Intelligent contract-based reinforcing steel bar engineering whole-process management system and method

Abstract

The invention discloses a reinforcement engineering whole-process management system and method based on an intelligent contract, and belongs to the technical field of engineering management. In order to solve the problems of low management efficiency, inconsistent data and difficult tracing, through a contract deployment execution module, an intelligent contract can be automatically executed based on a block chain technology, the construction process of the reinforcement engineering is managed according to preset rules and conditions, a construction plan management module can set a construction plan and resource management logic in the intelligent contract, and the management efficiency is improved. The purchase order traceability module realizes automation of purchase order generation, auditing, execution and settlement processes through an intelligent contract, the management efficiency is improved, the traceability information of the reinforcing steel bar material is recorded by using the Internet of Things technology, the traceability information is associated with the purchase order, and the management efficiency is improved. The retrospective management of the source of the reinforcing steel bar material is realized, the quality of the reinforcing steel bar is ensured, the responsible party can be quickly positioned when a problem occurs, and the risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering management, and in particular to a management system and method for the entire process of a steel bar engineering project based on smart contracts. Background Art

[0002] Steel bar engineering is an indispensable key technology in the construction industry, which covers the design, processing, installation and acceptance of steel bars. In buildings, steel bars are mainly used to reinforce and strengthen concrete structures such as columns, beams, slabs, walls, etc. to improve the tensile strength and earthquake resistance of the structure. At the same time, steel bars are also used in bridges, tunnels and other structures in civil engineering to enhance the rigidity and strength of the structure. Steel bar engineering is essential to ensure the stability, safety and durability of buildings.

[0003] However, there are still the following problems in actual operation: The traditional rebar project management process often involves a large amount of manual operation and paper document processing, resulting in inefficient management and prone to errors. At the same time, in the rebar project management, data is easily inconsistent due to manual operation or poor information transmission, and it is also very difficult to trace. Summary of the invention

[0004] The purpose of the present invention is to provide a whole-process management system and method for steel bar engineering based on smart contracts to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above purpose, the present invention provides the following technical solution: a steel bar engineering full process management system based on smart contracts, comprising: Data layer, used for: Based on the Internet of Things technology, the construction site data of the steel bar project is collected, acquired and stored in real time. The construction site data includes raw material information, processing parameters, transportation records and installation progress. Based on the smart contract, the construction progress is automatically updated according to the collected construction site data, and a progress report is generated; The network layer is used to: Provide communication and collaboration mechanisms among all parties involved to achieve real-time sharing and synchronization of data; The contract layer is used to: Deploy smart contracts, define the business logic and rules of the entire steel bar engineering process, automatically execute smart contracts, automatically review and confirm the construction plan according to preset rules and conditions, and update and display the execution status of the construction plan in real time. At the same time, smart contracts automatically schedule and manage construction resources according to the construction plan and progress, including steel bar materials and construction equipment; Application layer, used for: It provides a user interface and interactive functions for viewing data, initiating operations and monitoring progress. It automatically executes purchase orders through smart contracts to ensure that suppliers provide qualified steel bar raw materials in accordance with the agreed conditions. At the same time, it records the traceability information of the steel bar materials, including the manufacturer and batch number. It generates a steel bar acceptance page through smart contracts, and provides acceptance function for steel bar quality inspection data when the steel bars enter the site.

[0006] Furthermore, the data layer includes: Data acquisition module for: Use IoT sensors and RFID to collect steel bar engineering data at the construction site in real time, transmit the collected data to the system, and store and preliminarily process it. The steel bar engineering data includes raw material information, processing parameters, transportation records and installation progress. The raw material information includes material, size and weight, the processing parameters include cutting length and bending angle, the transportation records include transportation vehicle information and timestamp, and the installation progress includes completed and unfinished engineering quantities; through preset data interfaces and protocols; Report generation module for: The logic of data update and report generation is set in the smart contract. When new data is received, the update mechanism is automatically triggered. Based on the real-time collected construction site data, the smart contract automatically updates the construction progress, generates a corresponding progress report, and sends it to the participants through the network layer.

[0007] Furthermore, the data acquisition module includes: A real-time monitoring module is used to monitor the data collection response time of the IoT sensor in real time; wherein the data collection response time refers to the time elapsed between the IoT sensor executing the data collection action and obtaining the collected data; A comparison module, used for comparing the data collection response time with a preset data collection response time threshold; A target sensor determination module is used to, when the data acquisition response time exceeds a preset data acquisition response time threshold, use the IoT sensor corresponding to the data acquisition response time exceeding the preset data acquisition response time threshold as a target sensor; The data acquisition response coefficient acquisition module is used to obtain the data acquisition response coefficient using the data acquisition response time corresponding to each data acquisition of the target sensor, wherein the data acquisition response coefficient is obtained by the following formula:

