Acceptance data evidence method, device and equipment and readable storage medium
By obtaining coded information, measured data, and environmental data during the acceptance of building projects, and using BIM models and blockchain technology to construct an acceptance data evidence chain, the problems of data tampering and data silos are solved, and the credibility and traceability of data are improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING JIZHI DIGITAL TECH CO LTD
- Filing Date
- 2026-01-19
- Publication Date
- 2026-05-29
AI Technical Summary
In the construction project acceptance process, acceptance data is easily tampered with and lacks key context, resulting in low credibility and difficulty in traceability. The problem of data silos is serious, affecting the scientific analysis of data and the determination of responsibility.
By acquiring the coding information, on-site measured data, and environmental data of the target to be accepted, using the BIM model to obtain design information, and associating and binding these data to generate unique identifiers, and combining them with hash values to write into the blockchain network, an immutable chain of acceptance data evidence is constructed.
It improves the credibility and traceability of acceptance data, solves the data silo problem, and achieves data integrity, authenticity and traceability, supporting in-depth root cause analysis and responsibility determination.
Smart Images
Figure CN122113081A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of building engineering technology, and in particular to a method, apparatus, equipment and readable storage medium for storing acceptance data. Background Technology
[0002] Currently, in the construction project acceptance process, acceptance personnel often record acceptance data (such as on-site measured values) in spreadsheets or ordinary databases. This not only makes the acceptance data easy to tamper with, reducing its credibility, but also results in a lack of key context during the acceptance process, making it impossible to scientifically analyze the reasons for data deviations later. In addition, acceptance data and design values are stored in different systems, forming data silos, making it difficult to achieve automated correlation verification and traceability.
[0003] In summary, improving the reliability of acceptance data and facilitating its traceability are technical problems that urgently need to be solved by those skilled in the art. Summary of the Invention
[0004] In view of this, the purpose of this application is to provide a method, apparatus, device and readable storage medium for storing acceptance data, so as to improve the credibility of acceptance data and facilitate the improvement of acceptance data traceability.
[0005] To achieve the above objectives, this application provides the following technical solution: A method for storing acceptance data, comprising: Obtain the first coding information of the target to be accepted, the on-site measured data of the target to be accepted, and the environmental data collected synchronously with the on-site measured data; The design information of the target to be accepted is obtained from the BIM model according to the first coding information; the BIM model contains second coding information encoded using the same coding rules as the first coding information; The on-site measured data, the environmental data, the design information, and the timestamp when the on-site measured data was collected are associated and bound together to generate a unique identifier; Based on the on-site measured data, the environmental data, the design information, and the timestamp, the corresponding hash value is obtained; Write the unique identifier and the hash value into the blockchain network.
[0006] Optionally, the first coding information of the target to be accepted is obtained, including: Obtain the first LFC code of the target to be accepted; Based on the first encoding information, the design information of the target to be accepted is obtained from the BIM model, including: The design information of the target to be accepted is obtained from the BIM model according to the first LFC code; the BIM model is an LFC standard BIM model.
[0007] Optionally, it also includes: Based on the on-site measured data and design information of the target to be accepted, the acceptance result of the target to be accepted is generated; A trusted acceptance report is generated based on the acceptance results and the transaction ID; wherein, the transaction ID is generated when the unique identifier and the hash value are written into the blockchain network.
[0008] Optionally, it also includes: The on-site measured data are compensated based on the environmental data. Based on the on-site measured data, the environmental data, the design information, and the timestamp, the corresponding hash value is obtained, including: The corresponding hash value is obtained based on the on-site measured data, the environmental data, the design information, the timestamp, and the on-site measured data compensation information.
[0009] Optionally, based on the on-site measured data, the environmental data, the design information, the timestamp, and the on-site measured data compensation information, a corresponding hash value is obtained, including: A first hash value is generated based on the on-site measured data, the environmental data, and the timestamp; a second hash value is generated based on the design information; and a third hash value is generated based on the on-site measured data compensation information.
[0010] Optionally, it also includes: Obtain the version information of the BIM model; Generate a corresponding second hash value based on the design information, including: A second hash value is generated based on the design information and the version information of the BIM model.
