Construction project supervision method based on block chain

Abstract

The invention relates to the technical field of construction project supervision, and particularly discloses a construction project supervision method based on a block chain, and the method comprises the steps: carrying out the fusion collection of multi-source data of a construction project site, and carrying out the storage and sharing of the collected multi-source data of the construction project site based on the block chain, based on construction process parameters, material quality detection data and structural deformation data, a support vector machine model is used, a construction project quality classification result is output, construction project quality characteristic scores are matched, and based on project progress plan data of each task and resource allocation data of each task, the path length of an optimal path is output in combination with an ant colony algorithm. And matching the construction project progress characteristic score, matching the construction project site safety characteristic score based on the construction site safety data, and judging whether the construction project is qualified or not. According to the invention, the problems of poor consciousness of information sharing, serious information island phenomenon, repeated work, resource waste, low efficiency and error proneness of traditional project supervision are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction project supervision, and specifically provides a construction project supervision method based on blockchain. Background Technique

[0002] As a distributed database, blockchain has characteristics such as decentralization, immutability, consensus mechanism, and smart contracts, and can effectively solve problems such as difficult data sharing, poor security, and low information transparency in project supervision. It has great potential in improving data security, enhancing information transparency, improving sharing efficiency, and reducing transaction costs. With the development of technology, the application of blockchain technology in various fields has gradually deepened, and its application in the field of project supervision information sharing has become an important trend. At the same time, the combination of blockchain with new technologies such as the Internet of Things and artificial intelligence will further promote the development of project supervision information sharing towards the direction of intelligence and automation, prompting the industry to explore new supervision methods based on blockchain.

[0003] Nowadays, there are still some deficiencies in the research on construction project supervision based on blockchain. Specifically, the current information sharing awareness of traditional project supervision is not strong, and there is a lack of unified standards and perfect platforms, resulting in low information sharing efficiency, high costs, serious information island phenomena, duplicate work, and waste of resources. At present, project supervision information sharing mainly relies on traditional methods such as paper documents, emails, and office software, which are inefficient and error-prone, hindering the smooth progress of supervision work. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a construction project supervision method based on blockchain, which can effectively solve the problems involved in the above background technique.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A construction project supervision method based on blockchain, comprising the following steps: multi-source data fusion collection of the construction project site, wherein the multi-source data of the construction project site specifically includes construction process parameters, material quality inspection data, structural deformation data, project schedule data for each task, resource allocation data for each task, and construction site safety data; storing and sharing the collected multi-source data of the construction project site based on blockchain; extracting the construction process parameters, material quality inspection data, and structural deformation data from the multi-source data of the construction project site on the blockchain, constructing a construction project quality supervision model, and outputting a construction project quality supervision signal; based on the construction project quality supervision signal, using a support vector machine model, outputting a construction project quality classification result, and matching the construction project quality characteristic score; extracting the project schedule data for each task and the resource allocation data for each task from the multi-source data of the construction project site on the blockchain, constructing a construction project schedule supervision model, and outputting a construction project schedule signal for each task; based on the construction project schedule signal for each task, combining with the ant colony algorithm, outputting the path length of the optimal path, and matching the construction project schedule characteristic score; extracting the construction site safety data from the multi-source data of the construction project site on the blockchain, analyzing the construction site safety data, obtaining the construction site safety factor, and matching the construction site safety characteristic score; based on the construction project quality characteristic score, the construction project schedule characteristic score, and the construction site safety characteristic score, determining whether the construction project is qualified.

[0006] As a further method, storing and sharing the collected multi-source data of the construction project site based on blockchain, the specific analysis process is as follows: S1: Using an asymmetric encryption algorithm to encrypt the processed multi-source data of the construction project site, generating a pair of public and private keys, and using the public key to encrypt the multi-source data of the construction project site; S2: Using a hash function to perform a hash calculation on the encrypted multi-source data of the construction project site, generating a unique hash value; S3: Based on the consortium blockchain platform, storing the encrypted multi-source data of the construction project site and the corresponding hash value on the blockchain, and each multi-source data block of the construction project site contains the hash value of the previous multi-source data block of the construction project site, forming a chain structure; S4: Based on the intelligent contract function of the blockchain platform, writing intelligent contract code, and defining the access rights to the multi-source data of the construction project site, the sharing rules of the multi-source data of the construction project site, and the supervision process.

[0007] As a further method, extracting the construction process parameters, material quality inspection data, and structural deformation data from the multi-source data of the construction project site on the blockchain, constructing a construction project quality supervision model, and outputting a construction project quality supervision signal, the specific analysis process is as follows: Extracting the construction process parameters, material quality inspection data, and structural deformation data from the multi-source data of the construction project site on the blockchain: The construction process parameters specifically include the average length length of the steel bar weldavg-gf , the final penetration of precast piles; the material quality inspection data specifically includes the tensile strength of steel skl, the yield strength of steel sqf, and the bulk density of sand and gravel smd; the structural deformation data specifically includes the number of cracks fissure in the construction project structure n , the maximum width of cracks kd in the construction project structure, and the maximum inclination Inclination of the construction project structure f ; construct a construction project quality supervision model, and based on the construction process parameters, material quality inspection data, and structural deformation data, output a construction project quality supervision signal, which is used as the analysis basis for outputting the construction project quality classification result.

