Commodity logistics tracking method and system based on block chain

Abstract

The invention provides a commodity logistics tracking method and system based on a block chain, belongs to the field of computers, and solves the problem that the block chain cannot verify the authenticity of input data in a commodity traceability system. The method comprises the following steps: obtaining logistics transportation information of a cold chain commodity, wherein the logistics transportation information comprises a transportation time interval, a transportation path and a transportation vehicle associated with the cold chain commodity; querying commodity information of other cold-chain commodities matched with the logistics transportation information, wherein the commodity information comprises data of types, numbers and package sizes of the commodities; and when the total volume calculated based on the number of the commodities and the package size data is greater than the volume of the transport vehicle associated with the cold chain commodities, generating a logistics transportation data authenticity alarm and recording the logistics transportation data authenticity alarm to a block chain system.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a commodity logistics tracking method and system based on blockchain. Background Art

[0002] Blockchain has many advantages in product traceability, such as improving transparency, enhancing data immutability and reducing the risk of fraud. However, it also has some limitations. Blockchain can ensure that data cannot be changed once it is entered, but it cannot guarantee the authenticity of the input data itself. The product traceability system needs to rely on external devices (such as sensors or manual input) to upload data to the blockchain. If the original data is inaccurate or tampered with, the blockchain cannot verify or correct these errors. Summary of the invention

[0003] The embodiments of the present application provide a commodity logistics tracking method and system based on blockchain, which can solve the problem that blockchain cannot verify the authenticity of input data in the commodity traceability system.

[0004] A first aspect of an embodiment of the present application provides a commodity logistics tracking method based on blockchain, comprising:

[0005] Obtaining logistics and transportation information of cold chain products, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain products;

[0006] Querying commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data;

[0007] When the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transport vehicle associated with the cold chain goods, an authenticity alarm for the logistics and transportation data is generated and recorded in the blockchain system.

[0008] Optionally, it also includes:

[0009] In case of receiving a quality complaint message from a consignee regarding the cold chain product or the other cold chain products, the authenticity alarm record of the logistics transportation data is retrieved for the consignee.

[0010] Optionally, it also includes:

[0011] Obtain the first temperature of the cold chain products after they arrive at the delivery station;

[0012] Determine a second temperature for optimal taste of the cold chain product based on the product information of the cold chain product, where the second temperature is higher than the first temperature;

[0013] Calculating the ideal delivery time of the cold chain commodity according to the first temperature, the second temperature, the current ambient temperature and the type of the cold chain commodity, wherein the ideal delivery time is the time it takes for the cold chain commodity to approach the second temperature from the first temperature under the influence of the current ambient temperature;

[0014] The cold chain products are delivered based on the ideal delivery time.

[0015] Optionally, delivering the cold chain product based on the ideal delivery time includes:

[0016] Generate an ideal delivery route based on the ideal delivery time and delivery address of different cold chain products delivered in the same batch;

[0017] The cold chain products are delivered based on the ideal delivery path.

[0018] Optionally, it also includes:

[0019] Determine the second temperature for the best taste of different cold chain products based on the product information of the cold chain products;

[0020] The ideal placement position of the cold chain goods in the delivery vehicle is calculated based on the first temperature, the second temperature, the current ambient temperature and the type of the cold chain goods, wherein the cold chain goods in different placement positions are affected differently by the ambient temperature and the temperature of adjacent cold chain goods, so that after the ideal delivery time, it takes different cold chain goods under the influence of the current ambient temperature to approach the second temperature from the first temperature.

[0021] Optionally, the calculating the ideal placement position of the cold chain commodity in the delivery vehicle according to the first temperature, the second temperature, the current ambient temperature, and the type of the cold chain commodity includes:

[0022] The ideal placement position of the cold chain commodity in the delivery vehicle is calculated by a particle swarm optimization algorithm according to the first temperature, the second temperature, the current ambient temperature and the type of the cold chain commodity.

[0023] Optionally, also include:

[0024] Based on the determined ideal placement position, the distribution terminal displays a suggested placement order and the ideal placement position of the product storage space that matches the delivery vehicle.

[0025] The second aspect of the embodiment of the present application provides a commodity logistics tracking system based on blockchain, including:

[0026] An acquisition unit, used to acquire logistics and transportation information of cold chain commodities, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain commodities;

[0027] A query unit, used to query commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data;

[0028] An alarm unit is used to generate an alarm for the authenticity of logistics and transportation data and record it in the blockchain system when the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transportation vehicle associated with the cold chain goods.

[0029] A third aspect of an embodiment of the present application provides an electronic device, including a memory and a processor, wherein the processor is configured to implement the steps of the above-mentioned blockchain-based commodity logistics tracking method when executing a computer program stored in the memory.

[0030] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned blockchain-based commodity logistics tracking method.

