Airport aviation food guarantee multi-party cooperation method and system based on block chain

Abstract

The invention belongs to the technical field of civil airport informatization in the civil aviation industry, and discloses an airport aviation food guarantee multi-party cooperation method and system based on a block chain. The method comprises the following steps: accessing data through interfaces such as Webservice, Restful API, MQ message, FTP, ODBC and the like, and analyzing the data by adopting technologies such as XML (Extensible Markup Language)-to-data object, JSON (JavaScript Object Notation)-to-data object, deserialization and the like; variable structures of the airline credibility level, the accumulated service time of the airline, the flight number of the airline, the historical complaint number of the airline and the food guarantee airline and the payment refusal number of the airline are constructed and initialized, and the airline credibility number and the credibility level are calculated. According to the invention, an aviation food guarantee cooperative operation structure and an upper chain storage structure which consider the requirements of performance, storage capacity and the like are considered, and long-term continuous availability of the system is realized.

Description

Technical Field

[0001] The present invention belongs to the field of civil aviation industry civil airport information technology, and in particular to a blockchain-based airport catering multi-party collaboration method and system. Background Art

[0002] In traditional airport catering, there is business collaboration between different airlines and different catering companies and specific departments of catering companies. The airlines give business requirements, the catering companies provide catering services according to the requirements, and finally settle accounts with the airlines on a periodic basis. In this collaboration process, the communication costs of the multiple parties are high due to the lack of a trustworthy basis. Many business operations require repeated multi-step manual confirmation due to credibility issues, and the overall collaboration efficiency is low. At the same time, when the catering company and the airline reconcile and settle accounts at the end, the inconsistency of the information recorded separately by both parties often leads to refusal to pay and wrangling, which affects the normal income of the catering company. Summary of the invention

[0003] In order to overcome the problems existing in the related technologies, the disclosed embodiments of the present invention provide a blockchain-based airport catering service multi-party collaboration method and system. The present invention is aimed at the airport catering service business field, and aims to achieve reliable and efficient collaboration among multiple parties in the catering service scenario by adopting blockchain technology.

[0004] The technical solution is as follows: a blockchain-based multi-party collaborative method for airport catering security, comprising the following steps: S1, access flight plans, catering airline history, catering settlement history, contract airlines, historical flight cabin occupancy rate, flight reservations, and aircraft travel time relationship matrix data through Webservice, RestfulAPI, MQ message, FTP, ODBC and other interfaces, and use XML to data object, JSON to data object, deserialization and other technologies to parse the above data, among which flight plan data and flight reservation data are data for the next 3 days, and catering airline history, catering settlement history, and historical flight cabin occupancy rate are data for the past year; S2, construct and initialize the variable structure of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, number of refusal of airline catering guarantee, and calculate the trust number and trust level of airline; S3, construct the coordinated operation structure variables of airline catering guarantee, construct the on-chain storage structure variables according to the flight trust level, initialize the coordinated operation structure variables of airline catering guarantee and the on-chain storage structure variables according to the flight plan and contract, and perform the on-chain storage structure variable on-chain operation; S4, obtains the demand data such as catering type, quantity, additional requirements, etc. for different cabins of specific flights of airlines, queries the collaborative operation structure variables and the variables stored on the chain, verifies the legitimacy of the signature of the airline's entry of cabin catering requirements, and updates the collaborative operation structure variables and the variables stored on the chain based on version control; S5, obtain historical flight cabin occupancy rate and other data, construct the intermediate calculation variable structure of the flight cabin meal quantity demand, initialize the specific flight specific cabin booking data, calculate the specific flight specific cabin historical occupancy rate, calculate the specific flight historical complaint rate, calculate the relationship between flights during the meal delivery process, calculate the overall proportion of meal types in different cabins of a specific flight, calculate the number of meals required for different cabins of a specific flight, and update the collaborative operation structure variables and the on-chain storage variables; S6, obtain the confirmation status of the catering company's catering department and update its own catering status input data, retrieve and obtain the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the catering department's signature, and update the catering status to the collaborative operation structure variables and the on-chain storage variables; S7, obtain the confirmation status of the catering department of the airline catering company and update the input data of its own catering process record, query and obtain the collaborative operation structure variable and the on-chain storage variable, verify the legitimacy of the signature of the catering department, and update the catering process record to the collaborative operation structure variable and the on-chain storage variable; S8, obtain the data of the on-site catering status confirmed by the flight crew, retrieve the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the flight crew signature, and update the catering completion status to the collaborative operation structure variables and the on-chain storage variables.

[0005] In step S1, the flight plan, the history of airlines that provide food, the history of settlement of food, the contract airlines, the historical flight cabin occupancy rate, the flight booking, and the aircraft travel time relationship matrix data are accessed through interfaces such as Webservice, RestfulAPI, MQ message, FTP, and ODBC. The above data are parsed using technologies such as XML to data object, JSON to data object, and deserialization. The parsed flight plan data is set as , the parsed airline catering service historical data is processed by data attribute replication and set as , the parsed airline meal security settlement history data is processed by data attribute copying and set as , after parsing the contract airline data, the data attributes are copied and set to , the parsed historical flight cabin occupancy rate data is processed by data attribute copying and set as , the parsed flight booking data is processed by data attribute copying and set to , the analyzed stand travel time relationship matrix data is set as Among them, the flight plan data and flight booking data are data for the next three days, and the airline history of airline catering guarantee, the historical record of airline catering guarantee settlement, and the historical flight cabin occupancy rate are data for the past year.

[0006] In step S2, the variable structures of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, and number of refusal of airline catering guarantee are constructed and initialized, and the airline trust number and trust level are calculated, including: S201, construct airline trust level structure variables , used to record the trust levels of different airlines, where the key value is the airline name and the value is the level number; construct the cumulative service time structure variable of the airline catering guarantee airline , used to record the cumulative service time of different airlines, where the key value is the airline name and the value is the cumulative service time in days; construct the flight quantity structure variable of the airline catering service , used to record the cumulative number of flights with food service provided by different airlines, where the key value is the airline name and the value value is the cumulative number of flights with food service provided; construct the structure variable of the number of historical complaints of airlines with food service provided , used to record the number of complaints about flights of different airlines, where the key value is the name of the airline and the value is the number of complaints about flights; construct the structure variable of the number of airlines refusing to pay for food insurance , used to record the number of flights rejected by different airlines, where the key value is the airline name and the value is the number of rejected flights; S202, obtain , traverse , using the airline name in the single contract airline data as the key value and 0 as the value, and putting the constructed data into , complete the initialization; take the airline name in the obtained single data as the key value, and the accumulated service time in the obtained single data as the value, and put the constructed data into ,Finish Traverse; S203, obtain , traverse , get a single specific airline catering guarantee historical data, use the airline name in the single historical data as the key value, and query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1. If the airline complaint attribute in the acquired single airline food guarantee history data is yes, the airline name in the acquired single history data is used as the key value to query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1 to complete the traversal. ; S204, obtain , traverse , get a single specific airline meal guarantee settlement history record. If the specific record has the attribute of whether to refuse payment set to yes, use the airline name in the single history record as the key value to query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1 to complete the traversal. ; S205, obtain , traverse , get specific records, and query them separately using the key values ​​in the specific records , , , , and get , , , ,in Indicates the accumulated service time of the airline. Indicates the cumulative number of flights with guaranteed food for the airline. Indicates the number of flights complained about by the airline. The airline's credibility number is The calculation is as follows: in These are user-adjustable parameters used to adjust the impact of different elements on the calculation of the airline's credibility number.

[0007] Airline Trust Rating , calculated as follows: The calculated Put it as value , traversal completed .

