Personalized service recommendation method based on roaming AP airport indoor positioning

Abstract

The invention discloses a personalized service recommendation method based on roaming AP airport indoor positioning, and particularly relates to the field of big data analysis, and the method comprises the steps: determining an airport indoor AP coverage area, deploying and installing an AP, obtaining first airport key information based on the division of the airport indoor AP coverage area, carrying out the preprocessing of the first airport key information, and carrying out the processing of the first airport key information. Obtaining a first airport key information value corresponding to the first airport key information, obtaining second airport key information, preprocessing the second airport key information, obtaining a second airport key information value corresponding to the second airport key information, and constructing a key information value association model; and obtaining a third airport key information value through the first airport key information value and the second airport key information value, constructing a personalized service recommendation model, obtaining personalized service recommendation content for the passenger through the third airport key information value, and outputting the personalized service recommendation content to a user information end to obtain more comprehensive and accurate personalized service recommendation content for the passenger.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and more specifically, to a personalized service recommendation method based on roaming AP airport indoor positioning. Background Art

[0002] With the rapid development of wireless communication technology, Wi-Fi networks have become an indispensable part of daily life. As a place with dense traffic and diverse service needs, airports are important areas for Wi-Fi network deployment. With the maturity and popularization of roaming AP technology, high-precision indoor positioning can be achieved by receiving multiple AP signals and using algorithms such as triangulation positioning and fingerprint positioning. Nowadays, airport indoor positioning technology based on roaming AP has been widely used in various scenarios of airports, including terminal halls, boarding gates, baggage claim areas, etc., which can effectively improve the operational efficiency of airports and enhance the travel experience of tourists. With the continuous development of technologies such as big data and artificial intelligence, personalized service recommendations have become more accurate and intelligent. The system provides personalized service recommendations based on user preferences, needs and other factors.

[0003] The traditional personalized service recommendation method for indoor positioning in airports first establishes an indoor positioning system, selects appropriate positioning technology, and collects user location information in real time; user behavior analysis, identifies user behavior and infers user preferences; personalized service recommendation, formulates personalized service recommendation strategies based on user behavior and preferences, and generates specific recommendation content based on the recommendation strategy; effect evaluation and optimization, collects user feedback data on recommended content, evaluates the effect, and adjusts and optimizes the recommended strategy based on the evaluation results. The traditional personalized service recommendation method for indoor positioning in airports provides highly personalized service recommendations by accurately locating user locations and combining user behavior analysis, which significantly improves user experience satisfaction at the airport.

[0004] However, in actual use, it still has some shortcomings, such as limited positioning accuracy. The traditional personalized service recommendation method for airport indoor positioning is easily affected by the complexity of the indoor environment and is easily affected by the flow of people, resulting in signal attenuation and inaccurate positioning; personalized service recommendations are limited. The traditional personalized service recommendation method for airport indoor positioning has limited collection of personalized information such as users' personality preferences and behavior patterns, making it difficult to provide accurate personalized service recommendations. Summary of the invention

[0005] In order to overcome the above defects of the prior art, an embodiment of the present invention provides a personalized service recommendation method based on roaming AP airport indoor positioning, and solves the problems raised in the above background technology through the following method.

[0006] To achieve the above object, the present invention provides the following technical solution: a personalized service recommendation method based on roaming AP airport indoor positioning, including a running database, a central processor and a user information terminal, the method comprising:

[0007] S1: Determine the indoor AP coverage area of ​​the airport, divide the coverage area into individual sub-AP coverage areas in an equal-area manner, and deploy and install APs;

[0008] S2: based on the division of the indoor AP coverage area of ​​the airport, obtaining first airport key information, where the first airport key information is passenger location information;

[0009] S3: performing a preprocessing operation on the first airport key information, wherein the preprocessing operation is used to obtain a first airport key information value corresponding to the first airport key information;

[0010] S4: Acquire second airport key information, where the second airport key information is airport system information and passenger preference information;

[0011] S5: performing a preprocessing operation on the second airport key information, wherein the preprocessing operation is used to obtain a second airport key information value corresponding to the second airport key information;

[0012] S6: constructing a key information value association model, and obtaining a third airport key information value through the first airport key information value and the second airport key information value according to the key information value association model;

[0013] S7: construct a personalized service recommendation model, and obtain personalized service recommendation content for passengers through the third airport key information value according to the personalized service recommendation model;

[0014] S8: Output the passenger's personalized service recommendation content to the user information terminal.

