Intelligent identity tracking and aligning off-island digital goods picking platform

Abstract

The invention provides an off-island digital goods picking platform with intelligent identity tracking and alignment, and relates to the technical field of logistics management tracking, a block chain technology is utilized to generate an identity identifier for a user, the identity identifier is bound with order information, and the identity identifier is encrypted and uploaded to an identity tracking block chain for storage through a consensus mechanism. A delivery identification system is adopted to read user identity identification information, an identity tracking block chain is called to be matched and aligned with the identification information, identity verification updating and order association aggregation are carried out, multiple pieces of user association order information are obtained, and meanwhile delivery time and delivery positions of users are obtained to carry out delivery strategy analysis; according to the method and the device, the goods picking coordination strategy parameters are determined, and goods picking management is carried out based on the parameters, so that the problems of lack of real-time monitoring and dynamic scheduling capabilities, low goods picking efficiency and insufficient integration of identity verification and order information in the goods picking process are solved, and the effects of improving the goods picking efficiency, safety and user satisfaction and improving the service quality are achieved.

Description

Technical Field

[0001] The present invention relates to the field of logistics management and tracking technology, and in particular to an off-island digital pickup platform with intelligent identity tracking and alignment. Background Art

[0002] Off-island pickup means that after passengers purchase goods at duty-free shops, the warehouse will pack them, collect the packages, sort them, and transport them to the designated off-island port pickup point. Passengers will swipe their ID cards to find the packages and finally sign to pick up the goods. The traditional off-island pickup process usually involves multiple steps, including order processing, identity verification, product packaging, logistics transfer, and final user pickup. Each link may face problems such as information asynchrony, data security issues, logistics delays, and identity verification errors. For example, the existing pickup system often relies on manual operations or simple electronic data processing, lacks efficient data synchronization mechanisms and security guarantees, resulting in poor user experience and low pickup efficiency. In addition, the current identity verification system fails to effectively integrate information with orders, resulting in inefficient or incorrect identification links for goods with the same identity, further increasing security risks and pickup efficiency. In addition, the opacity of the logistics system often leads to users' uncertainty about the time and place of pickup, affecting overall service satisfaction.

[0003] In summary, the existing off-island pickup process often faces technical problems such as lack of real-time monitoring and dynamic scheduling capabilities, low pickup efficiency, insufficient integration of identity authentication and order information, and opaque logistics information. Summary of the invention

[0004] This application provides an off-island digital pickup platform with intelligent identity tracking and alignment, which is used to solve the technical problems faced in the existing off-island pickup process, such as lack of real-time monitoring and dynamic scheduling capabilities, low pickup efficiency, insufficient integration of identity authentication and order information, and opaque logistics information.

[0005] This application provides an off-island digital pickup platform with intelligent identity tracking and alignment, the platform includes:

[0006] An order information acquisition module is used to obtain the order information of the target user through the order management system, and the order information includes product information, order information, user identity information and off-island pickup information; an identity binding module is used to generate a target identity identifier for the target user using blockchain technology, and bind the order information and the target identity identifier, and encrypt and upload the order information and the target identity identifier to the identity tracking blockchain for storage through a consensus mechanism; an identity recognition module is used to read and obtain the user identity recognition information using the pickup recognition system, and at the same time call the identity tracking blockchain to match and align with the user identity recognition information to obtain the target identity identifier; an association aggregation module is used to perform identity authentication update and order association aggregation with the order management system based on the target identity identifier, obtain multiple user-associated order information, and at the same time, the identity tracking blockchain obtains the pickup time and pickup location of the target user; a pickup management module is used to perform a pickup strategy analysis on the multiple user-associated order information, the pickup time and pickup location, determine the pickup coordination strategy parameters, and perform off-island pickup management on the target user's order information based on the pickup coordination strategy parameters.

[0007] The intelligent identity tracking and alignment off-island digital pickup platform proposed in this application is intended to obtain the order information of the target user through the order management system, the order information including product information, order information, user identity information and off-island pickup information; use blockchain technology to generate a target identity identifier for the target user, and bind the order information and the target identity identifier, and encrypt and upload the order information and the target identity identifier to the identity tracking blockchain for storage through a consensus mechanism; use the pickup identification system to read and obtain the user identity identification information, and call the identity tracking blockchain to match and align with the user identity identification information to obtain the target identity identifier; based on the target identity identifier, the identity authentication is updated and the order association is aggregated with the order management system to obtain multiple user-associated order information, and the identity tracking area The blockchain obtains the pick-up time and pick-up location of the target user; performs a pick-up strategy analysis on the order information associated with the multiple users, the pick-up time and the pick-up location, determines the pick-up coordination strategy parameters, and manages the off-island pick-up for the target user's order information based on the pick-up coordination strategy parameters, thereby solving the technical problems faced in the existing off-island pick-up process, such as the lack of real-time monitoring and dynamic scheduling capabilities, low pick-up efficiency, insufficient integration of identity authentication and order information, and opaque logistics information. By applying blockchain technology, data security is improved, identity and order information is efficiently integrated to improve matching verification efficiency, and intelligent logistics is introduced to optimize the cargo scheduling process. Combined with real-time track tracking and dynamic adjustment of transportation routes, the adaptability and response speed of the logistics process are ensured, achieving the technical effect of improving the efficiency, safety and user satisfaction of the pick-up process and significantly improving service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A schematic diagram of the structure of the off-island digital pickup platform with intelligent identity tracking and alignment provided in an embodiment of the present application.

