetermined weight of each stage, the intelligent degree of the whole life cycle is obtained, including:

[0090] ; (13)

[0091] Wherein, represents the intelligent degree of the whole life cycle, represents the intelligent degree of stage i, represents the weight of stage i, n represents the number of stages, and the weight The weight can be obtained according to expert opinions in advance, and the determination method of the weight is not limited in the embodiment.

[0092] The embodiment of the present invention provides a method for evaluating the intelligence level of intelligent construction projects based on the human-intelligence collaboration ternary theory. Based on a quantitative evaluation system for the degree of intelligence in stages and throughout the entire life cycle, it analyzes the dynamic proportions of manual tasks, traditional equipment participation, human-machine collaboration, and independent completion of tasks by intelligent devices during the construction process from a non-intelligent perspective, and scientifically measures the intelligence level of each stage. At the same time, through the human-intelligence collaboration ternary theory, it reversely deduces the proportion of work independently completed by intelligent devices, overcoming the difficulties of directly calculating the proportion of independent completion of intelligent devices due to the diverse participation modes of intelligent devices, and the problem that existing methods cannot effectively reflect the proportion level of intelligent devices. By introducing traditional equipment depreciation correction parameters and dynamic adjustment formulas, the degree of intelligence is calculated in stages, and the weighted average method is used to integrate the stage results to quantify the comprehensive intelligence level of the entire life cycle. At the same time, combined with real-time data collection and dynamic analysis mechanisms, it dynamically captures the changing trends in the distribution of construction tasks and the process of intelligent implementation, providing quantitative support for optimizing resource allocation and construction paths, and ensuring the dynamic coordination of intelligent implementation with project goals.

[0093] At the same time, the present invention overcomes the limitations of static analysis in existing technologies, 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 overall and coordinated nature 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 obtain target project data of the intelligent construction project and intelligent correction parameters of traditional equipment at each stage;

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

[0097] The module 203 for determining the degree of intelligence at each stage is used to determine the degree of intelligence at each stage based on the tri-element theory of human-intelligence collaboration, using the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, the proportion of intelligent equipment involved in the human-machine collaboration ratio, and the corresponding traditional equipment intelligence correction parameters as evaluation parameters.

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

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

[0100] The processor 501 can be a central processing unit (CPU). The processor 501 can 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 thereof.

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

[0102] The memory 502 can include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function; The data storage area can store data created by the processor and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-transient memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transient solid-state memory device. In some embodiments, the memory 502 can optionally include a memory remotely arranged with respect to the processor, which can be connected to the processor through 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 a combination thereof.

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

[0104] The specific details of the above-mentioned electronic device can be understood by referring to the corresponding related description and effects in the embodiment shown in the figure, which will not be repeated here. Figure 1 The specific details of the above-mentioned electronic device can be understood by referring to the corresponding related description and effects in the embodiment shown in the figure, which will not be repeated here.

[0105] This embodiment also provides a computer storage medium storing computer-executable instructions capable of executing the method for evaluating the intelligent construction project intelligence level based on the triadic theory of human-intelligence collaboration in any of the above-mentioned method embodiments. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD); the storage medium may also include a combination of the above-mentioned 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 and are not limiting. 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 human-intelligence synergy triad theory, characterized by: include: Obtain target project data for smart construction projects and intelligent correction parameters for traditional equipment at each stage; Based on 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 total labor ratio, traditional equipment ratio, human-machine collaboration ratio, intelligent equipment ratio within human-machine collaboration ratio, and the corresponding intelligent correction parameters of traditional equipment at each stage of the project are used as evaluation parameters to obtain the degree of intelligence at 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; According to the tri-element theory of human-intelligence collaboration, the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, intelligent equipment ratio within human-machine collaboration ratio, and the corresponding intelligent correction parameters of traditional equipment at 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: independent completion by humans, completion by human-machine collaboration, and independent completion by intelligent devices, and the constraints are obtained. Among them, human-machine collaboration includes completion by humans and traditional equipment in collaboration, and completion by humans and intelligent devices in collaboration. Based on the constraints, the total labor ratio, and the traditional equipment ratio, determine the total proportion of tasks completed by human-machine collaboration and manual work independently. 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; Determine the degree of intelligence at each stage based on the total proportion of work completed through human-machine collaboration and independent manual work, as well as the intelligent contribution 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 work, as well as the intelligent contribution of traditional equipment, including: ； in, represents the degree of intelligence at stage i, represents the proportion of manual independent completion in stage i, It represents the total proportion of tasks completed by human-machine collaboration and those completed by humans independently. Indicates the proportion of human-machine collaboration, Indicates the proportion of intelligent devices involved in human-machine collaboration in stage i, Indicates the intelligent correction parameters of traditional equipment, represents the intelligent contribution value of traditional equipment in stage i; The process of determining the intelligent correction parameters of traditional equipment includes: Substitute the age, original intelligence level, and attenuation coefficient into the following formula: ； in, Indicates the intelligent correction parameters of traditional equipment, Indicates the original intelligence level of the device. represents the attenuation coefficient, Indicates the age of the equipment.

