Material management method and system, intelligent equipment and traceable data processing device

Abstract

The invention relates to the technical field of material management, and discloses a material management method and system, intelligent equipment and a traceable data processing device.The method comprises the steps that when supplier vehicles loaded with materials arrive at a construction site, vehicle numbers, material types and material weights form entry data; if the scanning data is consistent with the entry data, storing the scanning data and the entry data by using a cloud database, and indicating the supplier vehicle to enter the construction site; collecting the timestamp and the geographic position of each supplier vehicle in real time, and storing the timestamp and the geographic position by using a cloud database; executing the block chain encryption storage strategy, and storing the data in the cloud database by using a block chain; acquiring historical material consumption data stored in the block chain, executing a material inventory prediction strategy, and predicting future material demands; and executing the inventory dynamic adjustment strategy, and adjusting the stock purchase scheme of the inventory. The automation and intelligence of material management are improved, and the construction efficiency and transparency are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of material management, and specifically to a material management method, system, intelligent device, and traceable data processing device. Background Art

[0002] With the development of the industrial and construction fields, material management has gradually become a key link in modern construction management. Especially in large-scale engineering projects, the incoming and outgoing, consumption, and inventory management of materials directly affect the project progress and cost control.

[0003] Traditional material management methods often rely on manual records and manual inspections, which are not only inefficient but also prone to errors, resulting in inaccurate and untimely information. To improve the efficiency and transparency of material management, more and more industries have begun to adopt automated and intelligent technologies for material management. Traditional devices mostly rely on manual input and a single weighing function, lacking linkage with other management systems and intelligent applications, and unable to efficiently monitor and analyze real-time data such as material flow and inventory changes. This makes material management particularly difficult in the face of complex supply chains, diverse material types, and a large number of suppliers.

[0004] The present invention provides a material management method, system, intelligent device, and traceable data processing device. The material management method combining modern intelligent technology and blockchain encrypted storage will greatly improve the automation, intelligence, and security of material management, and promote the efficiency and transparency of engineering project management. Summary of the Invention

[0005] The present invention provides a material management method, system, intelligent device, and traceable data processing device, which helps to solve the problems mentioned in the above background art.

[0006] In a first aspect, the present application provides a material management method, which adopts the following technical solution: A material management method includes: When a supplier vehicle loaded with materials arrives at the construction site, two intelligent devices are configured at the construction site, denoted as the first device and the second device respectively; Automatically read the vehicle number using the license plate recognition technology loaded on the first device; Automatically identify the material type using the AI automatic recognition function loaded on the first device; Weigh the materials of the supplier vehicle using the second device to obtain the material weight; Form incoming data by combining the vehicle number, material type, and material weight; Use the terminal device to scan the paper documents carried by the vehicle, and compare whether the scanned data is consistent with the incoming data; if the scanned data is consistent with the incoming data, save the scanned data and the incoming data using the cloud database, and instruct the supplier vehicle to enter the construction site; By adopting an intelligent material management method, the efficiency of material management can be greatly improved. Traditional material management methods often rely on manual operations, such as manually recording the types, weights, arrival times of materials, etc. This is not only time-consuming but also prone to errors. By adding license plate recognition technology and AI automatic material type recognition to the equipment, the number of the supplier vehicle can be automatically read, and the materials can be automatically recognized. The incoming data of the materials can be directly transmitted to the cloud database when being recorded in real time without manual intervention, avoiding data omission or errors that may be caused by manual entry. Through this automated process, the time for material data entry is reduced, the work efficiency is improved, delays and mistakes in the traditional method are avoided, and the smooth and timely material management at the construction site is ensured.

[0007] During the process of the supplier vehicle entering the construction site, use an intelligent recognition camera to dynamically verify the material types, compare the material types with those in the incoming data, and record the comparison result as verification data; By using AI automatic recognition and intelligent recognition camera functions, the accuracy of material data can be effectively improved. In traditional material management, manual recognition and manual recording of material types and weights are often affected by human factors, such as recognition errors or negligence. The intelligent recognition technology can automatically confirm the material types under real-time monitoring and upload the relevant information to the system in real time, avoiding errors that may occur in the manual recognition process. In addition, by using blockchain technology to encrypt and store the data, the security and immutability of the data can be ensured, thus guaranteeing the transparency and accuracy of material management. This intelligent material recognition and data storage method not only improves the accuracy of the data but also provides a strong guarantee for subsequent material traceability.