[0008] As a further method, the specific analysis process of the construction project quality supervision model is as follows:

[0009]

[0010] In the formula, Quality is the construction project quality supervision signal, Craf is the construction process factor, Mquality is the material quality inspection factor, Deformation is the structural deformation factor, length avg-0 is the defined length of the steel bar weld stored in the database, Piles0 is the defined final penetration of the precast pile stored in the database, skl0 is the defined tensile strength of the steel stored in the database, sqf0 is the defined yield strength of the steel stored in the database, smd0 is the defined bulk density of sand and gravel stored in the database, A1 is the set weight factor of Craf, A2 is the set weight factor of Mquality, A3 is the set weight factor of Deformation, and e is the natural constant.

[0011] As a further method, based on the construction project quality supervision signal, use the support vector machine model to output the construction project quality classification result and match the construction project quality characteristic score. The specific analysis process is as follows: Obtain the construction project quality sample data with known status stored in the database, and divide it into a training set and a test set according to the set ratio; use the training set to train the support vector machine model, and minimize the objective function while satisfying the constraint conditions and 0 ≤ α i ≤ C; where α i is the Lagrange multiplier corresponding to the i-th construction project quality sample, α j is the Lagrange multiplier corresponding to the j-th construction project quality sample, y i is the i-th construction project quality sample, y jis the j-th construction project quality sample, i and j are the numbers of construction project quality samples, n is the total number of construction project quality samples, C is the penalty parameter, K(x i ,x j ) is the radial basis kernel function, σ is the width parameter of the radial basis kernel function; the trained support vector machine model is tested using the test set; the tested support vector machine model is input into the preprocessed construction project quality supervision signal, and the construction project quality is classified through the decision function, and the construction project quality classification result is output; the construction project quality classification result - construction project quality characteristic score mapping table pre-stored in the database is obtained, and by looking up the mapping table, the matching construction project quality characteristic score is found according to the construction project quality classification result.

[0012] As a further method, the progress plan data of each task project and the resource allocation data of each task in the multi-source data of the construction project site are extracted from the blockchain, and a construction project progress supervision model is constructed to output the construction project progress signal of each task. The specific analysis process is as follows: the progress plan data of each task project and the resource allocation data of each task in the multi-source data of the construction project site are extracted from the blockchain: the progress plan data of each task project specifically includes the completion ratio Com of the m-th task ratio,m , the actual progress prog of the m-th task m , the planned progress prog0 of the m-th task; the resource allocation data of each task specifically includes the material loss rate loss of the m-th task m , the equipment utilization rate Equipment of the m-th task m ; where, m is the number of each task, m = 1, 2, 3,..., o, and o is the total number of tasks; a construction project progress supervision model is constructed, and based on the progress plan data of each task project and the resource allocation data of each task, the construction project progress signal of each task is output, and the construction project progress signal of each task is used as the analysis basis for the path length of the output optimal path.

[0013] As a further method, the construction project progress supervision model, the specific analysis process is as follows:

[0014]

[0015] In the formula, Psign m is the construction project progress signal of the m-th task, Progress m is the project progress plan factor of the m-th task, Resource m is the resource allocation factor of the m-th task, B1 is the weight factor of the set Progress m , B2 is the weight factor of the set Resource m , and e is the natural constant.

[0016] As a further method, based on the construction project progress signals of each task, combined with the ant colony algorithm, the path length of the optimal path is output, and the construction project progress characteristic score is matched. The specific analysis process is as follows: Each task in the construction project is regarded as a node of the graph, and the sequence and dependency relationships between tasks are regarded as edges. Based on the construction project progress signals of each task, if the duration of the m-th task is t, then the weight d of the edge from the m-th task to the w-th task mw is expressed as d mw = k * t, where k is the proportionality coefficient stored in the database, and a task-progress graph is constructed; based on the ant colony algorithm, path optimization is performed on the task-progress graph to obtain the path length of the optimal path; obtain the mapping table of the path length of the optimal path - construction project progress characteristic score stored in advance in the database, and by looking up the mapping table, according to the path length of the optimal path, find the matching construction project progress characteristic score.

[0017] As a further method, extract the construction site safety data from the multi-source data of the construction project site on the blockchain, analyze the construction site safety data, obtain the construction project site safety factor, and match the construction project site safety characteristic score. The specific analysis process is as follows: Extract the construction site safety data from the multi-source data of the construction project site on the blockchain. The construction site safety data specifically includes the normal operation ratio Run of the construction site equipment, the construction site wind speed winds, and the normal wearing ratio helmet of the construction site personnel; based on the normal operation ratio of the construction site equipment, the construction site wind speed, and the normal wearing ratio of the construction site personnel helmets, comprehensively analyze to obtain the construction project site safety factor, and the construction project site safety factor is used as the analysis basis for matching the construction project site safety characteristic score;

[0018] The construction project site safety factor, the specific analysis process is as follows:

[0019]

[0020] In the formula, Safe is the construction project site safety factor;

[0021] Obtain the mapping table of the construction project site safety factor - construction project site safety characteristic score stored in advance in the database, and by looking up the mapping table, according to the construction project site safety factor, find the matching construction project site safety characteristic score.