[0008] In step S3, the flight catering support collaborative operation structure variable is constructed, the on-chain storage structure variable is constructed according to the flight trust level, the flight catering support collaborative operation structure variable and the on-chain storage structure variable are initialized according to the flight plan and contract, and the on-chain storage structure variable is put on-chain, including: S301: Construct the coordinated operation structure variables of the in-flight catering support. ; in Number of flights served by airline catering companies Indicates around The flight catering support collaborative operation structure variables constructed for each flight, in Indicates the flight number. Indicates the flight date, Indicates the airline company, Indicates the model. Indicates the overall status of the flight. Indicates flight route. Indicates the catering requirements for different cabins entered by the airline. Indicates the signature of the airline entering the catering requirements for different cabins, used to prove that it is entered for a specific airline. Indicates the estimated number of meals required for the flight. Indicates the signature of the catering department, used to confirm the entered catering requirements and catering quantities. It indicates the record of the meal preparation process by the airline catering department. It indicates the signature confirmation of the catering department on the meal preparation process. Indicates the meal preparation process record of the airline catering department. Indicates the signature confirmation of the airline crew. Indicates the update version number, which is used to solve the problem of update loss that may occur when multiple parties write; S302: Construct the storage structure that needs to be chained. Indicates around The on-chain collaborative operation structure variables constructed by each flight, The structure of Confirm, as follows: S303: Acquisition , traverse , get specific single flight plan data, get , traverse , obtain the specific single contract airline data, determine whether the airline attributes in the flight plan data are consistent with the airline attributes in the contract airline data, and obtain , using the airline name as the key to obtain the specific trust level of the airline, and construct The structure assigns the flight number, flight date, airline, aircraft type, flight status, and flight route attributes in the flight plan data to ,Will In Set to 1, Put in , construct the corresponding structure according to the specific trust level of the airline obtained , assign the flight number, flight date, airline, aircraft type, flight status, and flight route attributes in the flight plan data to ,Will In Set to 1, Put in , traversal completed ; S304: The data is stored in the blockchain and will be stored in the form of a key-value structure on the blockchain First, establish a trusted link with the blockchain management platform through the access key and development kit granted by the blockchain management platform, and then start traversing Data, get specific , get In and , combine them into a string, call the blockchain write interface, and pass in the constructed combined string as the key. As value, upload the data to the blockchain and complete the traversal .

[0009] In step S4, the demand data such as catering type, quantity, additional requirements, etc. of different cabins of specific flights of the airline are obtained, the collaborative operation structure variables and the on-chain storage variables are queried, the legitimacy of the signature of the airline's entry of cabin catering requirements is verified, and the collaborative operation structure variables and the on-chain storage variables are updated based on version control, including: S401: Obtain the data that the airline needs to enter; the airline enters the flight number that needs catering , Flight date , Catering requirements for different cabins And signature for catering request , , Catering requirements for specific cabins ,in Indicated as a specific cabin, Indicates the type of meal, It represents the number of meals required. When this variable is -1, it means that the airline has not specified the number of people. Indicated as additional requirements; S402: Retrieve specific information based on the airline's input and ,pass and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific ; S403: Yes Data is authenticated using the airline-specific public key Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the two is compared. If they are consistent, the data entry of the airline is cancelled. The catering requirements of different cabins are Data updated to and and respectively and In The attribute is incremented by 1; S404: Update and Data, through and Traversal , when traversing the current specific data flight number and date and and If the data is consistent, the specific data currently traversed is determined. Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned. Establish a link with the blockchain platform. and Combined into a query key, obtain specific data through the blockchain query interface to determine the specific data Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned.

[0010] In step S5, the data such as the historical flight cabin occupancy rate is obtained, the intermediate calculation variable structure of the flight cabin meal quantity demand is constructed, the specific flight cabin booking number data is initialized, the specific flight cabin historical occupancy rate is calculated, the specific flight cabin historical complaint rate is calculated, the relationship between flights in the meal delivery process is calculated, the overall proportion of meal types in different cabins of the specific flight is calculated, the number of meals required in different cabins of the specific flight is calculated, and the collaborative operation structure variables and the chain storage variables are updated, including: S501: Get historical flight cabin occupancy rate data , get flight booking data , get the historical data of airlines that provide food service , get flight schedule data , get the stand travel time relationship matrix data , obtain the coordinated operation structure variables of the airline catering support , get the storage structure that needs to be on-chain ; S502: Construct variable structure , used to store the intermediate calculation value of each flight that needs to calculate the number of meals required for different cabins on the flight. It is a hash table structure. The key value is a string consisting of the flight number and the flight date. The value value is The structure of It represents the number of people who have booked seats in a specific cabin of a specific flight. A list structure where Indicates the specific cabin space. Indicates the number of people booking for a specific cabin. The historical load factor of a specific flight is A list structure where Indicates the specific cabin space. It is expressed as the historical passenger load factor of a specific cabin. is the historical complaint rate of a specific flight, Indicates the assigned catering cart mark of a specific flight, which is used for subsequent calculation marks. It represents the auxiliary structure for calculating the catering car allocation for a specific flight, which is A list structure where Indicates the specific cabin space. It is expressed as the proportion of the same catering type in the same dining car and cabin. Indicates the number of meals provided for a specific cabin; S503: Traversal , get specific , get the specific flight number and flight date, construct List structure variables , traverse , find and Data with the same flight number is constructed based on the cabin space and number of seats booked in the specific data. The data structure is placed in Until all the The data with the same flight number ends the traversal ,by The flight number and flight date combination string is key, construct The structure is value, and Assignment , put the constructed key value and value into , continue to traverse , repeat the operation until the traversal is completed; S504: Traversal , get specific , the structure contains List variable of structure ,in Indicates the specific flight class. Indicates the cumulative number of flights with the same flight class. Indicates the cumulative passenger load factor of the same class of the same flight, traversing , query and The specific flight plan data with the same flight number and flight date, obtain the flight plan number of the specific flight plan data , traverse , get the The flight number is the same and the flight schedule number attribute is the same Consistent specific airline meal guarantee airline historical data, traversal , obtain the data that is consistent with the flight number and flight date of the specific airline’s historical data of catering support, and Accumulate +1 for the corresponding cabin Accumulate the passenger load factor and complete the traversal , the accumulated Structural data into , traverse , start calculating the historical average passenger load factor for a specific cabin , the specific calculation method is: by The combined string of flight number and flight date is key, and the query ,get ,renew Average passenger load factor of different classes, continue to traverse , repeat the operation until the traversal is completed; S505: Traversal , get specific , construct variables , used to represent the total number of historical service flights, construct variables , used to indicate the number of flights with complaints in historical service flights, traversing , query and The specific flight plan data with the same flight number and flight date, obtain the flight plan number of the specific flight plan data , traverse , get the The flight number is the same and the flight schedule number attribute is the same Consistent specific airline meal guarantee airline historical data, Add 1 to determine whether the complaint attribute of the specific airline in the historical data of the airline catering guarantee is yes. If yes, proceed Add 1 operation, traversal completed , calculate the historical complaint rate , the specific method is as follows: by The combined string of flight number and flight date is key, and the query ,get ,renew Historical complaint rate data, continue to traverse , repeat the operation until the traversal is completed; S506: Traversal , build a structure containing List structure variables ,in Indicates the specific cabin space. Indicates the type of meal, It is expressed as the number of the same type of meals in the same dining car. , construct variables , indicating the number of flights on which the vehicle has loaded meals, initially 0, traversing , query and The specific flight plan data with the same flight number and flight date, obtain the start time and end time of the flight meal guarantee plan in the specific flight plan data , camera position, continue to traverse , get the start time of the meal guarantee plan for specific flight plan data , camera position, traverse according to the two camera position data , get the travel time between the two ,when , it is considered that the catering requirements can be met, and the flight number and flight date are used as the key value to query , update the value in , will traverse , statistical summary , , value, Perform an add 1 operation; continue traversal , continue to follow up on the flight schedule data The judgment, when , it is considered that the same dining car has reached the upper limit of loading. A constant value that can be adjusted by the user to control the maximum number of flights that each dining car can carry. , end the traversal ; S507: Get the , traverse from the beginning , get specific , obtain the catering requirements entered by the airline , according to the cabin and meal type in the catering requirements, Query the number of cabin types and meal types that meet the requirements. The flight number and flight date are combined as keys to query , get the corresponding Structural data, assuming that the number of meals of the same type in a specific cabin is , then the proportion of the same catering type in the same dining car and cabin is The calculation method is: The different classes of space will be calculated Update and put in data of different cabin types , complete the pair Update; continue to traverse from the beginning , skip the flights that have been marked as having been assigned catering vehicles, and repeat the above steps until all flights have been calculated; S508: Traversal , get specific ,by The flight number and flight date are keys, and the query , get the corresponding Structural data, according to Flight number and flight date, query traversal , get the corresponding maximum number of passengers , assuming that the specific cabin meal quantity is ,from The historical passenger load factor of a specific cabin obtained from ,from Get the historical complaint rate of flights ,from Get the number of seats booked for a specific cabin on a specific flight ,from Get the proportion of the same catering type in the same dining car and cabin ,but The specific calculation method is as follows: renew middle ,Will Update to In property; S509: The data in the update is synchronized to the blockchain, and the traversal , get specific , and then establish a link with the blockchain platform to The flight number and flight date are used as the combined query key to obtain the specific ,if exist Attributes, then In Data updated to and will In The attribute is incremented by 1. The flight number and flight date are used as the combined query key, and the specific data is obtained through the blockchain query interface again to determine the specific data. Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned.