[0009] Figure 2 A schematic diagram of the process of information encryption and storage in the intelligent identity tracking and aligned off-island digital pickup platform provided in an embodiment of the present application.

[0010] Explanation of the reference numerals: order information acquisition module 11, identity binding module 12, identity recognition module 13, association aggregation module 14, and delivery management module 15. DETAILED DESCRIPTION

[0011] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0012] The intelligent identity tracking and alignment of the offshore digital pickup platform proposed in this application is conceived to convert the traditional physical pickup process into a more efficient and transparent digital operation process. In this process, after the user places an order to purchase goods through the electronic platform at the duty-free shop, all order information will be encrypted and stored on the blockchain. After the goods are packaged from the warehouse, they are sent to the designated offshore pickup point through the precise logistics system arrangement. After arriving at the pickup point, the user can quickly confirm his identity and pick up the corresponding goods through identity verification. The whole process not only optimizes the efficiency of logistics distribution, but also enhances the user's confidence and satisfaction with the pickup process through real-time data updates and order tracking. At the same time, in this process, the user's identity is quickly and accurately identified, and efficiently aligned with the user's order information. The process uses digital means, blockchain technology and encryption algorithms to ensure the security and privacy of identity information. Further, once the user verifies his identity at the pickup point, he can quickly retrieve order-related information that matches his identity, reduce waiting time, and improve user experience. In addition, the application of this tracking and alignment technology can also effectively prevent identity fraud and order information errors, and ensure the legitimacy and security of transactions.

[0013] Embodiment, this application provides an off-island digital pickup platform with intelligent identity tracking and alignment, such as Figure 1 As shown, the platform includes:

[0014] The order information acquisition module 11 is used to acquire the order information of the target user through the order management system, and the order information includes product information, order information, user identity information and off-island pickup information.

[0015] Specifically, the order management system is used to obtain detailed order information of the target user. This order information not only covers basic product information, namely the type, specification and quantity of the products purchased by the user, but also includes order information, such as order generation time, payment status and transaction number. At the same time, the order information also includes user identity information and off-island pickup information. The former includes the user's name, ID number and contact information, and the latter records in detail the scheduled pickup port and estimated pickup time of the product. For example, when a user purchases a product through a digital platform at a duty-free shop, the order management system automatically captures and records all relevant details of the transaction. The system will generate a comprehensive order record containing the type of product (such as perfume, watch, etc.), specific model, purchase quantity, order timestamp, payment method and status, user authentication information, and designated pickup port and time. The automation and digitization of this process ensures the accuracy and real-time update of the data, which facilitates the subsequent processing procedures, such as identity authentication and logistics scheduling. In addition, by combining user identity information with order information, the platform can quickly confirm the user's identity and match his order record through the identity authentication system when the user arrives at the pickup point, thereby simplifying the pickup process and reducing waiting time. This series of information integration and processing not only improves the efficiency of picking up goods, but also enhances the security of the entire picking up system, preventing the risks of identity fraud and incorrect order information.

[0016] The identity binding module 12 is used to generate a target identity identifier for the target user using blockchain technology, and bind the order information and the target identity identifier, and encrypt and upload the order information and the target identity identifier to the identity tracking blockchain for storage through a consensus mechanism.

[0017] Optionally, blockchain technology is applied to generate and store the target user's identity identifier and its related order information to improve the data security and traceability of the entire off-island pickup platform. First, when the target user completes the order generation in the order management system, a unique target identity identifier is generated for the user using blockchain technology. The identifier is a cryptographically generated hash value that not only uniquely represents the user's identity, but also effectively protects the user's privacy. Subsequently, the product details, payment information, user identity information, and scheduled pickup details in the order information are bound to the target identity identifier. This step is implemented through the blockchain technology of smart contracts, and the smart contract automatically executes the data binding program to ensure the consistency and integrity of the information. Next, the bound order information and target identity identifier are encrypted through the consensus mechanism of the blockchain. Among them, the consensus mechanism is the core part of the blockchain technology. It verifies and records information through protocols between multiple nodes in the network to ensure that the data cannot be tampered with and is consistent. In this embodiment, the encrypted information of each order will be uploaded to the identity tracking blockchain for storage. This blockchain not only contains the current order information of the target user, but also stores the user's historical order information in chronological order, forming a complete and traceable data chain. For example, suppose a user purchases a batch of duty-free goods and chooses to pick up the goods at a specific offshore port. At this time, the order management system will generate relevant order information and bind it to the user's identity identifier. Through smart contracts, this information is automatically encrypted and uploaded to the identity tracking blockchain. After that, both the user himself and the authorized pickup manager can verify the authenticity of the order and the user's identity at any time by verifying the information stored on the blockchain, thereby ensuring the safety and efficiency of the pickup process. Through the above steps, the security of data processing is significantly improved, the protection of user information and order information is enhanced, and transparency and efficiency are also brought to the offshore pickup process.

