Airport passenger travel data processing method and device based on artificial intelligence

Abstract

The invention provides an airport passenger travel data processing method and device based on artificial intelligence, and relates to the field of data processing. The method comprises the following steps: responding to a dining request input by a passenger through user equipment; boarding duration, boarding gate position information and carry-on luggage information of passengers are obtained; according to the boarding duration and the carry-on luggage information, determining the dining duration of the passenger; acquiring current position information of the passenger; acquiring real-time meal delivery duration, real-time queuing duration and dining duration corresponding to the dining place in the preset range; determining the dining duration based on the current position information and the real-time serving duration, the real-time queuing duration and the dining duration corresponding to the dining place; according to the dining duration, screening from the plurality of dining durations to obtain a first dining duration meeting a preset condition; determining a first dining place corresponding to the first dining duration; and sending the first dining place to the user equipment. By implementing the technical scheme, the problem of reasonable arrangement of travel time of airport passengers can be solved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and specifically to an airport passenger travel data processing method and device based on artificial intelligence. Background Art

[0002] In the current airport operating environment, passengers' convenient experience and efficient service have become one of the important indicators for measuring airport service quality. However, a common problem is that after arriving at the airport, passengers are faced with a relatively unfamiliar and large indoor space and often find it difficult to quickly familiarize themselves with and grasp the distribution of various airport service facilities, especially the location information of the dining area. This challenge is particularly prominent for passengers who want to enjoy a meal in limited time before boarding.

[0003] At present, even if passengers can access the Internet through mobile devices such as smartphones to query relevant information independently, the complex architectural structure, unknown catering layout and decentralized operations of different catering service providers in the airport often cause passengers to feel confused and anxious when looking for a suitable dining place, which in turn causes passengers to waste limited and precious time in the search process, affecting the overall reasonable arrangement of airport passengers' travel time.

[0004] Therefore, there is an urgent need for an airport passenger travel data processing method and device based on artificial intelligence. Summary of the invention

[0005] The present application provides an airport passenger travel data processing method and device based on artificial intelligence, which is convenient for solving the problem of reasonable arrangement of airport passenger travel time.

[0006] In a first aspect of the present application, a method for processing airport passenger travel data based on artificial intelligence is provided, the method comprising: responding to a dining request input by a passenger through a user device, the passenger is located in the airport and has passed security check but has not yet boarded the plane; according to the dining request, obtaining the passenger's boarding information, the boarding information including boarding time, boarding gate location information and carry-on luggage information, the boarding time being the time from the start of boarding to the end of boarding for the flight corresponding to the passenger; determining the available dining time for the passenger according to the boarding time and the carry-on luggage information; obtaining the passenger's current location information; obtaining the real-time meal delivery corresponding to the dining location within a preset range. The preset range is determined according to the current location information and the boarding gate location information; the meal time is determined based on the current location information and the real-time meal delivery time, real-time queue time and meal time corresponding to the meal location; according to the available meal time, a first meal time that meets the preset conditions is obtained from a plurality of meal times, the first meal time is any one of the plurality of meal times; a first meal location corresponding to the first meal time is determined, one meal time corresponds to one meal location; and the first meal location is sent to the user device so that the passenger can go to the first meal location for dining.

[0007] By adopting the above technical solution, passengers only need to input meal requests through user devices, and the system can automatically recommend suitable dining places for them, eliminating the tedious steps of finding restaurants and comparing dining times by themselves. The system tailors dining plans for passengers based on their boarding information and current location to ensure that passengers can enjoy suitable dining services within a limited time. The entire process, from receiving dining requests to recommending dining places, is almost entirely completed automatically by the system, reducing manual intervention and improving service efficiency. The system can obtain information such as meal delivery time, queuing time and dining time of dining places in real time to ensure that the recommended dining places are the latest and most in line with passenger needs. The system can recommend suitable dining places for passengers based on their specific circumstances and preferences, which not only ensures that passengers use their limited time efficiently in an unfamiliar airport environment, but also enhances passenger satisfaction, making it easier to solve the problem of reasonable travel time arrangements for airport passengers.

[0008] Optionally, determining the available dining time of the passenger based on the boarding time and the carry-on baggage information specifically includes: determining the end boarding time of the flight corresponding to the passenger based on the boarding time; obtaining the current time, and calculating the time between the current time and the end boarding time to obtain a target time; determining the number and weight of the carry-on baggage carried by the passenger based on the carry-on baggage information; determining a time increment based on the number and weight of the carry-on baggage; and calculating the difference between the target time and the time increment to obtain the available dining time of the passenger.

[0009] By adopting the above technical solution, by calculating the time between the current time and the end of the flight boarding time, a clear time window is provided for passengers to plan their meal time. Taking into account the impact of carry-on luggage on the speed of passengers' movements, the time increment is determined according to the number and weight of luggage, and the calculation of the available meal time is further refined to improve the accuracy of the results. By considering the carry-on luggage information, the system can provide each passenger with a more personalized recommendation for the available meal time. The accurate calculation of the available meal time helps passengers better arrange meal plans, avoid rushing to eat or missing meal opportunities due to time constraints, and helps reduce passengers' ineffective movement and waiting time in the airport, thereby improving overall travel efficiency.

[0010] Optionally, obtaining the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining places within the preset range specifically includes: obtaining the current position coordinate point according to the current position information; obtaining the boarding gate position coordinate point according to the boarding gate position information; drawing a circle with the current position coordinate point as the center and a radius of a preset length to obtain a target circle; simulating the target circle to move from the current position coordinate point along a preset trajectory line and stop moving when the center of the circle coincides with the boarding gate position coordinate point to obtain a coverage area, the preset trajectory line being the actual trajectory line between the current position coordinate point and the boarding gate position coordinate point; if it is determined that there is an overlap between the coverage area and the dining area, the dining place corresponding to the dining area is used as the dining place within the preset range, and the dining area is obtained by area expansion according to the ordering place corresponding to the dining place.

[0011] By adopting the above technical solution, by using the current position coordinate point and the boarding gate position coordinate point, combining the radius of the preset length to make a circle, and then simulating the target circle to move along the actual trajectory line until it coincides with the boarding gate position coordinate point, this process ensures the accuracy of the coverage area. This precise calculation based on geographic location can more accurately reflect the dining places that passengers may pass by on the way to the boarding gate. This method takes into account the actual walking path of passengers from the current location to the boarding gate, rather than simply defining it by a straight-line distance or a fixed range, thereby more personalized to meet the dining needs of passengers. The determination of the coverage area not only takes into account the current location and boarding gate location of the passenger, but also adapts to different paths and terrains by simulating the movement process, ensuring the comprehensiveness of the coverage area. The expansion of the dining area is based on the ordering place of the dining location, which means that the system can flexibly adjust the scope of the dining area to adapt to restaurants or fast food restaurants of different sizes, ensuring that the recommended dining locations are both convenient and practical. By obtaining the real-time meal delivery time, queuing time and dining time corresponding to the dining location, the system can provide passengers with the latest dining information to help them make more informed choices. This method combines geographic location information and real-time data to ensure efficient and accurate recommendations. Passengers can quickly get the dining places that best suit them without spending a lot of time comparing and choosing. By accurately calculating the coverage area and recommending dining places, the system can reduce passengers' ineffective movement and waiting time in the airport and improve their travel efficiency. Passengers can more easily find dining places that meet their needs and enjoy a pleasant dining experience, thereby enhancing their satisfaction with airport services.