[0011] In step S6, the confirmation status of the catering company's catering department is obtained and the catering company's catering status input data is updated, the collaborative operation structure variables and the on-chain storage variables are retrieved, the legitimacy of the catering department's signature is verified, and the catering status is updated to the collaborative operation structure variables and the on-chain storage variables, including: S601: Obtain the data required for the catering company's catering production department to confirm the status and update its own catering production status; the catering company's catering production department needs to enter the flight number that needs to confirm the status and update the catering production status , Flight date , Signature to confirm the entered meal requirements and meal quantities , Meal preparation process status record , The variable is a string, which records the process status of the meal preparation department of the airline catering company making the meal for the flight. Is a string structure, which is a pair Data and One-way hash calculation of the combined data, and encryption of the one-way hash value using the private key of the catering company's food production department; S602: Retrieve specific information based on the input from the catering production department of the airline catering company and ,pass and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific ; S603: Yes The data is verified using the public key of the catering company's catering department. Decrypt it, get the specific one-way hash value, and then calculate and Combine the one-way hash value of the data and compare the two. If they are consistent, it is passed. Otherwise, the data entry of the catering production department of the airline catering company is cancelled. , Data updated to and and respectively and In The attribute is incremented by 1; S604: Update and data.

[0012] In step S7, the confirmation status of the catering department of the airline catering company is obtained and the input data of the catering process record is updated, the collaborative operation structure variable and the chain storage variable are queried, the legitimacy of the signature of the catering department is verified, and the catering process record is updated to the collaborative operation structure variable and the chain storage variable, including: S701: Obtain the data required for the catering department of the airline catering company to confirm the status and update its own meal preparation process records; the catering department of the airline catering company needs to enter the flight number that needs to confirm the status and update the meal preparation process records , Flight date , Signature confirming the meal preparation process by the in-flight catering department , Meal preparation process status record , The variable is a string, which records the process status of the catering department of the airline catering company distributing the meals for the flight. Is a string structure, which is a pair The one-way hash calculation of the data is performed, and the one-way hash value is encrypted using the private key of the catering department of the airline catering company. S702: Retrieve specific information based on the input from the catering department of the airline catering company and ,pass and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific ; S703: Yes The data is verified using the public key of the catering department of the airline catering company. Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the airline catering company is compared. If they are consistent, the data entry is passed. Otherwise, the data entry of the airline catering company's catering department is cancelled. , Data updated to and and respectively and In The attribute is incremented by 1; S704: Update and data.

[0013] In step S8, the data of the on-site catering status confirmed by the flight crew of the catering service is obtained, the collaborative operation structure variables and the on-chain storage variables are retrieved, the legitimacy of the flight crew signature is verified, and the catering service completion status is updated to the collaborative operation structure variables and the on-chain storage variables, including: S801: Obtain the data of the on-site catering status confirmed by the flight crew of the catering service flight; S802: Retrieve specific information based on the airline's input and ,pass and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific ; S803: Yes The data is authenticated using the airline's public key Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the data is compared with the two. If they are consistent, the data entry is passed. Otherwise, the airline data entry is cancelled. Data updated to and and respectively and In The attribute is incremented by 1.

[0014] S804: Update and data.

[0015] Another object of the present invention is to provide a blockchain-based airport catering multi-party collaboration system, which implements the blockchain-based airport catering multi-party collaboration method, and the system includes: The data parsing module is used to access flight plans, catering airline history, catering settlement history, contract airlines, historical flight cabin occupancy rate, flight reservations, and aircraft travel time relationship matrix data through Webservice, RestfulAPI, MQ message, FTP, and ODBC interfaces, and parse the above data using XML to data object, JSON to data object, and deserialization technology; The blockchain operation module is used to construct and initialize the variable structures of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, and number of refusal of airline catering guarantee, and calculate the trust number and trust level of airline. The airline catering collaborative processing module is used to construct airline catering collaborative operation structure variables, construct on-chain storage structure variables according to the flight trust level, initialize airline catering collaborative operation structure variables and on-chain storage structure variables according to the flight plan and contract, and perform on-chain storage structure variable on-chain operations; The meal demand estimation module is used to obtain the meal type, quantity, and additional requirements for different cabins of specific flights of airlines, query the collaborative operation structure variables and the variables stored on the chain, verify the legitimacy of the signature of the airline entering the meal demand for cabins, and update the collaborative operation structure variables and the variables stored on the chain based on version control; Basic data module, used to obtain historical flight cabin occupancy rate data, construct the intermediate calculation variable structure of flight cabin meal quantity demand, initialize the specific flight specific cabin booking number data, calculate the specific flight specific cabin historical occupancy rate, calculate the specific flight historical complaint rate, calculate the relationship between flights during meal delivery, calculate the overall proportion of meal types in different cabins of a specific flight, calculate the number of meals required in different cabins of a specific flight, and update the collaborative operation structure variables and the on-chain storage variables; The data storage and processing module is used to obtain the confirmation status of the catering company's catering department and update its own catering status input data, retrieve and obtain the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the catering department's signature, and update the catering status to the collaborative operation structure variables and the on-chain storage variables; The interface processing module is used to obtain the confirmation status of the catering department of the airline catering company and update the input data of its own catering process record, query and obtain the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the signature of the catering department, and update the catering process record to the collaborative operation structure variables and the on-chain storage variables; The safety control module is used to obtain data from the flight crew confirming the on-site support status of the catering service, retrieve the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the flight crew signature, and update the catering service completion status to the collaborative operation structure variables and the on-chain storage variables.

[0016] In combination with all the above technical solutions, the beneficial effects of the present invention are as follows: data is accessed through interfaces such as Webservice, RestfulAPI, MQ message, FTP, ODBC, etc., and the above data is parsed using technologies such as XML to data object, JSON to data object, and deserialization; variable structures such as the airline's trust level, the cumulative service time of the airline that provides catering services, the number of flights of the airline that provides catering services, the number of historical complaints of the airline that provides catering services, and the number of refusal to pay of the airline that provides catering services are constructed and initialized, and the airline's trust number and trust level are calculated; a catering guarantee collaborative operation structure variable is constructed, and an on-chain storage structure variable is constructed according to the flight's trust level, and the catering guarantee collaborative operation structure variable and the on-chain storage structure variable are initialized according to the flight plan and contract, and an on-chain operation is performed; demand data such as the type, quantity, and additional requirements of catering for different cabins of a specific flight of the airline are obtained, the legitimacy of the signature of the catering requirements entered by the airline, and the collaborative operation structure variables and the on-chain storage variables are updated based on version control; historical flight cabins are obtained occupancy rate and other data, construct the intermediate calculation variable structure of the flight cabin meal quantity demand, initialize the specific flight specific cabin reservation number data, calculate the specific flight specific cabin historical occupancy rate, calculate the specific flight historical complaint rate, calculate the relationship between flights in the meal delivery process, calculate the overall proportion of meal types in different cabins of a specific flight, calculate the number of meals required in different cabins of a specific flight, and update the collaborative operation structure variables and the chain storage variables; obtain the confirmation status of the airline catering company's meal preparation department and update its own meal preparation status input data, verify the legitimacy of the meal department's signature, and update the meal preparation status to the collaborative operation structure variables and the chain storage variables; obtain the confirmation status of the airline catering company's meal preparation department and update its own meal preparation process record input data, verify the legitimacy of the meal preparation department's signature, and update the meal preparation process record to the collaborative operation structure variables and the chain storage variables; obtain the data of the on-site support status confirmed by the crew of the airline catering support flight, verify the legitimacy of the flight crew's signature, and update the airline catering support completion status to the collaborative operation structure variables and the chain storage variables. The present invention takes into account the requirements of performance, storage capacity, etc. for the coordinated operation structure of airline catering guarantee and the storage structure on the chain, thus achieving the long-term and continuous availability of the system. The present invention can provide a credible and unified system foundation for the business collaboration between the business departments of the airline catering company and the airline company, solve the occurrence of communication disputes when the records of both parties are inconsistent, and improve the efficiency of multi-party guarantee collaboration. At the same time, it proposes an airline catering guarantee coordinated operation structure and the storage structure on the chain that take into account the requirements of performance, storage capacity, etc. on the basis of meeting the business needs of users, thus achieving the long-term and continuous availability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings herein are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description, serve to explain the principles of the present disclosure; Figure 1 This is a flowchart of a multi-party collaborative method for airport catering security based on blockchain provided by an embodiment of the present invention; Figure 2 This is an example diagram of the structure variables of the coordinated operation of in-flight catering provided by an embodiment of the present invention; Figure 3 This is a schematic diagram of a blockchain-based airport catering multi-party collaborative system provided by an embodiment of the present invention; In the figure: 1. Data analysis module; 2. Blockchain operation module; 3. Airline catering collaborative processing module; 4. Meal demand estimation module; 5. Basic data module; 6. Data storage and processing module; 7. Interface processing module; 8. Security control module. DETAILED DESCRIPTION

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific implementation disclosed below.