[0022] As a further method, based on the scores of the quality characteristics, progress characteristics, and on-site safety characteristics of the construction project, it is determined whether the construction project is qualified. The specific analysis process is as follows: Denote the average value of the scores of the quality characteristics, progress characteristics, and on-site safety characteristics of the construction project as the supervision score of the construction project; Compare the supervision score of the construction project with the threshold score of the construction project supervision stored in the database; If the supervision score of the construction project is not lower than the threshold score of the construction project supervision, the construction project corresponding to the supervision score of the construction project is qualified; If the supervision score of the construction project is lower than the threshold score of the construction project supervision, the construction project corresponding to the supervision score of the construction project is unqualified, and a danger warning for the unqualified construction project needs to be issued.

[0023] Compared with the prior art, the embodiments of the present invention at least have the following advantages or beneficial effects:

[0024] (1) By providing a blockchain-based construction project supervision method, the present invention collects multi-source data covering key aspects of the construction project, comprehensively reflects the actual situation of the project, and provides rich information for supervision. Based on blockchain storage and sharing, it ensures the immutability, security, and reliable and timely access by multiple parties of the data, breaks the information barrier, and promotes collaborative work. Judging whether the project is qualified based on the comprehensive scores of quality, progress, and safety characteristics can comprehensively and objectively evaluate the overall situation of the project, avoid the one-sidedness of single-dimensional evaluation, provide strong support for project acceptance and decision-making, and improve the management level and overall benefits of the construction project.

[0025] (2) By constructing a model based on key quality data and outputting a supervision signal, and then classifying and matching scores through a support vector machine, the present invention can accurately evaluate the project quality, timely detect quality problems, provide a scientific basis for quality control, and ensure that the project quality meets the standards. Using progress and resource data to construct a model and combining with the ant colony algorithm to find the optimal path length and match scores helps to reasonably plan the task sequence and resource allocation, effectively monitor the progress, ensure the project is completed on time, and reduce the risk of delays and cost increases. Extracting safety data and analyzing to obtain safety factors and matching scores can timely detect potential safety hazards, take targeted measures, reduce the probability of safety accidents, and ensure the safety of personnel's lives and the smooth progress of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the following drawings.

[0027] Figure 1 It is a schematic flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0029] Referring to Figure 1 As shown, the present invention provides a construction project supervision method based on blockchain, including: performing multi-source data fusion collection on the construction project site, where the multi-source data on the construction project site specifically includes construction process parameters, material quality inspection data, structural deformation data, construction progress plan data for each task, resource allocation data for each task, and construction site safety data.

[0030] Based on blockchain, storing and sharing the multi-source data collected on the construction project site.

[0031] The specific analysis process is as follows: S1: Use an asymmetric encryption algorithm to encrypt the processed multi-source data on the construction project site, generate a pair of public and private keys, use the public key to encrypt the multi-source data on the construction project site, and only the corresponding private key can decrypt it; S2: Use a hash function to perform a hash calculation on the encrypted multi-source data on the construction project site to generate a unique hash value; S3: Based on the consortium blockchain platform, store the encrypted multi-source data on the construction project site and the corresponding hash value on the blockchain. Each multi-source data block on the construction project site contains the hash value of the previous multi-source data block on the construction project site, forming a chain structure to ensure the immutability and traceability of the multi-source data on the construction project site; S4: Based on the smart contract function of the blockchain platform, write smart contract code to define the access rights to the multi-source data on the construction project site, the sharing rules of the multi-source data on the construction project site, and the supervision process. The smart contract is automatically executed to achieve the storage and sharing of the multi-source data collected on the construction project site.

[0032] Fusing and collecting multi-source data, covering various aspects such as construction technology, material quality, and structural deformation, can comprehensively and accurately reflect the actual situation of the construction project site, providing a rich and accurate information basis for supervision work. Using an asymmetric encryption algorithm to encrypt data, only the corresponding private key can decrypt it, ensuring the confidentiality of data during transmission and storage; hash calculation generates a unique hash value, combined with the chain structure storage, to ensure the immutability of data. Once the data is modified, the hash value will change and can be detected in a timely manner; at the same time, this structure is also convenient for data tracing and can query the historical records of the data.

[0033] Based on the consortium blockchain platform, smart contracts are used to clarify data access rights, sharing rules, and supervision processes, enabling automatic data storage and sharing. This not only ensures the efficient circulation of data within the authorized scope but also prevents illegal access and abuse of data, improving the collaborative work efficiency of all participating parties and breaking information silos.

[0034] Extract construction process parameters, material quality inspection data, and structural deformation data from multi-source data at the construction site on the blockchain, construct a construction project quality supervision model, and output construction project quality supervision signals.