[0012] Optionally, determining the dining time based on the current position information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location specifically includes: obtaining a first moving distance between the current position and the dining location, a second moving distance between the dining location and the boarding gate location, and a moving speed of the passenger; determining, based on the first moving distance, the second moving distance and the moving speed, a front-end moving time required for the passenger to travel from the current position to the dining location, and a rear-end moving time required for the passenger to travel from the dining location to the boarding gate location; correcting the front-end moving time and the rear-end moving time respectively in combination with the time increment to obtain a front-end corrected time and a rear-end corrected time; and accumulating the front-end corrected time, the rear-end corrected time, the real-time meal delivery time, the real-time queuing time and the dining time to obtain the dining time.

[0013] By adopting the above technical solution, the system can accurately calculate the passenger's travel time by obtaining the first moving distance between the current location and the dining location, and the second moving distance between the dining location and the boarding gate. This accuracy ensures that the recommended meal time is closer to the actual situation. When calculating the moving time, not only the direct moving distance is considered, but also the front-end moving time and the back-end moving time are corrected in combination with the time increment. Combined with the real-time meal delivery time, queuing time and dining time, the system can provide passengers with the latest meal time forecast. This real-time performance ensures that passengers can make decisions based on the latest information and avoid wrong choices caused by information lag. By accumulating the duration of each time period, the system can quickly calculate the total meal time, which improves the efficiency of decision-making. Accurate meal time calculation provides passengers with more accurate meal planning. Based on this information, passengers can choose the most suitable dining location and dining time for themselves, avoiding rushing to eat or missing dining opportunities due to time constraints. For airport management, this accurate calculation also helps to optimize the allocation of catering resources in the airport and improve overall operational efficiency. By providing accurate and comprehensive information on meal times, the system can better meet passengers' dining needs, improve their satisfaction and airport travel experience. Passengers can enjoy the catering services provided by the airport with greater confidence, without worrying about missing meals or affecting boarding due to time issues.

[0014] Optionally, before determining the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location, the dining time corresponding to the dining location is obtained; the obtaining of the dining time corresponding to the dining location specifically includes: obtaining the type of meal corresponding to the dining location; determining, according to the current time, a historical dining time corresponding to the type of meal from the historical dining data corresponding to the dining location, the historical dining data including the historical dining times corresponding to the type of meal for each historical passenger; and calculating the average meal time corresponding to a plurality of the historical meal times to obtain the dining time corresponding to the dining location.

[0015] By adopting the above technical solution, by obtaining the types of meals corresponding to the dining venue, the system can determine the meal time based on the specific meal type. Different types of meals often have different meal times, and this distinction ensures the accuracy of the calculation. Using historical dining data to calculate the average meal time can reflect the meal time required for a certain type of meal under normal circumstances, thereby providing a more accurate and reliable prediction. Although the average meal time is used, this method still has certain personalized characteristics. Because the historical dining data is collected based on the actual meal time of past passengers, it reflects the dining habits of different passengers in different time periods and different types of meals. The system can adjust the calculation of meal time according to different types of meals and the current time, showing good adaptability. By calculating the average value of the historical meal time, the system can quickly obtain the meal time corresponding to the dining venue, improving the calculation efficiency. This method does not require real-time monitoring of each passenger's dining process, but relies on historical data, so it can provide real-time meal time information without adding additional burden. Accurate meal time information helps passengers make more informed dining choices. They can plan their dining time according to the duration of the meal, avoiding rushing to eat or missing dining opportunities due to time constraints. For airport management, this precise calculation also helps optimize the allocation of catering resources within the airport and improve overall operational efficiency, thereby further enhancing passengers' travel experience.

[0016] Optionally, obtaining the meal time corresponding to the dining location specifically also includes: obtaining the personalized dining information of the passenger; determining multiple personalized meal times corresponding to the meal types based on the personalized dining information; and calculating the average meal time corresponding to the multiple personalized meal times to obtain the meal time corresponding to the dining location.

[0017] By adopting the above technical solution, the system can provide each passenger with a more accurate and customized meal time prediction by obtaining the personalized meal information of the passengers. This personalized service can better meet the specific needs of passengers and improve their satisfaction. Personalized meal information provides a richer data basis for the calculation of meal time. Compared with relying solely on historical meal data, combining personalized information can more accurately predict the meal time of passengers in the current situation. This helps to reduce the prediction error caused by individual differences. Accurate meal time prediction helps passengers better plan their meal time and avoid rushing to eat or missing meal opportunities due to time constraints. This optimization not only improves the dining experience of passengers, but also reduces potential problems such as boarding delays that may be caused by improper meal time. By providing personalized meal time predictions, the system can show attention and respect for passenger needs. This attention helps to enhance passengers' trust and loyalty to airport services, thereby promoting the long-term development of airport catering business.

[0018] Optionally, the method further includes: determining from the first dining time a first front-end moving time required for the passenger to travel from the current position to the first dining location, and a first rear-end moving time required for the passenger to travel from the first dining location to the boarding gate location; obtaining a second dining time corresponding to a second dining location, the second dining time being any one of the plurality of dining times other than the first dining time that meets the preset condition, and the preset condition being that the dining time is less than the available dining time; determining from the second dining time a second front-end moving time required for the passenger to travel from the current position to the second dining location, and a second rear-end moving time required for the passenger to travel from the first dining location to the boarding gate location The second rear-end movement time required for the passenger to travel from the second dining location to the boarding gate location; correcting the first front-end movement time and the first rear-end movement time by the time increment to obtain the first front-end corrected time and the first rear-end corrected time; correcting the second front-end movement time and the second rear-end movement time by the time increment to obtain the second front-end corrected time and the second rear-end corrected time; if it is determined that the first front-end corrected time is greater than the second front-end corrected time, and the first rear-end corrected time is greater than the second rear-end corrected time, then preferentially sending the second dining location to the user device to facilitate the passenger to go to the second dining location for dining.

[0019] By adopting the above technical solution, the system can recommend the best dining location for passengers by calculating and comparing the front-end moving time, back-end moving time and corrected time of different dining locations. This optimization decision-making process reduces the hesitation time of passengers in choosing dining locations and improves overall efficiency. The system takes into account the passenger's current location, available dining time, and the actual dining time and moving time of different dining locations, and provides personalized dining location recommendations for each passenger. This customized service can better meet the specific needs of passengers and improve their satisfaction. By recommending the best dining location, the system helps passengers save moving time and dining time, allowing them to enjoy the airport's catering services more easily. This optimization not only improves the passenger's dining experience, but also reduces the anxiety and stress that may be caused by time constraints. By calculating the corrected front-end and back-end moving times, the system can more accurately predict the passenger's boarding time after dining at different dining locations. This prediction helps reduce the risk of boarding delays or missed flights due to time conflicts.