[0008] Among them, U 01represents the data collection response coefficient; n represents the number of data collection times of the target sensor before the data collection response time exceeds the preset data collection response time threshold; T ci represents the data collection response time corresponding to the i-th data collection; T ci-1 represents the data collection response time corresponding to the i-1th data collection; T c Indicates the data collection response time value corresponding to when the data collection response time exceeds the preset data collection response time threshold; T cy Indicates the preset data collection response time threshold; A data collection execution deviation coefficient acquisition module is used to retrieve the historical operation record of the target sensor, obtain the data collection execution deviation duration corresponding to the actual data collection time and the theoretical data collection time of the target sensor through the historical operation record, and obtain the data collection execution deviation coefficient through the data collection execution deviation duration; The comprehensive evaluation coefficient acquisition module is used to obtain the comprehensive evaluation coefficient using the data acquisition response coefficient and the data acquisition execution deviation coefficient, wherein the comprehensive evaluation coefficient is obtained by the following formula:

[0009] Among them, U represents the comprehensive evaluation coefficient; U 01 Indicates the data acquisition response coefficient; U 02 It represents the coefficient of deviation of data collection execution; The data collection anomaly judgment module is used to compare the comprehensive evaluation coefficient with a preset evaluation coefficient threshold. When the comprehensive evaluation coefficient exceeds the preset evaluation coefficient threshold, it is determined that there is a data collection anomaly in the Internet of Things sensor and an abnormality alarm is issued.

[0010] Furthermore, the data collection execution deviation coefficient acquisition module includes: A historical operation record retrieving module, used to retrieve the historical operation record of the target sensor; An actual data collection time acquisition module, used to retrieve the actual data collection time corresponding to the target sensor from the historical operation record; Theoretical data collection time acquisition module, used to obtain the theoretical data collection time corresponding to the target sensor according to the preset data collection frequency of the target sensor; A data collection execution deviation time acquisition module is used to acquire the data collection execution deviation time of the target sensor according to the actual data collection time and the theoretical data collection time corresponding to the target sensor; The deviation coefficient calculation module is used to obtain the data collection execution deviation coefficient according to the data collection execution deviation time of the target sensor, wherein the data collection execution deviation coefficient is obtained by the following formula:

[0011] Among them, U 02 represents the data collection execution deviation coefficient; n represents the number of data collection times of the target sensor before the data collection response time exceeds the preset data collection response time threshold; T pi represents the data collection execution deviation duration corresponding to the i-th data collection; T ci-1 represents the execution deviation time of data collection corresponding to the i-1th data collection; T cy Indicates the preset data collection response time threshold; T py represents the preset data collection execution deviation time threshold; t represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula:

[0012] Where, t represents the adjustment coefficient; T c Indicates the data collection response time value corresponding to when the data collection response time exceeds the preset data collection response time threshold; T p Indicates the data collection execution deviation duration corresponding to when the data collection response duration exceeds the preset data collection response duration threshold.

[0013] Furthermore, the network layer includes: Communication protocol modules for: Define the communication protocols and standards between all parties involved, and provide correct data transmission and parsing functions; Data synchronization module, used for: Realize real-time sharing and synchronization of data among all parties involved; Security authentication module for: Provides encryption technology and identity authentication mechanisms to encrypt and protect the security of the communication process and the privacy of data.

[0014] Furthermore, the contract layer includes: Contract deployment execution module, used for: Based on blockchain technology, smart contracts are deployed on the chain, and the execution of the contract is triggered through the on-chain mechanism. Smart contracts are automatically executed according to preset rules and conditions. At the same time, smart contract upgrade and maintenance functions are provided.

[0015] Furthermore, the contract layer further includes: Construction plan management module for: The logic of construction planning and resource management is set in the smart contract. Through the automatic execution mechanism, the construction plan is automatically reviewed and confirmed according to the preset rules and conditions, and the execution status of the construction plan is updated and displayed in real time. At the same time, the construction resources are automatically scheduled and managed according to the construction progress and resource requirements.

[0016] Furthermore, the application layer includes: Purchase order traceability module, used for: The execution logic of the purchase order is set in the smart contract, and the purchase order is automatically executed through the smart contract. The execution logic includes order generation, review, execution and settlement processes. At the same time, the Internet of Things technology is used to record the traceability information of the steel bar materials, and the traceability information is associated with the purchase order for traceability management.

[0017] Furthermore, the application layer further includes: Rebar acceptance monitoring module, used for: A rebar acceptance page is generated through smart contracts, and an acceptance function for the rebar quality inspection data is provided when the rebars enter the site. By comparing the rebar quality inspection data with the standard data, it is determined whether the rebars meet the requirements. The rebar quality inspection data includes the quality assurance number, material certificate, steel furnace number, steel grade, chemical composition and mechanical properties. A rebar processing inspection page is generated through smart contracts, and an inspection function for the surface quality of the steel is provided after processing. By comparing the steel surface quality with the processing standard, it is determined whether the rebar processing meets the requirements. The steel surface quality includes scarring, cracking, folding and delamination, and rust.