[0008] Real-time collect the timestamps and geographical locations of each supplier vehicle and save them using the cloud database; Execute the blockchain encryption storage strategy and store the data in the cloud database using blockchain; Obtain the historical material consumption data stored in the blockchain, execute the material inventory prediction strategy to predict future material requirements; execute the inventory dynamic adjustment strategy to adjust the inventory purchase plan.

[0009] Preferably, the execution of the blockchain encryption storage strategy and storing the data in the cloud database using blockchain includes: For any supplier vehicle: When the verification data shows that the types of materials verified dynamically by the intelligent recognition camera are consistent with the types of materials in the incoming data: Obtain the vehicle number V, material type M, material weight W, timestamp T, and geographical location L of the supplier vehicle in the cloud database, and form the material data D = {V, M, W, T, L}; Use the hash function H(·) to encrypt the material data and generate the hash value of the block storing the current material data; Record the hash value of the current block as C n , where n is the number of blocks in the blockchain; Obtain the features for evaluating the importance of the material data, and form the feature set A = {a1, a2, …, a b}, where b is the number of features; Calculate the weight of the material data D α i is the weight of the feature; Record the hash value of the previous block as C n-1 ; Calculate the hash value C of the current block n = H(ω × D || C n-1 ), and || represents the concatenation operation.

[0010] By adopting blockchain encryption storage technology, the security and anti-tampering ability of data can be significantly enhanced. In the traditional material management system, during the data storage and transmission process, it is vulnerable to the risk of tampering caused by humans or system vulnerabilities. The distributed ledger and encryption algorithm of blockchain technology ensure the immutability of data. Each transaction is packaged in a block and encrypted through the hash algorithm. Any modification can be quickly detected and traced. In this way, not only the integrity of the data is guaranteed, but also all operations related to materials can be effectively audited and verified. During the construction process, any improper operation or tampering behavior can be traced and monitored, thereby improving the security and credibility of the entire supply chain.

[0011] Preferably, implementing the blockchain encryption storage strategy to store the data in the cloud database using blockchain includes: When calculating the hash value of the current block, verify the hash value of the previous block: where, is arbitrary; Anti-tampering verification: where, D' respectively represent the existing and modified material data, and n ≥ 1.

[0012] By introducing blockchain technology, the transparency and traceability of material management can be greatly enhanced. The immutability and transparency of the blockchain enable all relevant data on material entry and consumption to be recorded and publicly stored in a distributed ledger, ensuring that any person can query and verify the usage of materials within the scope of their permissions. The data of each link such as material entry, weighing, scanning, and transportation can be traced, thus ensuring the full traceability of material management. Once any problem or dispute is discovered, the relevant data can be quickly queried and verified. This not only improves the management transparency of the construction site but also provides a powerful means to prevent potential supply chain fraud or data tampering, providing a fair and credible operating environment for all parties involved.

[0013] Preferably, obtaining the historical material consumption data stored in the blockchain, implementing a material inventory prediction strategy, and predicting future material requirements includes: Collect historical material consumption data U t ={X t ,Y t ,Z t ,T t}, where X t represents the material demand at time t, T t is the date on which time t falls, Y t represents the supply chain status at time t, and Z t represents the environmental characteristics at time t; Construct a feature matrix Use a machine learning algorithm to predict future material requirements where f(·) represents the machine learning algorithm model and k is the time interval after time t; Calculate the loss function using the mean squared error: where δ is the error threshold, n is the number of samples of historical material consumption data, is the predicted material demand, and X i is the actual material demand.

[0014] Preferably, obtaining the historical material consumption data stored in the blockchain, implementing a material inventory prediction strategy, and predicting future material requirements includes: Optimize the weights p t+k and the bias term q t+k ; Update where η represents the learning rate, is the gradient of the loss function; Update where η represents the learning rate, is the gradient of the loss function.