[0011] Optionally, the design information includes design standard values and material parameters.
[0012] An acceptance data storage device, comprising: The first acquisition module is used to acquire the first coding information of the target to be accepted, the on-site measured data of the target to be accepted, and the environmental data collected synchronously with the on-site measured data; The second acquisition module is used to acquire the design information of the target to be accepted from the BIM model according to the first encoding information; the BIM model is embedded with second encoding information encoded using the same encoding rules as the first encoding information; The association and binding module is used to associate and bind the on-site measured data, the environmental data, the design information, and the timestamp when the on-site measured data was collected, and generate a unique identifier. The hash value generation module is used to obtain the corresponding hash value based on the on-site measured data, the environmental data, the design information, and the timestamp; The writing module is used to write the unique identifier and the hash value into the blockchain network.
[0013] An electronic device, comprising: Memory, used to store computer programs; A processor, configured to implement the steps of the acceptance data storage method as described in any of the preceding claims when executing the computer program.
[0014] A readable storage medium storing a computer program that, when executed by a processor, implements the steps of the acceptance data notarization method as described in any of the preceding claims.
[0015] This application provides a method, apparatus, device, and readable storage medium for storing acceptance data. The method includes: acquiring first coded information of the target to be accepted, on-site measured data of the target to be accepted, and environmental data collected synchronously with the on-site measured data; acquiring design information of the target to be accepted from a BIM model according to the first coded information; embedding second coded information in the BIM model using the same coding rules as the first coded information; associating and binding the on-site measured data, environmental data, design information, and the timestamp when the on-site measured data was collected, and generating a unique identifier; obtaining the corresponding hash value according to the on-site measured data, environmental data, design information, and timestamp; and writing the unique identifier and hash value into a blockchain network.
[0016] The technical solution disclosed in this application not only acquires the on-site measured data of the target to be accepted, but also acquires the synchronously collected environmental data and the design information of the target to be accepted based on the first coding information of the target to be accepted and the second coding embedded with the same coding rule as the first coding information. It automatically associates and binds the acquired information and synchronously stores the unique identifiers and hash values of the key links of the entire chain of acquired information. Therefore, this application can not only improve the dimensions of data acquisition and association during the acceptance process to enhance data value and support in-depth root cause analysis, but also solve the problems of cross-system data fragmentation and data silos, providing a unified spatial benchmark for data traceability, thereby facilitating the improvement of acceptance data traceability and analysis capabilities. Moreover, this application can construct a complete and tamper-proof chain of acceptance data evidence to ensure the integrity, authenticity and traceability of acceptance data and improve the credibility of acceptance data.
[0017] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description
[0018] Figure 1 A flowchart illustrating an acceptance data storage method provided for some embodiments of this application; Figure 2 Flowcharts of acceptance data storage methods provided in some embodiments of this application; Figure 3 A schematic diagram of the structure of an acceptance data storage device provided in some embodiments of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in some embodiments of this application. Detailed Implementation
[0019] Currently, in the acceptance phase of building construction projects, acceptance personnel typically record acceptance data (such as on-site measured values) in spreadsheets or ordinary databases. This data is easily tampered with and difficult to trace. In the event of quality disputes, the authenticity and completeness of the data are difficult to prove, leading to difficulties in determining responsibility. Furthermore, simply storing on-site measured values leaves the acceptance process lacking crucial context, making it impossible to scientifically analyze the causes of data discrepancies later (e.g., distinguishing between construction quality defects and material thermal expansion and contraction). Additionally, design values (BIM (Building Information Modeling) models) from the design phase and measured values from the construction phase are stored in different systems with inconsistent coding systems, creating data silos and hindering automated correlation verification and traceability.