[0020] In a second aspect of the present application, an artificial intelligence-based airport passenger travel data processing device is provided, the airport passenger travel data processing device includes an acquisition module and a processing module, wherein the acquisition module is used to respond to a meal request input by a passenger through a user device, the passenger is located in the airport, and has not yet boarded the plane after passing security check; the processing module is used to obtain the passenger's boarding information according to the meal request, the boarding information includes boarding time, boarding gate location information and carry-on baggage information, the boarding time is the time from the start boarding time to the end boarding time of the flight corresponding to the passenger; the processing module is also used to determine the passenger's available meal time according to the boarding time and the carry-on baggage information; the acquisition module is also used to obtain the passenger's current location information; the acquisition module is also used to obtain preset the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining places within the preset range, the preset range being determined according to the current location information and the boarding gate location information; the processing module is further used to determine the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining places; the processing module is further used to filter out a first dining time that meets preset conditions from a plurality of the dining times according to the available dining time, the first dining time being any one of the plurality of the dining times; the processing module is further used to determine a first dining place corresponding to the first dining time, one dining time corresponding to one dining place; the processing module is further used to send the first dining place to the user device so that the passenger can go to the first dining place for dining.

[0021] In the third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs the method described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method described above is executed.

[0023] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: Passengers only need to input meal requests through user devices, and the system can automatically recommend suitable dining places for them, eliminating the tedious steps of finding restaurants and comparing dining times by themselves. The system tailors dining plans for passengers based on their boarding information and current location to ensure that passengers can enjoy suitable dining services within a limited time. The entire process, from receiving meal requests to recommending dining places, is almost entirely completed automatically by the system, reducing manual intervention and improving service efficiency. The system can obtain information such as meal delivery time, queue time, and dining time at dining places in real time to ensure that the recommended dining places are the latest and most in line with passenger needs. Through intelligent recommendations, passengers can be guided to dine in different restaurants to avoid some restaurants being too crowded while other restaurants are relatively deserted, thereby optimizing the allocation of airport catering resources. The system can recommend suitable dining places for passengers based on their specific circumstances and preferences, which not only ensures that passengers use their limited time efficiently in an unfamiliar airport environment, but also enhances passenger satisfaction, making it easier to solve the problem of reasonable travel time arrangements for airport passengers. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of an artificial intelligence-based airport passenger travel data processing method provided in an embodiment of the present application.

[0025] Figure 2 Another flowchart of an artificial intelligence-based airport passenger travel data processing method provided in an embodiment of the present application.

[0026] Figure 3 A module diagram of an artificial intelligence-based airport passenger travel data processing device provided in an embodiment of the present application.

[0027] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0028] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. DETAILED DESCRIPTION

[0029] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0031] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0032] In the current airport operation scenario, ensuring passengers' convenient experience and efficient service has become one of the core elements for judging the quality of airport services. However, a common problem is that when passengers first arrive at the airport, facing the huge and unfamiliar indoor environment, it is often difficult for them to quickly grasp the specific location of the airport's service facilities, especially the catering area. This poses a significant challenge for passengers who are eager to enjoy a meal in the tight time before boarding.

[0033] Although passengers can now use smartphones and other portable devices to access the Internet and try to independently query relevant information for each dining location, the complex architectural structure and unknown layout of the dining area inside the airport still make passengers feel confused and uneasy when choosing a suitable dining location. This situation not only consumes passengers' limited and precious time in the exploration process, but also has an adverse impact on the travel time planning of passengers throughout the airport.

[0034] In order to solve the above technical problems, this application provides an airport passenger travel data processing method based on artificial intelligence, referring to Figure 1 , Figure 1 Another flowchart of an airport passenger travel data processing method based on artificial intelligence provided by an embodiment of the present application. The airport passenger travel data processing method is applied to a server, including steps S110 to S190, which are as follows: S110 . In response to a meal request input by a passenger through a user device, the passenger is in the airport and has passed security check but has not yet boarded the plane.

[0035] Specifically, a server is a computer system or computer cluster that is able to receive, process and respond to requests from passengers' user devices. The server is located in the airport's data center and is remotely hosted by a cloud service provider and an AI smart screen. The server performs subsequent operations after receiving the passenger's dining request. This response is real-time, which means that the server will process it immediately or as soon as possible after the passenger submits the request. Passengers use their personal devices (such as applications on smartphones, web pages on tablets, or self-service terminals in the airport) to submit a dining request. This request can include the passenger's preferences (such as meal type, taste, allergy information, etc.), location information (obtained through the device's GPS or the airport's Wi-Fi positioning service), and the available dining time window. Among them, the passenger is currently at a certain location in the airport and has passed the airport's security check, which means that they have access to catering and other service facilities in the airport. At the same time, they have not yet boarded the plane, which provides them with a time window for dining in the airport.

[0036] S120. Obtain the passenger's boarding information according to the meal request. The boarding information includes boarding time, boarding gate location information, and carry-on baggage information. The boarding time is the time from the start time to the end time of boarding for the flight corresponding to the passenger.

[0037] Specifically, the server can obtain the passenger's boarding information through an interface with the airport information system, the airline system, or a third-party service provider. This information is crucial for determining the passenger's available dining time and recommending a suitable dining location. Boarding time refers to the time between the start and end of boarding for the passenger's corresponding flight. This time period usually starts a certain time before the flight takes off and lasts for a period of time until all passengers are boarded. This time period is very important for determining the time window in which passengers can stay in the airport and have a meal. Gate location information refers to the specific location of the gate to which the passenger should go. This information is crucial for planning the passenger's movement route from the dining location to the boarding gate. Carry-on baggage information refers to the number and type of carry-on baggage carried by the passenger, which affects the passenger's movement speed and dining choices.

[0038] S130. Determine the available meal time for the passenger based on the boarding time and carry-on baggage information.

[0039] Specifically, the server combines the boarding time and carry-on baggage information to calculate the time passengers have available for dining in the airport through an algorithm. This time is enough for passengers to move from their current location to the restaurant, eat, and return to the boarding gate, while ensuring that they can reach the boarding gate before boarding ends.

[0040] In a possible implementation, the available dining time of the passenger is determined according to the boarding time and the carry-on baggage information, specifically including: determining the end boarding time of the passenger's flight according to the boarding time; obtaining the current time, and calculating the time between the current time and the end boarding time to obtain the target time; determining the number and weight of the carry-on baggage carried by the passenger according to the carry-on baggage information; determining the time increment based on the number and weight of the carry-on baggage; and calculating the difference between the target time and the time increment to obtain the available dining time of the passenger.

[0041] Specifically, the server first determines the end boarding time of the flight based on the passenger's boarding time. This is the time point before which the passenger must complete the check-in procedures. The server obtains the current accurate time and calculates the time from the current time to the end boarding time of the flight. This time is the total time that the passenger can use for various activities in the airport before boarding, including meals. Generally speaking, the more luggage there is, the longer it takes for the passenger to move. For example, a passenger with two pieces of luggage may need more time to find a seat, arrange the luggage, etc. than a passenger with only one piece of luggage. The weight of the luggage may also affect the passenger's movement speed. Although the direct effect of weight on movement speed may not be as significant as the amount, heavy luggage may cause passengers to feel tired or need more rest time when moving. The specific time increment varies depending on the layout of the airport, the convenience of facilities, and the personal ability of the passenger. For example, at a busy airport, a passenger carrying multiple pieces of heavy luggage may need an additional 5-10 minutes to move; while at an airport with more convenient facilities and less traffic, this time may be shorter.