[0018] Another technical problem to be solved by the present invention is to provide a whole-process management method for a steel bar project based on a smart contract, comprising the following steps: Step 1: Configure IoT sensors and RFID devices, set parameters and interfaces for data collection, establish communication protocols and data synchronization mechanisms between all parties involved, deploy smart contracts on the blockchain, set trigger conditions and rules for contract execution, design user interaction interfaces, and provide data viewing, operation initiation, and progress monitoring functions; Step 2: Use IoT sensors and RFID technology to collect steel bar engineering data at the construction site in real time, transmit the collected data to the system, and store and preliminarily process it; Step 3: Based on the logic of the smart contract, the construction progress is automatically updated according to the real-time collected construction site data. According to the updated construction progress information, a progress report is automatically generated and sent to the participants through the network layer; Step 4: The smart contract automatically reviews and confirms the construction plan based on the preset rules and conditions. According to the construction plan and progress requirements, the smart contract automatically dispatches and manages construction resources, including steel materials and construction equipment; Step 5: Automatically execute the purchase order through the smart contract. At the same time, record the traceability information of the steel bar materials. When the steel bars arrive at the site, the steel bar quality inspection data is inspected through the steel bar acceptance page generated by the smart contract. After the steel bars are processed, compare the quality inspection data with the standard data to determine whether the steel bars meet the requirements.

[0019] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention deploys the execution module through the contract, and the smart contract can be automatically executed based on the blockchain technology, and the construction process of the steel bar project can be managed according to the preset rules and conditions, which greatly reduces the manual intervention, improves the management efficiency, and reduces the risk of human error. The construction plan management module can set the logic of the construction plan and resource management in the smart contract, and realize the automatic review and confirmation of the construction plan. With the change of the construction progress, the system can update and display the execution status of the construction plan in real time, and automatically dispatch and manage the construction resources as needed, which helps to ensure the smooth execution of the construction plan and improve the efficiency of resource utilization; 2. The purchase order traceability module of the present invention realizes the automation of purchase order generation, review, execution and settlement processes through smart contracts, thereby improving management efficiency. At the same time, the Internet of Things technology is used to record the traceability information of steel bar materials and associate it with the purchase order, thereby realizing the traceability management of the source of steel bar materials, which not only helps to ensure the quality of steel bars, but also can quickly locate the responsible party when problems occur, thereby reducing risks; 3. The steel bar acceptance monitoring module of the present invention generates a steel bar acceptance page through a smart contract, thereby realizing the automated acceptance of steel bar quality inspection data. By comparing the steel bar quality inspection data with the standard data, it can quickly determine whether the steel bar meets the requirements. Similarly, for the surface quality inspection of the steel bar after processing, the module can also provide intelligent comparison and judgment functions, ensuring the standardization and accuracy of steel bar acceptance and avoiding errors and delays caused by human factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a module schematic diagram of the whole process management system of steel bar engineering based on smart contract of the present invention; Figure 2 It is a schematic diagram of the whole process management process of the steel bar engineering based on smart contract of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] In order to solve the technical problems that the traditional steel bar engineering management process often involves a lot of manual operations and paper document processing, resulting in low management efficiency and prone to errors, and in the steel bar engineering management, data is easily inconsistent due to manual operations or poor information transmission, and it is also very difficult to trace back, please refer to Figure 1-2 , the present invention provides the following technical solutions: The whole process management system of steel bar engineering based on smart contracts includes: Data layer, used for: Based on the Internet of Things technology, the construction site data of the steel bar project is collected, acquired and stored in real time. The construction site data includes raw material information, processing parameters, transportation records and installation progress. Based on the smart contract, the construction progress is automatically updated according to the collected construction site data, and a progress report is generated; The network layer is used to: Provide communication and collaboration mechanisms among all parties involved to achieve real-time sharing and synchronization of data; The contract layer is used to: Deploy smart contracts, define the business logic and rules of the entire steel bar engineering process, automatically execute smart contracts, automatically review and confirm the construction plan according to preset rules and conditions, and update and display the execution status of the construction plan in real time. At the same time, smart contracts automatically schedule and manage construction resources according to the construction plan and progress, including steel bar materials and construction equipment; Application layer, used for: It provides a user interface and interactive functions for viewing data, initiating operations and monitoring progress. It automatically executes purchase orders through smart contracts to ensure that suppliers provide qualified steel bar raw materials in accordance with the agreed conditions. At the same time, it records the traceability information of the steel bar materials, including the manufacturer and batch number. It generates a steel bar acceptance page through smart contracts, and provides acceptance function for steel bar quality inspection data when the steel bars enter the site.

[0023] In the above embodiment, the reinforcement engineering data of the construction site is collected in real time through the Internet of Things technology, and the construction progress is automatically updated based on the smart contract to ensure the accuracy and real-time nature of the data, which helps managers to grasp the latest status of the project in a timely manner and make accurate decisions. The deployment and application of smart contracts make the management process of the entire reinforcement engineering more automated and intelligent. Smart contracts can automatically review and confirm construction plans, automatically schedule and manage construction resources, thereby reducing human intervention and errors and improving management efficiency. The communication and collaboration mechanism provided by the network layer enables all participants to share and synchronize data in real time, strengthens the collaboration and communication of all parties, helps to reduce information asymmetry, and improves the collaborative efficiency of the project.

[0024] In the above embodiment, the purchase order is automatically executed through the smart contract, ensuring that the supplier provides qualified steel bar raw materials according to the agreed conditions. At the same time, the traceability information of the steel bar material is recorded, so that the source and flow of the material can be traced, enhancing the transparency and reliability of supply chain management. The steel bar acceptance page is generated through the smart contract, providing an acceptance function for the steel bar quality inspection data, which can quickly compare the steel bar quality inspection data with the standard data, determine whether the steel bar meets the requirements, and improve the efficiency and accuracy of the acceptance. The automatic execution and real-time data update of the smart contract help reduce the risks caused by human errors and negligence, while improving management efficiency and helping to reduce the operating costs of the project.