[0020] While existing methods employ centralized databases to store acceptance data and use electronic signatures for authentication—where acceptance personnel input on-site measurement data into a centralized database and sign the data packets electronically to prove data origin—the centralized storage architecture still carries the risk of data tampering. Specifically, despite electronic signatures, the data stored in the centralized database can still be modified by individuals with high privileges or through system vulnerabilities, making its reliability dependent on trust in the database administrator. Furthermore, the data association dimension remains singular, resulting in weak traceability and analysis capabilities. Specifically, this solution typically only associates measurement values with the signatory, lacking automatic binding with key contexts, thus limiting data value and failing to support in-depth root cause analysis. Additionally, the inconsistent coding systems for on-site measurement data and design values make automated verification difficult. Specifically, design BIM models, construction components, and sensor equipment use different identifiers and are stored in different systems, making it difficult to automatically and accurately achieve data association and mutual verification between systems.
[0021] To this end, this application provides a method, apparatus, electronic device, and readable storage medium for storing acceptance data. It not only acquires on-site measured data of the target to be accepted, but also acquires synchronously collected environmental data and BIM-based design information of the target to be accepted, which is based on the target's first coded information and embedded with second coded information encoded using the same coding rules as the first coded information. This information is then automatically associated and bound to the target, improving the dimensions of data acquisition and association during the acceptance process, thereby increasing data value and solving the problems of cross-system data fragmentation and data silos. It provides a unified spatial benchmark for data traceability, thus facilitating improved acceptance data traceability and analysis capabilities. Furthermore, by synchronously storing the unique identifiers and hash values of all key links in the entire chain, including the acquired on-site measured data, environmental data, and design information, this application can construct a complete and tamper-proof chain of acceptance data evidence, ensuring the integrity, authenticity, and traceability of the data, and improving data credibility.
[0022] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.
[0023] See Figure 1 The flowchart below illustrates a method for storing acceptance data, provided in some embodiments of this application. It may include the following steps: S11: Obtain the first coding information of the target to be accepted, the on-site measured data of the target to be accepted, and the environmental data collected synchronously with the on-site measured data.
[0024] In some embodiments of this application, the entity executing the acceptance data storage method can be a computing device such as a portable computer, a personal computer, or a server.
[0025] During the acceptance of a building project, inspectors can use a mobile terminal to scan the barcode (such as a QR code or barcode) on the object to be inspected to obtain its initial coding information. Alternatively, the initial coding information can be affixed to or near the object, allowing inspectors to directly record it on their mobile terminal. After obtaining the initial coding information, the mobile terminal can send it to a computing device. The object to be inspected is any item in the building project that requires acceptance, such as a room or component (e.g., a window, an air conditioning unit, a section of pipe).
[0026] Furthermore, the field measurement equipment (such as laser rangefinders) can measure the actual field data of the target to be accepted and send this data to the computing device. The field measurement equipment also acquires and records corresponding timestamps when measuring the actual field data of the target to be accepted, and can send both the actual field data of the target to be accepted and the timestamps from when the data was collected to the computing device.
[0027] In addition, while the on-site measuring equipment measures the actual on-site data of the target to be accepted, the IoT sensors used to collect on-site environmental data can simultaneously measure the environmental data of the environment in which the target to be accepted is located (such as temperature, humidity and other environmental data), and send the collected environmental data to the computing device.
[0028] Therefore, some embodiments of this application not only collect and obtain on-site measured data of the target to be accepted during acceptance, but also simultaneously obtain environmental data, so as to obtain key context during the acceptance process, improve the dimension, diversity and value of data acquisition during the acceptance process, and facilitate subsequent scientific analysis of the causes of data deviation based on environmental data.
[0029] S12: Obtain the design information of the target to be accepted from the BIM model according to the first coding information; the BIM model contains second coding information encoded using the same coding rules as the first coding information.
[0030] In some embodiments of this application, based on the first coded information of the target to be inspected, the design information of the target can be obtained from the corresponding BIM model according to the first coded information of the target. Here, the BIM model is a digital representation process that includes various physical and functional characteristics of a building. Furthermore, the design information mentioned herein may include the design standard values of the target and material parameters (such as the coefficient of thermal expansion).
[0031] It should be noted that the BIM model mentioned above contains second coding information encoded using the same coding rules as the first coding information, so that the design information of the target to be accepted can be obtained from the BIM model based on the first coding information of the target to be accepted.
