Aviation logistics management system based on big data

Abstract

The invention discloses an aviation logistics management system based on big data, which comprises an analysis processing module, a management control module and an acquisition statistics module, and is characterized in that the analysis processing module is in network connection with the management control module, and the management control module is in network connection with the acquisition statistics module; the analysis processing module is in network connection with the acquisition statistics module, the analysis processing module is used for carrying out analysis control processing on the aviation logistics, the management control module is used for carrying out optimization management control on the aviation logistics, and the acquisition statistics module is used for carrying out acquisition statistics processing on aviation logistics data information. The analysis processing module comprises an index design module, a weight analysis module and an evaluation processing module, the index design module is in network connection with the weight analysis module, and the weight analysis module is in network connection with the evaluation processing module. The system has the characteristics of efficient management control and intelligent analysis processing.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to an aviation logistics management system based on big data. Background Art

[0002] In recent years, my country's civil aviation industry has achieved rapid development, with the volume of civil aviation passenger transport and cargo and mail transport steadily increasing. The scale of the industry ranks second in the world, and its contribution to the growth of world civil aviation exceeds 20%. my country is transforming from a major aviation transport country to a strong civil aviation country. At present, the digital economy with information technology as the main carrier is accelerating its popularization and application, reshaping the industrial structure and competition pattern. my country's civil aviation is actively promoting the quality-oriented development path of digitalization, intelligence and wisdom in the field of aviation transportation, and has successively proposed the construction of "smart airports" and "smart civil aviation". Through scientific and technological innovation and management innovation, my country's civil aviation is promoted to shift to the direction of high-quality development of civil aviation that focuses on quality, efficiency and benefits. However, the phenomenon of "focusing on passengers and neglecting cargo" in the civil aviation industry for a long time is relatively serious, and there are many links, many subjects, and complex processes in air logistics, which lags behind in information construction. It seriously restricts the high-quality development of my country's aviation logistics industry. Therefore, it is very necessary to design an aviation logistics management system based on big data for efficient management control and intelligent analysis and processing. Summary of the invention

[0003] The purpose of the present invention is to provide an aviation logistics management system based on big data to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: an aviation logistics management system based on big data, comprising: an analysis and processing module, a management control module and a collection and statistics module, the analysis and processing module is connected to the management control module through a network, the management control module is connected to the collection and statistics module through a network, the analysis and processing module is connected to the collection and statistics module through a network, the analysis and processing module is used to perform analysis and control on aviation logistics, the management control module is used to perform optimization management and control on aviation logistics, and the collection and statistics module is used to perform collection and statistics on aviation logistics data information.

[0005] According to the above technical solution, the analysis and processing module includes an indicator design module, a weight analysis module and an evaluation processing module. The indicator design module is network-connected to the weight analysis module, and the weight analysis module is network-connected to the evaluation processing module. The indicator design module is used to perform indicator design management for air logistics, the weight analysis module is used to perform weight analysis processing on air logistics indicators, and the evaluation processing module is used to perform evaluation and analysis processing on air logistics management.

[0006] According to the above technical solution, the management control module includes a logical framework module, a functional management module and a supervisory control module. The logical framework module and the functional management module are network-connected, and the functional management module and the supervisory control module are electrically connected. The logical framework module is used to perform air logistics logical framework design management, the functional management module controls and manages operation service functions, and the supervisory control module is used to supervise and control air logistics.

[0007] According to the above technical solution, the collection and statistics module includes a collection and sorting module and a statistical query module. The collection and sorting module is used to collect and sort the aviation logistics information, and the statistical query module is used to perform statistical query processing on the service data information.

[0008] According to the above technical solution, the operation method of the aviation logistics management system based on big data includes:

[0009] Step S1: Design indicators for the airport aviation logistics platform and analyze the weights of the indicators that have been designed;

[0010] Step S2: using fuzzy comprehensive evaluation method to conduct comprehensive evaluation on the airport's aviation logistics platform system;

[0011] Step S3: Further construct the logical framework of the airport aviation logistics platform, and carry out functional management and logistics supervision and control;

[0012] Step S4: Collect the operation and processing data information of the airport aviation logistics platform for users to conduct statistical inquiries.