[0025] The data layer includes: Data acquisition module for: Use IoT sensors and RFID to collect steel bar engineering data at the construction site in real time, transmit the collected data to the system, and store and preliminarily process it. The steel bar engineering data includes raw material information, processing parameters, transportation records and installation progress. The raw material information includes material, size and weight, the processing parameters include cutting length and bending angle, the transportation records include transportation vehicle information and timestamp, and the installation progress includes completed and unfinished engineering quantities; through preset data interfaces and protocols; Report generation module for: The logic of data update and report generation is set in the smart contract. When new data is received, the update mechanism is automatically triggered. Based on the real-time collected construction site data, the smart contract automatically updates the construction progress, generates a corresponding progress report, and sends it to the participants through the network layer.

[0026] In the above embodiment, the data acquisition module utilizes the Internet of Things sensors and RFID technology to obtain the construction site data of the steel bar project in real time and accurately, ensuring that managers can obtain the latest construction progress and make more accurate and timely decisions.

[0027] In the above embodiment, the automation function of the report generation module greatly reduces human intervention and errors. When new data is collected, the smart contract can automatically trigger the update mechanism to generate the latest progress report, which not only improves efficiency but also reduces the risk of human error. Since the construction progress and reports are automatically generated, managers can obtain the required information faster and make decisions faster. This fast decision-making process helps the project proceed smoothly and avoid delays.

[0028] In the above embodiment, the automatically generated progress report can be sent to the participants in real time through the network layer, which helps to enhance the collaboration and communication between the parties. All participants can keep abreast of the latest status of the project and jointly deal with possible problems. Based on real-time data and automatically generated reports, the management system can more accurately predict construction needs and resource consumption, which helps to optimize resource allocation and avoid waste and shortage of resources. Through real-time data monitoring and automatic report generation, the management system can promptly discover and deal with potential construction problems. This preventive risk management strategy helps reduce project risks and ensure the smooth progress of the project.

[0029] Specifically, the data acquisition module includes: A real-time monitoring module is used to monitor the data collection response time of the IoT sensor in real time; wherein the data collection response time refers to the time elapsed between the IoT sensor executing the data collection action and obtaining the collected data; A comparison module, used for comparing the data collection response time with a preset data collection response time threshold; A target sensor determination module is used to, when the data acquisition response time exceeds a preset data acquisition response time threshold, use the IoT sensor corresponding to the data acquisition response time exceeding the preset data acquisition response time threshold as a target sensor; The data acquisition response coefficient acquisition module is used to obtain the data acquisition response coefficient using the data acquisition response time corresponding to each data acquisition of the target sensor, wherein the data acquisition response coefficient is obtained by the following formula:

[0030] Among them, U 01 represents the data collection response coefficient; n represents the number of data collection times of the target sensor before the data collection response time exceeds the preset data collection response time threshold; T ci represents the data collection response time corresponding to the i-th data collection; T ci-1 represents the data collection response time corresponding to the i-1th data collection; T c Indicates the data collection response time value corresponding to when the data collection response time exceeds the preset data collection response time threshold; T cy Indicates the preset data collection response time threshold; A data collection execution deviation coefficient acquisition module is used to retrieve the historical operation record of the target sensor, obtain the data collection execution deviation duration corresponding to the actual data collection time and the theoretical data collection time of the target sensor through the historical operation record, and obtain the data collection execution deviation coefficient through the data collection execution deviation duration; The comprehensive evaluation coefficient acquisition module is used to obtain the comprehensive evaluation coefficient using the data acquisition response coefficient and the data acquisition execution deviation coefficient, wherein the comprehensive evaluation coefficient is obtained by the following formula:

[0031] Among them, U represents the comprehensive evaluation coefficient; U 01 Indicates the data acquisition response coefficient; U 02 It represents the coefficient of deviation of data collection execution; The data collection anomaly judgment module is used to compare the comprehensive evaluation coefficient with a preset evaluation coefficient threshold. When the comprehensive evaluation coefficient exceeds the preset evaluation coefficient threshold, it is determined that there is a data collection anomaly in the Internet of Things sensor and an abnormality alarm is issued.

[0032] The technical effect of the above technical solution is: it can monitor the data collection response time of the IoT sensor in real time to ensure the immediate grasp of the working status of the sensor. This is of great significance for timely discovering potential problems and improving system stability. By comparing the actual data collection response time with the preset threshold, the sensor with abnormal response time (i.e., the target sensor) can be accurately identified. This mechanism helps to quickly locate the source of the problem and reduce the troubleshooting time. Using the data collection response time data of the target sensor, the data collection response coefficient is calculated through a specific formula, which provides a quantitative indicator for evaluating the performance of the sensor. This helps to evaluate the operating status and work efficiency of the sensor more objectively and accurately.

[0033] By retrieving historical operation records and calculating the data collection execution deviation coefficient, the data collection execution deviation of the sensor can be further evaluated. This helps to discover potential problems in the data collection execution process of the sensor, such as time synchronization errors, execution delays, etc.