[0032] The above-mentioned methods enable the acquisition of not only on-site measured data of the target to be accepted and environmental data of the environment in which the target is located, but also design information of the target to be accepted during the acceptance process. This allows for the acquisition of key contexts during the acceptance process, improving the dimensionality, diversity, and value of data acquisition, and facilitating subsequent scientific analysis of the causes of data deviations based on environmental data.
[0033] S13: Associate and bind the field measured data, environmental data, design information and the timestamp when the field measured data was collected, and generate a unique identifier.
[0034] Based on the above, the on-site measured data of the target to be accepted, the synchronously collected environmental data, the design information of the target to be accepted, and the timestamp of the on-site measured data collection are associated and bound together to generate a unique identifier (ONE ID, i.e., Spatial Identifier)). This unique identifier is a spatially unique identifier, a unique digital identity card for the data (a three-dimensional identifier combining space, time, and data characteristics). That is, each acceptance data package generates an ONE ID, just like an ID card number, possessing uniqueness and immutability. For example, in the Longfor Hangzhou project application case: Component ID: S6-STEEL-023 → automatically generated ONE ID: LF-SH-2023-0865. Furthermore, as can be seen from the aforementioned association and binding, the three elements automatically bound are: spatial location (e.g., room level), timestamp, and data feature code.
[0035] In the above association and binding, the first coding information of the target to be accepted can also be included. That is, the first coding information of the target to be accepted, the on-site measured data of the target to be accepted, the synchronously collected environmental data, the design information of the target to be accepted, and the timestamp when the on-site measured data was collected can be associated and bound. Then, a unique identifier is generated based on the association and binding relationship.
[0036] The above process enables precise and automatic binding and association of on-site measured data, environmental data, and design information at the spatial object level. This means automatically binding and associating on-site measured data with key contexts during the acceptance process, enhancing data dimensionality and value, supporting in-depth root cause analysis, and facilitating accurate data cross-verification. Generating unique identifiers establishes logical connections and defined combinations among the aforementioned multi-dimensional data, providing unique and readable retrieval identifiers, supporting efficient verification and integrity proof, and enabling rapid tracing of original environmental parameters, thus improving the accuracy of liability determination.
[0037] S14: Obtain the corresponding hash value based on the on-site measured data, environmental data, design information, and timestamp.
[0038] In addition, hash calculations can be performed on the on-site measured data of the target to be accepted, the environmental data collected synchronously, the design information of the target to be accepted, and the timestamps when the on-site measured data were collected, to obtain the corresponding hash value (i.e., digital fingerprint).
[0039] It should be noted that some embodiments of this application do not limit the execution order of steps S14 and S15; they can be performed sequentially or in parallel.
[0040] S15: Write the unique identifier and hash value into the blockchain network.
[0041] Building upon the above, a unique identifier and hash value can be written as a transaction into the blockchain network. This leverages the immutability of the blockchain to ensure the authenticity of the data source and the integrity of the processing. Therefore, some embodiments of this application utilize blockchain technology for acceptance data storage, ensuring that the data from data collection to processing is immutable and traceable, guaranteeing the authenticity, integrity, and credibility of the data. It should be noted that when the unique identifier and hash value are written as a transaction into the blockchain network, the blockchain network can generate a corresponding transaction ID and send this ID to a computing device. This allows the computing device to acquire and store the transaction ID, facilitating subsequent querying and locating of transactions containing the corresponding unique identifier and hash value.
[0042] As described above, some embodiments of this application not only establish a mechanism for automatically binding on-site measured data, real-time environmental data, and design information, providing a complete decision-making context for acceptance results, and achieving precise data positioning and association, thus connecting the data chain of design, construction, and acceptance, but also provide a blockchain-based method for storing acceptance data, ensuring that the data from data collection to processing is tamper-proof and traceable. Therefore, some embodiments of this application not only achieve precise and automatic association of on-site measured data, environmental data, and BIM design values using coded information as the core index, solving the problem of cross-system data fragmentation and providing a unified spatial benchmark for data traceability, but also realize a blockchain-based evidence storage model for the entire acceptance chain: it does not simply put the final result on the chain, but synchronously stores fingerprint information of key links in the entire chain, such as data collection, environmental context, and design standards, constructing a complete, tamper-proof, and traceable chain of acceptance data evidence.