[0019] The innovation of the present invention lies in: the present invention focuses on the problems existing in the field of traditional civil aviation catering service, such as low multi-party collaboration efficiency, high communication and confirmation costs, and difficulty in tracing the source of problems. The present invention makes full use of the anti-tampering and anti-repudiation characteristics of blockchain technology, innovatively introduces blockchain technology, and constructs a unified multi-party trusted collaboration method and system for catering service. At the same time, the on-chain data structure of catering service is optimized according to the trust level of the airline to meet the needs of long-term and stable development of catering service, realizes efficient collaboration in catering service between airlines and catering companies, reduces the communication costs between multiple parties, reduces the occurrence of rejection scenes, and increases the profits of catering companies.

[0020] Embodiment 1, as Figure 1 As shown, the blockchain-based airport catering guarantee multi-party collaboration method provided by the embodiment of the present invention includes: S1, access flight plans, catering airline history, catering settlement history, contract airlines, historical flight cabin occupancy rate, flight booking, and aircraft travel time relationship matrix data through Webservice, RestfulAPI, MQ message, FTP, ODBC and other interfaces, and use XML to data object, JSON to data object, deserialization and other technologies to parse the above data; The historical data is taken from the past year. The flight plan data mainly includes flight number, flight date, airline, aircraft type, aircraft number, route, flight status, abnormal status, aircraft stand, planned landing time, actual landing time, planned take-off time, actual take-off time, flight schedule number, start time of the flight meal guarantee plan, end time of the flight meal guarantee plan, maximum number of passengers, etc. The historical data of the airline with flight meal guarantee mainly includes the airline with guarantee, catering personnel, guarantee time, number of catering compartments, signing crew, guarantee flight, whether the airline has complained, flight schedule number, etc. The historical record data of the settlement of flight meal guarantee mainly includes the airline, settlement time, settlement flight, settlement amount, whether payment is refused, etc. The contract airline data mainly includes the airline, contract start time, contract end time, contract flight rules, accumulated service time, etc. The historical flight cabin occupancy rate data mainly includes flight number, flight date, cabin type, cabin occupancy rate, flight booking data mainly includes flight number, cabin type, number of passengers who have purchased tickets for the cabin, and the cabin travel time relationship matrix data mainly includes the starting seat number, the terminal seat number, and the travel time.

[0021] The parsed flight plan data is processed by data attribute copying and set as , the parsed airline catering service historical data is processed by data attribute replication and set as , the parsed airline meal security settlement history data is processed by data attribute copying and set as , after parsing the contract airline data, the data attributes are copied and set to , the parsed historical flight cabin occupancy rate data is processed by data attribute copying and set as , the parsed flight booking data is processed by data attribute copying and set to , the analyzed stand travel time relationship matrix data is set as .

[0022] S2, construct and initialize the variable structures of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, and number of refusal of airline catering guarantee, and calculate the trust number and trust level of airline. The specific steps are as follows: S201, construct airline trust level structure variables , used to record the trust levels of different airlines, where the key value is the airline name and the value is the level number; construct the cumulative service time structure variable of the airline catering guarantee airline , used to record the cumulative service time of different airlines, where the key value is the airline name and the value is the cumulative service time in days; construct the flight quantity structure variable of the airline catering service , used to record the cumulative number of flights with food service provided by different airlines, where the key value is the airline name and the value value is the cumulative number of flights with food service provided; construct the structure variable of the number of historical complaints of airlines with food service provided , used to record the number of complaints about flights of different airlines, where the key value is the name of the airline and the value is the number of complaints about flights; construct the structure variable of the number of airlines refusing to pay for food insurance , used to record the number of rejected flights by different airlines, where the key value is the airline name and the value is the number of rejected flights.

[0023] S202, obtain , traverse , using the airline name in the single contract airline data as the key value and 0 as the value, and putting the constructed data into , complete the initialization; take the airline name in the obtained single data as the key value, and the accumulated service time in the obtained single data as the value, and put the constructed data into ,Finish Traverse.

[0024] S203, obtain , traverse , get a single specific airline catering guarantee historical data, use the airline name in the single historical data as the key value, and query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1. If the "Is the airline complained" attribute in the acquired single airline food guarantee history data is "yes", the name of the airline in the acquired single history data is used as the key value to query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1 to complete the traversal. .

[0025] S204, obtain , traverse , get a single specific airline meal guarantee settlement history record. If the "Is it rejected" attribute in the specific record is "yes", use the airline name in the single historical record as the key value to query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1 to complete the traversal. .

[0026] S205, obtain , traverse , get specific records, and query them separately using the key values ​​in the specific records , , , , and get , , , ,in Indicates the accumulated service time of the airline. Indicates the cumulative number of flights with guaranteed food for the airline. Indicates the number of flights complained about by the airline. The airline's credibility number is The calculation is as follows: in These are user-adjustable parameters used to adjust the impact of different elements on the calculation of the airline's credibility number.

[0027] Airline Trust Rating , calculated as follows: The larger the value, the worse the credibility. Put it as value , traversal completed This step is to give the recommended value of the airline's trust level, and the user can make manual adjustments as needed.

[0028] S3, construct the coordinated operation structure variables of airline catering guarantee, construct the on-chain storage structure variables according to the flight trust level, initialize the coordinated operation structure variables of airline catering guarantee and the on-chain storage structure variables according to the flight plan and contract, and perform the on-chain storage structure variable on-chain operation. The specific steps are as follows: S301: Construct the coordinated operation structure variables of the in-flight catering support. ; in Number of flights served by airline catering companies Indicates around The flight catering support collaborative operation structure variables constructed for each flight, ,in Indicates the flight number. Indicates the flight date, Indicates the airline company, Indicates the model. Indicates the overall status of the flight. Indicates flight route. Indicates the catering requirements for different cabins entered by the airline. Indicates the signature of the airline entering the catering requirements for different cabins, used to prove that it is entered for a specific airline. Indicates the estimated number of meals required for the flight. Indicates the signature of the catering department, used to confirm the entered catering requirements and catering quantities. It indicates the record of the meal preparation process by the airline catering department. It indicates the signature confirmation of the catering department on the meal preparation process. Indicates the meal preparation process record of the airline catering department. Indicates the signature confirmation of the airline crew. Indicates the update version number, which is used to solve the problem of update loss that may occur when multiple parties write; Figure 2 for Example; S302: Construct the storage structure that needs to be chained. Indicates around The on-chain collaborative operation structure variables constructed by each flight, The structure of Confirm, as follows: S303: Acquisition , traverse , get specific single flight plan data, get , traverse , obtain the specific single contract airline data, determine whether the airline attributes in the flight plan data are consistent with the airline attributes in the contract airline data, and obtain , using the airline name as the key to obtain the specific trust level of the airline, and construct The structure assigns the flight number, flight date, airline, aircraft type, flight status, and flight route attributes in the flight plan data to ,Will In Set to 1, Put in , construct the corresponding structure according to the specific trust level of the airline obtained , assign the flight number, flight date, airline, aircraft type, flight status, and flight route attributes in the flight plan data to ,Will In Set to 1, Put in , traversal completed .

[0029] S304: The data is stored in the blockchain. In order to maintain the high efficiency of data retrieval after being uploaded to the blockchain, the present invention will store it in the form of a key-value structure on the blockchain. , in order to improve the performance of multi-party reading and writing, and reduce the update loss problem caused by multiple parties writing the same data. Specifically, first establish a trusted link with the blockchain management platform through the access key and development kit granted by the blockchain management platform, and then start traversing Data, get specific , get In and , combine them into a string, call the blockchain write interface, and pass in the constructed combined string as the key. As value, upload the data to the blockchain and complete the traversal .