[0031] In summary, the commodity logistics tracking method based on blockchain provided by the embodiment of the present application obtains the logistics and transportation information of cold chain commodities, the logistics and transportation information includes the transportation time interval, the transportation route and the transportation vehicle associated with the cold chain commodities; queries the commodity information of other cold chain commodities matching the logistics and transportation information, the commodity information includes the type, quantity and packaging size data of the commodities; when the total volume calculated based on the quantity and packaging size data of the commodities is greater than the volume of the transportation vehicle associated with the cold chain commodities, generates a logistics and transportation data authenticity alarm and records it to the blockchain system. Thus, by checking the rationality of the quantity, packaging size and vehicle volume of commodities, it is possible to effectively identify possible data tampering or inaccurate input problems. For example, if it is found that the total volume of commodities of a cold chain transportation vehicle exceeds its volume, it may mean that the input data is not true, which helps to find the problem in advance. Once a problem is detected, the alarm generated by the system will be recorded on the blockchain to ensure that the alarm can be traced back to the subsequent review and the problem can be confirmed. This transparent record provides additional trust guarantee to ensure that data tampering can be tracked. Through sensors and smart contracts, the system can achieve a fully automated verification process, reducing errors caused by manual intervention and ensuring data consistency. Each step of the operation is transparently recorded on the blockchain, providing tamper-proof verification evidence.

[0032] Correspondingly, the system, electronic device, and computer-readable storage medium provided by the embodiments of the present invention also have the above-mentioned technical effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1A flowchart of a possible blockchain-based commodity logistics tracking method provided in an embodiment of the present application;

[0034] Figure 2 A schematic structural block diagram of a possible blockchain-based commodity logistics tracking system provided in an embodiment of the present application;

[0035] Figure 3 A schematic diagram of the hardware structure of a possible blockchain-based commodity logistics tracking system provided in an embodiment of the present application;

[0036] Figure 4 A schematic structural block diagram of a possible electronic device provided in an embodiment of the present application;

[0037] Figure 5 A schematic structural block diagram of a possible computer-readable storage medium provided for an embodiment of the present application. DETAILED DESCRIPTION

[0038] The embodiments of the present application provide a commodity logistics tracking method and related equipment based on blockchain, which can solve the problem that blockchain cannot verify the authenticity of input data in the commodity traceability system.

[0039] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0040] See also Figure 1 , which is a flowchart of a commodity logistics tracking method based on blockchain provided in an embodiment of the present application, may specifically include:

[0041] S110-S130.

[0042] S110, obtaining the logistics and transportation information of the cold chain products, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain products.

[0043] For example, logistics and transportation information includes the transportation time range and transportation route of cold chain products, as well as basic information of the transportation vehicles associated with the products (such as vehicle volume, license plate number, etc.). For example, if a fresh food distribution company is transporting frozen seafood, the logistics information includes the start time, end time, transportation route and cold chain transportation vehicle information of the seafood transportation.

[0044] For example, during transportation, IoT devices can collect information such as the quantity, packaging size, and vehicle volume of cold chain products in real time. The data can be directly uploaded through sensors to reduce errors in manual input. The automated collection of sensors can ensure the accuracy of the data, and each collection will be immediately uploaded to the chain to ensure transparency.

[0045] S120, query the commodity information of other cold chain commodities that match the logistics and transportation information, and the commodity information includes the type, quantity and packaging size data of the commodity. Match according to the logistics information of commodities on the same cold chain transport vehicle, for example, frozen meat and frozen vegetables are also transported on the same vehicle. The types, packaging specifications and quantities of these commodities can be collected through a database or sensor and matched with the logistics information. Assume that frozen seafood shares a refrigerated truck with frozen meat and vegetables, and the quantity and packaging size of each type of commodity are recorded according to the system data (such as 0.5 cubic meters per box of seafood, 0.6 cubic meters per box of meat, and 0.4 cubic meters per box of vegetables).

[0046] Exemplary, product information: includes the type, quantity and packaging size data of cold chain products.

[0047] S130: When the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transport vehicle associated with the cold chain goods, an authenticity alarm for the logistics and transportation data is generated and recorded in the blockchain system.

[0048] For example, the total volume of all cold chain commodities loaded on the vehicle is calculated by the obtained commodity quantity and packaging size data. The calculated total volume of commodities is compared with the maximum volume of the transport vehicle to check whether the loaded cold chain commodities exceed the carrying capacity of the vehicle. Assuming that the maximum volume of the cold chain transport vehicle is 70 cubic meters, and the calculated total volume of commodities is 73 cubic meters, it exceeds the volume of the vehicle. At this time, the system will determine that there are abnormalities in these logistics data, which may be that the quantity of commodities has been tampered with, input errors, or there is overloading. In the case where the total volume of commodities is greater than the volume of the vehicle, an alarm for the authenticity of logistics transportation data is generated, indicating that there may be untrue logistics information. The alarm information can be "The cold chain transport vehicle is overloaded, the total volume of commodities exceeds the maximum volume of the vehicle, please verify the quantity of commodities and the packaging size", and is sent to relevant managers through the system to further verify the root cause of the problem. The alarm information is stored in the blockchain system to ensure that the alarm record that cannot be tampered with can provide a reference for future audits or disputes. This alarm record helps to trace and confirm whether the problem is caused by data input errors or tampering. For example, a record is generated on the blockchain, including detailed information such as the alarm time, vehicle number, commodity type, volume calculation data, etc. Due to the transparency of the blockchain, relevant parties can view and track these records to ensure timely resolution of the problem.

[0049] For example, blockchain smart contracts can automatically calculate and compare the volume of goods according to set rules. Once the total volume of goods exceeds the volume of the vehicle, the smart contract will automatically generate an alarm message and record the relevant data in the blockchain to ensure the timeliness and immutability of the alarm. The smart contract automatically processes data verification, reduces manual intervention, and ensures the transparency and credibility of each step.