[0018] The identity recognition module 13 is used to use the pickup identification system to read and obtain the user identity recognition information, and at the same time call the identity tracking blockchain to match and align with the user identity recognition information to obtain the target identity identifier.

[0019] Furthermore, the pickup identification system ensures the security and accuracy of the pickup process. This system obtains necessary identification information from users by adopting advanced identification technologies such as biometrics, scanning ID documents, etc. This information usually includes but is not limited to the user's facial features, fingerprints, ID photos and digital ID information, etc., which are used to clearly verify the user's identity. Once these user identification information is obtained, the pickup identification system automatically calls the data stored on the identity tracking blockchain. The identity tracking blockchain is a secure database built using blockchain technology, which records all users' order information and the target identity identifiers associated with them. These identifiers are unique encrypted hash values ​​created by the system when the user first generates an order. Then, the system uses a specific algorithm to match and align the identification information obtained from the user with the data stored in the blockchain. This process involves a complex data comparison and verification process to ensure that the user information provided is consistent with the information stored on the chain, so as to identify the correct target identity identifier. For example, if the user provides fingerprints and ID cards at the pickup point, the pickup identification system will compare this information with the corresponding data on the blockchain, and after confirming the consistency of the information, retrieve the target identity identifier that matches this information from the blockchain. In this way, the platform can ensure that each pickup is strictly authenticated, greatly increasing the security of the transaction. In addition, by utilizing the immutability of blockchain technology, once the identity is verified and confirmed, the relevant pickup information will also be updated and encrypted to ensure the timeliness and accuracy of the information. This identity recognition and data matching mechanism not only strengthens the security protection of the system, but also improves the user experience and operational efficiency, ensuring the smooth progress of the pickup process.

[0020] The association aggregation module 14 is used to perform identity authentication update and order association aggregation with the order management system based on the target identity identifier to obtain multiple user-associated order information, and at the same time, the identity tracking blockchain obtains the pick-up time and pick-up location of the target user.

[0021] For example, in order to optimize and simplify the operation of users picking up multiple orders at different pickup locations and improve the overall pickup efficiency, identity authentication updates and order association aggregation are performed with the order management system based on the target identity identifier. Specifically, when the user's identity is successfully verified by the pickup identification system, the system will use the target identity identifier previously retrieved from the identity tracking blockchain. This identifier is a unique encrypted hash value that is closely associated with the user's order history. Then the order management system is accessed, and the identity identifier is used as a key index to update the user's identity authentication status. During the update process, it is checked whether the user has the need to pick up multiple orders at different pickup locations, and then the user's multiple orders are automatically associated and aggregated, which means that for multiple orders of the same user, regardless of whether these orders specify the same pickup location, the system can aggregate the processing flow of these orders. Through this aggregation, users do not need to repeat identity authentication when picking up goods, and the system has ensured that the identity authentication status of all related orders is updated and consistent. For example, if a user has multiple orders for different goods in the same area, the system will integrate these order information, and the user only needs to authenticate once to complete the pickup of all goods. In addition, the system also uses the identity tracking blockchain to continue to obtain the user's specific pickup information, such as the scheduled pickup time and location. This information is used to further optimize logistics and pickup plans to ensure that each order is ready at the designated time and location, providing users with a smooth and seamless pickup experience. Through the above steps, not only the efficiency of the pickup process is improved, but also security and user convenience are enhanced. Through intelligent aggregation and automatic update of identity authentication, repeated steps are reduced, significantly improving operational efficiency and customer satisfaction.

[0022] The pickup management module 15 is used to perform a pickup strategy analysis on the order information associated with the multiple users, the pickup time and the pickup location, determine the pickup coordination strategy parameters, and perform off-island pickup management on the order information of the target user based on the pickup coordination strategy parameters.

[0023] Specifically, in order to further optimize the off-island pickup process and ensure efficient order processing, a comprehensive analysis of multiple users' associated order information, scheduled pickup time and location is conducted to develop accurate pickup coordination strategy parameters and manage the user's order pickup accordingly. This step makes the pickup process smoother, reduces waiting time, and improves user satisfaction. First, the system centrally processes all user-associated order information, which includes but is not limited to the type, quantity, user identity information, and other order details associated with it. The purpose of this stage of processing is to aggregate multiple orders of the same user to ensure that they can be processed at one time when picking up the goods, reducing the user's waiting time at the pickup point. Next, for each user's order set, the scheduled pickup time and location are analyzed. This analysis focuses on evaluating and coordinating the timeline and geographic location between orders to ensure that all orders can be completed smoothly at the scheduled time and location. For example, if a user has multiple orders distributed at different pickup points, the system will analyze the distance and traffic conditions of these locations, adjust the pickup time, and ensure that users can arrange their trips reasonably and pick up all goods smoothly. Based on the analysis of the pickup time and location, the system will determine the pickup coordination strategy parameters, which include but are not limited to the priority of logistics scheduling, the prediction of the density of people at the pickup point, and the operational efficiency of the pickup point. For example, the system may adjust the opening hours of the pickup window or give priority to certain high-value or high-sensitivity orders based on the predicted traffic flow at the pickup point. Finally, the order information of the target user is managed based on the pickup coordination strategy parameters determined above to ensure that each order can be picked up at the optimal time and location. This management process not only includes the scheduling of orders and the precise control of the pickup time, but also involves real-time communication with users, such as reminders before pickup and route suggestions, to ensure the maximum user experience. In this way, the efficiency and smoothness of off-island pickup are significantly improved, the waiting burden of users is reduced, and the user experience of the entire pickup process is optimized. In addition, the implementation of this strategy also improves the accuracy and predictability of logistics operations, making pickup management more efficient and orderly.