[0013] According to the above technical solution, step S1 further includes the following steps:

[0014] Step S11: Analyze and process the airport aviation logistics platform through indicator design, and divide the indicators into external environment and internal platform indicators, wherein the external environment indicators include logistics data information and hardware interface data information, and the internal platform indicators include the electronic waybill utilization rate, data update frequency, logistics data sharing frequency and warehouse equipment data;

[0015] Step S12: After completing the design of the airport aviation logistics platform index, the hierarchical analysis method is used to determine the weight of each aviation logistics platform index data system. Specifically, the importance of the external environment and internal platform indicators is compared with each other. After the comparison matrix is ​​formed by the set expert scoring method, the consistency index test is performed on the comparison matrix, and the maximum eigenvalue λ of the comparison matrix is ​​obtained by analysis. max After that, the consistency index Z is calculated, and the formula is as follows:

[0016]

[0017] Where n is the order data set in the consistency test RI value table;

[0018] Step S13: After calculating the consistency index Z of the aviation logistics platform, further calculate the weight ratio data X of each index data system of the aviation logistics platform, the formula is:

[0019] According to the above technical solution, step S2 further includes:

[0020] A questionnaire survey was conducted among airport cargo terminals, freight forwarders, airline cargo departments, logistics companies and professionals in air logistics through WeChat, telephone and email. After obtaining the evaluation results, the fuzzy comprehensive evaluation method was used to obtain the evaluation result data of each indicator of the airport air logistics platform based on the design results of the airport air logistics platform indicators.

[0021] According to the above technical solution, step S3 further includes the following steps:

[0022] Step S31: The logic framework of the airport aviation logistics platform is constructed through five layers: infrastructure layer, digital platform layer, business management layer, production operation layer, and user operation layer. The real-time perception layer relies on sensors, electronic tags, GPS, and camera perception devices distributed in various links of the air cargo flow process to obtain data information, and transmits data through the Internet of Things, the Internet, and 5G communications. The data sharing layer transmits various data scattered in the upstream and downstream of the aviation logistics supply chain to the aviation logistics data platform, and collects data obtained from government departments and financial institutions through open interfaces to form a comprehensive data source for aviation logistics information;

[0023] Step S32: Connect the airport aviation logistics data with customs, taxation, insurance, logistics park, and comprehensive transportation agencies through blockchain, and store the data transmitted after the connection in blockchain nodes to achieve resource sharing and business collaboration;

[0024] Step S33: further connect the import and export goods information with the customs supervision system to provide the customs with the status information of the import and export goods, and realize the logistics process supervision of the port-supervised goods and the supervision and control of special goods.

[0025] According to the above technical solution, step S4 further includes the following steps:

[0026] Step S41: collect and organize the real-time operation data information of the airport aviation logistics management platform, and transmit it to the workbench for management personnel to review and analyze;

[0027] Step S42: Provide the regulatory authorities with information on flights, cargo volume, cargo type, and cargo flow, including flight statistics, cargo source statistics, cargo type statistics, cargo flow statistics, manifest / waybill query, cargo customs clearance status query, and security inspection status query, so that they can fully understand the development status of the aviation logistics industry.

[0028] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, by providing an analysis and processing module, a management and control module and a collection and statistics module, compares the importance of aviation logistics platform indicators that are difficult to quantify, and more reasonably solves the quantitative processing process of qualitative problems, thereby improving the feasibility and reliability of decision-making management of the aviation logistics platform, and enables air logistics platform managers to obtain effective and accurate analysis and processing basis for the problems and causes existing in the construction of the aviation logistics platform through the weights of the aviation logistics platform indicator data system. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0030] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] See also Figure 1 The present invention provides a technical solution: an aviation logistics management system based on big data, including: an analysis and processing module, a management control module and a collection and statistics module, the analysis and processing module is connected to the management control module through a network, the management control module is connected to the collection and statistics module through a network, the analysis and processing module is connected to the collection and statistics module through a network, the analysis and processing module is used to analyze and control aviation logistics, the management control module is used to optimize management and control of aviation logistics, and the collection and statistics module is used to collect and statistically process aviation logistics data information.