[0034] Combining the data collection response coefficient and the data collection execution deviation coefficient, the comprehensive evaluation coefficient is calculated through a specific formula, which provides a comprehensive indicator for comprehensively evaluating the performance of the sensor. This helps to understand the overall operating status of the sensor more comprehensively. The comprehensive evaluation coefficient is compared with the preset evaluation coefficient threshold. When the threshold is exceeded, it is determined that the IoT sensor has data collection anomalies and an abnormal alarm is issued. This mechanism can detect and report abnormal situations in a timely manner, which helps to quickly respond to and handle problems and prevent them from escalating.

[0035] Through the implementation of the above technical solutions, the data collection process of IoT sensors can be fully monitored and evaluated, and potential problems can be discovered and solved in a timely manner. This helps to improve the stability and reliability of the entire IoT system and ensure the accuracy and real-time nature of data collection.

[0036] In summary, this technical solution realizes the comprehensive management and optimization of the IoT sensor data collection process through mechanisms such as real-time monitoring, anomaly detection, data-driven performance evaluation and comprehensive evaluation, and improves the stability and reliability of the system.

[0037] Specifically, the data collection execution deviation coefficient acquisition module includes: A historical operation record retrieving module, used to retrieve the historical operation record of the target sensor; An actual data collection time acquisition module, used to retrieve the actual data collection time corresponding to the target sensor from the historical operation record; Theoretical data collection time acquisition module, used to obtain the theoretical data collection time corresponding to the target sensor according to the preset data collection frequency of the target sensor; A data collection execution deviation time acquisition module is used to acquire the data collection execution deviation time of the target sensor according to the actual data collection time and the theoretical data collection time corresponding to the target sensor; The deviation coefficient calculation module is used to obtain the data collection execution deviation coefficient according to the data collection execution deviation time of the target sensor, wherein the data collection execution deviation coefficient is obtained by the following formula:

[0038] Among them, U 02 represents the data collection execution deviation coefficient; n represents the number of data collection times of the target sensor before the data collection response time exceeds the preset data collection response time threshold; T pi represents the data collection execution deviation duration corresponding to the i-th data collection; T ci-1 represents the execution deviation time of data collection corresponding to the i-1th data collection; T cy Indicates the preset data collection response time threshold; T py represents the preset data collection execution deviation time threshold; t represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula:

[0039] Where, t represents the adjustment coefficient; T c Indicates the data collection response time value corresponding to when the data collection response time exceeds the preset data collection response time threshold; T p Indicates the data collection execution deviation duration corresponding to when the data collection response duration exceeds the preset data collection response duration threshold.

[0040] The technical effect of the above technical solution is: by retrieving the historical operation records of the target sensor, a detailed data basis is provided for subsequent analysis. The actual and theoretical data collection moments are obtained respectively, providing accurate starting and ending points for calculating the deviation duration of data collection execution. The deviation duration calculated based on the actual and theoretical data collection moments accurately quantifies the deviation of the sensor during the data collection execution process.

[0041] The data collection execution deviation coefficient (U02) is calculated through a specific formula. This coefficient not only takes into account the deviation duration of a single data collection, but also realizes a comprehensive evaluation of the execution deviation under the long-term operation state of the sensor by accumulating the previous n deviation durations and introducing the adjustment coefficient t. This calculation method is more scientific and comprehensive, and can more accurately reflect the actual operation state of the sensor.

[0042] By introducing the adjustment coefficient t, the technical solution can dynamically adjust the calculation weight of the deviation coefficient according to the actual values ​​of the data collection response time and the data collection execution deviation time. This mechanism makes the calculation of the deviation coefficient more flexible and can better adapt to the deviation conditions of different sensors and different operating environments. By accurately quantifying the data collection execution deviation and calculating the deviation coefficient, the system can promptly discover potential problems of sensors during the data collection execution process. For example, execution delays, time synchronization errors, etc. Once these problems are discovered and resolved, they will help improve the stability and reliability of the entire IoT system.

[0043] At the same time, the calculation of the deviation coefficient also provides an important reference for system maintenance and optimization. According to the size and change trend of the deviation coefficient, the system administrator can formulate corresponding maintenance plans and optimization strategies to further improve the operating efficiency and performance of the system.

[0044] In summary, this technical solution achieves a comprehensive assessment and effective management of the execution deviation of IoT sensor data collection by accurately quantifying the execution deviation of data collection, scientifically calculating the deviation coefficient, and introducing a flexible adjustment coefficient mechanism, thereby improving the stability and reliability of the system.

[0045] Network layer, including: Communication protocol modules for: Define the communication protocols and standards between all parties involved, and provide correct data transmission and parsing functions; Data synchronization module, used for: Realize real-time sharing and synchronization of data among all parties involved; Security authentication module for: Provides encryption technology and identity authentication mechanisms to encrypt and protect the security of the communication process and the privacy of data.

[0046] In the above embodiment, by defining clear communication protocols and standards through the communication protocol module, it is possible to ensure accurate data exchange between the participating parties, avoid communication barriers caused by inconsistent data formats or transmission errors, and improve the efficiency and accuracy of information interaction.