[0030] S4, obtains the demand data such as catering type, quantity, additional requirements, etc. for different cabins of specific flights of airlines, queries the collaborative operation structure variables and the variables stored on the chain, verifies the legitimacy of the signature of the airline's entry of cabin catering requirements, and updates the collaborative operation structure variables and the variables stored on the chain based on version control. The specific steps are as follows: S401: Obtain the data that the airline needs to enter; the airline enters the flight number that needs catering , Flight date , Catering requirements for different cabins And signature for catering request , ; Catering requirements for specific cabins ,in Indicated as a specific cabin, Indicates the type of meal, It represents the number of meals required. When this variable is -1, it means that the airline has not specified the number of people. Indicates additional requirements, which are custom attributes. If the airline has special requirements, they can be described in this attribute. This structure is consistent with the structure of the same variable in the above collaborative structure. Is a string structure, which is a pair The one-way hash calculation of the data is used, and the data obtained by encrypting the one-way hash value using the private key of the specific airline is used to prove that it is indeed the request of the specific airline and there is no forgery or tampering.

[0031] S402: Retrieve specific information based on the airline's input and Specific through and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific .

[0032] S403: Yes The data is verified using the public key of the specific airline. Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the two is compared. If they are consistent, the data entry of the airline is cancelled. The catering requirements of different cabins are Data updated to and and respectively and In The attribute is incremented by 1.

[0033] S404: Update and Data. and Traversal , when traversing the current specific data flight number and date and and If the data is consistent, the specific data currently traversed is determined. Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned. Establish a link with the blockchain platform. and Combined into a query key, obtain specific data through the blockchain query interface to determine the specific data Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned.

[0034] S5: Obtain historical flight cabin occupancy rate and other data, construct the intermediate calculation variable structure of the flight cabin meal quantity demand, initialize the specific flight specific cabin booking data, calculate the specific flight specific cabin historical occupancy rate, calculate the specific flight historical complaint rate, calculate the relationship between flights during meal delivery, calculate the overall proportion of meal types in different cabins of a specific flight, calculate the number of meals required for different cabins of a specific flight, update the collaborative operation structure variables and the on-chain storage variables. The specific steps are as follows: S501: Get historical flight cabin occupancy rate data , get flight booking data , get the historical data of airlines that provide food service , get flight schedule data , get the stand travel time relationship matrix data , obtain the coordinated operation structure variables of the airline catering support , get the storage structure that needs to be on-chain .

[0035] S502: Construct variable structure , used to store the intermediate calculation value of each flight that needs to calculate the number of meals required for different cabins on the flight. It is a hash table structure. The key value is a string consisting of the flight number and the flight date. The value value is The structure of It represents the number of people who have booked seats in a specific cabin of a specific flight. A list structure where Indicates the specific cabin space. Indicates the number of people booking for a specific cabin. The historical load factor of a specific flight is A list structure where Indicates the specific cabin space. It is expressed as the historical passenger load factor of a specific cabin. is the historical complaint rate of a specific flight, Indicates the assigned catering cart mark of a specific flight, which is used for subsequent calculation marks. It represents the auxiliary structure for calculating the catering car allocation for a specific flight, which is A list structure where Indicates the specific cabin space. It is expressed as the proportion of the same catering type in the same dining car and cabin. Indicates the number of meals provided for a specific cabin; S503: Traversal , get specific , get the specific flight number and flight date, construct List structure variables , traverse , find and Data with the same flight number is constructed based on the cabin space and number of seats booked in the specific data. data structure and put it into Until all the The data with the same flight number ends the traversal ,by The flight number and flight date combination string is key, construct The structure is value, and Assignment , put the constructed key value and value into , continue to traverse , repeat the operation until the traversal is completed.

[0036] S504: Traversal , get specific , the structure contains List variable of structure ,in Indicates the specific flight class. Indicates the cumulative number of flights with the same flight class. Indicates the cumulative passenger load factor of the same class of the same flight, traversing , query and The specific flight plan data with the same flight number and flight date, obtain the flight plan number of the specific flight plan data , traverse , get the The flight number is the same and the flight schedule number attribute is the same Consistent specific airline meal guarantee airline historical data, traversal , obtain the data that is consistent with the flight number and flight date of the specific airline’s historical data of catering support, and Accumulate +1 for the corresponding cabin Accumulate the passenger load factor and complete the traversal , the accumulated Structural data into , traverse , start calculating the historical average passenger load factor for a specific cabin , the specific calculation method is: by The combined string of flight number and flight date is key, and the query ,get ,renew Average passenger load factor of different classes in the , repeat the operation until the traversal is completed.

[0037] S505: Traversal , get specific , construct variables , used to represent the total number of historical service flights, construct variables , used to indicate the number of flights with complaints in historical service flights, traversing , query and The specific flight plan data with the same flight number and flight date, obtain the flight plan number of the specific flight plan data , traverse , get the The flight number is the same and the flight schedule number attribute is the same Consistent specific airline meal guarantee airline historical data, Add 1 to determine whether the attribute "Whether the airline has complaints" in the historical data of the specific airline catering guarantee is "yes". If so, proceed Add 1 operation, traversal completed , calculate the historical complaint rate , the specific method is as follows: by The combined string of flight number and flight date is key, and the query ,get ,renew Historical complaint rate data, continue to traverse , repeat the operation until the traversal is completed.

[0038] S506: Traversal , build a structure containing List structure variables ,in Indicates the specific cabin space. Indicates the type of meal, It is expressed as the number of the same type of meals in the same dining car. , construct variables , indicating the number of flights on which the vehicle has loaded meals, initially 0, traversing , query and The specific flight plan data with the same flight number and flight date, obtain the start time and end time of the flight meal guarantee plan in the specific flight plan data , camera position, continue to traverse , get the start time of the meal guarantee plan for specific flight plan data , camera position, traverse according to the two camera position data , get the travel time between the two ,when , it is considered that the catering requirements can be met, and the flight number and flight date are used as the key value to query , update the value in , will traverse , statistical summary , , value, Perform the addition operation. Continue traversal , continue to follow up on the flight schedule data The judgment, when , it is considered that the same dining car has reached the upper limit of loading. It is a user-adjustable constant value used to control the maximum number of flights that each dining car can carry. End traversal , end the traversal .

[0039] S507: Get the , traverse from the beginning , get specific , obtain the catering requirements entered by the airline , according to the cabin and meal type in the catering requirements, Query the number of cabin types and meal types that meet the requirements. The flight number and flight date are combined as keys to query , get the corresponding Structural data, assuming that the number of meals of the same type in a specific cabin is , then the proportion of the same catering type in the same dining car and cabin is The calculation method is: The different classes of space will be calculated Update and put in data of different cabin types , complete the pair Continue to traverse from the beginning , skip the flights that have been marked as having been assigned catering vehicles, and repeat the above steps until all flights are calculated.

[0040] S508: Traversal , get specific ,by The flight number and flight date are keys, and the query , get the corresponding Structural data, according to Flight number and flight date, query traversal , get the corresponding maximum number of passengers , assuming that the specific cabin meal quantity is ,from The historical passenger load factor of a specific cabin obtained from ,from Get the historical complaint rate of flights ,from Get the number of seats booked for a specific cabin on a specific flight ,from Get the proportion of the same catering type in the same dining car and cabin ,but The specific calculation method is as follows: renew middle ,Will Update to In property; S509: The data in the update is synchronized to the blockchain, and the traversal , get specific , and then establish a link with the blockchain platform to The flight number and flight date are used as the combined query key to obtain the specific ,if exist Attributes, then In Data updated to and will In The attribute is incremented by 1. The flight number and flight date are used as the combined query key, and the specific data is obtained through the blockchain query interface again to determine the specific data. Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned.

[0041] S6, obtain the confirmation status of the catering company's catering department and update its own catering status input data, retrieve and obtain the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the catering department's signature, and update the catering production status to the collaborative operation structure variables and the on-chain storage variables. The specific steps are as follows: S601: Obtain the data that the catering company's catering department needs to input to confirm the status and update its own catering status. Specifically, the catering company's catering department needs to enter the flight number that needs to confirm the status and update the catering status. , Flight date , Signature to confirm the entered meal requirements and meal quantities , Meal preparation process status record , The variable is a string, which records the process status of the meal preparation department of the airline catering company making the meal for the flight. Is a string structure, which is a pair Data and The one-way hash calculation of the combined data is used, and the data obtained by encrypting the one-way hash value using the private key of the catering company's catering production department is used to prove that it is indeed confirmed by the catering company's catering production department and there is no forgery or tampering.