[0024] Furthermore, if Figure 2 As shown, the order information and the target identity identifier are encrypted and uploaded to the identity tracking blockchain for storage, and the identity binding module 12 is also used to:

[0025] According to the data standardization format, a data preprocessing step is constructed, and the order information and the target identity identifier are format preprocessed according to the data preprocessing step to obtain standard order information and a standard identity identifier.

[0026] An encryption requirement assessment is performed on the standard order information and the standard identity identifier to obtain data encryption assessment level information.

[0027] A data transmission encryption algorithm is configured according to the data encryption evaluation level information.

[0028] The order information and the target identity identifier are encrypted based on the data transmission encryption algorithm, and the encrypted order information and the target identity identifier are uploaded to the identity tracking blockchain for storage.

[0029] Optionally, to ensure the security and confidentiality of the order information and target identifiers, a rigorous data encryption and upload process is adopted, which covers a series of steps from data preprocessing to encrypted upload to the identity tracking blockchain to ensure that all transmitted information meets the predetermined security standards. First, a data preprocessing step is constructed according to the established data standardization format. In this stage, all order information and target identifiers are formatted to ensure that the data has a uniform format before encryption, which includes cleaning any outliers in the data, unifying the format of data fields, and verifying the integrity of the data. For example, the system checks whether the date and time format in the order information is consistent to ensure that all identifiers conform to the specified pre-encryption format. Next, an encryption requirement assessment is performed on the standardized order information and target identifiers. In this step, the required data encryption level is determined based on the sensitivity and security requirements of the data. The data encryption assessment level information is obtained through a series of security analyses that take into account potential system threats and data sensitivity. For example, data involving financial transactions or personal sensitive information will be classified as data requiring a higher level of encryption. Furthermore, based on the obtained data encryption assessment level information, the system then configures the corresponding data transmission encryption algorithm. The selection of these algorithms depends on the encryption level requirements. Generally, the higher the encryption level, the higher the complexity of the selected encryption algorithm to ensure the security of the data during transmission and storage. Finally, the configured encryption algorithm will be used to encrypt the order information and target identity identifier. The encrypted data is considered safe and can be uploaded to the identity tracking blockchain for storage. During the upload process, each data block will be verified through the consensus mechanism of the blockchain to ensure that the authenticity and consistency of the data are maintained, while also ensuring the irreversibility and tamper-proof nature of the encrypted data. Through the above steps, the security of the order information and identity identifier is effectively ensured, thereby providing strong data protection for the entire off-island pickup platform and meeting the needs of a high-security business environment.

[0030] Furthermore, in obtaining the data encryption evaluation level information, the identity binding module 12 is further used to:

[0031] Data encryption assessment dimensions are obtained, where the data encryption assessment dimensions include a system threat general dimension and a data sensitivity dimension.

[0032] A risk assessment is performed on the order management system according to the conventional dimension of the system threat to obtain a system threat risk assessment coefficient.

[0033] Based on the data sensitivity dimension, a multi-dimensional analysis is performed on the standard order information and the standard identity identifier to obtain a data sensitivity coefficient.

[0034] The system threat risk assessment coefficient and the data sensitivity coefficient are subjected to an integrated encryption requirement assessment to obtain the data encryption assessment level information.

[0035] Furthermore, to ensure the security of data during transmission and storage, a detailed data encryption assessment process is adopted. This process conducts in-depth analysis and assessment of data security to determine the most suitable encryption level. First, the data encryption assessment dimensions are collected, including the general dimension of system threats and the dimension of data sensitivity. Among them, the general dimension of system threats focuses on the possible impact of external and internal threats on system security, such as network attacks, data leakage risks, and system vulnerabilities; while the data sensitivity dimension evaluates the sensitivity of information from the perspective of data content, considering the possible risks of various data elements such as personal identification information, transaction amount, geographic location, etc. Next, the order management system is risk assessed according to the general dimension of system threats. In this step, quantitative and qualitative analysis methods, such as risk assessment models and historical data analysis, are used to calculate the system threat risk assessment coefficient, which reflects the degree of threat that data may be subject to in the current system environment. Subsequently, based on the data sensitivity dimension, the system conducts a multi-dimensional analysis of standard order information and standard identity identifiers. This analysis covers multiple aspects of the data to determine the data sensitivity coefficient. This coefficient evaluates the degree of impact that different data types may cause when they are leaked or misused, thereby helping to determine the protection measures that need to be taken. Finally, the system threat risk assessment coefficient and data sensitivity coefficient are integrated for encryption requirements assessment. In this process, these two coefficients are comprehensively considered to form a comprehensive data encryption assessment level information, which will directly determine the encryption technology and strategy used in data transmission and storage. For example, if the assessment results indicate high risk and high sensitivity, the system will choose to apply a higher level of encryption standards to ensure the highest security of the data. Through such an assessment process, various data security challenges can be accurately identified and responded to, providing a safe and reliable digital environment for all participants in the offshore pickup platform.