[0042] Furthermore, the embodiment of the present application provides a method for calculating the time increment, and the specific calculation formula is as follows: ; Among them, T increment is the time increment in minutes; k 1 is the luggage quantity influence coefficient; k 2 is the luggage weight influence coefficient; k 3 is the nonlinear influence coefficient of the average weight; k 4 is the overweight penalty coefficient; N is the number of carry-on luggage actually carried by the passenger; W is the actual weight of the carry-on luggage carried by the passenger; N max is the maximum number of luggage that is set. If the number exceeds this, the impact is considered to increase significantly. max is the maximum luggage weight, exceeding which the impact increases; β and γ control the nonlinear growth rate of quantity and weight respectively; is a maximum number of luggage N max The proportional factor makes the impact of the number of luggage not linear, but controlled by exponential β. When N is close to Nmax When , the time increment will grow faster, and β controls the degree of nonlinearity of the quantity effect; is a maximum weight W max The proportional factor makes the influence of the total luggage weight also have nonlinear characteristics. γ is the index that controls this influence. When W is close to W max When S eff is the passenger's action efficiency factor or speed factor, which can be set based on the passenger's body shape, age, physical fitness or psychological state, and can also be obtained through observation data or smart devices; S eff Higher values ​​indicate faster actions, S eff Lower values ​​indicate less efficient actions; represents the nonlinear effect of the average weight of each piece of luggage, keeping the above settings unchanged; Indicates overweight penalty, keeping the above settings unchanged; is a random disturbance term, which represents the random noise caused by unpredictable factors such as airport passenger flow, traffic or emergencies. It can be simulated by setting a Gaussian noise, which will not be described here.

[0043] For example, suppose the actual number of luggage N = 3, the total weight W = 10 kg, and the maximum number of luggage N max =2, maximum luggage weight W max =10 kg, the influence coefficient of quantity k 1 = 1 minute, weight influence coefficient k 2 = 0.5 minutes, the coefficient of the nonlinear term k 3 =0.2, overweight penalty coefficient k 4 =2 minutes / kg, nonlinear index of quantity β=1.2, nonlinear index of weight γ=1.5, passenger movement efficiency S eff = 0.9, nonlinear average weight exponent α = 1.5, luggage weight threshold W threshold = 10 kg, random disturbance term Taking a value from N(0, 0.5), assuming it is 0.3, the resulting time increment is approximately 3 minutes.

[0044] S140: Obtain the passenger's current location information.

[0045] Specifically, the server can rely on a variety of technologies to determine the passenger's current location information, including but not limited to: first, such as Wi-Fi positioning, Bluetooth positioning or cellular network positioning, these technologies can determine the passenger's location by analyzing the signals emitted by the passenger's device; second, the passenger sends a dining request to the server by installing a specific application on the user's device, and the dining request can be used to share their location information. These applications can communicate with the server to provide real-time location updates; third, the airport is equipped with special positioning equipment or systems, such as cameras, RFID tag readers, etc., for tracking the movement of passengers.

[0046] S150, obtaining the real-time meal delivery time, real-time queue time and meal time corresponding to the dining locations within a preset range, wherein the preset range is determined according to the current location information and the boarding gate location information.

[0047] Specifically, the server collects real-time information about dining locations within a preset range, including the time it takes to serve the meal, the time it takes to queue, and the time it takes to eat. The preset range is determined based on the passenger's current location information and the boarding gate location information. The preset range means that the dining areas corresponding to the multiple dining locations within the range are all available for dining, with the purpose of ensuring that the recommended dining locations are convenient for passengers to reach and will not delay their boarding time. Dining locations include restaurants, fast food restaurants, cafes, etc. in the airport, which are located within the preset range and are willing to provide real-time information to the server. The real-time serving time refers to the time it takes from the passenger placing an order to the meal being prepared, which may vary depending on factors such as the busyness of the restaurant, the chef's work efficiency, and the complexity of the menu. The real-time queuing time refers to the time it takes for passengers to wait outside the restaurant or at the ordering counter to order a meal, which reflects the restaurant's congestion and service efficiency. The meal time refers to the time it takes for passengers to start eating and finish eating, which may vary depending on the type of meal (such as fast food or full meal), the passenger's dining habits and personal preferences.

[0048] In a possible implementation, the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining places within a preset range are obtained, specifically including: obtaining the current position coordinate point according to the current position information; obtaining the boarding gate position coordinate point according to the boarding gate position information; drawing a circle with the current position coordinate point as the center and a radius of a preset length to obtain a target circle; simulating the target circle to move from the current position coordinate point along a preset trajectory line and stop moving when the center of the circle coincides with the boarding gate position coordinate point to obtain a coverage area, the preset trajectory line being the actual trajectory line between the current position coordinate point and the boarding gate position coordinate point; if it is determined that there is an overlap between the coverage area and the dining area, the dining place corresponding to the dining area is taken as the dining place within the preset range, and the dining area is obtained by expanding the area according to the ordering place corresponding to the dining place.

[0049] Specifically, according to the current location information of the passenger, the server first determines the current location coordinate point of the passenger. At the same time, the server also obtains the location information of the boarding gate and determines the location coordinate point of the boarding gate. The server takes the current location coordinate point of the passenger as the center of the circle, selects a preset length as the radius, and draws a circle, which is called the target circle. The preset length is determined based on factors such as the passenger's walking speed, expected meal time, and boarding time to ensure that the passenger has enough time to eat and return to the boarding gate. The server then simulates the target circle starting from the passenger's current location coordinate point and moving along the actual trajectory line of the passenger to the boarding gate. The actual trajectory line takes into account factors such as the layout of the airport, the walking path, and the prohibited area to ensure the accuracy and practicality of the simulation. When the center of the target circle coincides with the boarding gate location coordinate point, the simulation stops. At this time, the strip area covered by the target circle is called the coverage area. Among them, after the center of the target circle scans from the starting point to the end point along the preset trajectory line for multiple moments, the center line of the strip area formed is consistent with the preset trajectory line.

[0050] Furthermore, the dining area is obtained by expanding the area based on the dining locations, such as the ordering areas of restaurants and fast food restaurants, to ensure that the entire range of passengers' activities from ordering to dining is covered, because the ordering area is the preferred location for passengers to arrive at the dining location when they want to eat. The dining area includes a circular area and a square area. The specific shape is expanded with reference to the actual floor space of the dining location and is not limited here. The server checks whether the coverage area overlaps with the dining area. If the coverage area overlaps with the dining area, the dining locations corresponding to these dining areas are deemed to be within the preset range. For the dining locations within these preset ranges, the server further obtains information such as their real-time meal delivery time, real-time queuing time, and dining time.