[0015] Before determining the indoor coverage area of ​​the airport, it is necessary to understand the different areas in the airport in advance, including the number of passengers and employees in the waiting hall, boarding gate, check-in area, rest area and shops, and understand the indoor building structure of the airport, including floor layout, load-bearing wall location, ceiling height, etc., evaluate the impact of building materials on wireless signals, and select APs of appropriate size based on the technical specifications, maximum coverage distance and penetration strength of the AP, and arrange an AP point every 30 meters according to the area of ​​the airport to ensure that the entire airport is within the coverage of the AP, while also avoiding interference caused by signal overlap. After the AP is installed, perform a signal coverage test, use professional wireless test tools to measure the signal strength and coverage of each area, and diagnose possible problems based on the test results, such as signal blind spots, interference, etc., and optimize by adjusting the AP position, channel allocation or increasing the number of APs.

[0016] Preferably, the method for obtaining the key information of the first airport is to determine the location of the device held by the passenger through the access point of the wireless local area network, deploy multiple wireless network access points in an equal-area distribution manner in the airport, set the same user name and password for all roaming APs, and collect the key information of the first airport, including AP signal strength, MAC address of the 2.4G frequency band, signal arrival time, and signal arrival time difference.

[0017] Preferably, the process of obtaining the first airport key information value is:

[0018] A1: Preprocess the data of the first airport key information and filter out the key information related to the location of the target passenger's equipment in the first airport key information;

[0019] A2: Match the collected key information related to the target passenger’s device location with the pre-established location information database;

[0020] A3: The grid positioning algorithm is applied based on the matched key information to calculate the passenger positioning information, i.e. the key information value of the first airport.

[0021] The acquisition of the first airport key information value is based on the screening and processing of the first airport key information. The first airport key information includes multiple groups of AP signal strengths, MAC addresses of the 2.4G frequency band, signal arrival times, and signal arrival time differences. Data related to the time point to be measured are screened out, and these parameters are used to estimate the distance between the passenger device and the AP point, and a grid positioning algorithm is applied to estimate the passenger's real-time positioning information, i.e., the first airport key information value.

[0022] Preferably, the second airport key information includes aircraft flight information, weather conditions and passenger personalized preferences, and the passenger personalized preferences and passenger behavior patterns are obtained from the passenger service system and the consumption system, and the airport's aircraft flight information is obtained using the API provided by the airport, and the local real-time weather information is obtained.

[0023] Preferably, the process of obtaining the second airport key information value is:

[0024] B1: pre-process the data of the second airport key information and filter out the key information related to passengers in the second airport key information;

[0025] B2: Comprehensively analyze the key passenger-related information, including flight information, real-time weather information, and passenger preferences;

[0026] B3: Construct passenger behavior preference information based on the comprehensive analysis results, that is, the second airport key information value.

[0027] The acquisition of the second airport key information value needs to be based on the screening and processing of the second airport key information. The second airport key information mainly includes aircraft flight information, weather conditions and passengers' personalized preferences, wherein the aircraft flight information includes aircraft flight number, departure place and destination, departure time and arrival time, cabin layout, flight status, baggage policy, catering services and transfer information, weather conditions include temperature, humidity, air pressure, precipitation, cloud conditions, wind direction, wind speed, visibility and air quality, and passengers' personalized preferences include transportation mode selection, travel purpose, accommodation type, food preferences, interests and hobbies, leisure methods and language and culture. The second airport key information is associated to build a strong correlation between aircraft flight information, weather conditions and passengers' personalized preferences to obtain the second airport key information value.

[0028] Preferably, the method for constructing a key information value association model specifically includes:

[0029] C1: Collect enough samples, integrate the first airport key information values ​​and the second airport key information values ​​of multiple groups of passengers into the passenger data information database, and normalize the data;

[0030] C2: Associate any first airport key information value of a passenger with the corresponding second airport key information value of the passenger, and use the associated data to analyze the user's behavior patterns and preference characteristics under different positioning;

[0031] C3: Based on the associated data, a key information value association model is constructed, and the model is trained and optimized;

[0032] C4: Obtain the associated information value between any first airport key information value and the corresponding second airport key information value through the key information value association model, that is, the third airport key information value.