[0015] Preferably, when implementing the inventory dynamic adjustment strategy and adjusting the inventory replenishment plan, it includes: The replenishment plan is divided into a first plan and a second plan; The first plan is to set an inventory threshold point. When the remaining materials in the inventory reach the inventory threshold point, replenishment is carried out. Specifically: Inventory threshold point where τ, respectively represent the standard normal distribution value and the standard deviation of the predicted material demand; The second plan is to set an additional inventory

[0016] Through the inventory optimization strategy based on historical material consumption data and prediction algorithms, accurate inventory management and dynamic adjustment can be achieved. By predicting future material requirements through machine learning algorithms, managers can adjust the inventory level in advance according to the prediction results, avoiding the occurrence of excessive or shortage of materials. By setting inventory thresholds and real-time monitoring of inventory status, when the inventory approaches the preset threshold, the system will automatically trigger a replenishment plan to ensure the timeliness and accuracy of material supply. This data-based inventory dynamic adjustment method not only improves the accuracy of inventory management, reduces inventory backlogs and capital occupancy, but also effectively reduces construction delays or cost increases caused by material shortages, thereby reducing the overall operating cost.

[0017] In a second aspect, the present application provides a material management system, adopting the following technical solution: A material management system includes: Vehicle identification module: Automatically reads the vehicle number and identifies the material type; Weighing and data collection module: Weighs the materials and collects relevant data; Data consistency verification module: Compares the consistency of the incoming data and the scanned data; Intelligent identification camera module: Dynamically verifies the material type and compares it with the incoming data; Time and location collection module: Real-time collects timestamps and geographical locations; Cloud data storage module: Saves scanned data, incoming data, material data, etc.; Blockchain encryption storage module: Encrypts and stores data in the blockchain to ensure data security and immutability; Historical data acquisition and prediction module: Acquires the stored historical material consumption data and conducts inventory prediction; Inventory prediction and adjustment module: Conducts dynamic inventory adjustment based on material demand prediction; Replenishment plan decision module: Adjusts the replenishment plan according to the inventory prediction.

[0018] In a third aspect, the present application provides a traceable data processing device, adopting the following technical solution: A traceable data processing device; A data processing unit, a blockchain storage module, a query and analysis interface, a monitoring and alarm module, and an audit log record.

[0019] In a fourth aspect, the present application provides an intelligent device, adopting the following technical solution: An intelligent device, comprising: a weighing sensor, a platform, a signal conditioner, a controller, a display screen, a data interface module, and a power supply system.

[0020] The present invention has the following beneficial effects: 1. For this material management method, by adopting an intelligent material management method, the entire process of material arrival and management becomes more efficient. Traditional material management usually relies on manual data entry, manual information verification, and item-by-item inspection of material types and weights, which is not only cumbersome but also vulnerable to human errors. By introducing automated devices such as license plate recognition systems and AI automatic material recognition technologies, when the supplier's vehicle arrives at the construction site, the system can automatically read the vehicle number and identify the material types. The material weight is weighed by the first device and automatically recorded, and all these data will be immediately uploaded to the cloud database. Through this automated data collection and transmission method, the time for manual input and the error rate of manual operations are greatly reduced, thereby improving the overall efficiency of material management. The construction site management personnel can obtain accurate arrival data in real time, reducing waiting and processing time, ensuring the smooth progress of material arrival, and thus improving the construction progress and the efficiency of material supply.

[0021] 2. For this material management method, through the combination of intelligent identification and blockchain technology, the accuracy and reliability of data in material management can be significantly improved. Traditional material management methods rely on manual inspections and records, which may result in data omissions, errors, or duplicate records, leading to inaccurate information. By integrating an AI automatic identification system, the system can automatically analyze material types and weights, reducing the occurrence of human errors. In addition, using blockchain technology to encrypt and store all material arrival data in a distributed ledger ensures the immutability and high credibility of the data. Each transaction has an independent timestamp, and the integrity of the information is ensured through a hash function, not only improving the accuracy of the data but also providing a reliable basis for subsequent traceability. The system will perform data verification in real time. If there is any data inconsistency, it can issue a warning in a timely manner and require correction, thus effectively avoiding the spread of incorrect data. Through these technical means, managers can rely on more accurate data for decision-making, ensuring the smooth progress of material management.