[0035] The specific analysis process is as follows: Extract construction process parameters, material quality inspection data, and structural deformation data from multi-source data at the construction site on the blockchain: The construction process parameters specifically include the average length of steel bar welds, length avg-gf , the final penetration of precast piles, Piles; the material quality inspection data specifically includes the tensile strength of steel, skl, the yield strength of steel, sqf, and the bulk density of sand and gravel, smd; the structural deformation data specifically includes the number of cracks in the construction project structure, fissure n , the maximum width of cracks in the construction project structure, kd, and the maximum inclination of the construction project structure, Inclination f ; Construct a construction project quality supervision model, and based on the construction process parameters, material quality inspection data, and structural deformation data, output construction project quality supervision signals, which are used as the analysis basis for outputting the construction project quality classification results.

[0036] For the construction project quality supervision model, the specific analysis process is as follows:

[0037]

[0038] In the formula, Quality is the construction project quality supervision signal, Craf is the construction process factor, Mquality is the material quality inspection factor, Deformation is the structural deformation factor, length avg-0 is the defined length of steel bar welds stored in the database, Piles0 is the defined final penetration of precast piles stored in the database, skl0 is the defined tensile strength of steel stored in the database, sqf0 is the defined yield strength of steel stored in the database, smd0 is the defined bulk density of sand and gravel stored in the database, A1 is the set weight factor of Craf, A2 is the set weight factor of Mquality, A3 is the set weight factor of Deformation, and e is the natural constant.

[0039] Extract multi-dimensional data such as construction techniques, material quality, and structural deformation from the blockchain. These data are true, reliable, and immutable, comprehensively covering the key factors affecting project quality and providing a rich and accurate data foundation for quality supervision.

[0040] Calculate the construction technique factor, material quality inspection factor, and structural deformation factor through a series of formulas respectively, and then comprehensively obtain the quality supervision signal. This quantification method can transform complex quality influencing factors into specific values, making quality assessment more scientific and objective, and avoiding subjective judgment biases.

[0041] The calculation of each factor targets different types of data. For example, the construction technique factor considers the length of the steel bar weld and the penetration of the precast pile, the material quality inspection factor involves the strength of steel and the bulk density of sand and gravel, etc., and the structural deformation factor covers the number, width, and inclination of cracks, which can accurately locate the source of quality problems and facilitate the adoption of targeted measures.

[0042] Based on the construction project quality supervision signal, use the support vector machine model to output the construction project quality classification result and match the construction project quality characteristic score.

[0043] The specific analysis process is as follows: Obtain the construction project quality sample data with known status stored in the database, and divide it into a training set and a test set according to 7:3; Use the training set to train the support vector machine model, by minimizing the objective function while satisfying the constraint conditions and 0 ≤ α i ≤ C; where α i is the Lagrange multiplier corresponding to the i-th construction project quality sample, α j is the Lagrange multiplier corresponding to the j-th construction project quality sample, y i is the i-th construction project quality sample, y j is the j-th construction project quality sample, i and j are the construction project quality sample numbers, n is the total number of construction project quality samples, C is the penalty parameter, K(x i , x j ) is the radial basis kernel function, σ is the width parameter of the radial basis kernel function; Use the test set to test the trained support vector machine model; Input the tested support vector machine model into the preprocessed construction project quality supervision signal, classify the construction project quality through the decision function, and output the construction project quality classification result; Obtain the mapping table of construction project quality classification result - construction project quality characteristic score stored in advance in the database, and through looking up the mapping table, according to the construction project quality classification result, find the matching construction project quality characteristic score.

[0044] Using the quality sample data of construction projects with known status in the database, it is divided into a training set and a test set according to a certain proportion to train and test the support vector machine model. This training method based on a large amount of sample data enables the model to learn the internal characteristics and laws of the quality data, thereby classifying the quality of construction projects more accurately with high reliability of the results.

[0045] The model is trained by minimizing the objective function and satisfying specific constraint conditions, and the radial basis kernel function is used to process the data. Supported by rigorous mathematical theories, it can effectively process non-linearly separable quality data, adapt to complex quality classification situations, and improve the effectiveness and accuracy of classification.

[0046] After classifying the quality of construction projects, by looking up the pre-stored mapping table to match the quality characteristic scores, the quality status is converted into specific numerical values, which is convenient for intuitively and quantitatively evaluating the quality of construction projects.

[0047] Extract the engineering progress plan data and resource allocation data of each task from the multi-source data of the construction project site on the blockchain, construct a construction project progress supervision model, and output the construction project progress signals of each task.

[0048] The specific analysis process is as follows: Extract the engineering progress plan data and resource allocation data of each task from the multi-source data of the construction project site on the blockchain: The engineering progress plan data of each task specifically includes the completion ratio Com of the m-th task ratio,m 、the actual progress prog of the m-th task m 、the planned progress prog0 of the m-th task; The resource allocation data of each task specifically includes the material loss rate loss of the m-th task m 、the equipment utilization rate Equipment of the m-th task m ; where m is the number of each task, m = 1, 2, 3,..., o, and o is the total number of tasks; Construct a construction project progress supervision model, based on the engineering progress plan data and resource allocation data of each task, output the construction project progress signals of each task, and the construction project progress signals of each task are used as the analysis basis for the path length of the output optimal path.