[0036] Furthermore, in determining the delivery coordination strategy parameters, the delivery management module 15 is further used to:

[0037] The pick-up time and the pick-up location are converted into a standardized format according to the data preprocessing step to obtain a standard pick-up time and a standard pick-up location.

[0038] Based on the multiple user-associated order information, the standard pickup time and the standard pickup location, a dynamic analysis of logistics division is performed to obtain pickup logistics scheduling strategy parameters.

[0039] According to the pickup logistics scheduling strategy parameters, a turnover logistics transport order is generated, and a transportation scheduling analysis is performed on the turnover logistics transport order to obtain the pickup transportation scheduling strategy parameters.

[0040] The pickup coordination strategy parameters are determined based on the pickup logistics scheduling strategy parameters and the pickup transportation scheduling strategy parameters.

[0041] Specifically, the overall pickup process is optimized by accurately managing the pickup time, location and logistics transportation arrangements. The pickup coordination strategy parameter determination process covers the standardization of pickup time and location to the generation and application of logistics scheduling strategy parameters, ensuring efficient and smooth pickup operations. The pickup time and location are converted into a standardized format according to the established data preprocessing steps. The purpose of this step is to ensure that all pickup time and location data follow a unified format standard for subsequent processing and analysis. For example, the pickup time is unified in the format of year, month, day, hour, minute and second, and the pickup location is clearly defined as a specific GPS coordinate or a predetermined standard location code. Next, based on the standardized pickup time and location and the order information associated with multiple users, the system performs a dynamic analysis of logistics division. At this stage, the system evaluates the time and geographic location relationship between different orders, and optimizes the allocation and scheduling of logistics resources through algorithms, which includes determining which orders can be processed together, which need to be operated independently, and how to arrange transportation routes and schedules to maximize efficiency. According to the above analysis results, the pick-up logistics scheduling strategy parameters are generated, and the turnover logistics transport order is formulated accordingly. Each transport order records the logistics arrangements including loading, route, time, etc. in detail, which are based on the previously determined logistics scheduling strategy. Then, these turnover logistics transport orders are further transported and scheduled to ensure that the transportation plan of each order is optimal, and the pick-up transportation scheduling strategy parameters are obtained from them. Finally, the final pick-up coordination strategy parameters are determined by combining the pick-up logistics scheduling strategy parameters and the pick-up transportation scheduling strategy parameters. These parameters comprehensively consider multiple factors such as logistics efficiency, cost, time arrangement and user satisfaction, ensuring that the user's order pick-up can be completed in the most efficient way at the best time and place. For example, if multiple orders can be picked up at the same place, the system may adjust the pick-up time to reduce congestion, or adjust the transportation route to avoid peak traffic. Through the above steps, not only the efficiency of the pick-up process is improved, but also the overall service quality and user pick-up experience are greatly improved by optimizing logistics and transportation arrangements.

[0042] Furthermore, the picking-up logistics scheduling strategy parameters are obtained, and the picking-up management module 15 is further used to:

[0043] A logistics warehousing database is obtained, and a matching search is performed in the logistics warehousing database based on the multiple user-related order information to obtain a set of information on deployable goods.

[0044] The cargo parcels in the deployable cargo information set are sorted using a time priority algorithm to obtain a logistics warehousing task queue.

[0045] Perform logistics time analysis and urgency assessment on the standard pickup time and the standard pickup location to obtain a pickup urgency coefficient.

[0046] The logistics warehousing task queue is dynamically inserted and adjusted based on the pickup urgency coefficient to obtain the pickup logistics scheduling strategy parameters.

[0047] Exemplarily, the process of formulating a logistics scheduling strategy is initiated by accessing a logistics warehousing database. The logistics warehousing database is a comprehensive information storage system that records the storage location, status, and related order information of all goods. The system matches and searches in this database based on the order information associated with multiple users, and identifies all the available goods information sets related to these orders. This step ensures that all subsequent operations are based on the latest and most accurate inventory data. Next, the time priority algorithm is used to sort the individual goods packages in the available goods information set. The time priority algorithm is an efficient sorting mechanism that optimizes the processing order of goods based on the urgency of picking up the goods, the storage time, and the target picking up time. For example, orders that need to be picked up in a short time will be given a higher priority to ensure a quick response to user needs. Subsequently, the system performs logistics time analysis and urgency evaluation on the standard picking up time and picking up location. This stage involves a detailed analysis of the picking up time and location of each order, evaluating the picking up urgency of each order, and calculating a picking up urgency coefficient, which reflects the priority of each order and is an important basis for adjusting the logistics task queue. Finally, based on the calculated pickup urgency coefficient, the system dynamically inserts and adjusts the logistics warehousing task queue, which means that the system will dynamically adjust the order processing order in the task queue according to the urgency of each order to ensure that those orders that need to be processed most quickly can be executed first. This dynamic adjustment mechanism makes the entire logistics operation more flexible and efficient, greatly improving the timeliness and customer satisfaction of pickup. Through the above strategy, the efficiency and adaptability of pickup logistics scheduling are ensured, the entire off-island pickup process is optimized, the operational efficiency is improved, and the user's expectations for fast and accurate pickup are met.