[0022] 3. Through the introduction of blockchain technology, the material management system can achieve a high degree of transparency and traceability in this material management method. In traditional material management systems, data is often stored centrally and there is often a lack of real-time monitoring of operations, making it vulnerable to the risks of human tampering or information loss. However, blockchain technology stores material data in an encrypted manner in a decentralized ledger, ensuring that every material transaction cannot be tampered with or forged. In this way, data such as the arrival, use, and consumption of all materials at the construction site can be accurately recorded, and query and auditing functions are provided. Whether it is the transportation route of materials, supplier information, arrival time, weighing data, etc., they can all be clearly traced. Through real-time monitoring and data verification, any anomalies or disputes can be quickly discovered and processed. This fully traceable management method not only strengthens the trust among all parties, but also effectively improves the transparency of the entire material management process, providing accurate and reliable data support for management decisions.

[0023] 4. Through the inventory optimization strategy based on historical consumption data and prediction algorithms, this material management method can achieve precise inventory management and cost control. Traditional inventory management often relies on manual experience and regular inventory checks, which may lead to situations of excessive or insufficient inventory, resulting in waste of funds or material shortages. By combining historical consumption data and environmental factors and using machine learning algorithms to predict future material requirements, a scientific basis can be provided for inventory management in advance. The system will automatically adjust the inventory threshold according to the predicted demand to ensure that the supply of materials matches the actual demand. Once the inventory approaches the preset threshold, the system will automatically generate a replenishment order to reduce project delays caused by material shortages. At the same time, by optimizing and adjusting the inventory, over-purchasing can be avoided, reducing inventory backlogs and expired materials, thereby reducing inventory costs. Through this dynamic inventory adjustment based on data analysis, not only is the accuracy of material supply improved, but also the waste of funds and management costs caused by unreasonable inventory are greatly reduced.

[0024] 5. This material management method can significantly enhance the data security and anti-tampering ability of the material management system through blockchain encryption storage technology. In traditional material management systems, data is vulnerable to malicious tampering or system vulnerabilities during storage and transmission, especially in an environment of multi-person operation and information sharing. Blockchain technology, through decentralized ledger records and encryption algorithms, ensures that every piece of material transaction data is securely stored and cannot be arbitrarily tampered with. Each material transaction generates a unique hash value, and all data is associated with a timestamp. Once the data is tampered with, the corresponding hash value will change, enabling real-time detection. In addition, blockchain technology also provides data transparency and traceability. Any modification or operation will leave a record, ensuring the auditability of the system. This enhancement of data security and anti-tampering ability not only prevents data loss or errors but also provides reliable evidence to ensure the integrity and fairness of the material management process. Through this technical guarantee, the overall security of material management has been significantly improved, reducing the risk of malicious data tampering. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic flowchart of the method of the present invention.

[0026] Figure 2 It is a schematic diagram of the module of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] Embodiment 1. Refer to Figure 1 , a material management method, including: When a supplier vehicle loaded with materials arrives at the construction site, two intelligent devices are configured at the construction site, respectively denoted as the first device and the second device; Automatically read the vehicle number using the license plate recognition technology loaded on the first device; Use the AI automatic recognition function loaded on the first device to identify the material type; Use the second device to weigh the materials of the supplier vehicle to obtain the material weight; Form the incoming data by combining the vehicle number, material type, and material weight; Scan the paper documents carried by the vehicle using a terminal device, and compare whether the scanned data is consistent with the incoming data; if the scanned data is consistent with the incoming data, save the scanned data and the incoming data using a cloud database, and instruct the supplier vehicle to enter the construction site. By adopting an intelligent material management method, the efficiency of material management can be greatly improved. Traditional material management methods often rely on manual operations, such as manually recording the types, weights, arrival times of materials, etc. This is not only time-consuming but also prone to errors. By adding license plate recognition technology and AI automatic material type recognition to intelligent device systems, the numbers of supplier vehicles can be automatically read, and materials can be automatically identified. The incoming data of materials can be directly transmitted to the cloud database when being recorded in real time without manual intervention, avoiding data omissions or errors that may be caused by manual entry. Through this automated process, the time for material data entry is reduced, work efficiency is improved, delays and mistakes in the traditional method are avoided, and the smooth and timely material management at the construction site is ensured.