[0047] In the above embodiment, the data synchronization module can realize real-time sharing and synchronization of data among all participating parties, ensuring that all relevant parties can obtain the latest project progress information in a timely manner, which helps to improve the collaboration efficiency among all parties and reduce decision-making delays or errors caused by information asymmetry.

[0048] In the above embodiment, the security authentication module encrypts and protects the communication process and data privacy by adopting encryption technology and identity authentication mechanism, effectively preventing data leakage or illegal tampering, ensuring the confidentiality of sensitive information, enhancing the security of the system, and meeting the high requirements for data security and privacy protection in modern engineering management.

[0049] Contract layer, including: Contract deployment execution module, used for: Based on blockchain technology, smart contracts are deployed on the chain, and the execution of the contract is triggered through the on-chain mechanism. Smart contracts are automatically executed according to preset rules and conditions. At the same time, smart contract upgrade and maintenance functions are provided.

[0050] Construction plan management module for: The logic of construction planning and resource management is set in the smart contract. Through the automatic execution mechanism, the construction plan is automatically reviewed and confirmed according to the preset rules and conditions, and the execution status of the construction plan is updated and displayed in real time. At the same time, the construction resources are automatically scheduled and managed according to the construction progress and resource requirements.

[0051] In the above embodiment, through the contract deployment execution module, the smart contract can be automatically executed based on blockchain technology, and the construction process of the steel bar project can be managed according to preset rules and conditions, which greatly reduces manual intervention, improves management efficiency, and reduces the risk of human error. The construction plan management module can set the logic of construction plan and resource management in the smart contract to realize automatic review and confirmation of the construction plan. As the construction progress changes, the system can update and display the execution status of the construction plan in real time, and automatically dispatch and manage construction resources as needed, which helps to ensure the smooth execution of the construction plan and improve resource utilization efficiency.

[0052] In the above embodiment, since the smart contract is deployed on the blockchain, all execution records and status updates are public, transparent and tamper-proof, which enhances the credibility and verifiability of the data, helps all parties to establish a trust relationship, and reduces disputes and disputes. The contract deployment and execution module not only supports the deployment and execution of smart contracts, but also provides upgrade and maintenance functions, so that the system can adjust and optimize the logic of smart contracts according to actual conditions to adapt to changing construction needs and management requirements.

[0053] Application layer, including: Purchase order traceability module, used for: The execution logic of the purchase order is set in the smart contract, and the purchase order is automatically executed through the smart contract. The execution logic includes order generation, review, execution and settlement processes. At the same time, the Internet of Things technology is used to record the traceability information of the steel bar materials, and the traceability information is associated with the purchase order for traceability management.

[0054] Rebar acceptance monitoring module, used for: A rebar acceptance page is generated through smart contracts, and an acceptance function for the rebar quality inspection data is provided when the rebars enter the site. By comparing the rebar quality inspection data with the standard data, it is determined whether the rebars meet the requirements. The rebar quality inspection data includes the quality assurance number, material certificate, steel furnace number, steel grade, chemical composition and mechanical properties. A rebar processing inspection page is generated through smart contracts, and an inspection function for the surface quality of the steel is provided after processing. By comparing the steel surface quality with the processing standard, it is determined whether the rebar processing meets the requirements. The steel surface quality includes scarring, cracking, folding and delamination, and rust.

[0055] In the above embodiment, the purchase order traceability module realizes the automation of purchase order generation, review, execution and settlement processes through smart contracts, thereby improving management efficiency. At the same time, the traceability information of steel bar materials is recorded by using Internet of Things technology and associated with purchase orders, thus realizing the traceability management of the source of steel bar materials, which not only helps to ensure the quality of steel bars, but also can quickly locate the responsible party when problems occur, thus reducing risks.

[0056] In the above embodiment, the steel bar acceptance monitoring module generates a steel bar acceptance page through a smart contract, realizing the automated acceptance of steel bar quality inspection data. By comparing the steel bar quality inspection data with the standard data, it can quickly determine whether the steel bar meets the requirements. Similarly, for the surface quality inspection of the steel bar after processing, the module can also provide intelligent comparison and judgment functions, ensuring the standardization and accuracy of steel bar acceptance and avoiding errors and delays caused by human factors.

[0057] In the above embodiment, through the smart contract technology of the application layer, the management efficiency of the whole process management system of the steel bar project has been significantly improved. The automatic execution of the smart contract reduces manual operations and reduces the possibility of errors. The technical solution of the application layer helps to enhance the quality control of the steel bar quality and processing process. Through automated acceptance and intelligent inspection, situations that do not meet the requirements can be discovered and handled in a timely manner to prevent unqualified materials from entering the project site. At the same time, the traceability management function also helps to quickly locate the cause and the person responsible when a problem occurs, and strengthen risk management.