[0050] For example, a standardized commodity information database can be created, containing the packaging size data of each cold chain commodity, for the logistics system to call. This can prevent size errors when entering data. The database can also be combined with blockchain to ensure that each packaging size is well documented. Standardized commodity information reduces size errors caused by human input, and by storing data on blockchain, the transparency and traceability of information are guaranteed.

[0051] In summary, the commodity logistics tracking method based on blockchain provided by the above embodiment of the present application obtains the logistics and transportation information of cold chain commodities, the logistics and transportation information includes the transportation time interval, the transportation route and the transportation vehicle associated with the cold chain commodities; queries the commodity information of other cold chain commodities matching the logistics and transportation information, the commodity information includes the type, quantity and packaging size data of the commodities; when the total volume calculated based on the quantity and packaging size data of the commodities is greater than the volume of the transportation vehicle associated with the cold chain commodities, generates a logistics and transportation data authenticity alarm and records it to the blockchain system. Thus, by checking the rationality of the quantity, packaging size and vehicle volume of the commodities, it is possible to effectively identify possible data tampering or inaccurate input problems. For example, if it is found that the total volume of commodities of a cold chain transportation vehicle exceeds its volume, it may mean that the input data is not true, which helps to find the problem in advance. Once a problem is detected, the alarm generated by the system will be recorded on the blockchain to ensure that the alarm can be traced back to the subsequent review and the problem can be confirmed. This transparent record provides additional trust guarantee to ensure that data tampering can be tracked. Through sensors and smart contracts, the system can achieve a fully automated verification process, reducing errors caused by manual intervention and ensuring data consistency. Each step of the operation is transparently recorded on the blockchain, providing tamper-proof verification evidence.

[0052] In some examples, this also includes:

[0053] In case of receiving a quality complaint message from a consignee regarding the cold chain product or the other cold chain products, the authenticity alarm record of the logistics transportation data is retrieved for the consignee.

[0054] For example, the receiving end can submit complaints about the quality of cold chain products through the system. The complaint information may include whether the product is in the best edible state, whether it is damaged or spoiled. After receiving the complaint message from the receiving end, the system will compare it with the logistics and transportation data previously stored in the blockchain to determine whether there are any abnormalities related to logistics and transportation (such as improper temperature, transportation delays, etc.). This process ensures that the system has a basis for tracing product problems.

[0055] Exemplarily, the system retrieves the logistics and transportation data related to the batch of cold chain products and the authenticity alarm records generated previously based on the received quality complaint message. When a quality complaint occurs, the system can retrieve all logistics information alarm records related to the batch of products. For example, if an alarm that the volume of the product exceeds the vehicle volume has been triggered before, this alarm record can provide clues for potential problems in the transportation of the product. This retrieval mechanism can help quickly locate whether the product has experienced problems that may affect the quality (such as overloading or other abnormalities) during transportation. The system further determines whether the problem originates from the logistics and transportation process by analyzing the correlation between the alarm information during transportation and the complaint content of the receiving end. For example, if the alarm record shows that the temperature during the transportation of the product exceeds the standard, or the sealing is reduced due to excessive loading of the product, these problems may be associated with the reduction of product quality. By combining the authenticity alarm of logistics data with the complaint content, the system can analyze whether the product quality problem is caused by improper operation during transportation. The alarm record provides tamper-proof evidence and can be used as a basis for handling complaints, compensation or taking corrective measures. Based on the analysis results, the system can provide feedback to the receiving end and provide operational solutions to supply chain managers. For example, if there is indeed an alarm, the responsible party can be determined based on the transportation record and corresponding compensation measures can be taken; if no abnormality is found, it can be judged that the problem may originate from other links (such as quality problems of warehousing or the goods themselves). Through transparent records on the blockchain, the receiving end and the supply chain party can clearly see the transportation process at each stage. If the alarm information is associated with a quality problem, the system will push the supply chain manager to take measures to improve the problem or compensate the receiving end. Therefore, by combining the quality complaint message of the receiving end with the logistics transportation alarm record, the system can automatically trace the problem after receiving the complaint and quickly locate the potential source of quality problems. This automated traceability mechanism reduces the workload of manual analysis and improves the efficiency of solving supply chain problems. Blockchain ensures the transparency and immutability of alarm records and transportation data. Whenever a quality problem occurs, the receiving end and the supply chain management party can fairly view the relevant data in the logistics process to ensure that the allocation of responsibilities is based on real and reliable data. When a product quality problem is discovered, the system can quickly provide immutable evidence (such as alarm records) to determine the responsible party, reducing disputes caused by opaque logistics transportation data. Alarm information can serve as strong evidence to trace quality problems, thus avoiding invalid complaints or improper allocation of responsibilities. By combining the complaint and alarm records at the receiving end, supply chain managers can continuously optimize the logistics management process to ensure that similar problems are avoided in the future. For example, if a certain type of alarm is often found to be associated with quality problems of a specific product, managers can optimize the transportation process, adjust the vehicle load, or upgrade the cold chain equipment in advance.

[0056] For example, after a catering company received a batch of cold chain seafood, it found that some of the seafood had deteriorated, so it submitted a quality complaint. After receiving the complaint, the system retrieved the transportation data and alarm records of the batch of cold chain seafood and found that the alarm that the total volume of the goods exceeded the vehicle volume had been triggered. It may be due to overloading that the cold chain equipment could not maintain a low temperature, resulting in a decline in the quality of the seafood. The system fed back this alarm information to the catering company and suggested that the supply chain management party make compensation.