[0043] This application provides a method for storing acceptance data, which obtains first coded information of a target to be accepted, and may include: Obtain the first LFC code of the target to be accepted; Based on the first coding information, the design information of the target to be accepted is obtained from the BIM model, which may include: The design information of the target to be accepted is obtained from the BIM model based on the first LFC code; the BIM model is the LFC standard BIM model.
[0044] In some embodiments of this application, when obtaining the first coding information of the target to be accepted, the first LFC (Longfor Foundation Classes) code of the target to be accepted can be obtained. Correspondingly, when obtaining the design information of the target to be accepted from the BIM model based on the first coding information, the design information of the target to be accepted can be obtained from the BIM model based on the first LFC code, and the BIM model is specifically an LFC standard BIM model (i.e., a BIM model based on LFC standard coding, in which LFC coding information is embedded). Therefore, some embodiments of this application can achieve accurate data positioning and association based on LFC spatial coding, establishing a data chain connecting design, construction, and acceptance.
[0045] LFC is an enterprise-level standard independently developed by Longfor Group to standardize the definition, coding, and association of data objects throughout the entire building lifecycle. It ensures the consistency and associativity of data across different systems at each stage from design and construction to operation and maintenance, and is the core foundation for achieving data interoperability. For example, LFC can include S1-S6 levels: S1 (Spatial Level 1) is a city-level spatial unit, the highest level in the LFC spatial hierarchy, used to identify and manage projects located in different cities at the group level. For example, S1-xx represents all projects in city xx; S2 (Spatial Level 2) is a project cluster-level spatial unit, referring to a project cluster composed of multiple sub-projects or plots within the same city. For example, S2-xx-yy represents the "project cluster in district yy of city xx"; S3 (Spatial Level 3) is a single building-level spatial unit, referring to an independent, fully functional single building within a project cluster, such as a residential building or a commercial building. For example, S3-xx-yy-001-T3 represents the "T3 office building in the project cluster in district yy of city xx"; S4 (Spatial Level 4) is a floor-level spatial unit, referring to a specific floor within a single building, such as the ground floor above ground, the second basement level, etc. For example, S4-F21 represents the "21st floor"; S5 (Spatial Level 4) is the floor-level spatial unit. Level 5 (S5) refers to room-level spatial units, which are the smallest spatial units within a floor that have independent functions or can be independently identified, such as an office, an apartment, or a utility room. For example, S5-R2109 represents "Room 2109," which is the basic unit for linking and querying acceptance data. S6 (Spatial Level 6) refers to component-level spatial units, which are the physical components or equipment that make up a room, such as a window, an air conditioning unit, or a section of pipe. For example, S6-FAC-AHU-021 represents "Air conditioning unit numbered 021." In a query, one can penetrate from the S5 level to its contained S6 level components. Based on the above, BIM can specifically be a BIM model with embedded LFCS1-S6 standard coding, which serves as the data carrier and object source for intelligent queries.
[0046] For example, for the acceptance of room-level, component-level, etc., the S5 level can be the core operation level, and the above BIM model can contain S5 / S6 coding information and corresponding design information.
[0047] Based on the above process, it can be seen that some embodiments of this application realize automatic binding of multi-source data based on LFC spatial coding: using the enterprise-level LFC spatial coding standard as the core index, it realizes accurate and automatic association between on-site measured data, environmental data and BIM design values, solves the problem of data fragmentation across coefficients, and provides a unified spatial benchmark for data traceability.
[0048] See Figure 2 This is a flowchart illustrating an acceptance data storage method provided in some embodiments of this application. An acceptance data storage method provided in some embodiments of this application may further include: Based on the on-site measured data and design information of the target to be accepted, generate the acceptance results of the target to be accepted; A trusted acceptance report is generated based on the acceptance results and transaction IDs; the transaction ID is generated when a unique identifier and hash value are written into the blockchain network.
