Big data analysis payment system and method based on geographic position

Abstract

The invention discloses a big data analysis payment system and method based on a geographic position. The big data analysis payment system comprises a geographic information data storage module, a common route analysis module, a geographic position acquisition module, a geographic position analysis module, a payment information confirmation module, a consumption record calling module, a user payment habit analysis module, a payment limit setting module, a payment anomaly detection module and a limited payment authentication module. The method has the beneficial effects that the geographic position meeting the storage condition is stored, the common route of the user and the staying area on the common route are analyzed according to the stored geographic position, and the real-time position of the user is further analyzed according to the common route of the user; the payment limit at any geographic position is analyzed and set through the payment habit of the user, the payment limit at the current real-time position of the user is acquired, and the payment amount is compared with the payment limit so as to detect the abnormal payment condition.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a big data analysis payment system and method based on geographic location. Background Art

[0002] The payment system refers to the bridge that connects consumers, merchants or platforms, and financial institutions. It manages payment data, calls third-party payment platform interfaces, and records payment information. The payment information includes the corresponding order number, payment amount, etc. The payment system appears, is generated, developed, and is constantly improved due to the market demand for debt repayment and capital transfer in the course of economic activities. The payment system is a social system. In each historical period of economic development, there are corresponding payment systems for capital transfer and debt liquidation and settlement.

[0003] However, the existing technology still has many shortcomings. The existing payment method is to scan the code to pay through the mobile client, and the payment verification method includes password verification. However, if the password is leaked and the mobile client is held by others, the existing technology cannot restrict the person holding the mobile client, that is, restrict their consumption behavior, which will undoubtedly cause economic losses to people.

[0004] Based on the above problems, there is an urgent need to propose a big data analysis payment system and method based on geographic location, which stores geographic locations that meet the storage conditions, analyzes the user's frequently used routes and the stay areas on the frequently used routes based on the stored geographic locations, further analyzes the user's real-time location based on the user's frequently used routes, sets the payment amount at any geographic location through analysis of the user's payment habits, obtains the payment amount at the user's current real-time location, and compares the payment amount with the payment amount to detect payment anomalies. Summary of the invention

[0005] The purpose of the present invention is to provide a big data analysis payment system and method based on geographic location to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: A big data analysis payment system based on geographic location, the big data analysis payment system includes a geographic information data storage module, a common route analysis module, a geographic location acquisition module, a geographic location analysis module, a payment information confirmation module, a consumption record retrieval module, a user payment habit analysis module, a payment limit setting module, a payment anomaly detection module, and a payment restriction authentication module. The geographic information data storage module is used to pre-store the geographic location information data of the user each time and the user's frequently used routes. The frequently used routes are classified according to holidays and weekdays. The frequently used route analysis module is used to analyze the user's frequently used routes according to the user's geographic location information. The geographic location acquisition module is used to acquire the user's real-time geographic location. The geographic location analysis module is used to analyze whether the user's current real-time geographic location is within the payment restricted range. The payment information confirmation module is used to confirm the payment information when the user performs a payment operation. The consumption record retrieval module is used to retrieve the user's daily consumption records. The user payment habit analysis module is used to analyze the user's daily payment habits. The payment limit setting module is used to set the payment limit according to the user's daily payment habits. The restricted payment authentication module is used when the user's payment behavior is restricted by geographic location. The payment anomaly detection module is used to detect anomalies in the payment process. The user verifies his own identity through the restricted payment authentication module.

[0007] Furthermore, the geographic information data storage module stores the start time node information of the user's stay at the corresponding geographic location and the end time node information of leaving the corresponding geographic location while storing the geographic location information, and calculates the user's stay time at the corresponding geographic location based on the start time node and the end time node, and further stores the stay time in the geographic information data storage module. The geographic information data storage module filters the data according to the calculated residence time while storing the geographic information data. When the residence time is greater than or equal to the residence time threshold, the geographic information data storage module stores the corresponding geographic location. The frequent patterns appearing in the user's historical trajectory reflect the individual's living habits and behavioral patterns. The individual's residence locations are analyzed, and then the relationship between the residence location, i.e., the geographic location, and payment is combined to analyze the user's payment habits at any geographic location, so that it is possible to detect whether there is any abnormality in the current payment based on the user's current geographic location and payment amount.