[0051] For example, suppose that passenger Mr. Wang is in Terminal 3 of an international airport preparing to take an evening flight. His current location is the international arrival hall of Terminal 3, and his boarding gate is located at the other end of Terminal 3, near the security check area. The server first determines the coordinates of Mr. Wang's current location and the location of the boarding gate. The server uses Mr. Wang's current location as the center of the circle and selects a suitable radius, such as 50 meters, to draw a target circle. The server uses path planning software to simulate the target circle starting from Mr. Wang's current location and moving along his actual trajectory to the boarding gate. When the center of the target circle reaches the boarding gate, the simulation stops, and the coverage area formed at this time covers Mr. Wang's possible path to the boarding gate. The server checks whether the coverage area overlaps with the dining area in the airport. Assuming that the coverage area overlaps with the dining area corresponding to a fast food restaurant located in the center of the terminal hall, then this fast food restaurant is regarded as a dining location within the preset range. The server further obtains information such as the real-time serving time, real-time queuing time, and dining time of this fast food restaurant, and provides this information to Mr. Wang to help him make dining decisions. In this example, the server determines dining locations within a preset range through complex simulation and calculation processes, and obtains real-time information about these locations, thereby providing travelers with more accurate and personalized dining recommendations.

[0052] S160: Determine the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location.

[0053] Specifically, the server takes into account the current location information, real-time information of the dining location, and the passenger's flight time to calculate an appropriate dining time, which should be enough for the passenger to arrive at the dining location, order food, wait for the food, eat, and return to the boarding gate.

[0054] In a possible implementation, the dining time is determined based on the current position information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location, specifically including: obtaining a first moving distance between the current position and the dining location, a second moving distance between the dining location and the boarding gate, and the passenger's moving speed; based on the first moving distance, the second moving distance and the moving speed, determining the front-end moving time required for the passenger to travel from the current position to the dining location, and the rear-end moving time required for the passenger to travel from the dining location to the boarding gate; in combination with the time increment, respectively correcting the front-end moving time and the rear-end moving time to obtain the front-end corrected time and the rear-end corrected time; accumulating the front-end corrected time, the rear-end corrected time, the real-time meal delivery time, the real-time queuing time and the dining time to obtain the dining time.

[0055] Specifically, the server first obtains the first moving distance between the passenger's current position and the dining location, and the second moving distance between the dining location and the boarding gate location. These distances are obtained through map data, airport layout diagrams or positioning technology. At the same time, the server also obtains the passenger's moving speed. This speed is based on the passenger's historical walking data, the average walking speed in the airport, or the speed information entered by the passenger, which is obtained by the user device in advance. Based on the first moving distance and the second moving distance, as well as the passenger's moving speed, the server calculates the front-end moving time required for the passenger to travel from the current position to the dining location, and the rear-end moving time required for the passenger to travel from the dining location to the boarding gate location. Considering that the passenger's carry-on luggage affects the moving time, the server introduces a time increment to correct the front-end moving time and the rear-end moving time. Through this time increment, the server obtains the corrected front-end moving time and the rear-end moving time, that is, the front-end correction time and the rear-end correction time. Finally, the server accumulates the front-end correction time, the rear-end correction time, the real-time meal delivery time, the real-time queuing time, and the dining time to obtain the total time required for the passenger to dine in the airport, that is, the dining time.

[0056] For example, assume that passenger Mr. Zhang is in Terminal 5 of an international airport preparing to take an evening flight. His current location is the domestic departure hall of Terminal 5, and his boarding gate is located at the other end of Terminal 5, near the remote gate. Mr. Zhang has completed security check and hopes to find a restaurant for dinner. The server determines that the first moving distance between Mr. Zhang's current location and the restaurant is 300 meters, and the second moving distance between the restaurant and the boarding gate is 500 meters. At the same time, the server assumes that Mr. Zhang's moving speed is 1.2 meters per second (about 4.32 kilometers per hour). Based on the above information, the server calculates that the front-end moving time required for Mr. Zhang to go from his current location to the restaurant is 250 seconds (about 4.17 minutes), and the back-end moving time required from the restaurant to the boarding gate is 416.67 seconds (about 6.94 minutes). Considering the impact of Mr. Zhang's carry-on suitcase on movement, the server introduces a time increment (such as 10% additional time) to correct the front-end moving time and the back-end moving time. After correction, the front-end correction time is 275 seconds (about 4.58 minutes), and the back-end correction time is 458.33 seconds (about 7.64 minutes). Assume that the restaurant's real-time meal delivery time is 15 minutes, the real-time queue time is 10 minutes, and the dining time is 30 minutes. The server adds these times with the front-end correction time and the back-end correction time, and the total time required for Mr. Zhang to dine in the airport is 1 hour and 17.22 minutes.

[0057] S170: Filter out a first meal time satisfying a preset condition from a plurality of meal times according to the available meal times, where the first meal time is any one of the plurality of meal times.

[0058] Specifically, the server calculates multiple possible meal duration options based on the passenger's current location, gate location, real-time information of the dining location, and the passenger's moving speed. From these possible meal durations, the server selects an optimal meal duration as the first meal duration based on preset screening conditions, such as the shortest total duration, the shortest queue time, the fastest meal delivery speed, etc. This first meal duration is one of the multiple meal durations, and it meets the screening conditions set by the server. In the embodiment of the present application, the preset condition is preferably that the meal duration is less than the available meal duration, so as to ensure the adequacy of the passenger's time to the greatest extent.

[0059] S180: Determine a first dining location corresponding to the first dining duration, where one dining duration corresponds to one dining location.

[0060] Specifically, after determining an optimal dining time, the server further determines a dining location corresponding to the dining time. Among them, one dining time corresponds to one dining location, which means that the server pre-associates a specific dining location for each calculated dining time, so that passengers can directly find the corresponding restaurant or dining area according to the recommended dining time. The first dining time is the optimal dining time selected by the server from multiple possible dining times based on factors such as the passenger's current location, boarding gate location, real-time information of the dining location, and the passenger's movement speed. The first dining location is the specific dining location corresponding to the first dining time, that is, the restaurant or dining area recommended by the server for passengers to go to for dinner.

[0061] S190: Send the first dining location to the user device, so that the passenger can go to the first dining location for dining.

[0062] Specifically, the server can send information about the first dining location, such as the restaurant name, location, contact information, etc., to the passenger's user device through the network. In this way, the passenger can view the recommended dining location information on the user device. By sending the information about the first dining location to the user device, the server provides a convenient way for the passenger to obtain detailed information about the dining location and go to the location for dining accordingly. This helps to improve the passenger's airport dining experience and reduce the time they spend looking for a suitable restaurant in the airport. Among them, the server can also display the planned path to the first dining location to the user device, so as to navigate the passenger to the first dining location through the user device. The specific situation is set according to actual needs and will not be repeated here.

[0063] Therefore, passengers only need to input meal requests through user devices, and the server can automatically recommend suitable dining places for them, eliminating the tedious steps of finding restaurants and comparing dining times. The server tailors dining plans for passengers based on their boarding information and current location to ensure that passengers can enjoy suitable dining services within a limited time. The entire process, from receiving meal requests to recommending dining places, is almost entirely completed automatically by the server, reducing manual intervention and improving service efficiency. The server can obtain information such as meal delivery time, queuing time, and dining time at dining places in real time to ensure that the recommended dining places are the latest and most in line with passenger needs. The server can recommend suitable dining places for passengers based on their specific circumstances and preferences, which not only ensures efficient use of time for airport passengers within a limited time, but also enhances passenger satisfaction, making it easier to solve the problem of reasonable travel time arrangements for airport passengers.