[0049] In some embodiments of this application, after obtaining the on-site measured data and design information of the target to be accepted, the acceptance result of the target to be accepted can be generated based on the on-site measured data and design information of the target to be accepted. Specifically, the on-site measured data of the target to be accepted can be compared with the design standard value in the design information of the target to be accepted to generate a qualified / unqualified acceptance result.
[0050] Then, a trusted acceptance report can be generated based on the transaction ID generated when the acceptance results, unique identifier, and hash value are written into the blockchain network. Furthermore, the generated trusted acceptance report can also include on-site measured data, environmental data, design information, BIM version information, and timestamps from the time the on-site measured data was collected, among other relevant information. Thus, some embodiments of this application implement a dynamically context-bound trusted acceptance report generation mechanism: the generated trusted acceptance report dynamically binds environmental data and design standard versions, giving the acceptance conclusion a complete decision-making context and significantly improving the scientific analysis value and dispute resolution capabilities of the acceptance data.
[0051] Generating credible acceptance reports produces reports with legally binding evidentiary value. Their credibility is independent of any single institution. Furthermore, generating credible acceptance reports allows for the summarization of acceptance data, highlighting key information, standardizing acceptance criteria, reducing disputes, solidifying processing procedures, and facilitating traceability and review. Including transaction IDs in the credible acceptance report enables any relevant party to use that ID to query and verify the completeness of the report on the blockchain network, confirming its integrity and authenticity.
[0052] It should be noted that, Figure 2 Taking LFC coding and the data binding and evidence storage engine in computing devices as an example, the data binding and evidence storage engine can be used to obtain LFC codes, obtain on-site measured data and environmental data of the target to be accepted, obtain the design information of the target to be accepted from the LFC standard BIM model based on LFC codes, and associate and bind relevant data, generate hash fingerprints of key data and send them to the blockchain network for tamper-proof evidence storage, and finally generate a credible acceptance report based on the evidence storage results. The report may contain transaction IDs pointing to relevant transactions on the blockchain.
[0053] As can be seen from the above, some embodiments of this application provide a method for storing acceptance data based on blockchain technology, ensuring that the data throughout the entire process from data collection and processing to report generation is tamper-proof and traceable.
[0054] The acceptance data storage method provided in some embodiments of this application may further include: Compensation is made for the on-site measured data based on environmental data; Based on on-site measured data, environmental data, design information, and timestamps, the corresponding hash values can be obtained, which may include: The corresponding hash value is obtained based on the on-site measured data, environmental data, design information, timestamps, and on-site measured data compensation information.
[0055] In some embodiments of this application, after obtaining the on-site measured data of the target to be accepted and the environmental data collected synchronously with the on-site measured data, compensation can be performed on the on-site measured data based on the environmental data. During this process, on-site measured data compensation information can be generated (e.g., the on-site measured data compensation information can be in the form of a dynamic compensation calculation log, or other forms). For example, this on-site measured data compensation information may include compensation process record information, compensation values, and the on-site measured data after compensation.
[0056] Based on the above, the corresponding hash value is obtained according to the on-site measured data, environmental data, design information and timestamp. Specifically, the hash value is obtained by performing hash calculation based on the on-site measured data, environmental data, design information, timestamp and on-site measured data compensation information.
[0057] Compensating on-site measured data based on environmental data can improve the accuracy of the compensated on-site measured data. Furthermore, incorporating the on-site measured data compensation information into the hash value calculation can also store the digital fingerprint of this information in the blockchain network, preventing the on-site measured data compensation information from being tampered with, ensuring the authenticity of the on-site measured data compensation information, and enabling the traceability of the on-site measured data compensation information.
[0058] This application provides a method for storing acceptance data, which obtains a corresponding hash value based on on-site measured data, environmental data, design information, timestamps, and on-site measured data compensation information. This method may include: The first hash value is generated based on the on-site measured data, environmental data, and timestamps. The second hash value is generated based on the design information. The third hash value is generated based on the compensation information of the on-site measured data.