[0033] The analysis and processing module includes an indicator design module, a weight analysis module and an evaluation processing module. The indicator design module is connected to the weight analysis module through a network, and the weight analysis module is connected to the evaluation processing module through a network. The indicator design module is used to perform indicator design management for air logistics, the weight analysis module is used to perform weight analysis and processing on air logistics indicators, and the evaluation processing module is used to perform evaluation and analysis on air logistics management.

[0034] The management and control module includes a logical framework module, a functional management module and a supervisory control module. The logical framework module and the functional management module are network connected, and the functional management module and the supervisory control module are electrically connected. The logical framework module is used to perform design and management of the air logistics logical framework, the functional management module controls and manages the operation service functions, and the supervisory control module is used to supervise and control air logistics.

[0035] The collection and statistics module includes a collection and sorting module and a statistical query module. The collection and sorting module is used to collect and sort aviation logistics information, and the statistical query module is used to perform statistical query processing on service data information.

[0036] A method for operating an aviation logistics management system based on big data includes:

[0037] Step S1: Design indicators for the airport aviation logistics platform and analyze the weights of the indicators that have been designed;

[0038] Step S2: using fuzzy comprehensive evaluation method to conduct comprehensive evaluation on the airport's aviation logistics platform system;

[0039] Step S3: Further construct the logical framework of the airport aviation logistics platform, and carry out functional management and logistics supervision and control;

[0040] Step S4: Collect the operation and processing data information of the airport aviation logistics platform for users to conduct statistical inquiries.

[0041] Step S1 further comprises the following steps:

[0042] Step S11: Analyze and process the airport aviation logistics platform through indicator design, and divide the indicators into external environment and internal platform indicators, wherein the external environment indicators include logistics data information and hardware interface data information, and the internal platform indicators include the electronic waybill utilization rate, data update frequency, logistics data sharing frequency and warehouse equipment data;

[0043] Step S12: After completing the design of the airport aviation logistics platform index, the hierarchical analysis method is used to determine the weight of each aviation logistics platform index data system. Specifically, the importance of the external environment and internal platform indicators is compared with each other. After the comparison matrix is ​​formed by the set expert scoring method, the consistency index test is performed on the comparison matrix, and the maximum eigenvalue λ of the comparison matrix is ​​obtained by analysis. max After that, the consistency index Z is calculated, and the formula is as follows:

[0044]

[0045] Where n is the order data set in the consistency test RI value table;

[0046] Step S13: After calculating the consistency index Z of the aviation logistics platform, further calculate the weight ratio data X of each index data system of the aviation logistics platform, the formula is: Through this step, the difficult-to-quantify aviation logistics platform indicators are compared in terms of importance, which reasonably solves the quantitative processing process of qualitative problems, improves the feasibility and reliability of aviation logistics platform decision-making management, and enables aviation logistics platform managers to obtain effective and accurate analysis and processing basis for the problems and causes of aviation logistics platform construction through the weights of the aviation logistics platform indicator data system.

[0047] Step S2 further comprises:

[0048] A questionnaire survey was conducted among airport cargo terminals, freight forwarders, airline cargo departments, logistics companies and professionals in air logistics through the distribution of questionnaires. The questionnaires were conducted through WeChat, telephone and email. After obtaining the evaluation results, the fuzzy comprehensive evaluation method was used to obtain the evaluation result data of each indicator of the airport air logistics platform based on the design results of the airport air logistics platform indicators. Through this step, human reference opinions are further provided for the management of the air logistics platform, making the management analysis of the air logistics platform more comprehensive and specific.