[0048] Furthermore, the pickup transportation scheduling strategy parameters are obtained, and the pickup management module 15 is further used to:

[0049] The transportation target is analyzed and extracted from the turnover logistics transport order to determine the package logistics arrival time period and the package transportation delivery location.

[0050] The transport vehicle dispatch table is obtained through the logistics transportation system, and idle vehicle matching analysis is performed according to the package logistics arrival time period and the transport vehicle dispatch table to obtain dispatchable vehicle information.

[0051] A path fitness evaluation function is constructed, and the Dijkstra algorithm and the path fitness evaluation function are used to perform path planning and optimization for the package transportation and delivery location to determine the target transportation route.

[0052] Based on the dispatchable vehicle information and the target transportation route, the pickup transportation scheduling strategy parameters are obtained.

[0053] Furthermore, the transportation target analysis and extraction of the turnover logistics transport order is carried out. The key to this process is to accurately determine the logistics arrival time period and transportation and distribution location of each package. The transportation target analysis covers an in-depth interpretation of the order details, such as the analysis of the destination, the expected arrival time, and specific logistics requirements, so as to provide data support for subsequent vehicle scheduling and route planning. For example, if a package needs to be delivered to a specific busy area before the peak period, this information will directly affect the decision of transportation scheduling. Next, the transportation vehicle scheduling table is obtained through the logistics transportation system. The system analyzes the current vehicle usage through the transportation vehicle scheduling table, including which vehicles are idle, the location of the vehicle and its operating status, and then uses this information to match the scheduled logistics arrival time period of the package to ensure that the most suitable vehicle is selected for scheduling. This step ensures the optimal use of resources and reduces waiting time and transportation costs. Then, the path fitness evaluation function is constructed, and the Dijkstra algorithm is used for path planning optimization. The path fitness evaluation function is designed based on factors such as road conditions, distance, expected travel time, and possible delays to ensure that the most efficient transportation route is found. The Dijkstra algorithm is a well-known computer algorithm used to solve the single-source shortest path problem in a directed or undirected graph, that is, the shortest path from a specified starting node (source point) in the graph to all other nodes. It gradually expands the set of visited nodes, starting from the source point, and gradually adds the unvisited nodes closest to the source point, while updating the shortest paths of other unvisited nodes. Through the Dijkstra algorithm, the system can calculate the shortest or fastest route from the starting point to the end point, which is crucial to improving transportation efficiency and reducing transportation costs. Finally, based on the determined dispatchable vehicle information and the optimized target transportation route, the system obtains the final pick-up transportation scheduling strategy parameters, which integrate the specific arrangements of vehicle scheduling and detailed guidance of route planning, and provide accurate execution instructions for actual logistics transportation operations. Through the above steps, the transportation scheduling in the pick-up process can be effectively optimized to ensure that the goods can arrive at the designated location on time and safely, while significantly improving the operating efficiency and service quality of the entire logistics system.

[0054] Furthermore, the platform also includes:

[0055] The transportation road condition acquisition module is used to track the real-time trajectory of the dispatchable vehicle information, obtain the vehicle's current location information and transportation route progress information, and obtain the traffic network status through the logistics transportation system.

[0056] The arrival prediction module is used to predict the arrival time based on the transportation route progress information and the traffic network status, obtain the predicted arrival time, and issue a route update instruction if the predicted arrival time exceeds a preset timeout threshold.

[0057] The route updating module is used to dynamically adjust the path planning of the vehicle's current position information based on the traffic network conditions according to the route updating instruction and the path fitness evaluation function to obtain a transportation update route.