[0057] In some examples, this also includes:

[0058] Obtain the first temperature of the cold chain products after they arrive at the delivery station;

[0059] Determine a second temperature for optimal taste of the cold chain product based on the product information of the cold chain product, where the second temperature is higher than the first temperature;

[0060] Calculating the ideal delivery time of the cold chain commodity according to the first temperature, the second temperature, the current ambient temperature and the type of the cold chain commodity, wherein the ideal delivery time is the time it takes for the cold chain commodity to approach the second temperature from the first temperature under the influence of the current ambient temperature;

[0061] The cold chain products are delivered based on the ideal delivery time.

[0062] It is understandable that goods are often delivered via mobile vehicles such as electric vehicles that do not have cold chain or insulation conditions, and the temperature of the goods is easily affected by the ambient temperature during the delivery process.

[0063] Exemplarily, when the cold chain commodity arrives at the distribution site, the system obtains the current temperature of the commodity through a sensor, which is called the "first temperature". This is the first temperature obtained by the commodity after leaving the cold chain environment. The system can obtain the temperature information of the cold chain commodity in real time through sensors or temperature monitoring equipment to ensure that the temperature record during distribution is accurate. This temperature data will serve as the basis for subsequent calculations. According to the information of the commodity (such as fresh food or refrigerated beverages), the system queries the database for the best eating or drinking temperature of the commodity, which is called the "second temperature" and is usually higher than the current first temperature. Different cold chain commodities have their own optimal taste temperature. For example, the optimal taste temperature of a certain ice cream is minus 5 degrees Celsius, and the optimal drinking temperature of a certain beverage is 10 degrees Celsius. By querying the database or pre-set standards, the system can automatically determine the second temperature. Based on the first temperature (current temperature) of the commodity, the second temperature (optimal taste temperature), the current ambient temperature, and the type of commodity, the system calculates the time required for the commodity to gradually approach its optimal taste temperature from the current temperature (ideal delivery time). Through the difference between the first temperature and the optimal taste temperature of the commodity, combined with the influence of the ambient temperature, the system can calculate the ideal delivery time required for the commodity. This time will ensure that the temperature of the goods is closest to the optimal eating temperature when they reach the customer. Based on the calculated ideal delivery time, the system arranges the delivery order and route of cold chain goods. The system will ensure that the temperature of the goods can gradually approach its optimal taste temperature during the delivery process through scheduling optimization. Based on the calculated ideal delivery time, the system can dynamically adjust the delivery order, giving priority to goods with temperatures close to the target temperature, ensuring that the temperature of the goods meets the optimal taste requirements when they are delivered. This method combines the factors of temperature and time to optimize the accuracy of delivery.

[0064] It is understandable that by considering the actual temperature change process of the goods, the temperature of the goods is ensured to be closer to the optimal taste temperature when they reach the hands of the customers, thereby improving the user experience. Through delivery scheduling based on temperature changes, the system can ensure that the temperature changes of the goods during transportation are more natural, so that they reach the optimal temperature when delivered, avoiding temperature deviations caused by early or late delivery. By calculating the ideal delivery time, the system can dynamically adjust the delivery route, giving priority to goods with faster temperature changes or arranging in advance goods that require longer time to adjust the temperature. Dynamic adjustment of delivery routes can maximize logistics efficiency, reduce unnecessary use of cold chain equipment, thereby reducing energy consumption, and ensure that goods are delivered at the most appropriate temperature. By ensuring that the goods reach the ideal temperature during delivery, the user experience is enhanced and the quality and taste of the goods are guaranteed to the greatest extent.

[0065] Assume that when a batch of refrigerated beverages arrive at a distribution station, the first temperature is 5°C, the optimal drinking temperature is 10°C, and the current ambient temperature is 25°C. Based on these parameters, the system calculates that the ideal delivery time required for the beverage to gradually warm up from 5°C to 10°C in the current environment is 2 hours. The system arranges delivery based on this time to ensure that the beverage is close to 10°C when it reaches the customer, providing the best drinking experience.

[0066] Some frozen foods are stored in a frozen environment at -18°C, and the optimal eating temperature is -5°C. The temperature of the goods when they arrive at the delivery station is -10°C, and the current ambient temperature is 20°C. The system calculates that it takes about 3 hours to deliver frozen foods from -10°C to -5°C. Therefore, the system arranges the delivery sequence and route of the goods to ensure that the frozen foods are at the optimal eating temperature when they are delivered.

[0067] In some examples, delivering the cold chain product based on the ideal delivery time includes:

[0068] Generate an ideal delivery route based on the ideal delivery time and delivery address of different cold chain products delivered in the same batch;

[0069] The cold chain products are delivered based on the ideal delivery path.

[0070] For example, each item will be given an ideal delivery time based on the aforementioned temperature calculation process, which represents the time required for the item to approach the optimal taste temperature from the initial temperature at the current ambient temperature. For example, different types of frozen or refrigerated items have different rates of temperature change, so the ideal delivery time will also be different. The delivery address of each item provides the geographical location of the delivery. These addresses are combined with the ideal delivery time to determine the order and path of delivery. Using the ideal delivery time and the delivery address as input, the path planning algorithm is used to generate the best delivery path. These algorithms can balance the length of the delivery path, the ideal delivery time of each item, and the distance between the final delivery addresses. The ideal path generation process takes into account the ideal delivery time of each item, so the delivery route is not only based on the shortest distance planning, but also combines the time requirements of each item to dynamically adjust the path order. For example, first deliver those items with shorter ideal delivery times to ensure that they arrive within the ideal time, or give priority to those items that require a long time to heat up, giving them more time to adjust the temperature. After determining the ideal delivery path, the system will arrange the delivery of cold chain products according to the generated route. Path planning not only optimizes the temperature control of goods, but also ensures the efficiency of the delivery process, minimizing the driving time and mileage of delivery vehicles. During the delivery process, the delivery vehicles will deliver different goods in sequence according to the generated path, ensuring that each item is delivered according to its ideal delivery time. The optimization of vehicle paths can also reduce the operating time of the cold chain system and save energy.