[0049] Step S3 further comprises the following steps:

[0050] Step S31: Construct the logical framework of the airport air logistics platform through five layers: infrastructure layer, digital platform layer, business management layer, production operation layer, and user operation layer. The real-time perception layer relies on sensors, electronic tags, GPS, and camera perception devices distributed in various links of the air cargo flow process to obtain data information, and transmits data through the Internet of Things, the Internet, and 5G communications. The data sharing layer transmits various data scattered in the upstream and downstream of the air logistics supply chain to the air logistics data platform, and collects data obtained from government departments and financial institutions through open interfaces to form a comprehensive data source for air logistics information. In this step, the platform presentation layer is the interface for displaying information on the air logistics platform, which can be divided into cargo owner subsystem, airport cargo terminal subsystem, airline subsystem, and supervision subsystem according to different user objects. Subsystem and integrated management system. All participants in the logistics service chain access the subsystem interface through web pages and mobile clients to conduct information interaction processes such as logistics information query, business decision-making and business processing. The user operation layer aviation logistics platform, based on business processes and user usage scenarios, provides various forms such as web pages, smart mobile terminals, self-service terminals, AR / VR equipment, logistics robots, etc. to open up business processes and integrate platform services throughout the aviation logistics service chain, providing various users of the aviation logistics service chain with rich and convenient terminal equipment and interface design with good user experience, realizing the visualization, collaboration, intelligence and personalization of aviation logistics business, comprehensively improving the efficiency and service quality of aviation logistics, and conducting real-time data mining and intelligent analysis of massive data, providing a basis for intelligent decision-making and application support in aviation logistics.

[0051] Step S32: Connect the airport air logistics data with the customs, taxation, insurance, logistics park, and comprehensive transportation agencies through blockchain, and store the data transmitted after the connection in blockchain nodes to achieve resource sharing and business collaboration; because a complete air logistics business ecosystem also requires efficient cooperation from government supervision, customs quarantine, and financial services departments, this step ensures the security of data transmission and storage while achieving resource sharing, business collaboration, and co-building of an air logistics business ecosystem. For example, when the shipper places an order on the air logistics platform, it can handle online insurance, online tax refunds, electronic invoices and other services. Freight forwarders can conduct online customs declaration and license applications on the platform. Resources are shared and businesses are mutually recognized between logistics parks, truly realizing the smart air logistics vision of "one form for logistics, one inspection for customs clearance, one network for operation, and one platform for supervision" for the entire air logistics process.

[0052] Step S33: further connect the import and export goods information with the customs supervision system to provide the customs with the status information of the import and export goods, and realize the logistics process supervision of the port-supervised goods and the supervision and control of special goods.

[0053] Step S4 further comprises the following steps:

[0054] Step S41: collect and organize the real-time operation data information of the airport aviation logistics management platform, and transmit it to the workbench for management personnel to review and analyze;

[0055] Step S42: Provide the regulatory authorities with information on flights, cargo volume, cargo type, and cargo flow, including flight statistics, cargo source statistics, cargo type statistics, cargo flow statistics, manifest / waybill query, cargo customs clearance status query, and security inspection status query, so that they can fully understand the development status of the aviation logistics industry.

[0056] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0057] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An aviation logistics management system based on big data, comprising: The analysis and processing module, the management and control module and the collection and statistics module are characterized in that: the analysis and processing module is connected to the management and control module through a network, the management and control module is connected to the collection and statistics module through a network, the analysis and processing module is connected to the collection and statistics module through a network, the analysis and processing module is used to perform analysis and control on air logistics, the management and control module is used to optimize the management and control of air logistics, and the collection and statistics module is used to perform collection and statistics on air logistics data information.

2. The aviation logistics management system based on big data according to claim 1 is characterized by: The analysis and processing module includes an indicator design module, a weight analysis module and an evaluation processing module. The indicator design module is network-connected to the weight analysis module, and the weight analysis module is network-connected to the evaluation processing module. The indicator design module is used to perform indicator design management for air logistics, the weight analysis module is used to perform weight analysis processing on air logistics indicators, and the evaluation processing module is used to perform evaluation and analysis processing on air logistics management.

3. The aviation logistics management system based on big data according to claim 1 is characterized by: The management control module includes a logical framework module, a functional management module and a supervisory control module. The logical framework module and the functional management module are network-connected, and the functional management module and the supervisory control module are electrically connected. The logical framework module is used to perform air logistics logical framework design management, the functional management module controls and manages operation service functions, and the supervisory control module is used to supervise and control air logistics.