[0033] The step of associating the first airport key information value with the corresponding second airport key information value is to combine the real-time positioning information of the passenger in the first airport key information value with the information related to the real-time positioning of the passenger in the second airport key information value, such as the real-time positioning of the passenger near the store, tourist attractions, weather conditions, public facilities and the flight information of the passenger, and comprehensively analyze the possible movement trajectory of the passenger based on the real-time positioning information and action preference information of the passenger.

[0034] Preferably, the passenger data information database is obtained by collecting sufficient passenger positioning information and passenger behavior preference information and processing and integrating the data, wherein sufficient data refers to collecting positioning information and behavior preference information of multiple groups of different passengers in the airport, the passenger positioning information includes points where each passenger may appear in the airport, and the points are divided into units of 5 square meters, and the passenger behavior preference information includes a variety of different behavior preference situations, covering all possible situations of all passengers.

[0035] Preferably, the method for constructing a personalized service recommendation model specifically includes:

[0036] D1: Import the third airport key information value, and encode and convert the third airport key information value;

[0037] D2: Based on the passenger's third airport key information value, including the passenger's location information and the passenger's possible movement trajectory under the location, recommend nearby related stores and services;

[0038] D3: Combine the real-time flight information and aircraft flight information in the third airport key information to formulate relevant push information for passengers in real time;

[0039] D4: Model training is performed using the historical third airport key information collected in the operation database and the third airport key information collected in real time;

[0040] D5: Collect passengers’ feedback on the personalized service recommendation model, and regularly optimize and update the model.

[0041] Personalized service recommendation information is formulated for passengers in combination with the key information value of the third airport, and the possible movement trajectory of the passengers obtained in the above process, including arrival at the airport, waiting, transfer and aircraft arrival, among which, when arriving at the airport, the route guidance information of baggage check-in, security check requirements and location information of the terminal hall are pushed to the passengers according to the real-time positioning of the passengers. During the waiting process, the store information in the airport is recommended to the passengers according to the positioning information and registration time of the passengers, and the passengers are reminded of the boarding time in time. During the transfer process, the transfer flight information is pushed to the passengers and the weather conditions of the transfer place are pushed in real time, and the passengers are reminded of clothing matters. When the plane arrives, the weather conditions of the destination should be pushed to the passengers according to the positioning information of the passengers and the personal preferences of the passengers, and reasonable travel plans, scenic spot information and hotel information should be pushed to the passengers according to the weather conditions.

[0042] Preferably, the user information terminal refers to an electronic device used by passengers to receive personalized recommendation information, including the user's mobile phone and smart watch; the operation database includes a location information database and a passenger data information database, which is used to receive all data information in the steps of the personalized service recommendation method based on roaming AP airport indoor positioning, and collect all data information output in each step in real time; the central processor is used to control the data information instructions in each step.

[0043] Technical effects and advantages of the present invention:

[0044] 1. The present invention conducts surveys and collects data on the airport area before AP deployment to understand the flow of people and indoor structures in each area, and deploys an AP point every 30 meters to ensure that each AP point fully covers the entire airport area without interfering with each other, and uses the grid positioning method to calculate the real-time positioning information of the passengers at the first airport, that is, the key information value of the first airport;

[0045] 2. The present invention obtains the second airport key information and accurately investigates the passengers' individual preferences through three methods: questionnaire survey, user behavior analysis and user social media interaction. The second airport key information value is obtained through the second airport key information, and the first airport key information value is associated with the second airport key information value to obtain the third airport key information value. The personalized recommendation service content formulated for passengers is more accurate and comprehensive. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a diagram of the method steps of the present invention.

[0047] Figure 2 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0050] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0051] As attached Figure 1 The personalized service recommendation method based on roaming AP airport indoor positioning shown includes an operating database, a central processor and a user information terminal.

[0052] The operation database includes a location information database and a passenger data information database, which are used to receive all data information in the steps of the personalized service recommendation method based on roaming AP airport indoor positioning, and collect all data information output in each step in real time; the central processor is used to centrally control the data information instructions in each step; the user information terminal refers to an electronic device used by passengers to receive personalized recommendation information, including the user's mobile phone and smart watch.

[0053] S1: Determine the indoor AP coverage area of ​​the airport, divide the coverage area into individual sub-AP coverage areas in an equal-area manner, and deploy and install APs.