[0071] Take a cold chain delivery task containing three kinds of fresh food as an example: refrigerated beverages (optimal drinking temperature 10°C, current temperature 5°C, ideal delivery time 2 hours); frozen seafood (optimal eating temperature -5°C, current temperature -10°C, ideal delivery time 3 hours); refrigerated vegetables (optimal storage temperature 4°C, current temperature 0°C, ideal delivery time 1.5 hours).

[0072] The delivery addresses of each product are as follows: Beverages: Customer A (2 kilometers from the warehouse); Seafood: Customer B (5 kilometers from the warehouse); Vegetables: Customer C (3 kilometers from the warehouse).

[0073] By calculating the ideal delivery time, the system found that refrigerated vegetables have the shortest ideal delivery time and should be delivered first, followed by refrigerated beverages and finally frozen seafood. Based on the balance between address and time, the system generated a delivery route from the warehouse to customer C, then to customer A, and finally to customer B, ensuring that each product arrives at the optimal time.

[0074] It is understandable that by combining the ideal delivery time and delivery address of different cold chain products, the path generated by the system takes into account not only the geographical distance, but also the temperature requirements of the products, ensuring that the products are delivered at the best time and maintaining their best quality. Unlike traditional shortest path delivery, this method can optimize the delivery time of each product and avoid the temperature of the products deviating from the optimal taste temperature when they arrive, thereby improving the user experience. Since the path planning algorithm also takes into account the optimization goal of the shortest distance, the system can ensure the maximum efficiency of the delivery path and reduce the driving time and mileage of the vehicle while meeting the temperature requirements of the products. By reducing the running time of the vehicle and optimizing the delivery path, it helps to reduce logistics costs and energy consumption of cold chain equipment while ensuring the quality of the products. When there are multiple cold chain products in the same batch, the system can dynamically adjust the delivery order according to the ideal delivery time of each product, first delivering those products that require shorter delivery time, and delaying the delivery of those products with longer ideal time. This flexible delivery scheduling method ensures that products with higher temperature sensitivity are delivered first, reducing the quality loss caused by rapid temperature changes of products during transportation. Through this delivery method that combines temperature and time, customers can experience a temperature that is more in line with their expectations when they receive cold chain products, such as the optimal drinking temperature of cold drinks or the optimal storage temperature of frozen foods, which significantly improves customer satisfaction with cold chain logistics services. By optimizing the delivery time and route of goods, the temperature of the goods received by customers is closer to their optimal use temperature, improving the overall quality of logistics services.

[0075] In some examples, this also includes:

[0076] Determine the second temperature for the best taste of different cold chain products based on the product information of the cold chain products;

[0077] The ideal placement position of the cold chain goods in the delivery vehicle is calculated based on the first temperature, the second temperature, the current ambient temperature and the type of the cold chain goods, wherein the cold chain goods in different placement positions are affected differently by the ambient temperature and the temperature of adjacent cold chain goods, so that after the ideal delivery time, it takes different cold chain goods under the influence of the current ambient temperature to approach the second temperature from the first temperature.

[0078] Exemplarily, according to the types of different commodities and their temperature requirements, the system obtains the optimal taste temperature (second temperature) of cold chain commodities from the database. For example, the optimal consumption temperature of frozen foods is usually lower than that of refrigerated beverages, while the storage temperature of refrigerated vegetables may be different. Different cold chain commodities have their own optimal storage or consumption temperatures. For example, the optimal consumption temperature of ice cream is -10°C, while the optimal drinking temperature of a certain fruit juice beverage is 5°C. By querying the types of commodities and their optimal taste temperatures, the system can determine the second temperature and provide data support for subsequent temperature control and placement optimization. The current temperature of each commodity when it arrives at the delivery vehicle is called the "first temperature", and the system obtains the current external ambient temperature (the temperature outside the vehicle). These temperature parameters will serve as the basis for calculating the placement of commodities. Based on the first temperature, second temperature, current ambient temperature and type of commodities, the system calculates the ideal placement of commodities in the vehicle. Different placement positions (such as the front, rear, upper and lower positions of the compartment) will be affected differently by the external ambient temperature and the temperature of adjacent commodities. The system needs to calculate a reasonable placement position based on these influences so that the temperature of the commodity can gradually approach its optimal temperature during the delivery process.