[0029] During the process of the supplier vehicle entering the construction site, use an intelligent recognition camera to dynamically verify the material types, compare the material types with those in the incoming data, and record the comparison result as verification data. By using AI automatic recognition and intelligent recognition camera functions, the accuracy of material data can be effectively improved. In traditional material management, manual recognition and manual recording of material types and weights are often affected by human factors, such as recognition errors or oversights. The intelligent recognition technology can automatically confirm the material types under real-time monitoring and upload the relevant information to the system in real time, avoiding errors that may occur during the manual recognition process. In addition, by using blockchain technology to encrypt and store data, the security and immutability of the data can be ensured, thus guaranteeing the transparency and accuracy of material management. This intelligent material recognition and data storage method not only improves the accuracy of the data but also provides a strong guarantee for subsequent material traceability.

[0030] Collect the timestamp and geographical location of each supplier vehicle in real time and save them using a cloud database. Execute the blockchain encryption storage strategy and store the data in the cloud database using blockchain. Obtain the historical material consumption data stored in the blockchain, execute the material inventory prediction strategy to predict future material requirements; execute the inventory dynamic adjustment strategy to adjust the inventory purchase plan.

[0031] Execute the blockchain encryption storage strategy and store the data in the cloud database using blockchain, including: For any supplier vehicle: When the verification data shows that the types of materials verified dynamically using the intelligent recognition camera are consistent with the types of materials in the incoming data: Obtain the vehicle number V, material type M, material weight W, timestamp T, and geographical location L of the supplier vehicle in the cloud database, and form the material data D = {V, M, W, T, L}; Use the hash function H(·) to encrypt the material data and generate the hash value of the block storing the current material data; Record the hash value of the current block as C n , where n is the number of blocks in the blockchain; Obtain the characteristics for evaluating the importance of the material data, and form the feature set A = {a1, a2, …, a b}, where b is the number of features; Calculate the weight of the material data D α i is the weight of the feature; Record the hash value of the previous block as C n-1 ; Calculate the hash value C of the current block n = H(ω × D || C n-1 ), where || represents the concatenation operation.

[0032] By adopting blockchain encryption storage technology, the security and anti-tampering ability of data can be greatly enhanced. In the traditional material management system, during the data storage and transmission process, it is vulnerable to the risk of tampering caused by human factors or system vulnerabilities. The distributed ledger and encryption algorithm of blockchain technology ensure the immutability of data. Each transaction is packaged in a block and encrypted through the hash algorithm. Any modification can be quickly detected and traced. In this way, not only the integrity of the data is guaranteed, but also all operations related to materials can be effectively audited and verified. During the construction process, any improper operation or tampering behavior can be traced and monitored, thus improving the security and credibility of the entire supply chain.

[0033] Execute the blockchain encryption storage strategy, and store the data in the cloud database using blockchain, including: When calculating the hash value of the current block, verify the hash value of the previous block: where, is arbitrary; Anti-tampering verification: where, D' represent the existing and modified material data respectively, and n ≥ 1.

[0034] By introducing blockchain technology, the transparency and traceability of material management can be greatly enhanced. The immutability and transparency of the blockchain enable all relevant data on the entry and consumption of materials to be recorded and publicly stored in a distributed ledger, ensuring that any person can query and verify the usage of materials within the scope of their permissions. The data of each link in the process of material entry, weighing, scanning, transportation, etc. can be traced, thus ensuring the full traceability of material management. Once any problems or disputes are discovered, the relevant data can be quickly queried and verified. This not only improves the management transparency of the construction site but also provides a powerful means to prevent potential supply chain fraud or data tampering, providing a fair and trustworthy operating environment for all parties concerned.