[0049] For the construction project progress supervision model, the specific analysis process is as follows:

[0050]

[0051] In the formula, Psign m is the construction project progress signal of the m-th task, Progress m is the engineering progress plan factor of the m-th task, Resource m is the resource allocation factor of the m-th task, and B1 is the set Progress mThe weight factor, and B2 is the set Resource m The weight factor, and e is the natural constant.

[0052] Extract the task schedule and resource allocation data from the blockchain. The immutability and traceability of blockchain data ensure the authenticity and reliability of the data. Using this multi-dimensional data to build a model can comprehensively reflect the actual situation of the project progress and provide a solid data foundation for progress supervision.

[0053] Calculate the project schedule factor and resource allocation factor respectively through a specific formula, and then comprehensively obtain the progress signal, converting the complex progress and resource status into specific values to achieve accurate quantitative analysis of the progress of each task, facilitating supervisors to clearly understand the progress trend of each task.

[0054] Based on the construction project progress signals of each task, combined with the ant colony algorithm, output the path length of the optimal path and match the construction project progress characteristic score.

[0055] The specific analysis process is as follows: Consider each task in the construction project as a node of the graph, and consider the precedence relationship and dependency relationship between tasks as edges. Based on the construction project progress signals of each task, if the duration of the m-th task is t, then the weight d of the edge (m, w) from the m-th task to the w-th task mw can be expressed as d mw = k * t, where k is the proportionality coefficient stored in the database, and construct a task-schedule graph; perform path optimization on the task-schedule graph based on the ant colony algorithm to obtain the path length of the optimal path. The process is as follows:

[0056] Determine the heuristic information η mw , Construct a heuristic information matrix; create a pheromone matrix τ corresponding to the number of nodes in the task-schedule graph. Initially, each element τ mw is set to a constant D; in the ant colony algorithm, each ant v selects the next node to visit according to the pheromone concentration and heuristic information. The probability that ant v transfers from node m to node w is calculated as follows:

[0057]

[0058] In the formula, allowed v is the set of nodes that ant v has not visited and satisfy the task precedence and dependency relationships, s is the node number in the set of nodes that ant v has not visited and satisfy the task precedence and dependency relationships, v is the number of each ant, v = 1, 2, 3,..., f, and f is the total number of ants;

[0059] Ants visit nodes in sequence according to the selected probability until the entire engineering task sequence is completed and the termination node of the graph is reached, forming a complete path.

[0060] For the path walked by each ant v, calculate the path length L according to the weight of the edge. v ; A6: Update the pheromone matrix: a1: Natural evaporation of pheromone, τ mw (g + 1) = (1 - ρ)τ mw (g), where g is the iteration number, g = 1, 2, 3,..., x, x is the total number of iterations, ρ is the pheromone evaporation coefficient, and τ mw (g) is the pheromone concentration from node m to node w at the g-th iteration, and τ mw (g + 1) is the pheromone concentration from node m to node w at the (g + 1)-th iteration; a2: According to the path walked by the ant, increase the corresponding pheromone concentration on the corresponding path. The total pheromone increment Δτ on path (m, w) mw is In the formula, Q is a constant. is the amount of pheromone left by the v-th ant on path (m, w) it walked, and h is the total number of ants that walked path (m, w); a3: The finally updated pheromone concentration τ mw (g + 1)' is τ mw (g + 1)' = τ mw (g + 1) + Δτ mw ;

[0061] Repeat the steps until the total number of iterations x is reached; The shortest path length among the paths walked by all ants is the path length of the optimal path.

[0062] Obtain the mapping table of path length - construction project progress characteristic score for the optimal path pre-stored in the database. By looking up the mapping table and according to the path length of the optimal path, find the matching construction project progress characteristic score.

[0063] Abstracting construction project tasks into nodes and edges of a graph fully considers the sequence and dependency relationships between tasks, can model and analyze the project progress as a whole, avoids looking at tasks in isolation, and is more in line with the actual situation of construction projects.

[0064] Determine the weight of the edge based on the construction project progress signals of each task. The weight combines factors such as task duration, enabling the model to accurately reflect the impact of each task on the overall progress and providing an accurate basis for progress analysis.

[0065] The ant colony algorithm can efficiently find the optimal path to complete the project in a complex task network by simulating the ant foraging process and continuously iterating and optimizing using pheromone and heuristic information, helping to optimize the task execution order, reasonably arrange resources, and improve the project progress efficiency.

[0066] After calculating the path length of the optimal path, the construction project progress characteristic score is matched through a mapping table, and the project progress situation is quantified into specific values, which is convenient for supervisors to intuitively and clearly evaluate the project progress status, compare it with the planned progress, timely discover progress deviations and take measures to adjust, considering not only the current progress but also the optimal path to complete the project.