[0079] Exemplarily, the factors considered in the calculation may include: the degree of contact between the goods and the external environment, such as certain locations of the vehicle (such as near the door, roof) may be more affected by the ambient temperature, while the goods located inside the compartment are less affected by temperature changes. The influence of adjacent goods, such as some frozen goods (such as ice cream) may affect the temperature of nearby refrigerated goods (such as beverages), so the temperature transfer between adjacent goods also needs to be taken into consideration. Based on the temperature requirements of different goods and the influence of external temperature, the system can reasonably allocate the placement of goods in the compartment. For example, frozen goods with high temperatures and need to be kept low can be placed at the bottom of the vehicle or far away from the door, while relatively temperature-insensitive goods can be placed near the door for priority delivery. Based on the temperature distribution in the vehicle and the placement of the goods, the system can calculate the speed of temperature change of the goods during the delivery process to ensure that the temperature of the goods gradually approaches its optimal taste temperature within the ideal delivery time. Through reasonable placement of goods, the system can optimize the temperature distribution in the compartment so that the goods can naturally heat up or cool down during the entire delivery process, and finally approach their optimal taste temperature when they are delivered to customers. This temperature change not only relies on cold chain equipment, but also utilizes the temperature environment inside the vehicle to achieve precise control.

[0080] Assume that a cold chain vehicle is transporting the following commodities: frozen seafood (current temperature -18°C, optimal eating temperature -5°C); refrigerated milk (current temperature 2°C, optimal drinking temperature 4°C); frozen ice cream (current temperature -20°C, optimal eating temperature -10°C); refrigerated vegetables (current temperature 1°C, optimal storage temperature 4°C). The system calculates the ideal placement based on the temperature requirements of these commodities: frozen seafood and ice cream need to be placed in a cooler area of ​​the vehicle, such as away from the door, to reduce the impact of the outside temperature. Refrigerated milk and vegetables can be placed close to the door because these commodities are not sensitive to temperature changes and need to be delivered first. With this placement method, the temperature of ice cream and seafood will be kept in a lower range, while the temperature of milk and vegetables can be gradually increased to approach their optimal taste temperature. This method makes full use of the temperature difference between the inside and outside of the vehicle and the mutual temperature influence between commodities, optimizes the temperature control during the cold chain distribution process, improves logistics efficiency, and ultimately provides users with higher quality cold chain services.

[0081] It is understandable that by reasonably distributing cold chain goods in different positions in the carriage, the system can take advantage of the temperature difference between the inside and outside of the carriage and the temperature influence of adjacent goods to achieve dynamic control of the temperature of different goods. This method can reduce the dependence on cold chain equipment while ensuring that the goods gradually approach their optimal taste temperature during the distribution process. By optimizing the temperature environment in the carriage, the system can improve the accuracy of cold chain logistics, reduce cold chain energy consumption, and ensure that the goods maintain the best quality when delivered. The system not only considers the influence of ambient temperature, but also analyzes the temperature transfer between goods. For example, goods with higher temperatures may affect the temperature changes of neighboring goods, so this mutual interference can be reduced through reasonable placement. By reducing the temperature interference between goods, the system can more effectively control temperature changes and ensure that different goods can reach their ideal temperature state. According to the ideal placement position, the system can optimize the loading process so that the goods can naturally reach the target temperature during transportation. There is no need to rely too much on the refrigeration function of cold chain equipment, which effectively improves the energy efficiency and product quality in the logistics process. Through reasonable placement and temperature control, the system can optimize the space utilization of cold chain carriages and reduce transportation costs while ensuring that the temperature of the goods is appropriate. Through this delivery method with optimized temperature and placement, customers can experience a more expected temperature when they receive the goods. For example, cold drinks can be delivered at a suitable drinking temperature, and frozen foods can be kept at their low temperature, which significantly improves user satisfaction. The precision of temperature control not only improves the quality of goods, but also enhances customers' trust and satisfaction with cold chain logistics services.

[0082] In some examples, calculating the ideal placement position of the cold chain commodity in the delivery vehicle according to the first temperature, the second temperature, the current ambient temperature, and the type of the cold chain commodity includes:

[0083] The ideal placement position of the cold chain commodity in the delivery vehicle is calculated by a particle swarm optimization algorithm according to the first temperature, the second temperature, the current ambient temperature and the type of the cold chain commodity.

[0084] For example, assume that each particle represents a candidate solution (in the cold chain scenario, a particle can represent the placement of the product in the vehicle). The particle iteratively searches for the optimal solution in the solution space by updating the speed and position. The update of the particle's position and speed is jointly affected by the current particle's position, the particle's individual optimal solution, and the global optimal solution. By continuously updating the particle's position, it gradually approaches the global optimal solution (an ideal placement solution that allows the product to reach the optimal temperature during distribution). In the cold chain scenario, the particle represents the placement of the cold chain product in the distribution vehicle. Assume that the compartment can be divided into multiple different temperature-affected areas (such as near the door, near the middle of the compartment, the upper and lower floors, etc.), and the temperature of each area is affected differently by the external ambient temperature and the temperature of the adjacent products. The particle can be represented as a position vector, and each dimension corresponds to the placement of a cold chain product. Assuming that the compartment of the distribution vehicle is divided into n areas for placement, each dimension of the particle can represent an area number. Position vector x i =(x i1 ,x i2 ,…,x in ), where x ij Indicates that the placement of the i-th particle (cold chain product) is in area j. The particle speed of particle swarm optimization can be redefined as the step size or change amplitude of adjusting the product placement plan. Its significance is no longer to control the movement of the physical position of the product, but to guide the algorithm on how to search for a better product placement plan in the solution space, indicating the degree to which the current product placement plan is close to a better solution. The speed vector v i =(v i1 ,v i2 ,…,v in ), where v ij Represents the velocity of the i-th particle in the j-th dimension (region number).