[0035] Obtain the historical material consumption data stored in the blockchain, execute the material inventory prediction strategy, and predict future material requirements, including: Collect the historical material consumption data U t ={X t ,Y t ,Z t ,T t}, where X t represents the material demand at time t, T t is the date when time t is located, Y t represents the supply chain status at time t, and Z t represents the environmental characteristics at time t; Construct the feature matrix Use machine learning algorithms to predict future material requirements where f(·) represents the machine learning algorithm model, and k is the time interval after time t; Use the mean squared error to calculate the loss function: where δ is the error threshold, n is the number of samples of historical material consumption data, is the predicted material demand, and X i is the actual material demand.

[0036] Obtain the historical material consumption data stored in the blockchain, execute the material inventory prediction strategy, and predict future material requirements, including: Optimize the weights p t+k and the bias term q t+k ; Update where η represents the learning rate, is the gradient of the loss function; Update where η represents the learning rate, is the gradient of the loss function.

[0037] Implement the inventory dynamic adjustment strategy and adjust the inventory replenishment plan, including: The replenishment plan is divided into the first plan and the second plan; The first plan is to set the inventory threshold point. When the remaining materials in the inventory reach the inventory threshold point, replenishment is carried out. Specifically: Inventory threshold point Among them, τ, respectively represent the standard normal distribution value and the standard deviation of the predicted material demand; The second plan is to set additional inventory

[0038] Through the inventory optimization strategy based on historical material consumption data and prediction algorithms, accurate inventory management and dynamic adjustment can be achieved. By predicting future material requirements through machine learning algorithms, managers can adjust the inventory level in advance according to the prediction results, avoiding the occurrence of excessive or shortage of materials. By setting inventory thresholds and real-time monitoring of inventory status, when the inventory approaches the preset threshold, the system will automatically trigger a replenishment plan to ensure the timeliness and accuracy of material supply. This data-based inventory dynamic adjustment method not only improves the accuracy of inventory management, reduces inventory backlogs and capital occupancy, but also effectively reduces construction delays or cost increases caused by material shortages, thereby reducing the overall operating cost.

[0039] Example 2, refer to Figure 2 , a material management system, including: Vehicle identification module: Automatically read the vehicle number and identify the material type; Weighing and data collection module: Weigh the materials and collect relevant data; Data consistency verification module: Compare the consistency of the incoming data and the scanned data; Intelligent identification camera module: Dynamically verify the material type and compare it with the incoming data; Time and location collection module: Real-time collect timestamps and geographical locations; Cloud data storage module: Save scanned data, incoming data, material data, etc.; Blockchain encryption storage module: Encrypt and store the data in the blockchain to ensure data security and immutability; Historical data acquisition and prediction module: Acquire the stored historical material consumption data and perform inventory prediction; Inventory prediction and adjustment module: Perform inventory dynamic adjustment based on material demand prediction; Replenishment plan decision module: Adjust the replenishment plan according to the inventory prediction.

[0040] Example 3, a traceable data processing device, including: Data processing unit, blockchain storage module, query and analysis interface, monitoring and alarm module, audit log record.

[0041] Embodiment 4, an intelligent device, comprising: a weighing sensor, a platform, a signal conditioner, a controller, a display screen, a data interface module, and a power supply system.

[0042] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0043] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A material management method, characterized in that: include: When a supplier's vehicle loaded with materials arrives at the construction site, the construction site is configured with two intelligent devices, which are respectively recorded as the first device and the second device; Automatically read the vehicle number using the license plate recognition technology loaded on the first device; Use the AI ​​automatic recognition function installed on the first device to identify the type of material; Weigh the materials on the supplier's vehicle using a second device to obtain the weight of the materials; The vehicle number, material type and material weight are combined into the entry data; Use the terminal device to scan the paper documents carried by the vehicle to obtain the scanned data; Compare the scanning data and approach data to see if they are consistent; If the scanned data and the entry data are consistent, the scanned data and the entry data will be saved using the cloud database, and the supplier's vehicle will be instructed to enter the construction site; When the supplier's vehicle enters the construction site, the intelligent recognition camera is used to dynamically verify the material type, compare the material type with the material type in the on-site data, and record the comparison result as verification data; The timestamp and geographic location of each supplier’s vehicle are collected in real time and stored in a cloud database; Execute blockchain encryption storage strategy and use blockchain to store data in cloud database; Obtain historical material consumption data stored in the blockchain, execute material inventory forecasting strategies, and predict future material demand; Implement dynamic inventory adjustment strategies and adjust inventory purchase plans.