[0067] Extract the construction site safety data from the multi-source data of the construction project site on the blockchain, analyze the construction site safety data, obtain the construction project site safety factor, and match the construction project site safety characteristic score.

[0068] The specific analysis process is as follows: Extract the construction site safety data from the multi-source data of the construction project site on the blockchain. The construction site safety data specifically includes the normal operation ratio Run of construction site equipment, the wind speed winds at the construction site, and the normal wearing ratio helmet of construction site personnel. Based on the normal operation ratio of construction site equipment, the wind speed at the construction site, and the normal wearing ratio of construction site personnel, comprehensively analyze to obtain the construction project site safety factor, and the construction project site safety factor is used as the analysis basis for matching the construction project site safety characteristic score.

[0069] For the construction project site safety factor, the specific analysis process is as follows:

[0070]

[0071] In the formula, Safe is the construction project site safety factor;

[0072] Obtain the mapping table of construction project site safety factor - construction project site safety characteristic score pre-stored in the database. By searching the mapping table, according to the construction project site safety factor, find the matching construction project site safety characteristic score.

[0073] Extract the construction site safety data from the blockchain. Utilize the characteristics of the blockchain that it cannot be tampered with and is traceable to ensure the authenticity of the data, provide an accurate basis for safety analysis, and avoid misjudgment caused by data fraud.

[0074] Select multi-dimensional data such as the normal operation ratio of equipment, wind speed, and helmet wearing ratio of personnel, comprehensively consider equipment, environment, and personnel factors, and comprehensively reflect the safety status of the construction site, avoiding the one-sidedness of single-factor evaluation.

[0075] According to the safety factor, match the safety characteristic score by searching the pre-stored mapping table, quantitatively rate the safety status of the construction site, and provide a clear and intuitive reference for safety management decisions.

[0076] Based on the scores of the quality characteristics, progress characteristics, and on-site safety characteristics of the construction project, determine whether the construction project is qualified.

[0077] The specific analysis process is as follows: Denote the average value of the scores of the quality characteristics, progress characteristics, and on-site safety characteristics of the construction project as the supervision score of the construction project; Compare the supervision score of the construction project with the threshold score of the construction project supervision stored in the database; If the supervision score of the construction project is not lower than the threshold score of the construction project supervision, the construction project corresponding to the supervision score is qualified; If the supervision score of the construction project is lower than the threshold score of the construction project supervision, the construction project corresponding to the supervision score is unqualified, and a danger warning for the unqualified construction project needs to be issued.

[0078] Considering the construction project from three key dimensions of quality, progress, and safety changes the limitations of single-dimension evaluation, can more comprehensively reflect the overall situation of the project, and ensure the objectivity and accuracy of the project evaluation results.

[0079] Calculate the average value of the characteristic scores of each dimension to obtain the supervision score, and compare it with the threshold score of the supervision in the database. Make a judgment through the comparison of quantitative data, avoiding subjective randomness, and making the judgment process more scientific and standardized.

[0080] For unqualified projects, a danger warning can be issued in a timely manner, which helps the construction participants quickly detect the problems existing in the project, take improvement measures in a timely manner, reduce project risks, and reduce losses.

[0081] In a specific embodiment, the average length of the steel bar weld is 12.5 mm (the defined value in the database is 10 mm), and the final penetration of the precast pile is 50 mm (the defined value in the database is 45 mm);

[0082] The tensile strength of the steel is 550 MPa (the defined value in the database is 500 MPa), the yield strength of the steel is 400 MPa (the defined value in the database is 380 MPa), and the bulk density of sand and gravel is 1.8 t / m 3 (the defined value in the database is 1.7 t / m 3 );

[0083] The number of cracks is 30, the maximum width of the cracks is 0.3 mm, and the maximum inclination of the structure is 0.5°.

[0084] Progress and resource data (total number of tasks 3):

[0085] Task 1: Completion ratio 80%, actual progress 7 days, planned progress 8 days, material loss rate 5%, equipment utilization rate 90%;

[0086] Task 2: Completion ratio 60%, actual progress 5 days, planned progress 6 days, material loss rate 8%, equipment utilization rate 85%;

[0087] Task 3: Completion ratio 40%, actual progress 3 days, planned progress 4 days, material loss rate 10%, equipment utilization rate 80%;

[0088] Safety data:

[0089] The normal operation ratio of on-site construction equipment is 95%, the wind speed at the construction site is 5 m / s, and the helmet wearing ratio at the construction site is 98%.

[0090] Use the asymmetric encryption algorithm to encrypt data, generate public and private key pairs, perform hash calculation to generate a unique hash value, store the data in the consortium chain, and the chain structure ensures immutability. The smart contract defines the data access rights for the supervision party and the construction party.

[0091] The set weight factor of Craf is 0.2, the set weight factor of A2 for Mquality is 0.2, and the set weight factor of A3 for Deformation is 0.6. The calculated construction project quality supervision signal is 23.1798.

[0092] Classify as "good" through the support vector machine model, and the score matching the construction project quality characteristics is 85.