[0058] Optionally, in order to ensure that the goods arrive at the destination on time, an efficient dynamic route adjustment and real-time arrival time prediction mechanism is proposed. This mechanism ensures the flexibility and punctuality of the transportation process by integrating real-time vehicle trajectory tracking, traffic network status analysis and advanced path planning technology. Specifically, the real-time trajectory tracking of the dispatchable vehicle information is achieved through the GPS device installed on the transport vehicle. This step allows the system to obtain the current location information of each vehicle and its progress information on the scheduled transportation route. In addition, the system also accesses the logistics transportation system in real time to obtain data about the current traffic network status, such as road congestion, accident information, temporary road condition changes, etc., which are crucial for subsequent route adjustments. Next, based on the collected transportation route progress information and traffic network status, the system uses an algorithm to predict the arrival time. This algorithm comprehensively considers factors such as the current speed of the vehicle, the traffic conditions of the route, and historical data to predict the time when the vehicle arrives at each pick-up point. If the arrival time predicted by the system exceeds the preset timeout threshold, it means that the vehicle may be delayed due to traffic delays or other factors, and the system will automatically issue a route update instruction. Among them, the timeout threshold is set according to the actual situation. Finally, according to the route update instructions issued, the path fitness evaluation function is used to dynamically adjust the path planning of the vehicle's current location information. The path fitness evaluation function is a complex algorithm model that calculates the optimal driving path based on the current traffic conditions, the geographical characteristics of the route, and the predicted traffic changes. The system uses this function to re-plan the vehicle's route to avoid congested areas or bypass emergencies to ensure that the goods can reach the destination safely and on time in the shortest time. Through this series of dynamic adjustments and real-time monitoring measures, the logistics efficiency and timeliness of off-island pickup have been significantly improved, while also reducing the additional costs that may be caused by traffic delays, providing users with a more reliable and efficient service experience.

[0059] Furthermore, the platform also includes:

[0060] The position coding module is used to perform position coding on the parcel shelf by using a preset coding rule through the pick-up management system to obtain a parcel shelf identification code set, wherein the preset coding rule includes a shelf coding rule and a position coding rule.

[0061] The shelf allocation module is used to allocate the order package to the shelf through the pickup management system when the order package of the target user arrives at the pickup location, and to associate and record the package shelf identification code set to obtain the target shelf identification code.

[0062] The integrated storage module is used to associate and integrate the target shelf identification code with the multiple user-associated order information and the target identity identifier for storage, obtain an inventory synchronization database, and manage user off-island pickup based on the inventory synchronization database.

[0063] Specifically, the pick-up management system uses preset coding rules to encode the location of the parcel shelf. These preset coding rules include shelf coding rules and location coding rules to ensure that the location of each shelf can be uniquely determined and easily queried. Among them, the shelf coding rule is responsible for assigning a unique code to each shelf, while the location coding rule provides the specific location information of the shelf in the warehouse. For example, the shelf coding may include information about the row and column of the shelf, while the location coding may contain the identification of the warehouse area or specific section. Next, when the target user's order package arrives at the pick-up location, the pick-up management system will automatically assign the order package to the shelf. The system selects the most suitable shelf location and records the assignment based on the type, size and pick-up priority of the goods. Subsequently, the parcel shelf identification code set mentioned above is used for association and recording. Each order package will be associated with a specific shelf identification code to form a clear logistics record chain. Then, the system associates and integrates the obtained target shelf identification code with multiple user-associated order information and target identity identifiers to form an inventory synchronization database. This database not only records the shelf location of each order, but also integrates user identity information and order status, making the entire pick-up process more transparent and traceable. Finally, based on the inventory synchronization database, the pickup management system performs user off-island pickup management, which includes follow-up inquiries, processing status records, pickup completion, and return services. The system allows users to query the status and shelf location of their orders through the online platform or on-site service points. When picking up the goods, the system will update the order status to "completed". If there is a return request, the system can also quickly process and update the corresponding information. Through this systematic and automated pickup management strategy, not only the efficiency of off-island pickup is significantly improved, but also the accuracy of inventory management and the quality of user service are enhanced. In addition, this approach also helps to reduce errors and delays, ensuring that users can smoothly pick up their orders within the scheduled time.

[0064] Through the technical solutions of the above-mentioned embodiments, the intelligent identity tracking and aligned off-island digital pickup platform provided by this application solves the technical problems faced in the existing off-island pickup process, such as the lack of real-time monitoring and dynamic scheduling capabilities, low pickup efficiency, insufficient integration of identity authentication and order information, and opaque logistics information. It improves data security by applying blockchain technology, efficiently integrates identity and order information to improve matching verification efficiency, and introduces intelligent logistics to optimize the cargo scheduling process. Combined with real-time track tracking and dynamic adjustment of transportation routes, it ensures the adaptability and response speed of the logistics process, achieving the technical effect of improving the efficiency, safety and user satisfaction of the pickup process and significantly improving service quality.

[0065] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. Intelligent identity tracking and alignment of the offshore digital pickup platform, characterized by: The platform includes: An order information acquisition module is used to acquire the target user's order information through the order management system. The order information includes product information, order information, user identity information, and off-island pickup information; An identity binding module, used to generate a target identity identifier for the target user using blockchain technology, and bind the order information and the target identity identifier, and encrypt and upload the order information and the target identity identifier to the identity tracking blockchain for storage through a consensus mechanism; An identity recognition module is used to use a pickup recognition system to read and obtain user identity recognition information, and at the same time call the identity tracking blockchain to match and align with the user identity recognition information to obtain the target identity identifier; An association aggregation module is used to perform identity authentication update and order association aggregation with the order management system based on the target identity identifier to obtain multiple user-associated order information, and at the same time, the identity tracking blockchain obtains the pick-up time and location of the target user; The pickup management module is used to perform a pickup strategy analysis on the order information associated with the multiple users, the pickup time and the pickup location, determine the pickup coordination strategy parameters, and perform off-island pickup management on the order information of the target user based on the pickup coordination strategy parameters.