[0064] In a possible implementation, before determining the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location, the dining time corresponding to the dining location is obtained; obtaining the dining time corresponding to the dining location specifically includes: obtaining the type of meal corresponding to the dining location; according to the current time, determining the historical dining time corresponding to the type of meal from the historical dining data corresponding to the dining location, the historical dining data including the historical dining time corresponding to each historical passenger for each type of meal; calculating the average dining time corresponding to multiple historical meal times to obtain the dining time corresponding to the dining location.

[0065] Specifically, before determining the meal time, the server first needs to know how long it takes on average for a passenger to complete a meal at a specific dining location. This meal time is an important component of calculating the total meal time. In the embodiment of the present application, the meal time can be calculated in two ways, one of which is as follows: the server first identifies the types of meals provided at the dining location, which include fast food, buffet, dinner, etc. Different types of meals often correspond to different meal times. The server then selects the corresponding historical meal time from the historical dining data of the dining location according to the current time and meal type, such as lunch time and dinner time. The historical dining data contains a large number of historical meal time records of passengers dining at the dining location, which are classified by meal type. With these historical meal time data, the server calculates their average value to obtain a relatively accurate meal time estimate. This average meal time represents the average level of time required for passengers to dine at the dining location at the current time and meal type.

[0066] For example, suppose that a passenger, Mr. Sun, is preparing to eat at an international airport during lunch time. He chooses a well-known restaurant in the airport as his dining location. Before the server calculates the total dining time for him, it needs to obtain the dining time of this restaurant. The server recognizes that the type of food provided by the restaurant selected by Mr. Sun is Western-style formal meals. The server selects all dining time records during lunch time and the type of meal is Western-style formal meals from the restaurant's historical dining data. These records include the dining time of a large number of passengers dining at this restaurant in the past few days, weeks, or even months. The server calculates the average of these historical dining times, assuming that the average dining time is 1 hour and 15 minutes. This average dining time represents the average level of time required for passengers to dine in this restaurant at the current time (lunch time) and the type of meal (Western-style formal meals).

[0067] In one possible implementation, refer to Figure 2 , Figure 2 Another flow chart of an airport passenger travel data processing method based on artificial intelligence provided in an embodiment of the present application, obtaining the meal time corresponding to the dining location, specifically includes steps S210 to S230, and the above steps are as follows: S210, obtaining the passenger's personalized dining information; S220, determining multiple personalized meal times corresponding to the meal types based on the personalized dining information; S230, calculating the average meal time corresponding to the multiple personalized meal times to obtain the meal time corresponding to the dining location.

[0068] Specifically, the above content is the second method for calculating the meal duration provided by the embodiment of the present application: the server first obtains personalized dining information about the passenger, which includes the passenger's previous dining habits, preferred meal types, dining speed, etc. This information comes from the passenger's previous dining records, preference data collected through questionnaires or applications, or the information about their expected meal duration entered by the passenger himself. With the passenger's personalized dining information, the server can determine multiple personalized meal durations that the passenger may spend under the currently selected meal type based on this information. This means that for the same type of meal, different passengers may have different meal durations due to personal preferences and habits. The server then calculates the average of these personalized meal durations to obtain a more personalized meal duration estimate. This average meal duration is calculated based on the personal data and preferences of the individual passenger, and therefore better reflects the time that the passenger may spend in actual dining. Finally, this average meal duration based on the passenger's personalized information is used as the meal duration corresponding to the dining location.

[0069] Among them, the embodiment of the present application provides the above two methods to determine the meal duration, that is, by simultaneously referring to the historical data of multiple passengers at the same dining location and the personalized dining information of a single passenger for a certain type of meal, the server can more comprehensively evaluate the passenger's meal duration in different dining locations and meal types. This comprehensive consideration reduces the deviation that may be caused by a single data source and improves the accuracy of meal duration estimation. The introduction of personalized dining information allows the server to take into account individual differences between passengers. Different passengers have different dining habits, preferences, and speeds. Through personalized data, the server can provide each passenger with a meal duration recommendation that is more in line with their actual needs, further improving the passenger's overall experience of dining while traveling at the airport.

[0070] In a possible implementation, a first front-end moving time required for a passenger to travel from a current position to a first dining location, and a first rear-end moving time required for a passenger to travel from the first dining location to a boarding gate are determined from the first dining time; a second dining time corresponding to a second dining location is obtained, where the second dining time is any one of a plurality of dining times other than the first dining time that satisfies a preset condition, and the preset condition is that the dining time is less than the available dining time; a second front-end moving time required for a passenger to travel from the current position to a second dining location, and a second rear-end moving time required for a passenger to travel from the second dining location to a boarding gate are determined from the second dining time; the first front-end moving time and the first rear-end moving time are corrected by a time increment to obtain a first front-end corrected time and a first rear-end corrected time; the second front-end moving time and the second rear-end moving time are corrected by a time increment to obtain a second front-end corrected time and a second rear-end corrected time; if it is determined that the first front-end corrected time is greater than the second front-end corrected time, and the first rear-end corrected time is greater than the second rear-end corrected time, the second dining location is preferentially sent to the user device so that the passenger can travel to the second dining location for dining.

[0071] Specifically, the above content describes that when there are two or more recommended plans with the same dining time but different corresponding dining locations, the server will give priority to the plan with a shorter combined time for the passenger to move to the dining location and the passenger to go to the boarding gate after the meal. The purpose is to minimize the time for passengers to move back and forth with their carry-on luggage within a limited time, and focus more time on the actual available dining time, thereby ensuring the passengers' dining ease and further improving the passengers' airport travel experience. The server first calculates the first front-end movement time required for the passenger to travel from the current location to the first dining location and the first rear-end movement time required from the first dining location to the boarding gate location based on the first dining time. The server then obtains the second dining time corresponding to the second dining location that meets the condition that the dining time is less than the passenger's available dining time. Then, the second front-end movement time required for the passenger to travel from the current location to the second dining location and the second rear-end movement time required from the second dining location to the boarding gate location are calculated.

[0072] In addition, since the actual moving time may be different from the expected time due to the carry-on luggage, the server introduces a time increment to correct the front-end moving time and the rear-end moving time. The corrected time is respectively referred to as the first front-end corrected time, the first rear-end corrected time, the second front-end corrected time, and the second rear-end corrected time. Finally, the server will compare the corrected front-end and rear-end moving times. If the corrected time of the first dining place, whether the front end or the rear end, is longer than the corrected time of the second dining place, the server will give priority to sending the information of the second dining place to the user device so that the passenger can go to the second dining place for dining, so that the passenger can use the time more efficiently, and can enjoy the meal without missing the boarding. Secondly, if there are other situations except that the first front-end corrected time is longer than the second front-end corrected time, and the first rear-end corrected time is longer than the second rear-end corrected time, the embodiment of the present application can send the first dining place and the second dining place to the user device at the same time, and include the front-end and rear-end moving time, meal delivery time, queuing time and dining time of the two dining places, so as to display it to the passenger through the user device for the passenger to choose the dining place to go to.