[0054] What needs to be specifically explained in this embodiment is that before determining the indoor coverage area of ​​the airport, it is necessary to understand in advance the different areas in the airport, including the number of passengers and employees in the waiting hall, boarding gate, check-in area, rest area and shops, and understand the indoor building structure of the airport, including floor layout, load-bearing wall position, ceiling height, etc., evaluate the impact of building materials on wireless signals, and select APs of appropriate size according to the technical specifications, maximum coverage distance and penetration strength of the APs, and arrange an AP point every 30 meters according to the area of ​​the airport to ensure that the entire airport is within the coverage of the APs, while also avoiding interference caused by signal overlap. After the AP is installed, perform a signal coverage test, use professional wireless test tools to measure the signal strength and coverage of each area, and diagnose possible problems based on the test results, such as signal blind spots, interference, etc., and optimize by adjusting the AP position, channel allocation or increasing the number of APs.

[0055] S2: based on the division of the indoor AP coverage area of ​​the airport, obtaining first airport key information, where the first airport key information is passenger location information;

[0056] The method for obtaining the key information of the first airport is to determine the location of the passenger's device through the access point of the wireless local area network, deploy multiple wireless network access points in an equal-area distribution manner in the airport, set the same user name and password for all roaming APs, and collect the key information of the first airport, including AP signal strength, MAC address of the 2.4G frequency band, signal arrival time, and signal arrival time difference.

[0057] S3: performing a preprocessing operation on the first airport key information, wherein the preprocessing operation is used to obtain a first airport key information value corresponding to the first airport key information;

[0058] The process of obtaining the first airport key information value is as follows:

[0059] A1: Preprocess the data of the first airport key information and filter out the key information related to the location of the target passenger's equipment in the first airport key information;

[0060] A2: Match the collected key information related to the target passenger’s device location with the pre-established location information database;

[0061] A3: The grid positioning algorithm is applied based on the matched key information to calculate the passenger positioning information, i.e. the key information value of the first airport.

[0062] What needs to be specifically explained in this embodiment is that the acquisition of the first airport key information value is based on the screening and processing of the first airport key information. The first airport key information includes multiple groups of AP signal strengths, MAC addresses of the 2.4G frequency band, signal arrival times, and signal arrival time differences. Data related to the time point to be measured are screened out, and these parameters are used to estimate the distance between the passenger device and the AP point, and a grid positioning algorithm is applied to estimate the passenger's real-time positioning information, that is, the first airport key information value.

[0063] S4: Acquire second airport key information, where the second airport key information is airport system information and passenger preference information;

[0064] The second airport key information includes aircraft flight information, weather conditions and passengers' personalized preferences. Passenger personalized preferences and passenger behavior patterns are obtained from the passenger service system and consumption system. The airport's aircraft flight information and local real-time weather information are obtained using the API provided by the airport.

[0065] It should be specifically noted in this embodiment that the personalized preferences of passengers are obtained through questionnaires, user behavior analysis, and user social media interactions. After passengers book their trips, their preference information is collected through online questionnaires or forms. The preference information may include accommodation type, dining preferences, activity interests, travel purposes, budget range, special needs, etc. User behavior analysis requires the use of browsing data, click streams, search history, and purchase behavior of websites and mobile applications to analyze passengers' preferences. It is also possible to monitor passengers' activities on social media, such as likes, shares, comments, etc., to understand passengers' interests and preferences, and thus obtain passengers' personalized preferences.

[0066] S5: performing a preprocessing operation on the second airport key information, wherein the preprocessing operation is used to obtain a second airport key information value corresponding to the second airport key information;

[0067] The process of obtaining the second airport key information value is as follows:

[0068] B1: pre-process the data of the second airport key information and filter out the key information related to passengers in the second airport key information;

[0069] B2: Comprehensively analyze the key passenger-related information, including flight information, real-time weather information, and passenger preferences;

[0070] B3: Construct passenger behavior preference information based on the comprehensive analysis results, that is, the second airport key information value.

[0071] What needs to be specifically explained in this embodiment is that the acquisition of the second airport key information value needs to be based on the screening and processing of the second airport key information. The second airport key information mainly includes aircraft flight information, weather conditions and passengers' personalized preferences, wherein the aircraft flight information includes the aircraft flight number, departure place and destination, departure time and arrival time, cabin layout, flight status, baggage policy, catering services and transfer information, weather conditions include temperature, humidity, air pressure, precipitation, cloud conditions, wind direction, wind speed, visibility and air quality, and passengers' personalized preferences include transportation mode selection, travel purpose, accommodation type, food preferences, interests and hobbies, leisure methods and language and culture. The second airport key information is associated with each other, and a strong correlation between the aircraft flight information, weather conditions and passengers' personalized preferences is constructed to obtain the second airport key information value.