[0058] This embodiment now proposes a whole process management method for steel bar engineering based on smart contracts, including the following steps: Step 1: Configure IoT sensors and RFID devices, set parameters and interfaces for data collection, establish communication protocols and data synchronization mechanisms between all parties involved, deploy smart contracts on the blockchain, set trigger conditions and rules for contract execution, design user interaction interfaces, and provide data viewing, operation initiation, and progress monitoring functions; Step 2: Use IoT sensors and RFID technology to collect steel bar engineering data at the construction site in real time, transmit the collected data to the system, and store and preliminarily process it; Step 3: Based on the logic of the smart contract, the construction progress is automatically updated according to the real-time collected construction site data. According to the updated construction progress information, a progress report is automatically generated and sent to the participants through the network layer; Step 4: The smart contract automatically reviews and confirms the construction plan based on the preset rules and conditions. According to the construction plan and progress requirements, the smart contract automatically dispatches and manages construction resources, including steel materials and construction equipment; Step 5: Automatically execute the purchase order through the smart contract. At the same time, record the traceability information of the steel bar materials. When the steel bars arrive at the site, the steel bar quality inspection data is inspected through the steel bar acceptance page generated by the smart contract. After the steel bars are processed, compare the quality inspection data with the standard data to determine whether the steel bars meet the requirements.

[0059] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The whole process management system of steel bar engineering based on smart contract is characterized by: include: Data layer, used for: Based on the Internet of Things technology, the construction site data of the steel bar project is collected, acquired and stored in real time. The construction site data includes raw material information, processing parameters, transportation records and installation progress. Based on the smart contract, the construction progress is automatically updated according to the collected construction site data, and a progress report is generated; The network layer is used to: Provide communication and collaboration mechanisms among all parties involved to achieve real-time sharing and synchronization of data; The contract layer is used to: Deploy smart contracts, define the business logic and rules of the entire steel bar engineering process, automatically execute smart contracts, automatically review and confirm the construction plan according to preset rules and conditions, and update and display the execution status of the construction plan in real time. At the same time, smart contracts automatically schedule and manage construction resources according to the construction plan and progress, including steel bar materials and construction equipment; Application layer, used for: It provides a user interface and interactive functions for viewing data, initiating operations and monitoring progress. It automatically executes purchase orders through smart contracts to ensure that suppliers provide qualified steel bar raw materials in accordance with the agreed conditions. At the same time, it records the traceability information of the steel bar materials, including the manufacturer and batch number. It generates a steel bar acceptance page through smart contracts, and provides acceptance function for steel bar quality inspection data when the steel bars enter the site.

2. The whole process management system of steel bar engineering based on smart contract as claimed in claim 1, characterized in that: The data layer includes: Data acquisition module for: Use IoT sensors and RFID to collect steel bar engineering data at the construction site in real time, transmit the collected data to the system, and store and preliminarily process it. The steel bar engineering data includes raw material information, processing parameters, transportation records and installation progress. The raw material information includes material, size and weight, the processing parameters include cutting length and bending angle, the transportation records include transportation vehicle information and timestamp, and the installation progress includes completed and unfinished engineering quantities; through preset data interfaces and protocols; Report generation module for: The logic of data update and report generation is set in the smart contract. When new data is received, the update mechanism is automatically triggered. Based on the real-time collected construction site data, the smart contract automatically updates the construction progress, generates a corresponding progress report, and sends it to the participants through the network layer.

3. The steel bar engineering whole process management system based on smart contract as claimed in claim 1, characterized in that: Data acquisition module, including: A real-time monitoring module is used to monitor the data collection response time of the IoT sensor in real time; wherein the data collection response time refers to the time elapsed between the IoT sensor executing the data collection action and obtaining the collected data; A comparison module, used for comparing the data collection response time with a preset data collection response time threshold; A target sensor determination module is used to, when the data acquisition response time exceeds a preset data acquisition response time threshold, use the IoT sensor corresponding to the data acquisition response time exceeding the preset data acquisition response time threshold as a target sensor; The data acquisition response coefficient acquisition module is used to obtain the data acquisition response coefficient using the data acquisition response time corresponding to each data acquisition of the target sensor, wherein the data acquisition response coefficient is obtained by the following formula: ； Among them, U 01 represents the data collection response coefficient; n represents the number of data collection times of the target sensor before the data collection response time exceeds the preset data collection response time threshold; T ci represents the data collection response time corresponding to the i-th data collection; T ci-1 represents the data collection response time corresponding to the i-1th data collection; T c Indicates the data collection response time value corresponding to when the data collection response time exceeds the preset data collection response time threshold; T cy Indicates the preset data collection response time threshold; A data collection execution deviation coefficient acquisition module is used to retrieve the historical operation record of the target sensor, obtain the data collection execution deviation duration corresponding to the actual data collection time and the theoretical data collection time of the target sensor through the historical operation record, and obtain the data collection execution deviation coefficient through the data collection execution deviation duration; The comprehensive evaluation coefficient acquisition module is used to obtain the comprehensive evaluation coefficient using the data acquisition response coefficient and the data acquisition execution deviation coefficient, wherein the comprehensive evaluation coefficient is obtained by the following formula: ； Among them, U represents the comprehensive evaluation coefficient; U 01 Indicates the data acquisition response coefficient; U 02 It represents the coefficient of deviation of data collection execution; The data collection anomaly judgment module is used to compare the comprehensive evaluation coefficient with a preset evaluation coefficient threshold. When the comprehensive evaluation coefficient exceeds the preset evaluation coefficient threshold, it is determined that there is a data collection anomaly in the Internet of Things sensor and an abnormality alarm is issued.