[0093] Ant colony algorithm optimization: Task dependency: Task 1 → Task 2 → Task 3. After iterative calculation, the total length of the optimal path is 15, and the score matching the construction project progress characteristics is 75.

[0094] After calculation, the construction project on-site safety factor is 1.1636, and the score matching the construction project safety characteristics is 80.

[0095] The calculated supervision score is 80, and the supervision threshold in the database is 75. Since 80 > 75, this construction project is qualified.

[0096] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology can make various modifications, supplements, or use similar methods to replace the specific embodiments described, as long as they do not deviate from the structure of the invention or exceed the scope defined by this claim book, they should fall within the protection scope of the present invention.

Claims

1. A construction project supervision method based on blockchain, characterized in that, Including the following steps: Carry out multi-source data fusion acquisition on the construction site of a construction project. The multi-source data on the construction site of the construction project specifically includes construction process parameters, material quality inspection data, structural deformation data, project schedule plans for each task, resource allocation data for each task, and construction site safety data; Based on the blockchain, store and share the multi-source data collected on the construction site of the construction project; Extract the construction process parameters, material quality inspection data, and structural deformation data from the multi-source data on the construction site of the construction project from the blockchain, construct a construction project quality supervision model, and output a construction project quality supervision signal; Based on the construction project quality supervision signal, use a support vector machine model to output a construction project quality classification result and match the construction project quality characteristic score; Extract the project schedule plans for each task and the resource allocation data for each task from the multi-source data on the construction site of the construction project from the blockchain, construct a construction project schedule supervision model, and output a construction project schedule signal for each task; Based on the construction project schedule signals for each task, combined with the ant colony algorithm, output the path length of the optimal path and match the construction project schedule characteristic score; Extract the construction site safety data from the multi-source data on the construction site of the construction project from the blockchain, analyze the construction site safety data to obtain a construction site safety factor, and match the construction site safety characteristic score; Based on the construction project quality characteristic score, the construction project schedule characteristic score, and the construction site safety characteristic score, determine whether the construction project is qualified.

2. The construction project supervision method based on blockchain according to claim 1, characterized in that: The specific analysis process for storing and sharing the multi-source data collected on the construction site of the construction project based on the blockchain is as follows: S1: Use an asymmetric encryption algorithm to encrypt the processed multi-source data on the construction site of the construction project to generate a pair of public and private keys, and use the public key to encrypt the multi-source data on the construction site of the construction project; S2: Use a hash function to perform a hash calculation on the encrypted multi-source data on the construction site of the construction project to generate a unique hash value; S3: Based on the consortium blockchain platform, store the encrypted multi-source data on the construction site of the construction project and the corresponding hash value on the blockchain. Each multi-source data block on the construction site of the construction project contains the hash value of the previous multi-source data block on the construction site of the construction project, forming a chain structure; S4: Based on the intelligent contract function of the blockchain platform, write intelligent contract code to define the access rights to the multi-source data on the construction site of the construction project, the sharing rules for the multi-source data on the construction site of the construction project, and the supervision process.

3. The construction project supervision method based on blockchain according to claim 1, characterized in that: The specific analysis process for extracting the construction process parameters, material quality inspection data, and structural deformation data from the multi-source data on the construction site of the construction project from the blockchain, constructing a construction project quality supervision model, and outputting a construction project quality supervision signal is as follows: Extract the construction process parameters, material quality inspection data, and structural deformation data from the multi-source data on the construction site of the construction project from the blockchain: The construction process parameters specifically include the average length length of the steel bar welds avg-gf , and the final penetration of the precast piles Piles; The material quality inspection data specifically includes the tensile strength skl of steel, the yield strength sqf of steel, and the bulk density smd of sand and gravel; The structural deformation data specifically includes the number of cracks fissure in the construction project structure n , the maximum width kd of the cracks in the construction project structure, and the maximum inclination Inclination of the construction project structure f ; Construct a construction project quality supervision model. Based on the construction process parameters, material quality inspection data, and structural deformation data, output a construction project quality supervision signal. The construction project quality supervision signal serves as the analysis basis for outputting the construction project quality classification result.

4. The construction project supervision method based on blockchain according to claim 3, characterized in that: For the construction project quality supervision model, the specific analysis process is as follows: In the formula, Quality is the construction project quality supervision signal, Craf is the construction technology factor, Mquality is the material quality detection factor, Deformation is the structural deformation factor, length avg-0 is the defined length of the steel bar weld stored in the database, Piles0 is the defined final penetration of the precast pile stored in the database, skl0 is the defined tensile strength of the steel stored in the database, sqf0 is the defined yield strength of the steel stored in the database, smd0 is the defined bulk density of the sand and gravel stored in the database, A1 is the set weight factor of Craf, A2 is the set weight factor of Mquality, A3 is the set weight factor of Deformation, and e is the natural constant.