[0072] S6: constructing a key information value association model, and obtaining a third airport key information value through the first airport key information value and the second airport key information value according to the key information value association model;

[0073] The method for constructing a key information value association model specifically includes:

[0074] C1: Collect enough samples, integrate the first airport key information values ​​and the second airport key information values ​​of multiple groups of passengers into the passenger data information database, and normalize the data;

[0075] C2: Associate any first airport key information value of a passenger with the corresponding second airport key information value of the passenger, and use the associated data to analyze the user's behavior patterns and preference characteristics under different positioning;

[0076] C3: Based on the associated data, a key information value association model is constructed, and the model is trained and optimized;

[0077] C4: Obtain the associated information value between any first airport key information value and the corresponding second airport key information value through the key information value association model, that is, the third airport key information value.

[0078] The passenger data information database is obtained by collecting enough passenger location information and passenger behavior preference information and processing and integrating the data, wherein enough data refers to collecting location information and behavior preference information of multiple groups of different passengers in the airport. The passenger location information includes the points where each passenger may appear in the airport, and the points are divided into units of 5 square meters. The passenger behavior preference information includes a variety of different behavior preference situations, covering all possible situations of all passengers.

[0079] What needs to be specifically explained in this embodiment is that enough passenger information data is collected to build a passenger data information database. The enough passenger behavior preference information refers to multiple groups of passenger information data of different age groups and different genders, which should cover enough types. In addition, for the selection of passenger samples, passengers with different travel purposes and different personality preferences should be selected as samples as much as possible. At least 1,000 groups of data should be collected for each type of passenger, and the collected data should be stored in the passenger data information database.

[0080] What needs to be specifically explained in this embodiment is the step of associating the first airport key information value with the corresponding airport second key information value, combining the real-time positioning information of the passenger in the first airport key information value with the information related to the real-time positioning of the passenger in the second airport key information value, such as the passenger's real-time positioning of nearby stores, tourist attractions, weather conditions, public facilities and the passenger's flight information, and comprehensively analyzing the passenger's possible movement trajectory based on the passenger's real-time positioning information and action preference information.

[0081] S7: construct a personalized service recommendation model, and obtain personalized service recommendation content for passengers through the third airport key information value according to the personalized service recommendation model;

[0082] The method for constructing a personalized service recommendation model specifically includes:

[0083] D1: Import the third airport key information value, and encode and convert the third airport key information value;

[0084] D2: Based on the passenger's third airport key information value, including the passenger's location information and the passenger's possible movement trajectory under the location, recommend nearby related stores and services;

[0085] D3: Combine the real-time flight information and aircraft flight information in the third airport key information to formulate relevant push information for passengers in real time;

[0086] D4: Model training is performed using the historical third airport key information collected in the operation database and the third airport key information collected in real time;

[0087] D5: Collect passengers’ feedback on the personalized service recommendation model and regularly optimize and update the model

[0088] What needs to be specifically explained in this embodiment is that personalized service recommendation information is formulated for passengers in combination with the third airport key information value, and the possible movement trajectory of the passengers obtained in the above process, including arrival at the airport, waiting, transfer and aircraft arrival, wherein when arriving at the airport, the route guidance information of baggage check-in, security check requirements and location information of the terminal hall are pushed to the passengers according to the real-time positioning of the passengers; during the waiting process, the store information in the airport is recommended to the passengers according to the positioning information and registration time of the passengers, and the passengers are reminded of the boarding time in time; during the transfer process, the transfer flight information is pushed to the passengers and the weather conditions of the transfer place are pushed in real time, and the passengers are reminded of clothing matters; when the plane arrives, the weather conditions of the destination should be pushed to the passengers according to the positioning information of the passengers and the personal preferences of the passengers, and reasonable travel plans, scenic spot information and hotel information should be pushed to the passengers according to the weather conditions.

[0089] S8: Output the passenger's personalized service recommendation content to the user information terminal.

[0090] It should be specifically explained in this embodiment that the user information terminal may include electronic devices such as passenger mobile phones and smart watches, and the methods for receiving personalized service recommendation content include APP push, SMS notification, and mini-program push.