[0059] In some embodiments of this application, when obtaining the corresponding hash value based on the on-site measured data, environmental data, design information, timestamp, and on-site measured data compensation information, a corresponding first hash value (H1) can be generated based on the on-site measured data, environmental data, and timestamp; a corresponding second hash value (H2) can be generated based on the design information; and a corresponding third hash value (H3) can be generated based on the on-site measured data compensation information.
[0060] The above method can generate corresponding hash values from multidimensional data according to physical input (on-site measured data, environmental data), standard input (design information), and compensation process (on-site measured data compensation information), so as to support fine-grained data verification and more accurately locate changes.
[0061] The acceptance data storage method provided in some embodiments of this application may further include: Obtain the version information of the BIM model; Generating a corresponding second hash value based on the design information can include: A second hash value is generated based on the design information and the version information of the BIM model.
[0062] In some embodiments of this application, version information of the BIM model (such as version number) can also be obtained. Based on this, when generating the corresponding second hash value according to the design information, the corresponding second hash value can be generated according to the design information of the target to be accepted and the version information of the BIM model, so as to realize the uploading of the version information of the BIM model used for acceptance to the blockchain through this process, thereby ensuring the traceability and non-repudiation of version changes.
[0063] This application provides a method for storing acceptance data in some embodiments, where the design information may include design standard values and material parameters.
[0064] In some embodiments of this application, the design information of the target to be accepted obtained from the BIM model may specifically include design standard values and material parameters, thereby improving the reliability and accuracy of acceptance. It should be noted that the design information may also include other parameters according to acceptance requirements, or the parameters included in the corresponding design information may be adaptively adjusted according to the type of target to be accepted.
[0065] This application also provides an acceptance data storage device, see [link to relevant documentation]. Figure 3 This is a schematic diagram of the structure of an acceptance data storage device provided in some embodiments of this application, which may include: The first acquisition module 31 is used to acquire the first coding information of the target to be accepted, the on-site measured data of the target to be accepted, and the environmental data collected synchronously with the on-site measured data; The second acquisition module 32 is used to acquire the design information of the target to be accepted from the BIM model according to the first coding information; the BIM model is embedded with second coding information encoded using the same coding rule as the first coding information; The association and binding module 33 is used to associate and bind on-site measured data, environmental data, design information and timestamps to generate a unique identifier; The hash value generation module 34 is used to obtain the corresponding hash value based on the on-site measured data, environmental data, design information and timestamp; The writing module 35 is used to write the unique identifier and hash value into the blockchain network.
[0066] Some embodiments of this application provide an acceptance data storage device, wherein the first acquisition module 31 may include: a first acquisition submodule, used to acquire the first LFC code of the target to be accepted; The second acquisition module 32 may include: a second acquisition submodule, used to acquire the design information of the target to be accepted from the BIM model according to the first LFC code; the BIM model is an LFC standard BIM model.
[0067] An acceptance data storage device provided in some embodiments of this application may further include: The first generation module is used to generate the acceptance results of the target to be accepted based on the on-site measured data and design information of the target to be accepted. The second generation module is used to generate a trusted acceptance report based on the acceptance results and the transaction ID; wherein, the transaction ID is generated when the unique identifier and hash value are written into the blockchain network.
[0068] An acceptance data storage device provided in some embodiments of this application may further include: The compensation module is used to compensate the on-site measured data based on environmental data; The hash value generation module 34 may include a hash value generation submodule, which is used to obtain the corresponding hash value based on the field measured data, environmental data, design information, timestamps and field measured data compensation information.
[0069] This application provides an acceptance data storage device in some embodiments. The hash value generation submodule may include a hash value generation unit, which is used to generate a corresponding first hash value based on on-site measured data, environmental data and timestamps, generate a corresponding second hash value based on design information, and generate a corresponding third hash value based on on-site measured data compensation information.
[0070] An acceptance data storage device provided in some embodiments of this application may further include: The third acquisition module is used to obtain the version information of the BIM model; The hash value generation unit may include a hash value generation subunit, which is used to generate a corresponding second hash value based on the design information and the version information of the BIM model.
[0071] This application provides an acceptance data storage device in some embodiments, where the design information may include design standard values and material parameters.