5. The construction project supervision method based on blockchain according to claim 4, characterized in that: Based on the construction project quality supervision signals, use the support vector machine model to output the construction project quality classification results and match the construction project quality characteristic scores. The specific analysis process is as follows: Obtain the construction project quality sample data with known status stored in the database and divide it into a training set and a test set according to a set ratio; Train the support vector machine model using the training set by minimizing the objective function while satisfying the constraint conditions and 0 ≤ α i ≤ C; Among them, α i is the Lagrange multiplier corresponding to the i-th construction project quality sample, and α j is the Lagrange multiplier corresponding to the j-th construction project quality sample, y i is the i-th construction project quality sample, y j is the j-th construction project quality sample, i and j are the numbers of construction project quality samples, n is the total number of construction project quality samples, C is the penalty parameter, K(x i , x j ) is the radial basis kernel function, and σ is the width parameter of the radial basis kernel function; Use the test set to test the trained support vector machine model; Input the tested support vector machine model into the preprocessed construction project quality supervision signals, classify the construction project quality through the decision function, and output the construction project quality classification results; Obtain the mapping table of construction project quality classification results - construction project quality characteristic scores pre-stored in the database. By looking up the mapping table, find the matching construction project quality characteristic scores according to the construction project quality classification results.

6. The construction project supervision method based on blockchain according to claim 1, characterized in that: Extract the task project schedule data and task resource allocation data from the multi-source data of the construction project site on the blockchain, construct a construction project schedule supervision model, and output the construction project schedule signals for each task. The specific analysis process is as follows: Extract the task project schedule data and task resource allocation data from the multi-source data of the construction project site on the blockchain: The specific data of the project progress plan for each task includes the completion ratio Com of the m-th task ratio,m , the actual progress prog of the m-th task m , and the planned progress prog0 of the m-th task; The specific task resource allocation data specifically includes the material loss rate loss of the m-th task m , the equipment utilization rate Equipment of the m-th task m ; Where m is the task number, m = 1, 2, 3,..., o, and o is the total number of tasks; Construct a construction project schedule supervision model. Based on the task project schedule data and task resource allocation data for each task, output the construction project schedule signals for each task. The construction project schedule signals for each task are used as the analysis basis for the path length of the output optimal path.

7. The construction project supervision method based on blockchain according to claim 6, characterized in that: For the construction project schedule supervision model, the specific analysis process is as follows: Wherein, Psign m is the progress signal of the m-th task construction project, Progress m is the progress plan factor of the m-th task project, Resource m is the resource allocation factor of the m-th task, B1 is the set weight factor of Progress m , B2 is the set weight factor of Resource m , and e is the natural constant.

8. The construction project supervision method based on blockchain according to claim 7, wherein: Based on the construction project schedule signals for each task, combined with the ant colony algorithm, output the path length of the optimal path and match the construction project schedule characteristic scores. The specific analysis process is as follows: Regarding each task in a construction project as a node of a graph, and regarding the precedence and dependency relationships between tasks as edges. Based on the construction project progress signals of each task, if the duration of the m-th task is t, then the weight d of the edge from the m-th task to the w-th task mw is expressed as d mw = k * t, where k is a proportionality coefficient stored in the database, and a task-progress graph is constructed; Perform path optimization on the task - schedule graph based on the ant colony algorithm to obtain the path length of the optimal path; Obtain the mapping table of the path length of the optimal path - construction project schedule characteristic scores pre-stored in the database. By looking up the mapping table, find the matching construction project schedule characteristic scores according to the path length of the optimal path.

9. The construction project supervision method based on blockchain according to claim 1, characterized in that: Extract the construction site safety data from the multi-source data of the construction project site on the blockchain, analyze the construction site safety data, obtain the construction project site safety factor, and match the construction project site safety characteristic scores. The specific analysis process is as follows: Extract the construction site safety data from the multi-source data of the construction project site on the blockchain. The construction site safety data specifically includes the normal operation ratio Run of construction site equipment, the wind speed winds at the construction site, and the normal wearing ratio helmet of construction site personnel's helmets; Based on the normal operation ratio of construction site equipment, the wind speed at the construction site, and the normal wearing ratio of construction site personnel's helmets, comprehensively analyze to obtain the construction project site safety factor. The construction project site safety factor is used as the analysis basis for matching the construction project site safety characteristic scores; For the construction project site safety factor, the specific analysis process is as follows: In the formula, Safe is the construction project site safety factor; Obtain the mapping table of construction project site safety factors - construction project site safety characteristic scores pre-stored in the database. By searching the mapping table, according to the construction project site safety factors, find the matching construction project site safety characteristic scores.

10. A construction project supervision method based on blockchain according to claim 1, characterized in that: Based on the construction project quality characteristic scores, construction project progress characteristic scores, and construction project site safety characteristic scores, determine whether the construction project is qualified. The specific analysis process is as follows: Record the average value of the construction project quality characteristic scores, construction project progress characteristic scores, and construction project site safety characteristic scores as the construction project supervision score; Compare the construction project supervision score with the construction project supervision threshold score stored in the database; If the construction project supervision score is not lower than the construction project supervision threshold score, the construction project corresponding to the construction project supervision score is qualified; If the construction project supervision score is lower than the construction project supervision threshold score, the construction project corresponding to the construction project supervision score is unqualified, and a dangerous warning for unqualified construction projects needs to be issued.

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