[0091] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0092] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A personalized service recommendation method based on roaming AP airport indoor positioning, comprising an operation database, a central processor and a user information terminal, characterized in that: The method comprises: S1: Determine the indoor AP coverage area of ​​the airport, divide the coverage area into individual sub-AP coverage areas in an equal-area manner, and deploy and install APs; S2: based on the division of the indoor AP coverage area of ​​the airport, obtaining first airport key information, where the first airport key information is passenger location information; S3: performing a preprocessing operation on the first airport key information, wherein the preprocessing operation is used to obtain a first airport key information value corresponding to the first airport key information; S4: Acquire key information of a second airport, where the key information of the second airport is airport system information and passenger preference information; S5: performing a preprocessing operation on the second airport key information, wherein the preprocessing operation is used to obtain a second airport key information value corresponding to the second airport key information; S6: constructing a key information value association model, and obtaining a third airport key information value through the first airport key information value and the second airport key information value according to the key information value association model; S7: construct a personalized service recommendation model, and obtain personalized service recommendation content for passengers through the third airport key information value according to the personalized service recommendation model; S8: Output the passenger's personalized service recommendation content to the user information terminal.

2. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 1 is characterized by: The method for obtaining the key information of the first airport is to determine the location of the passenger's device through the access point of the wireless local area network, deploy multiple wireless network access points in an equal-area distribution manner in the airport, set the same user name and password for all roaming APs, and collect the key information of the first airport, including AP signal strength, MAC address of the 2.4G frequency band, signal arrival time, and signal arrival time difference.

3. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 1 is characterized by: The process of obtaining the first airport key information value is as follows: A1: Preprocess the data of the first airport's key information and filter out the key information related to the location of the target passenger's equipment from the first airport's key information; A2: Match the collected key information related to the target passenger’s device location with the pre-established location information database; A3: The grid positioning algorithm is applied based on the matched key information to calculate the passenger positioning information, i.e. the key information value of the first airport.

4. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 1, characterized in that: The second airport key information includes aircraft flight information, weather conditions and passengers' personalized preferences. Passenger personalized preferences and passenger behavior patterns are obtained from the passenger service system and consumption system. The airport's aircraft flight information and local real-time weather information are obtained using the API provided by the airport.

5. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 1, characterized in that: The process of obtaining the second airport key information value is as follows: B1: pre-process the data of the second airport key information and filter out the key information related to passengers in the second airport key information; B2: Comprehensively analyze the key passenger-related information, including flight information, real-time weather information, and passenger preferences; B3: Construct passenger behavior preference information based on the comprehensive analysis results, that is, the second airport key information value.

6. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 1, characterized in that: The method for constructing a key information value association model specifically includes: C1: Collect enough samples, integrate the first airport key information values ​​and the second airport key information values ​​of multiple groups of passengers into the passenger data information database, and normalize the data; C2: Associate any first airport key information value of a passenger with the corresponding second airport key information value of the passenger, and use the associated data to analyze the user's behavior patterns and preference characteristics under different positioning; C3: Based on the associated data, a key information value association model is constructed, and the model is trained and optimized; C4: Obtain the associated information value between any first airport key information value and the corresponding second airport key information value through the key information value association model, that is, the third airport key information value.

7. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 6 is characterized by: The passenger data information database is obtained by collecting enough passenger location information and passenger behavior preference information and processing and integrating the data, wherein enough data refers to collecting location information and behavior preference information of multiple groups of different passengers in the airport. The passenger location information includes the points where each passenger may appear in the airport, and the points are divided into units of 5 square meters. The passenger behavior preference information includes a variety of different behavior preference situations, covering all possible situations of all passengers.

8. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 1, characterized in that: The method for constructing a personalized service recommendation model specifically includes: D1: Import the third airport key information value, and encode and convert the third airport key information value; D2: Based on the passenger's third airport key information value, including the passenger's location information and the passenger's possible movement trajectory under the location, recommend nearby related stores and services; D3: Combine the real-time flight information and aircraft flight information in the third airport key information to formulate relevant push information for passengers in real time; D4: Model training is performed using the historical third airport key information collected in the operation database and the third airport key information collected in real time; D5: Collect passengers’ feedback on the personalized service recommendation model, and regularly optimize and update the model.

9. The personalized service recommendation method based on roaming AP airport indoor positioning according to claim 1, characterized in that: The user information terminal refers to an electronic device used by passengers to receive personalized recommendation information, including the user's mobile phone and smart watch; the operation database includes a location information database and a passenger data information database, which is used to receive all data information in the steps of the personalized service recommendation method based on roaming AP airport indoor positioning, and collect all data information output in each step in real time; the central processor is used to centrally control the data information instructions in each step.

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