2. The material management method according to claim 1, characterized in that: The execution of the blockchain encryption storage strategy to store the data in the cloud database using the blockchain includes: For any Supplier Vehicle: When the verification data shows that the material type dynamically verified by the intelligent recognition camera is consistent with the material type in the on-site data: Obtain the vehicle number V, material type M, material weight W, timestamp T and geographic location L of the supplier's vehicle in the cloud database, and form material data D = {V, M, W, T, L}; Use the hash function H(·) to encrypt the material data and generate the hash value of the block that stores the current material data; The hash value of the current block is recorded as C n , n is the number of blocks in the blockchain; Get the set features for assessing the importance of material data and form a feature set A = {a1, a2, ..., a b }, where b is the number of features; Calculate the weight of material data D 1≤i≤b,α i is the weight of the feature; Let the hash value of the previous block be C n-1 ; Calculate the hash value C of the current block n =H(ω×D||C n-1 ), || represents the concatenation operation.

3. The material management method according to claim 2, characterized in that: The execution of the blockchain encryption storage strategy to store the data in the cloud database using the blockchain includes: When calculating the hash value of the current block, the hash value of the previous block is verified: in, for any; Tamper-proof verification: in, Respectively represent existing and modified material data, n≥1.

4. The material management method according to claim 1, characterized in that: The method of obtaining the historical material consumption data stored in the blockchain, executing the material inventory forecasting strategy, and forecasting future material demand includes: Collect historical material consumption data t ={X t ,Y t ,Z t ,T t }, where X t represents the material demand at time t, T t is the date of time t, Y t represents the supply chain status at time t, Z t represents the environmental characteristics at time t; Constructing the feature matrix Use machine learning algorithms to predict future material needs Where f(·) represents the machine learning algorithm model, k is the time interval after time t; The loss function is calculated using mean squared error: Among them, δ is the error threshold, n is the number of samples of historical material consumption data, is the predicted material demand, X i The actual material demand.

5. The material management method according to claim 4, characterized in that: The method of obtaining the historical material consumption data stored in the blockchain, executing the material inventory forecasting strategy, and forecasting future material demand includes: Optimize the weights p of the machine learning algorithm model t+k and the bias term q t+k ; renew Among them, η represents the learning rate, is the gradient of the loss function; renew Among them, η represents the learning rate, is the gradient of the loss function.

6. The material management method according to claim 4, characterized in that: The implementation of the dynamic inventory adjustment strategy and the adjustment of the inventory purchase plan include: The purchase plan is divided into a first plan and a second plan; The first solution is to set an inventory threshold point. When the remaining materials in the inventory reach the inventory threshold point, replenishment is carried out. Specifically: Inventory threshold point in, They represent the standard normal distribution value and the standard deviation of the predicted material demand respectively; The second option is to set up additional inventory 7. A material management system, characterized in that: include: Vehicle identification module: automatically reads vehicle number and identifies material type; Weighing and data collection module: weigh the materials and collect relevant data; Data consistency verification module: compare the consistency of approach data and scan data; Intelligent recognition camera module: dynamically verify material types and compare with incoming data; Time and location collection module: real-time collection of timestamps and geographic locations; Cloud data storage module: save scanning data, on-site data, material data, etc.; Blockchain encryption storage module: encrypts and stores data in the blockchain to ensure data security and non-tamperability; Historical data acquisition and forecasting module: acquires stored historical material consumption data and performs inventory forecasting; Inventory forecasting and adjustment module: Dynamically adjust inventory based on material demand forecast; Purchase plan decision module: adjust the purchase plan according to inventory forecast.

8. A traceable data processing device, characterized in that: include: Data processing unit, blockchain storage module, query and analysis interface, monitoring and alarm module, audit log record.

9. A smart device, characterized in that: include: Load cells, platforms, signal conditioners, controllers, displays, data interface modules and power supply systems.

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