[0042] S602: Retrieve specific information based on the input from the catering production department of the airline catering company and Specific through and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific .

[0043] S603: Yes Use the public key of the catering company's catering department to verify the data. Decrypt it, get the specific one-way hash value, and then calculate and Combine the one-way hash value of the data and compare the two. If they are consistent, it is passed. Otherwise, the data entry of the catering production department of the airline catering company is cancelled. , Data updated to and and respectively and In The attribute is incremented by 1.

[0044] S604: Update and Data. The processing method is consistent with S404.

[0045] S7: Obtain the confirmation status of the catering department of the airline catering company and update the input data of its own catering process record, query and obtain the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the signature of the catering department, and update the catering process record to the collaborative operation structure variables and the on-chain storage variables. The specific steps are as follows: S701: Obtain the data that the catering department of the airline catering company needs to input to confirm the status and update its own meal preparation process records. Specifically, the catering department of the airline catering company needs to enter the flight number that needs to confirm the status and update the meal preparation process records. , Flight date , Signature confirming the meal preparation process by the in-flight catering department , Meal preparation process status record , The variable is a string, which records the process status of the catering department of the airline catering company distributing the meals for the flight. Is a string structure, which is a pair The data is calculated by a one-way hash, and the one-way hash value is encrypted using the private key of the catering department of the airline catering company to prove that it is indeed confirmed by the catering department of the airline catering company and there is no forgery or tampering.

[0046] S702: Retrieve specific information based on the input from the catering department of the airline catering company and Specific through and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific .

[0047] S703: Yes Use the public key of the catering department of the airline catering company to verify the data. Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the airline catering company is compared. If they are consistent, the data entry is passed. Otherwise, the data entry of the airline catering company's catering department is cancelled. , Data updated to and and respectively and In The attribute is incremented by 1.

[0048] S704: Update and Data. The processing method is consistent with S404.

[0049] S8, obtain the data of the on-site support status confirmed by the flight crew of the catering support flight, retrieve and obtain the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the flight crew signature, and update the catering support completion status to the collaborative operation structure variables and the on-chain storage variables. The specific steps are as follows: S801: Get the data of the crew confirming the on-site catering status of the flight. This part of the data will be signed and confirmed by the crew using the airline's business system, and the airline's business system will enter the flight number , Flight date , Confirmation signature for on-site catering status , Is a string structure, which is a pair The one-way hash calculation of the data is used, and the data obtained by encrypting the one-way hash value using the airline's private key is used to prove that it is indeed confirmed by the airline and there is no forgery or tampering.

[0050] S802: Retrieve specific information based on the airline's input and Specific through and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific .

[0051] S803: Yes The data is verified using the airline's public key Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the data is compared with the two. If they are consistent, the data entry is passed. Otherwise, the airline data entry is cancelled. Data updated to and and respectively and In The attribute is incremented by 1.

[0052] S804: Update and Data. The processing method is consistent with S404.

[0053] Embodiment 2, as Figure 3 As shown, the blockchain-based airport catering multi-party collaborative system provided by the embodiment of the present invention includes a data analysis module 1, a blockchain operation module 2, an airline catering collaborative processing module 3, a meal demand estimation module 4, a basic data module 5, a data storage processing module 6, an interface processing module 7, and a security control module 8; Data parsing module 1 is used to access flight plans, catering airline history, catering settlement history, contract airlines, historical flight cabin occupancy rate, flight reservations, and aircraft travel time relationship matrix data through Webservice, RestfulAPI, MQ message, FTP, and ODBC interface, and parse the above data using XML to data object, JSON to data object, and deserialization technology; Blockchain operation module 2 is used to construct and initialize the variable structures of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, and number of refusal of airline catering guarantee, and calculate the trust number and trust level of airline. The airline catering collaborative processing module 3 is used to construct the airline catering collaborative operation structure variables, construct the on-chain storage structure variables according to the flight trust level, initialize the airline catering collaborative operation structure variables and the on-chain storage structure variables according to the flight plan and contract, and perform the on-chain storage structure variable on-chain operation; Meal demand estimation module 4 is used to obtain the type, quantity, and additional requirements of catering for different cabins of specific flights of airlines, query the collaborative operation structure variables and the variables stored on the chain, verify the legitimacy of the signature of the airline entering the catering demand for cabins, and update the collaborative operation structure variables and the variables stored on the chain based on version control; Basic data module 5, used to obtain historical flight cabin occupancy rate data, construct the intermediate calculation variable structure of the flight cabin meal quantity demand, initialize the specific flight specific cabin booking data, calculate the specific flight specific cabin historical occupancy rate, calculate the specific flight historical complaint rate, calculate the relationship between flights during meal delivery, calculate the overall proportion of meal types in different cabins of a specific flight, calculate the number of meals required for different cabins of a specific flight, and update the collaborative operation structure variables and the on-chain storage variables; Data storage and processing module 6, used to obtain the confirmation status of the catering company's catering department and update its own catering status input data, retrieve and obtain the collaborative operation structure variables and the chain storage variables, verify the legitimacy of the catering department's signature, and update the catering status to the collaborative operation structure variables and the chain storage variables; Interface processing module 7, used to obtain the confirmation status of the catering department of the airline catering company and update the input data of its own catering process record, query and obtain the collaborative operation structure variables and the chain storage variables, verify the legitimacy of the signature of the catering department, and update the catering process record to the collaborative operation structure variables and the chain storage variables; The safety control module 8 is used to obtain the data of the on-site support status confirmed by the flight crew of the catering support flight, retrieve and obtain the collaborative operation structure variables and the on-chain storage variables, verify the legitimacy of the flight crew signature, and update the catering support completion status to the collaborative operation structure variables and the on-chain storage variables.

[0054] It can be seen from the above embodiments that the present invention proposes a method and system for multi-party collaboration in airport catering security based on blockchain technology, which can significantly improve the efficiency of trusted business collaboration between airlines and catering companies, provide airlines and catering companies with a unified multi-party collaboration system for catering security, and effectively reduce the occurrence of payment rejections due to inconsistent accounting between the two parties under traditional methods. At the same time, the present invention can, on the basis of meeting the needs of catering business collaboration, provide an on-chain storage structure optimization method that can take into account both blockchain performance and storage capacity according to the trust level of the airline, so that the system can operate stably for a long time without worrying too much about the problem of poor blockchain performance due to large storage capacity.

[0055] The present invention is aimed at the field of civil aviation catering service, and directly addresses the problems existing in traditional catering services, such as low multi-party collaboration efficiency, lack of mutual trust, communication, and high confirmation costs. It can reduce the occurrence of refusal to pay in catering services and significantly improve the profit level of catering companies. At present, there are 281 transport airports and 82 transport airlines in the national civil aviation. Many airlines and airports have their own catering service branches and subsidiaries, which can be promoted as customers. There is a large market space, and it is expected to generate large commercial benefits. At the same time, after the system of the present invention is put into production, it can bring revenue improvement to catering companies. Taking a domestic airport catering company with a throughput of 20 million as an example, its catering service for a large airline alone will bring more than 2 million refusal to pay losses each year. After the system of the present invention is put into operation, the refusal to pay phenomenon will be significantly reduced.

[0056] The present invention makes full use of the anti-tampering and anti-repudiation characteristics of blockchain technology, proposes a method and system for multi-party collaboration in airport catering based on blockchain technology, builds a method for efficient and reliable collaboration of multi-party catering involving airlines and catering companies, and provides an optimization method for the on-chain storage structure that can take into account both blockchain performance and storage capacity, so that the system can operate stably for a long time without worrying too much about the problem of poor blockchain performance due to large storage capacity. The present invention combines the specific business characteristics of catering, deeply applies blockchain technology, optimizes the structure according to the business, and fills the technical gap in this business field.