2. The intelligent identity tracking and alignment off-island digital pickup platform as claimed in claim 1, characterized in that: The identity binding module is also used for: According to the data standardization format, construct a data preprocessing step, perform format preprocessing on the order information and the target identity identifier according to the data preprocessing step, and obtain standard order information and a standard identity identifier; Performing encryption requirement assessment on the standard order information and standard identity identifier to obtain data encryption assessment level information; According to the data encryption assessment level information, configure a data transmission encryption algorithm; The order information and the target identity identifier are encrypted based on the data transmission encryption algorithm, and the encrypted order information and the target identity identifier are uploaded to the identity tracking blockchain for storage.

3. The intelligent identity tracking and alignment off-island digital pickup platform as claimed in claim 2, characterized in that: The identity binding module is also used for: Obtaining data encryption assessment dimensions, wherein the data encryption assessment dimensions include a system threat general dimension and a data sensitivity dimension; Performing risk assessment on the order management system according to the conventional dimension of the system threat to obtain a system threat risk assessment coefficient; Performing a multi-dimensional analysis on the standard order information and the standard identity identifier based on the data sensitivity dimension to obtain a data sensitivity coefficient; The system threat risk assessment coefficient and the data sensitivity coefficient are subjected to an integrated encryption requirement assessment to obtain the data encryption assessment level information.

4. The intelligent identity tracking and alignment off-island digital pickup platform as claimed in claim 2, characterized in that: The delivery management module is also used for: According to the data preprocessing step, the pick-up time and the pick-up location are converted into a standardized format to obtain a standard pick-up time and a standard pick-up location; Performing a dynamic analysis of logistics division based on the multiple user-associated order information, the standard pickup time and the standard pickup location to obtain pickup logistics scheduling strategy parameters; Generate a turnover logistics transport order according to the pickup logistics scheduling strategy parameters, perform transportation scheduling analysis on the turnover logistics transport order, and obtain the pickup transportation scheduling strategy parameters; The pickup coordination strategy parameters are determined based on the pickup logistics scheduling strategy parameters and the pickup transportation scheduling strategy parameters.

5. The intelligent identity tracking and alignment off-island digital pickup platform as claimed in claim 4, characterized in that: The delivery management module is also used for: Acquire a logistics warehousing database, and perform matching searches in the logistics warehousing database based on the associated order information of the plurality of users to obtain a set of information on goods that can be dispatched; Using a time priority algorithm to sort the cargo packages in the deployable cargo information set to obtain a logistics warehousing task queue; Performing logistics time analysis and urgency assessment on the standard pickup time and the standard pickup location to obtain a pickup urgency coefficient; The logistics warehousing task queue is dynamically inserted and adjusted based on the pickup urgency coefficient to obtain the pickup logistics scheduling strategy parameters.

6. The intelligent identity tracking and alignment off-island digital pickup platform as claimed in claim 4, characterized in that: The delivery management module is also used for: Analyze and extract the transportation target of the turnover logistics transport order to determine the arrival time period of the package logistics and the package transportation and delivery location; Obtain a transport vehicle dispatch table through the logistics transportation system, perform idle vehicle matching analysis based on the package logistics arrival time period and the transport vehicle dispatch table, and obtain dispatchable vehicle information; Constructing a path fitness evaluation function, using the Dijkstra algorithm and the path fitness evaluation function to perform path planning and optimization for the package transportation and delivery location, and determining a target transportation route; Based on the dispatchable vehicle information and the target transportation route, the pickup transportation scheduling strategy parameters are obtained.

7. The intelligent identity tracking and alignment off-island digital pickup platform as claimed in claim 6, characterized in that: The platform also includes: The transportation road condition acquisition module is used to track the real-time trajectory of the dispatchable vehicle information, obtain the vehicle's current location information and transportation route progress information, and obtain the traffic network status through the logistics transportation system; An arrival prediction module is used to predict the arrival time based on the transportation route progress information and the traffic network status, obtain the predicted arrival time, and issue a route update instruction if the predicted arrival time exceeds a preset timeout threshold; The route updating module is used to dynamically adjust the path planning of the vehicle's current position information based on the traffic network conditions according to the route updating instruction and the path fitness evaluation function to obtain a transportation update route.

8. The intelligent identity tracking and alignment off-island digital pickup platform as claimed in claim 1, characterized in that: The platform also includes: A position coding module, used to perform position coding on the parcel shelf by using a preset coding rule through the pick-up management system to obtain a parcel shelf identification code set, wherein the preset coding rule includes a shelf coding rule and a position coding rule; A shelf allocation module, used for allocating the order package of the target user to a shelf through the pickup management system when the order package arrives at the pickup location, and performing association records based on the package shelf identification code set to obtain a target shelf identification code; The integrated storage module is used to associate and integrate the target shelf identification code with the multiple user-associated order information and the target identity identifier for storage, obtain an inventory synchronization database, and manage user off-island pickup based on the inventory synchronization database.

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