[0072] This application also provides an electronic device, see [link to document]. Figure 4 This is a schematic diagram of the structure of an electronic device provided in some embodiments of this application, which may include: Memory 41 is used to store computer programs; When the processor 42 executes the computer program stored in the memory 41, it can implement the steps of any of the above-described methods for storing acceptance data.
[0073] This application also provides a readable storage medium storing a computer program, which, when executed by a processor, can implement the steps of any of the above-described methods for storing acceptance data.
[0074] For a description of the relevant parts of the acceptance data storage device, electronic device and readable storage medium provided in some embodiments of this application, please refer to the detailed description of the corresponding parts of the acceptance data storage method provided in some embodiments of this application, and will not be repeated here.
[0075] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0076] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0077] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0078] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0079] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.
[0080] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.
Claims
1. A method for storing acceptance data, characterized in that, include: Obtain the first coding information of the target to be accepted, the on-site measured data of the target to be accepted, and the environmental data collected synchronously with the on-site measured data; The design information of the target to be accepted is obtained from the BIM model according to the first coding information; the BIM model contains second coding information encoded using the same coding rules as the first coding information; The on-site measured data, the environmental data, the design information, and the timestamp when the on-site measured data was collected are associated and bound together to generate a unique identifier; Based on the on-site measured data, the environmental data, the design information, and the timestamp, the corresponding hash value is obtained; Write the unique identifier and the hash value into the blockchain network.
2. The method for storing acceptance data according to claim 1, characterized in that, Obtain the first coding information of the target to be accepted, including: Obtain the first LFC code of the target to be accepted; Based on the first encoding information, the design information of the target to be accepted is obtained from the BIM model, including: The design information of the target to be accepted is obtained from the BIM model according to the first LFC code; the BIM model is an LFC standard BIM model.
3. The method for storing acceptance data according to claim 1, characterized in that, Also includes: Based on the on-site measured data and design information of the target to be accepted, the acceptance result of the target to be accepted is generated; A trusted acceptance report is generated based on the acceptance results and the transaction ID; wherein, the transaction ID is generated when the unique identifier and the hash value are written into the blockchain network.
4. The method for storing acceptance data according to claim 1, characterized in that, Also includes: The on-site measured data are compensated based on the environmental data. Based on the on-site measured data, the environmental data, the design information, and the timestamp, the corresponding hash value is obtained, including: The corresponding hash value is obtained based on the on-site measured data, the environmental data, the design information, the timestamp, and the on-site measured data compensation information.
5. The method for storing acceptance data according to claim 4, characterized in that, Based on the on-site measured data, the environmental data, the design information, the timestamp, and the on-site measured data compensation information, the corresponding hash values are obtained, including: A first hash value is generated based on the on-site measured data, the environmental data, and the timestamp; a second hash value is generated based on the design information; and a third hash value is generated based on the on-site measured data compensation information.
6. The method for storing acceptance data according to claim 5, characterized in that, Also includes: Obtain the version information of the BIM model; Generate a corresponding second hash value based on the design information, including: A second hash value is generated based on the design information and the version information of the BIM model.
7. The method for storing acceptance data according to claim 1, characterized in that, The design information includes design standard values and material parameters.
8. An acceptance data storage device, characterized in that, include: The first acquisition module is used to acquire the first coding information of the target to be accepted, the on-site measured data of the target to be accepted, and the environmental data collected synchronously with the on-site measured data; The second acquisition module is used to acquire the design information of the target to be accepted from the BIM model according to the first encoding information; the BIM model is embedded with second encoding information encoded using the same encoding rules as the first encoding information; The association and binding module is used to associate and bind the on-site measured data, the environmental data, the design information, and the timestamp when the on-site measured data was collected, and generate a unique identifier. The hash value generation module is used to obtain the corresponding hash value based on the on-site measured data, the environmental data, the design information, and the timestamp; The writing module is used to write the unique identifier and the hash value into the blockchain network.
9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the acceptance data storage method as described in any one of claims 1 to 7 when executing the computer program.
10. A readable storage medium, characterized in that, The readable storage medium stores a computer program that, when executed by a processor, implements the steps of the acceptance data storage method as described in any one of claims 1 to 7.