[0057] In the traditional civil aviation catering business, the cooperation mode of each participant relies on a relatively primitive mode. The airline first signs a service contract with the catering company to agree on the details of the catering service. In the subsequent catering service process of specific flights, the airline will first send the catering company specific flight catering service requirements through telephone, instant messaging, etc. when the flight is in the planning stage. Then, the catering company's dispatch department drives the catering preparation department to prepare meals based on these requirements and the estimated number of passengers and other flight conditions that need to be guaranteed through walkie-talkies, telephones, and instant messaging. It drives the catering department to prepare meals based on flight dynamics. After completion, the caterer will confirm and sign with the crew of the specific flight to complete the meal service guarantee for the flight. In this guarantee process, the different participants rely on various forms of information transmission methods, and the understanding of the entire process of airline catering guarantee requires repeated information transmission, which has low coordination efficiency. At the same time, due to the use of non-standard information transmission methods, multiple parties lack a credible basis. When problems such as flight catering delays, catering errors, and inconsistencies in the ledgers of both parties occur, it is often difficult to conduct a rapid investigation and confirmation of responsibilities between the airline and the catering company, and between different departments of the catering company. This often leads to the airline's refusal to pay for specific flights, which will reduce the profits of the catering company. After adopting the technical solution of the present invention, there will be a trusted collaboration system based on blockchain technology between the catering company and the airlines. Different airlines will uniformly and standardizedly enter the catering requirements, and the airline crew will confirm the final service and be able to view the catering situation of each flight in real time through the system; the catering company can also unify the collaboration between different internal departments, thereby improving the collaborative efficiency of multi-party catering. At the same time, because all collaborative data are reliably stored based on blockchain technology, when problems occur, the responsibility can be quickly determined based on the data of mutual trust among multiple parties, which can significantly reduce the phenomenon of airline refusal to pay and increase the profits of the catering company.

[0058] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered within the protection scope of the present invention.

Claims

1. A blockchain-based multi-party collaborative method for airport catering security, characterized in that: The method comprises the following steps: S1, access flight plans, airline catering history, catering settlement history, contract airlines, historical flight cabin occupancy rate, flight booking, and aircraft travel time relationship matrix data, and use XML to data object, JSON to data object, and deserialization technology to parse the above data; S2, construct and initialize the variable structure of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, number of refusal of airline catering guarantee, and calculate the trust number and trust level of airline; S3, construct the structural variables of the coordinated operation of in-flight catering support; S4, obtain the type, quantity, and additional requirements of catering for different cabins on specific flights of airlines, query the collaborative operation structure variables and the variables stored on the chain, and verify the legitimacy of the signature of the airline's entry of catering requirements; S5, obtain historical flight cabin occupancy rate data and construct an intermediate calculation variable structure for flight cabin catering quantity requirements; S6, obtaining the confirmation status from the catering company's catering department and updating its own catering status input data; S7, obtain the confirmation status of the catering department of the airline catering company and update the input data of its own catering process record, query and obtain the collaborative operation structure variables and the on-chain storage variables; S8, verify the legitimacy of the flight crew signature, and update the completion status of the flight catering service to the collaborative operation structure variables and the on-chain storage variables.

2. The blockchain-based airport catering multi-party collaboration method according to claim 1 is characterized in that: In step S1, the data is parsed by using XML to data object, JSON to data object, and deserialization technology, including: the parsed flight plan data is set as , the parsed airline catering service historical data is processed by data attribute replication and set as , the parsed airline meal security settlement history data is processed by data attribute copying and set as , after parsing the contract airline data, the data attributes are copied and set to , the parsed historical flight cabin occupancy rate data is processed by data attribute copying and set as , the parsed flight booking data is processed by data attribute copying and set to , the analyzed stand travel time relationship matrix data is set as .

3. The blockchain-based airport catering multi-party collaboration method according to claim 1 is characterized in that: In step S2, the variable structures of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, and number of refusal of airline catering guarantee are constructed and initialized, and the airline trust number and trust level are calculated, including: S201, construct airline trust level structure variables , used to record the trustworthiness of different airlines; construct the cumulative service time structure variable of airlines providing catering services , used to record the cumulative service time of different airlines; construct the flight quantity structure variable of airlines providing catering services , used to record the cumulative number of flights with in-flight catering service for different airlines; construct the structural variable of the number of historical complaints of airlines with in-flight catering service , used to record the number of complaints about flights of different airlines; construct the structural variable of the number of airlines refusing to pay for catering services , used to record the number of flights refused by different airlines; S202, obtain , traverse , using the airline name in the single contract airline data as the key value and 0 as the value, and putting the constructed data into , complete the initialization; take the airline name in the obtained single data as the key value, and the accumulated service time in the obtained single data as the value, and put the constructed data into ,Finish Traverse; S203, obtain , traverse , get a single specific airline catering guarantee historical data, use the airline name in the single historical data as the key value, and query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1. If the airline complaint attribute in the acquired single airline food guarantee history data is yes, the airline name in the acquired single history data is used as the key value to query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1 to complete the traversal. ; S204, obtain , traverse , get a single specific airline meal guarantee settlement history record. If the specific record has the attribute of whether to refuse payment set to yes, use the airline name in the single history record as the key value to query If the return value is null, put 1 as the value If the returned value is not null, the return value is incremented by 1 to complete the traversal. ; S205, obtain , traverse , get specific records, and query them separately using the key values ​​in the specific records , , , , and get , , , ,in Indicates the accumulated service time of the airline. Indicates the cumulative number of flights with guaranteed food for the airline. Indicates the number of flights complained about by the airline. The airline's credibility number is The calculation is as follows: in These are user-adjustable parameters used to adjust the impact of different elements on the calculation of the airline's credibility number; Airline Trust Rating , calculated as follows: The calculated Put it as value , traversal completed .

4. The blockchain-based airport catering guarantee multi-party collaboration method according to claim 1 is characterized in that: In step S3, the flight catering support collaborative operation structure variables are constructed, including: S301: Construct the coordinated operation structure variables of the in-flight catering support. ； in The number of flights served by the airline catering company, Indicates around The flight catering support collaborative operation structure variables constructed for each flight, ,in Indicates the flight number. Indicates the flight date, Indicates the airline company, Indicates the model. Indicates the overall status of the flight. Indicates flight route. Indicates the catering requirements for different cabins entered by the airline. Indicates the signature of the airline entering the catering requirements for different cabins, used to prove that it is entered for a specific airline. Indicates the estimated number of meals required for the flight. Indicates the signature of the catering department, used to confirm the entered catering requirements and catering quantities. It indicates the record of the meal preparation process by the airline catering department. It indicates the signature confirmation of the catering department on the meal preparation process. Indicates the meal preparation process record of the airline catering department. Indicates the signature confirmation of the airline crew. Indicates the update version number, which is used to solve the problem of update loss that may occur when multiple parties write; S302: Construct the storage structure that needs to be chained. ， ； Indicates around The on-chain collaborative operation structure variables constructed by each flight, The structure of Confirm, as follows: S303: Acquisition , traverse , get specific single flight plan data, get , traverse , obtain the specific single contract airline data, determine whether the airline attributes in the flight plan data are consistent with the airline attributes in the contract airline data, and obtain , using the airline name as the key to obtain the specific trust level of the airline, and construct The structure assigns the flight number, flight date, airline, aircraft type, flight status, and flight route attributes in the flight plan data to ,Will In Set to 1, Put in , construct the corresponding structure according to the specific trust level of the airline obtained , assign the flight number, flight date, airline, aircraft type, flight status, and flight route attributes in the flight plan data to ,Will In Set to 1, Put in , traversal completed ; S304: The data is stored in the blockchain and will be stored in the form of a key-value structure on the blockchain First, establish a trusted link with the blockchain management platform through the access key and development kit granted by the blockchain management platform, and then start traversing Data, get specific , get In and , combine them into a string, call the blockchain write interface, and pass in the constructed combined string as the key. As value, upload the data to the blockchain and complete the traversal .

5. The blockchain-based airport catering multi-party collaboration method according to claim 1 is characterized in that: In step S4, the catering type, quantity, and additional requirements of different cabins of the airline's specific flights are obtained, the collaborative operation structure variables and the chain storage variables are queried, and the legitimacy of the signature of the airline's entry of the cabin catering requirements is verified, including: S401: Obtain the data that the airline needs to enter; the airline enters the flight number that needs catering , Flight date , Catering requirements for different cabins And signature for catering request , ； To meet the specific catering requirements for different cabins, ,in, Indicated as a specific cabin, Indicates the type of meal, It represents the number of meals required. When this variable is -1, it means that the airline has not specified the number of people. Indicated as additional requirements; S402: Retrieve specific information based on the airline's input and ,pass and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific ; S403: Yes Data is authenticated using the airline-specific public key Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the two is compared. If they are consistent, the data entry of the airline is cancelled. The catering requirements of different cabins are Data updated to and and respectively and In The attribute is incremented by 1; S404: Update and Data, through and Traversal , when traversing the current specific data flight number and date and and If the data is consistent, the specific data currently traversed is determined. Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned; a link with the blockchain platform is established. and Combined into a query key, obtain specific data through the blockchain query interface to determine the specific data Is it equal to In The value is reduced by 1. If it is equal, The data is updated to the specific data traversed. If it is not equal, the update is abandoned.