[0073] This application also provides an airport passenger travel data processing device based on artificial intelligence, referring to Figure 3 , Figure 3A module schematic diagram of an airport passenger travel data processing device based on artificial intelligence provided in an embodiment of the present application, wherein the airport passenger travel data processing device is a server, and the server includes an acquisition module 31 and a processing module 32, wherein the acquisition module 31 responds to a meal request input by a passenger through a user device, and the passenger is located in the airport and has passed the security check but has not yet boarded the plane; the processing module 32 acquires the passenger's boarding information according to the meal request, and the boarding information includes the boarding time, the boarding gate location information, and the carry-on baggage information, and the boarding time is the time between the start boarding time and the end boarding time of the flight corresponding to the passenger; the processing module 32 determines the passenger's available meal time according to the boarding time and the carry-on baggage information; the acquisition module 31 acquires the passenger's current location information; The acquisition module 31 acquires the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining places within a preset range, and the preset range is determined according to the current location information and the boarding gate location information; the processing module 32 determines the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining places; the processing module 32 selects a first dining time that meets the preset conditions from multiple dining times according to the available dining time, and the first dining time is any one of the multiple dining times; the processing module 32 determines a first dining place corresponding to the first dining time, and one dining time corresponds to one dining place; the processing module 32 sends the first dining place to the user device so that the passenger can go to the first dining place for dining.

[0074] In a possible implementation, the processing module 32 determines the available dining time of the passenger according to the boarding time and the carry-on baggage information, specifically including: the processing module 32 determines the end boarding time of the flight corresponding to the passenger according to the boarding time; the acquisition module 31 acquires the current time, and calculates the time between the current time and the end boarding time to obtain the target time; the processing module 32 determines the number and weight of the carry-on baggage carried by the passenger according to the carry-on baggage information; the processing module 32 determines the time increment based on the number and weight of the carry-on baggage; the processing module 32 calculates the difference between the target time and the time increment to obtain the available dining time of the passenger.

[0075] In a possible implementation, the acquisition module 31 acquires the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining places within a preset range, specifically including: the processing module 32 obtains the current position coordinate point according to the current position information; the processing module 32 obtains the boarding gate position coordinate point according to the boarding gate position information; the processing module 32 draws a circle with the current position coordinate point as the center and a radius of a preset length to obtain a target circle; the processing module 32 simulates the target circle moving from the current position coordinate point along a preset trajectory line, and stops moving when the center of the circle coincides with the boarding gate position coordinate point, to obtain a coverage area, and the preset trajectory line is the actual trajectory line between the current position coordinate point and the boarding gate position coordinate point; if the processing module 32 determines that there is an overlap between the coverage area and the dining area, the dining place corresponding to the dining area is used as the dining place within the preset range, and the dining area is obtained by expanding the area according to the ordering place corresponding to the dining place.

[0076] In a possible implementation, the dining time is determined based on the current position information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location, specifically including: the acquisition module 31 acquires the first moving distance between the current position and the dining location, the second moving distance between the dining location and the boarding gate location, and the moving speed of the passenger; the processing module 32 determines the front-end moving time required for the passenger to travel from the current position to the dining location, and the rear-end moving time required for the passenger to travel from the dining location to the boarding gate location based on the first moving distance, the second moving distance and the moving speed; the processing module 32 corrects the front-end moving time and the rear-end moving time respectively in combination with the time increment to obtain the front-end corrected time and the rear-end corrected time; the processing module 32 accumulates the front-end corrected time, the rear-end corrected time, the real-time meal delivery time, the real-time queuing time and the dining time to obtain the dining time.

[0077] In a possible implementation, the processing module 32 obtains the dining time corresponding to the dining location by the acquisition module 31 before determining the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location; obtaining the dining time corresponding to the dining location specifically includes: the acquisition module 31 obtains the type of meal corresponding to the dining location; the processing module 32 determines the historical dining time corresponding to the type of meal from the historical dining data corresponding to the dining location according to the current time, the historical dining data including the historical dining time corresponding to each historical passenger for each type of meal; the processing module 32 calculates the average meal time corresponding to multiple historical meal times to obtain the dining time corresponding to the dining location.

[0078] In a possible implementation, the acquisition module 31 acquires the meal duration corresponding to the dining location, and specifically also includes: the acquisition module 31 acquires the personalized dining information of the passenger; the processing module 32 determines multiple personalized meal durations corresponding to the meal types according to the personalized dining information; the processing module 32 calculates the average meal duration corresponding to the multiple personalized meal durations to obtain the meal duration corresponding to the dining location.

[0079] In a possible implementation, the processing module 32 determines from the first dining time the first front-end moving time required for the passenger to travel from the current location to the first dining location, and the first rear-end moving time required for the passenger to travel from the first dining location to the boarding gate location; the acquisition module 31 acquires the second dining time corresponding to the second dining location, where the second dining time is any one of the multiple dining times other than the first dining time that meets a preset condition, and the preset condition is that the dining time is less than the available dining time; the processing module 32 determines from the second dining time the second front-end moving time required for the passenger to travel from the current location to the second dining location, and the first rear-end moving time required for the passenger to travel from the first dining location to the boarding gate location. The second rear-end movement time required for the second dining location to reach the boarding gate location; the processing module 32 corrects the first front-end movement time and the first rear-end movement time by time increment to obtain the first front-end corrected time and the first rear-end corrected time; the processing module 32 corrects the second front-end movement time and the second rear-end correction time by time increment to obtain the second front-end corrected time and the second rear-end corrected time; if the processing module 32 determines that the first front-end correction time is greater than the second front-end correction time, and the first rear-end correction time is greater than the second rear-end correction time, then the second dining location is sent to the user device in priority to facilitate the passenger to go to the second dining location for dining.

[0080] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0081] The present application also provides an electronic device, referring to Figure 4 , Figure 4 The electronic device may include: at least one processor 41 , at least one network interface 44 , a user interface 43 , a memory 45 , and at least one communication bus 42 .

[0082] The communication bus 42 is used to realize the connection and communication between these components.

[0083] The user interface 43 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 43 may also include a standard wired interface and a wireless interface.

[0084] The network interface 44 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0085] Among them, the processor 41 may include one or more processing cores. The processor 41 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 45, and calling data stored in the memory 45. Optionally, the processor 41 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 41 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 41, and it can be implemented separately through a chip.

[0086] Among them, the memory 45 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 45 includes a non-transitory computer-readable storage medium. The memory 45 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 45 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 45 may also be optionally at least one storage device located away from the aforementioned processor 41. As Figure 4As shown, the memory 45 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of an airport passenger travel data processing method based on artificial intelligence.