4. The whole process management system of steel bar engineering based on smart contract as claimed in claim 1, characterized in that: The data acquisition execution deviation coefficient acquisition module includes: A historical operation record retrieving module, used to retrieve the historical operation record of the target sensor; An actual data collection time acquisition module, used to retrieve the actual data collection time corresponding to the target sensor from the historical operation record; Theoretical data collection time acquisition module, used to obtain the theoretical data collection time corresponding to the target sensor according to the preset data collection frequency of the target sensor; A data collection execution deviation time acquisition module is used to acquire the data collection execution deviation time of the target sensor according to the actual data collection time and the theoretical data collection time corresponding to the target sensor; The deviation coefficient calculation module is used to obtain the data collection execution deviation coefficient according to the data collection execution deviation time of the target sensor, wherein the data collection execution deviation coefficient is obtained by the following formula: ； Among them, U 02 represents the data collection execution deviation coefficient; n represents the number of data collection times of the target sensor before the data collection response time exceeds the preset data collection response time threshold; T pi represents the data collection execution deviation duration corresponding to the i-th data collection; T ci-1 represents the execution deviation time of data collection corresponding to the i-1th data collection; T cy Indicates the preset data collection response time threshold; T py represents the preset data collection execution deviation time threshold; t represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula: ； Where, t represents the adjustment coefficient; T c Indicates the data collection response time value corresponding to when the data collection response time exceeds the preset data collection response time threshold; T p Indicates the data collection execution deviation duration corresponding to when the data collection response duration exceeds the preset data collection response duration threshold.

5. The steel bar engineering whole process management system based on smart contract as claimed in claim 1, characterized in that: The network layer includes: Communication protocol modules for: Define the communication protocols and standards between all parties involved, and provide correct data transmission and parsing functions; Data synchronization module, used for: Realize real-time sharing and synchronization of data among all parties involved; Security authentication module for: Provides encryption technology and identity authentication mechanisms to encrypt and protect the security of the communication process and the privacy of data.

6. The steel bar engineering whole process management system based on smart contract as claimed in claim 1, characterized in that: The contract layer includes: Contract deployment execution module, used for: Based on blockchain technology, smart contracts are deployed on the chain, and the execution of the contract is triggered through the on-chain mechanism. Smart contracts are automatically executed according to preset rules and conditions. At the same time, smart contract upgrade and maintenance functions are provided.

7. The whole process management system of steel bar engineering based on smart contract as claimed in claim 4, characterized in that: The contract layer also includes: Construction plan management module for: The logic of construction planning and resource management is set in the smart contract. Through the automatic execution mechanism, the construction plan is automatically reviewed and confirmed according to the preset rules and conditions, and the execution status of the construction plan is updated and displayed in real time. At the same time, the construction resources are automatically scheduled and managed according to the construction progress and resource requirements.

8. The steel bar engineering whole process management system based on smart contract as claimed in claim 1, characterized in that: The application layer includes: Purchase order traceability module, used for: The execution logic of the purchase order is set in the smart contract, and the purchase order is automatically executed through the smart contract. The execution logic includes order generation, review, execution and settlement processes. At the same time, the Internet of Things technology is used to record the traceability information of the steel bar materials, and the traceability information is associated with the purchase order for traceability management.

9. The steel bar engineering whole process management system based on smart contract as claimed in claim 8, characterized in that: The application layer further includes: Rebar acceptance monitoring module, used for: A rebar acceptance page is generated through smart contracts, and an acceptance function for the rebar quality inspection data is provided when the rebars enter the site. By comparing the rebar quality inspection data with the standard data, it is determined whether the rebars meet the requirements. The rebar quality inspection data includes the quality assurance number, material certificate, steel furnace number, steel grade, chemical composition and mechanical properties. A rebar processing inspection page is generated through smart contracts, and an inspection function for the surface quality of the steel is provided after processing. By comparing the steel surface quality with the processing standard, it is determined whether the rebar processing meets the requirements. The steel surface quality includes scarring, cracking, folding and delamination, and rust.

10. A method for managing the entire process of a steel bar project based on a smart contract, which is implemented based on the entire process management system of a steel bar project based on a smart contract according to any one of claims 1 to 9, and is characterized in that: The steps include: Step 1: Configure IoT sensors and RFID devices, set parameters and interfaces for data collection, establish communication protocols and data synchronization mechanisms between all parties involved, deploy smart contracts on the blockchain, set trigger conditions and rules for contract execution, design user interaction interfaces, and provide data viewing, operation initiation, and progress monitoring functions; Step 2: Use IoT sensors and RFID technology to collect steel bar engineering data at the construction site in real time, transmit the collected data to the system, and store and preliminarily process it; Step 3: Based on the logic of the smart contract, the construction progress is automatically updated according to the real-time collected construction site data. According to the updated construction progress information, a progress report is automatically generated and sent to the participants through the network layer; Step 4: The smart contract automatically reviews and confirms the construction plan based on preset rules and conditions. According to the construction plan and progress requirements, the smart contract automatically dispatches and manages construction resources, including steel materials and construction equipment; Step 5: Automatically execute the purchase order through the smart contract. At the same time, record the traceability information of the steel bar materials. When the steel bars arrive at the site, the steel bar quality inspection data is inspected through the steel bar acceptance page generated by the smart contract. After the steel bars are processed, compare the quality inspection data with the standard data to determine whether the steel bars meet the requirements.

Images