[0085] The goal of the particle swarm optimization algorithm is to find an optimal placement plan so that the temperature of each cold chain product is close to the optimal taste temperature during the distribution process. To this end, a fitness function needs to be defined to measure the quality of a placement plan. The fitness function can be designed based on the following parameters: First temperature T1: the current temperature of the product. Second temperature T2: the optimal taste temperature of the product. Current ambient temperature Te : The ambient temperature outside the vehicle. The temperature of adjacent products affects T adj : Heat transfer between adjacent items. The goal of the fitness function is to minimize the following two factors: temperature deviation, which measures the difference between the final temperature of an item and its optimal temperature; temperature change rate: based on the location of the item in the vehicle, the temperature change rate of the current item is estimated. This change rate is determined by the external ambient temperature and the temperature of the adjacent items. The fitness function F(x) can be expressed as:

[0086]

[0087] Where f is a function that represents the relationship between the temperature change rate at different locations in the vehicle and the external ambient temperature and the temperature of the adjacent goods. α and β are weight parameters used to adjust the influence of temperature deviation and temperature change rate in the optimization process. i1 and T i2 are the first temperature and the second temperature of the i-th product respectively.

[0088] The speed and position of each particle will be updated according to the individual optimal solution and the global optimal solution. For the jth dimension of the ith particle, the update formula for position and speed is as follows: ;x ij (t+1)=x ij (t)+v ij (t+1), where ω is the inertia weight, which is used to control the change of particle speed. c1 and c2 are learning factors, which control the speed at which particles approach the individual optimal solution and the global optimal solution. r1 and r2 are random numbers, which enhance the randomness of the algorithm. ij is the individual optimal solution of particle i in the jth dimension. j It is the global optimal solution.

[0089] Specifically, the above method may include: randomly generating a number of particles (i.e., placement plans for cold chain products), each particle representing the placement position of a group of products; calculating the fitness value of each particle according to the fitness function to evaluate the pros and cons of the placement plan; adjusting the placement position of each product according to the speed and position update formula of particle swarm optimization; repeatedly executing speed update, position update and fitness calculation until a preset number of iterations is reached or the fitness converges; finding the optimal product placement plan so that the temperature of each product is close to its optimal taste temperature during the distribution process.

[0090] The above describes the commodity logistics tracking method based on blockchain in the embodiment of the present application. The following describes the commodity logistics tracking system based on blockchain in the embodiment of the present application.

[0091] See also Figure 2In the embodiments of the present application, an embodiment of a commodity logistics tracking system based on blockchain is described, which may include:

[0092] An acquisition unit 201 is used to acquire logistics and transportation information of cold chain commodities, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain commodities;

[0093] A query unit 202 is used to query commodity information of other cold chain commodities that match the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data;

[0094] The alarm unit 203 is used to generate a logistics transportation data authenticity alarm and record it to the blockchain system when the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transportation vehicle associated with the cold chain goods.

[0095] In summary, the commodity logistics tracking system based on blockchain provided by the above embodiment obtains the logistics and transportation information of cold chain commodities, the logistics and transportation information includes the transportation time interval, transportation route and the transportation vehicle associated with the cold chain commodities; queries the commodity information of other cold chain commodities matching the logistics and transportation information, the commodity information includes the type, quantity and packaging size data of the commodities; when the total volume calculated based on the quantity and packaging size data of the commodities is greater than the volume of the transportation vehicle associated with the cold chain commodities, generates a logistics and transportation data authenticity alarm and records it to the blockchain system. Thus, by checking the rationality of the quantity, packaging size and vehicle volume of commodities, it is possible to effectively identify possible data tampering or inaccurate input problems. For example, if it is found that the total volume of commodities of a cold chain transportation vehicle exceeds its volume, it may mean that the input data is not true, which helps to find the problem in advance. Once a problem is detected, the alarm generated by the system will be recorded on the blockchain to ensure that the alarm can be traced back to and the problem can be confirmed in subsequent reviews. This transparent record provides additional trust guarantee to ensure that data tampering can be tracked. Through sensors and smart contracts, the system can achieve a fully automated verification process, reducing errors caused by manual intervention and ensuring data consistency. Each step of the operation is transparently recorded on the blockchain, providing tamper-proof verification evidence.

[0096] In some examples, this also includes:

[0097] Based on the determined ideal placement position, the distribution terminal displays a suggested placement order and the ideal placement position of the product storage space that matches the delivery vehicle.

[0098] above Figure 2The commodity logistics tracking system based on blockchain in the embodiment of the present application is described from the perspective of modular functional entities. The commodity logistics tracking system based on blockchain in the embodiment of the present application is described in detail from the perspective of hardware processing. Please refer to Figure 3 , an embodiment of a blockchain-based commodity logistics tracking system 300 in an embodiment of the present application includes:

[0099] An input device 301, an output device 302, a processor 303 and a memory 304, wherein the number of the processor 303 can be one or more. Figure 3 In some embodiments of the present application, the input device 301, the output device 302, the processor 303 and the memory 304 may be connected via a bus or other means, wherein: Figure 3 The example of connecting through bus is taken in the following.

[0100] Wherein, by calling the operation instruction stored in the memory 304, the processor 303 is used to perform the following steps:

[0101] Obtaining logistics and transportation information of cold chain products, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain products;

[0102] Querying commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data;

[0103] When the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transport vehicle associated with the cold chain goods, an authenticity alarm for the logistics and transportation data is generated and recorded in the blockchain system.