[0087] exist Figure 4 In the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 41 can be used to call an application program stored in the memory 45 for an airport passenger travel data processing method based on artificial intelligence. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0088] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0089] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0090] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0092] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0093] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0094] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0095] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. An airport passenger travel data processing method based on artificial intelligence, characterized in that: The method comprises: In response to a meal request input by a passenger through a user device, the passenger is in an airport and has passed security check but has not yet boarded a plane; According to the meal request, the boarding information of the passenger is obtained, wherein the boarding information includes boarding time, boarding gate location information, and carry-on baggage information, wherein the boarding time is the time from the start boarding time to the end boarding time of the flight corresponding to the passenger; Determining the available meal time for the passenger according to the boarding time and the carry-on baggage information; Obtaining the current location information of the passenger; Obtaining real-time meal delivery time, real-time queue time, and meal time corresponding to dining locations within a preset range, wherein the preset range is determined according to the current location information and the boarding gate location information; Determine the dining time based on the current location information and the real-time meal delivery time, real-time queue time and dining time corresponding to the dining location; According to the available meal time, a first meal time satisfying a preset condition is obtained from a plurality of the meal time, wherein the first meal time is any one of the plurality of the meal time; Determine a first dining location corresponding to the first dining duration, where one dining duration corresponds to one dining location; The first dining location is sent to the user device, so that the traveler can go to the first dining location for dining.

2. The method for processing airport passenger travel data based on artificial intelligence according to claim 1, characterized in that: The determining, according to the boarding time and the carry-on luggage information, the available dining time of the passenger specifically includes: Determine the end boarding time of the flight corresponding to the passenger according to the boarding time; Obtaining the current time, and calculating the duration between the current time and the end boarding time to obtain the target duration; Determining the quantity and weight of the carry-on luggage carried by the passenger according to the carry-on luggage information; determining a time increment based on the number and weight of the carry-on luggage; The difference between the target duration and the time increment is calculated to obtain the available dining time of the passenger.

3. The method for processing airport passenger travel data based on artificial intelligence according to claim 1, characterized in that: The obtaining of the real-time meal delivery time, real-time queue time and meal time corresponding to the dining locations within the preset range specifically includes: According to the current position information, obtain the current position coordinate point; According to the boarding gate location information, obtaining the boarding gate location coordinate point; Draw a circle with the current position coordinate point as the center and a radius of a preset length to obtain a target circle; Simulate the target circle to move from the current position coordinate point along a preset trajectory line, and stop moving when the center of the circle coincides with the boarding gate position coordinate point, to obtain a coverage area, wherein the preset trajectory line is an actual trajectory line between the current position coordinate point and the boarding gate position coordinate point; If it is determined that there is an overlap between the coverage area and the dining area, the dining location corresponding to the dining area is used as the dining location within the preset range, and the dining area is obtained by expanding the area according to the ordering place corresponding to the dining location.

4. The method for processing airport passenger travel data based on artificial intelligence according to claim 2 is characterized in that: The determining of the dining time based on the current location information and the real-time meal delivery time, real-time queue time, and dining time corresponding to the dining location specifically includes: Acquire a first moving distance between the current position and the dining location, a second moving distance between the dining location and the boarding gate location, and a moving speed of the passenger; Based on the first moving distance, the second moving distance, and the moving speed, determining a front-end moving time required for the passenger to travel from the current location to the dining location, and a rear-end moving time required for the passenger to travel from the dining location to the boarding gate location; In combination with the time increment, the front-end moving duration and the back-end moving duration are respectively corrected to obtain the front-end corrected duration and the back-end corrected duration; The front-end correction time, the back-end correction time, the real-time meal delivery time, the real-time queuing time and the meal time are accumulated to obtain the meal time.

5. The method for processing airport passenger travel data based on artificial intelligence according to claim 2 is characterized in that: Before determining the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining place, obtaining the dining time corresponding to the dining place; The obtaining of the dining time corresponding to the dining location specifically includes: Obtaining the meal types corresponding to the dining location; According to the current moment, determining the historical dining duration corresponding to the meal type from the historical dining data corresponding to the dining location, wherein the historical dining data includes the historical dining duration corresponding to each historical passenger for the meal type; The average meal duration corresponding to the plurality of historical meal durations is calculated to obtain the meal duration corresponding to the dining location.

6. The method for processing airport passenger travel data based on artificial intelligence according to claim 5 is characterized in that: The obtaining of the dining time corresponding to the dining location specifically includes: Obtaining personalized dining information of the passenger; Determining, according to the personalized meal information, a plurality of personalized meal durations corresponding to the meal types; The average meal duration corresponding to the multiple personalized meal durations is calculated to obtain the meal duration corresponding to the dining location.

7. The method for processing airport passenger travel data based on artificial intelligence according to claim 4 is characterized in that: The method further comprises: Determine, from the first dining time, a first front-end moving time required for the passenger to travel from the current location to the first dining location, and a first rear-end moving time required for the passenger to travel from the first dining location to the boarding gate location; Acquire a second dining time corresponding to a second dining location, where the second dining time is any one of the plurality of dining times, except the first dining time, that satisfies the preset condition, and the preset condition is that the dining time is less than the available dining time; Determine from the second dining time the second front-end moving time required for the passenger to travel from the current location to the second dining location, and the second rear-end moving time required for the passenger to travel from the second dining location to the boarding gate location; Correcting the first front-end moving duration and the first rear-end moving duration by using the time increment to obtain a first front-end corrected duration and a first rear-end corrected duration; Correcting the second front-end moving duration and the second back-end moving duration by using the time increment to obtain a second front-end corrected duration and a second back-end corrected duration; If it is determined that the first front-end correction time is greater than the second front-end correction time, and the first back-end correction time is greater than the second back-end correction time, the second dining location is preferentially sent to the user device to facilitate the passenger to go to the second dining location for dining.

8. An airport passenger travel data processing device based on artificial intelligence, characterized in that: The airport passenger travel data processing device comprises an acquisition module (31) and a processing module (32), wherein: The acquisition module (31) is used to respond to a dining request input by a passenger through a user device, wherein the passenger is in the airport and has passed security check but has not yet boarded the aircraft; The processing module (32) is used to obtain the boarding information of the passenger according to the dining request, wherein the boarding information includes boarding time, boarding gate location information and carry-on baggage information, and the boarding time is the time from the start boarding time to the end boarding time of the flight corresponding to the passenger; The processing module (32) is further used to determine the available dining time of the passenger according to the boarding time and the carry-on luggage information; The acquisition module (31) is also used to acquire the current location information of the passenger; The acquisition module (31) is further used to acquire the real-time meal delivery time, real-time queuing time and meal time corresponding to the dining places within a preset range, wherein the preset range is determined according to the current location information and the boarding gate location information; The processing module (32) is further used to determine the dining time based on the current location information and the real-time meal delivery time, real-time queuing time and dining time corresponding to the dining location; The processing module (32) is further used to select, according to the available meal time, from the plurality of meal time periods to obtain a first meal time period that meets a preset condition, wherein the first meal time period is any one of the plurality of meal time periods; The processing module (32) is further used to determine a first dining location corresponding to the first dining duration, where one dining duration corresponds to one dining location; The processing module (32) is also used to send the first dining location to the user device so that the traveler can go to the first dining location for dining.

9. An electronic device, characterized in that: The electronic device comprises a processor (41), a memory (45), a user interface (43) and a network interface (44), wherein the memory (45) is used to store instructions, the user interface (43) and the network interface (44) are both used to communicate with other devices, and the processor (41) is used to execute the instructions stored in the memory (45) so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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