2. The method for evaluating the intelligent level of intelligent construction projects based on the human-intelligence synergy triad theory according to claim 1 is characterized in that: Based on the intelligence level of each stage and the predetermined weight of each stage, the intelligence level of the entire life cycle is obtained, including: ； in, Indicates the degree of intelligence throughout the entire life cycle. represents the degree of intelligence at stage i, represents the weight of stage i, and n represents the number of stages.

3. The method for evaluating the intelligent level of intelligent construction projects based on the human-intelligence synergy triad theory according to claim 1 or 2 is characterized in that: The process of determining the intelligent correction parameters of traditional equipment includes: Determine the attenuation factor based on the legacy equipment type.

4. An intelligent construction project intelligence level assessment device based on the human-intelligence synergy triad theory, characterized by: include: The data acquisition module is used to obtain the target project data of the intelligent construction project and the 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 collaboration proportion, and the proportion of intelligent equipment participation in human-machine collaboration 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 determine the degree of intelligence at each stage based on the tri-element theory of human-intelligence collaboration. This module uses the total labor ratio, traditional equipment ratio, human-machine collaboration ratio, the proportion of intelligent equipment involved in human-machine collaboration ratio, and the corresponding traditional equipment intelligent correction parameters as evaluation parameters. The module for determining the degree of intelligence of the entire life cycle is used to obtain the degree of intelligence of the entire life cycle based on the degree of intelligence of each stage and the predetermined weight of each stage; The module for determining the staged intelligence level performs the following steps, including: The tasks completed at each stage are divided into three categories: independent completion by humans, completion by human-machine collaboration, and independent completion by intelligent devices, and the constraints are obtained. Among them, human-machine collaboration includes completion by humans and traditional equipment in collaboration, and completion by humans and intelligent devices in collaboration. Based on the constraints, the total labor ratio, and the traditional equipment ratio, determine the total proportion of tasks completed by human-machine collaboration and manual work independently. 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; Determine the degree of intelligence at each stage based on the total proportion of work completed through human-machine collaboration and independent manual work, as well as the intelligent contribution 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 work, as well as the intelligent contribution of traditional equipment, including: ； in, represents the degree of intelligence at stage i, represents the proportion of manual independent completion in stage i, It represents the total proportion of tasks completed by human-machine collaboration and those completed by humans independently. Indicates the proportion of human-machine collaboration, Indicates the proportion of intelligent devices involved in human-machine collaboration in stage i, Indicates the intelligent correction parameters of traditional equipment, represents the intelligent contribution value of traditional equipment in stage i; The process of determining the intelligent correction parameters of traditional equipment includes: Substitute the age, original intelligence level, and attenuation coefficient into the following formula: ； in, Indicates the intelligent correction parameters of traditional equipment, Indicates the original intelligence level of the device. represents the attenuation coefficient, Indicates the age of the equipment.

5. 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 1-3.

6. A computer storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by the processor, the steps of the intelligent construction project intelligence level evaluation method based on the human-intelligence collaboration ternary theory as described in any one of claims 1-3 are implemented.

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