[0104] By calling the operation instructions stored in the memory 304, the processor 303 is also used to execute Figure 1 Any method in the corresponding embodiment.

[0105] See also Figure 4 , Figure 4 A schematic diagram of an embodiment of an electronic device provided in an embodiment of the present application.

[0106] like Figure 4 As shown, an embodiment of the present application provides an electronic device, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0107] Obtaining logistics and transportation information of cold chain products, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain products;

[0108] Querying commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data;

[0109] When the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transport vehicle associated with the cold chain goods, an authenticity alarm for the logistics and transportation data is generated and recorded in the blockchain system.

[0110] In the specific implementation process, when the processor 420 executes the computer program 411, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0111] Since the electronic device introduced in this embodiment is a device used to implement a blockchain-based commodity logistics tracking system in the embodiment of the present application, based on the method introduced in the embodiment of the present application, technical personnel in this field can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0112] See also Figure 5 , Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present application.

[0113] like Figure 5 As shown, this embodiment provides a computer-readable storage medium 500, on which a computer program 511 is stored. When the computer program 511 is executed by a processor, the following steps are implemented:

[0114] Obtaining logistics and transportation information of cold chain products, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain products;

[0115] Querying commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data;

[0116] When the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transport vehicle associated with the cold chain goods, an authenticity alarm for the logistics and transportation data is generated and recorded in the blockchain system.

[0117] By calling the operation instructions stored in the memory 304, the processor 303 is also used to execute Figure 1 Any method in the corresponding embodiment.

[0118] See also Figure 4 , Figure 4 A schematic diagram of an embodiment of an electronic device provided in an embodiment of the present application.

[0119] like Figure 4 As shown, an embodiment of the present application provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0120] Obtaining logistics and transportation information of cold chain products, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain products;

[0121] Querying commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data;

[0122] When the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transport vehicle associated with the cold chain goods, an authenticity alarm for the logistics and transportation data is generated and recorded in the blockchain system.

[0123] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0124] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0125] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0128] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0129] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A commodity logistics tracking method based on blockchain, characterized in that: include: Obtaining logistics and transportation information of cold chain products, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain products; Querying commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data; When the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transport vehicle associated with the cold chain goods, an authenticity alarm for the logistics and transportation data is generated and recorded in the blockchain system.

2. The method according to claim 1, characterized in that Also includes: In case of receiving a quality complaint message from a consignee regarding the cold chain product or the other cold chain products, the authenticity alarm record of the logistics transportation data is retrieved for the consignee.

3. The method according to claim 1, characterized in that Also includes: Obtain the first temperature of the cold chain products after they arrive at the delivery station; Determine a second temperature for optimal taste of the cold chain product based on the product information of the cold chain product, where the second temperature is higher than the first temperature; Calculating the ideal delivery time of the cold chain commodity according to the first temperature, the second temperature, the current ambient temperature and the type of the cold chain commodity, wherein the ideal delivery time is the time it takes for the cold chain commodity to approach the second temperature from the first temperature under the influence of the current ambient temperature; The cold chain products are delivered based on the ideal delivery time.

4. The method according to claim 3, characterized in that The delivering of the cold chain product based on the ideal delivery time includes: Generate an ideal delivery route based on the ideal delivery time and delivery address of different cold chain products delivered in the same batch; The cold chain products are delivered based on the ideal delivery path.

5. The method according to claim 3, characterized in that: Also includes: Determine the second temperature for the best taste of different cold chain products based on the product information of the cold chain products; The ideal placement position of the cold chain goods in the delivery vehicle is calculated based on the first temperature, the second temperature, the current ambient temperature and the type of the cold chain goods, wherein the cold chain goods in different placement positions are affected differently by the ambient temperature and the temperature of adjacent cold chain goods, so that after the ideal delivery time, it takes different cold chain goods under the influence of the current ambient temperature to approach the second temperature from the first temperature.

6. The method according to claim 5, characterized in that The calculating the ideal placement position of the cold chain commodity in the delivery vehicle according to the first temperature, the second temperature, the current ambient temperature and the type of the cold chain commodity includes: The ideal placement position of the cold chain commodity in the delivery vehicle is calculated by a particle swarm optimization algorithm according to the first temperature, the second temperature, the current ambient temperature and the type of the cold chain commodity.

7. The method according to claim 6, characterized in that Also includes: Based on the determined ideal placement position, the distribution terminal displays a suggested placement order and the ideal placement position of the product storage space that matches the delivery vehicle.

8. A commodity logistics tracking system based on blockchain, characterized in that: The system comprises: An acquisition unit, used to acquire logistics and transportation information of cold chain commodities, wherein the logistics and transportation information includes a transportation time interval, a transportation route, and a transportation vehicle associated with the cold chain commodities; A query unit, used to query commodity information of other cold chain commodities matching the logistics and transportation information, wherein the commodity information includes commodity type, quantity and packaging size data; An alarm unit is used to generate an alarm for the authenticity of logistics and transportation data and record it in the blockchain system when the total volume calculated based on the quantity and packaging size data of the goods is greater than the volume of the transportation vehicle associated with the cold chain goods.

9. An electronic device, characterized in that: The electronic device includes at least one processor and at least one memory connected to the processor, wherein the processor is used to call program instructions in the memory to execute the blockchain-based commodity logistics tracking method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the blockchain-based commodity logistics tracking method according to any one of claims 1 to 7.

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