4. The aviation logistics management system based on big data according to claim 1 is characterized by: The collection and statistics module includes a collection and sorting module and a statistical query module. The collection and sorting module is used to collect and sort the aviation logistics information, and the statistical query module is used to perform statistical query processing on the service data information.

5. The aviation logistics management system based on big data according to claim 1 is characterized by: The method for operating an aviation logistics management system based on big data includes: Step S1: Design indicators for the airport aviation logistics platform and analyze the weights of the indicators that have been designed; Step S2: using fuzzy comprehensive evaluation method to conduct comprehensive evaluation on the airport's aviation logistics platform system; Step S3: Further construct the logical framework of the airport aviation logistics platform, and carry out functional management and logistics supervision and control; Step S4: Collect the operation and processing data information of the airport aviation logistics platform for users to conduct statistical inquiries.

6. The aviation logistics management system based on big data according to claim 5 is characterized by: The step S1 further comprises the following steps: Step S11: Analyze and process the airport aviation logistics platform through indicator design, and divide the indicators into external environment and internal platform indicators, wherein the external environment indicators include logistics data information and hardware interface data information, and the internal platform indicators include the electronic waybill utilization rate, data update frequency, logistics data sharing frequency and warehouse equipment data; Step S12: After completing the design of the airport aviation logistics platform index, the hierarchical analysis method is used to determine the weight of each aviation logistics platform index data system. Specifically, the importance of the external environment and internal platform indicators is compared with each other. After the comparison matrix is ​​formed by the set expert scoring method, the consistency index test is performed on the comparison matrix, and the maximum eigenvalue λ of the comparison matrix is ​​obtained by analysis. max After that, the consistency index Z is calculated, and the formula is as follows: Where n is the order data set in the consistency test RI value table; Step S13: After calculating the consistency index Z of the aviation logistics platform, further calculate the weight ratio data X of each index data system of the aviation logistics platform, the formula is:

7. The aviation logistics management system based on big data according to claim 5 is characterized by: The step S2 further comprises: A questionnaire survey was conducted among airport cargo terminals, freight forwarders, airline cargo departments, logistics companies and professionals in air logistics through WeChat, telephone and email. After obtaining the evaluation results, the fuzzy comprehensive evaluation method was used to obtain the evaluation result data of each indicator of the airport air logistics platform based on the design results of the airport air logistics platform indicators.

8. The aviation logistics management system based on big data according to claim 5 is characterized by: The step S3 further comprises the following steps: Step S31: The logic framework of the airport aviation logistics platform is constructed through five layers: infrastructure layer, digital platform layer, business management layer, production operation layer, and user operation layer. The real-time perception layer relies on sensors, electronic tags, GPS, and camera perception devices distributed in various links of the air cargo flow process to obtain data information, and transmits data through the Internet of Things, the Internet, and 5G communications. The data sharing layer transmits various data scattered in the upstream and downstream of the aviation logistics supply chain to the aviation logistics data platform, and collects data obtained from government departments and financial institutions through open interfaces to form a comprehensive data source for aviation logistics information; Step S32: Connect the airport aviation logistics data with customs, taxation, insurance, logistics park, and comprehensive transportation agencies through blockchain, and store the data transmitted after the connection in blockchain nodes to achieve resource sharing and business collaboration; Step S33: further connect the import and export goods information with the customs supervision system to provide the customs with the status information of the import and export goods, and realize the logistics process supervision of the port-supervised goods and the supervision and control of special goods.

9. The aviation logistics management system based on big data according to claim 5, characterized in that: The step S4 further comprises the following steps: Step S41: collect and organize the real-time operation data information of the airport aviation logistics management platform, and transmit it to the workbench for management personnel to review and analyze; Step S42: Provide the regulatory authorities with information on flights, cargo volume, cargo type, and cargo flow, including flight statistics, cargo source statistics, cargo type statistics, cargo flow statistics, manifest / waybill query, cargo customs clearance status query, and security inspection status query, so that they can fully understand the development status of the aviation logistics industry.

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