6. The blockchain-based airport catering multi-party collaboration method according to claim 1 is characterized in that: In step S5, historical flight cabin occupancy rate data is obtained, and the intermediate calculation variable structure of the flight cabin catering quantity demand is constructed, including: S501: Get historical flight cabin occupancy rate data , get flight booking data , get the historical data of airlines that provide food service , get flight schedule data , get the stand travel time relationship matrix data , obtain the coordinated operation structure variables of the airline catering support , get the storage structure that needs to be on-chain ; S502: Construct variable structure , used to store the intermediate calculation value of each flight that needs to calculate the number of meals required for different cabins on the flight. It is a hash table structure. The key value is a string consisting of the flight number and the flight date. The value value is structure; S503: Traversal , get specific , get the specific flight number and flight date, construct List structure variables , traverse , find and Data with the same flight number is constructed based on the cabin space and number of seats booked in the specific data. The data structure is placed in Until all the The data with the same flight number ends the traversal ,by The flight number and flight date combination string is key, construct The structure is value, and Assignment , put the constructed key value and value into , continue to traverse , repeat the operation until the traversal is completed; S504: Traversal , get specific , the structure contains List variable of structure , traverse , query and The specific flight plan data with the same flight number and flight date, obtain the flight plan number of the specific flight plan data , traverse , get the The flight number is the same and the flight schedule number attribute is the same Consistent specific airline meal guarantee airline historical data, traversal , obtain the data that is consistent with the flight number and flight date of the specific airline’s historical data of catering support, and Accumulate +1 for the corresponding cabin Accumulate the passenger load factor and complete the traversal , the accumulated Structural data into , traverse , start calculating the historical average passenger load factor for a specific cabin , the specific calculation method is: by The combined string of flight number and flight date is key, and the query ,get ,renew Average passenger load factor of different classes in the , repeat the operation until the traversal is completed; S505: Traversal , get specific , construct variables , get the flight schedule number of the specific flight schedule data , traverse , get the The flight number is the same and the flight schedule number attribute is the same Consistent specific airline meal guarantee airline historical data, Add 1 to determine whether the complaint attribute of the specific airline in the historical data of the airline catering guarantee is yes. If yes, proceed Add 1 operation, traversal completed , calculate the historical complaint rate , the specific method is as follows: by The combined string of flight number and flight date is key, and the query ,get ,renew Historical complaint rate data, continue to traverse , repeat the operation until the traversal is completed; S506: Traversal , build a structure containing List structure variables ,in Indicates the specific cabin space. Indicates the type of meal, It is expressed as the number of the same type of meals in the same dining car. , build variables ; S507: Get the , traverse from the beginning , get specific , obtain the catering requirements entered by the airline , according to the cabin and meal type in the catering requirements, Query the number of cabin types and meal types that meet the requirements. The flight number and flight date are combined as keys to query , get the corresponding Structural data, assuming that the number of meals of the same type in a specific cabin is , then the proportion of the same catering type in the same dining car and cabin is The calculation method is: S508: Traversal , get specific ,by The flight number and flight date are keys, and the query , get the corresponding Structural data, according to Flight number and flight date, query traversal , get the corresponding maximum number of passengers , assuming that the specific cabin meal quantity is ,from The historical passenger load factor of a specific cabin obtained from ,from Get the historical complaint rate of flights ,from Get the number of seats booked for a specific cabin on a specific flight ,from Get the proportion of the same catering type in the same dining car and cabin ,but The specific calculation method is as follows: renew middle ,Will Update to In property; S509: The data in the update is synchronized to the blockchain, and the traversal , get specific , and then establish a link with the blockchain platform.

7. The blockchain-based airport catering multi-party collaboration method according to claim 1 is characterized in that: In step S6, the confirmation status of the food preparation department of the airline catering company is obtained and the input data of the food preparation status of the airline catering company is updated, including: S601: Obtain the data required for the catering company's catering production department to confirm the status and update its own catering production status; the catering company's catering production department needs to enter the flight number that needs to confirm the status and update the catering production status , Flight date , Signature to confirm the entered meal requirements and meal quantities , Meal preparation process status record , The variable is a string, which records the process status of the meal preparation department of the airline catering company making the meal for the flight. Is a string structure, which is a pair Data and One-way hash calculation of the combined data, and encryption of the one-way hash value using the private key of the catering company's food production department; S602: Retrieve specific information based on the input from the catering production department of the airline catering company and ,pass and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific ; S603: Yes The data is verified using the public key of the catering company's catering department. Decrypt it, get the specific one-way hash value, and then calculate and Combine the one-way hash value of the data and compare the two. If they are consistent, it is passed. Otherwise, the data entry of the catering production department of the airline catering company is cancelled. , Data updated to and and respectively and In The attribute is incremented by 1; S604: Update and data.

8. The blockchain-based airport catering multi-party collaboration method according to claim 1 is characterized in that: In step S7, the confirmation status of the catering department of the airline catering company is obtained and the input data of the catering process record of the airline catering company is updated, and the collaborative operation structure variables and the on-chain storage variables are queried and obtained, including: S701: Obtain the data required for the catering department of the airline catering company to confirm the status and update its own catering process records; S702: Retrieve specific information based on the input from the catering department of the airline catering company and , S703: Yes The data is verified using the public key of the catering department of the airline catering company. Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the airline catering company is compared. If they are consistent, the data entry is passed. Otherwise, the data entry of the airline catering company's catering department is cancelled. , Data updated to and and respectively and In The attribute is incremented by 1; S704: Update and data.

9. The blockchain-based airport catering multi-party collaboration method according to claim 1 is characterized in that: In step S8, the legitimacy of the flight crew signature is verified, and the completion status of the flight catering guarantee is updated to the collaborative operation structure variable and the on-chain storage variable, including: S801: Obtain the data of the on-site catering status confirmed by the flight crew of the catering service flight; S802: Retrieve specific information based on the airline's input and ,pass and Traversal , when the current traversal Flight number and date and and If they remain consistent, the traversal is complete ,Will As a variable that meets the requirements, a link with the blockchain platform is then established, and Combine into a query key and obtain the specific ; S803: Yes The data is authenticated using the airline's public key Decrypt it, get the specific one-way hash value, and then calculate The one-way hash value of the data is compared with the two. If they are consistent, the data entry is passed. Otherwise, the airline data entry is cancelled. Data updated to and and respectively and In The attribute is incremented by 1; S804: Update and data.

10. A blockchain-based airport catering multi-party collaborative system, characterized by: The system implements the blockchain-based airport catering guarantee multi-party collaboration method as described in any one of claims 1 to 9, and the system includes: The data parsing module (1) is used to access flight plans, catering airline history, catering settlement history, contract airlines, historical flight cabin occupancy rates, flight reservations, and aircraft travel time relationship matrix data, and parse the above data using XML to data object, JSON to data object, and deserialization technology; Blockchain operation module (2), used to construct and initialize the variable structures of airline trust level, cumulative service time of airline catering guarantee, number of flights of airline catering guarantee, number of historical complaints of airline catering guarantee, number of refusal of airline catering guarantee, and calculate the trust number and trust level of airline catering guarantee; The in-flight catering collaborative processing module (3) is used to construct the in-flight catering collaborative operation structure variables; The meal demand estimation module (4) is used to obtain the meal type, quantity, and additional requirements of different cabins on specific flights of airlines, query the collaborative operation structure variables and the variables stored on the chain, and verify the legitimacy of the signature of the airline's entry of the meal demand; Basic data module (5), used to obtain historical flight cabin occupancy rate data and construct an intermediate calculation variable structure for flight cabin catering quantity requirements; The data storage and processing module (6) is used to obtain the confirmation status of the food preparation department of the airline catering company and update its own food preparation status input data; The interface processing module (7) is used to obtain the confirmation status of the catering department of the airline catering company and update the input data of its own catering process record, and query and obtain the collaborative operation structure variables and the chain storage variables; The safety control module (8) is used to verify the legitimacy of the flight crew's signature and update the completion status of the flight catering guarantee to the collaborative operation structure variables and the on-chain storage variables.

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