[0008] Furthermore, the geographic information data storage module is connected to the common route analysis module, and the common route analysis module obtains the geographic location information stored in a certain period of time through the geographic information data storage module, and the common route analysis module analyzes the user's common routes according to the acquired geographic location information. Further, the plurality of stay areas are divided according to the stay time of the geographical locations stored in the certain time period, the common route analysis module connects all the geographical locations in the certain time period in the order of time nodes, and divides the starting position and the end position, and the common route analysis module obtains the first angle formed by the connection line of three consecutive geographical locations at the time node including the starting position from the starting point. , the three geographical locations are respectively the first location, the second location and the third location in the order of time nodes, wherein the line connecting the first location and the second location is the first straight line, the line connecting the second location and the third location is the second straight line, the line connecting the first location and the third location is the third straight line, and the first angle is the first angle between the first straight line and the second straight line, If the first angle Less than or equal to the angle threshold, the common route analysis module further obtains the first center point position of the third straight line, takes the first center point position as the first center of the circle, and preliminarily divides the first stay area into the first radius. A historical movement trajectory is composed of a series of coordinate points with timestamps, each coordinate point contains geographic location information, and a person's activities over a period of time can be recorded as such a continuous trajectory. The coordinate points on this trajectory are the geographic locations where the user stays, such as restaurants and cinemas that the user has visited, where the user will consume. Moreover, since the coordinate points generated by users visiting the same place multiple times are not completely consistent, there may be deviations. The coordinate points can be expanded to an accurate range, so that we attribute the coordinate points within the range, that is, the geographic locations, to the range as a coordinate point, and then conduct an overall analysis of the coordinate point.

[0009] Further, the common route analysis module takes the third position as the first starting point, and again obtains the second angle formed by the connection lines of three consecutive geographical locations at the time node including the first starting point. , If the second angle is less than or equal to the angle threshold, the common route analysis module further obtains the geographical location with the longest time interval from the first starting point among the three geographical locations as the second starting point, obtains the midpoint of the second center point positions of the first starting point and the second starting point, takes the midpoint as the second circle center, further obtains the geographical location other than the first starting point and the second starting point among the three geographical locations, and calculates the distance between the second circle center and the geographical location , further calculate the distance between the second circle center and the second position of the three points this time ,Compare and the sizes of the second circle, selecting the larger one as the second radius, and dividing the second stay area according to the second center and the second radius; If the second angle If the angle is greater than the angle threshold, the common route analysis module removes the second position of the three points on the line connecting the geographical locations within a certain time period, and replaces the second position with the first center of the circle, that is, connects the first position, the first center of the circle, and the third position, and attaches the radius information of the first stop area at the first center of the circle. According to the above steps, the third stay area, the fourth stay area, ..., the nth stay area are divided, and the common route analysis module connects the first position, the first center of the circle, the second center of the circle, ..., the nth center of the circle, and the end point position, and attaches the radius information of the nth stay area at the nth center of the circle, so that the final center of the circle is located at the center of multiple consecutive coordinate points on the trajectory, and the geographical location farthest from the center of the circle is obtained, and the distance between the two is used as the radius of the circle, and a circle is made with the center of the circle and the radius to form a stay area, and the stay area is used as a coordinate point. When the geographical location is obtained later, the geographical location in the stay area is regarded as part of the stay area, and the stay area is analyzed as a whole. Moreover, people's purchasing level and consumption concept will not change within a certain period of time. Therefore, according to people's historical stay locations and consumption information at the location, the payment limit of the designated location can be set for the user to detect payment abnormalities.

[0010] Furthermore, the payment information confirmation module obtains the user's payment operation. When it is detected that the user is performing a payment operation, the geographic location acquisition module obtains the user's real-time location information and transmits the user's real-time location information to the geographic location analysis module. The geographic location analysis module is connected to the geographic information data storage module. The geographic location analysis module obtains the user's frequently used route information through the geographic information data storage module and analyzes the user's real-time location based on the user's frequently used route information.

[0011] Furthermore, the geographic location analysis module compares the user's real-time location with the user's common route information. When the user's real-time location is on any common route, the common route classification is obtained according to whether it is a weekday or a holiday, and further confirms whether the user's real-time location is in a stop area divided on the common route. If so, the payment limit of the corresponding stay area is obtained through the payment limit setting module; If not, that is, the current real-time location is any connection node on the common route, the payment limit at the real-time location is further obtained through the payment limit setting module; When the user's real-time location is not on any common route, the user's identity is authenticated through the restricted payment authentication module. When the user is not on his or her common route, the user's identity needs to be authenticated when paying.

[0012] Furthermore, the payment limit setting module is connected to the consumption record retrieval module and the user payment habit analysis module. The user payment habit analysis module obtains the user's past daily consumption records through the consumption record retrieval module, and obtains the location and time information of the consumption. The user payment habit analysis module classifies according to holidays and weekdays, and obtains the weekday consumption records and holiday consumption records of the geographical locations corresponding to the connection nodes on all the stay areas and all the commonly used routes through the consumption record retrieval module. The user habit analysis module further calculates the average daily consumption at the geographical locations corresponding to each stay area and each connection node on weekdays and holidays, and the payment amount setting module uses the average daily consumption as the payment amount at the geographical locations corresponding to each stay area and connection node on weekdays and holidays. The consumption generated on holidays and weekdays is different, and the stay locations on holidays and weekdays are also different, so it is necessary to distinguish the situation and analyze the consumption habits on weekdays and holidays respectively, so as to select the appropriate comparison object according to the current time point, and further detect whether abnormal payment occurs.

[0013] Furthermore, the payment limit setting module is connected to the payment information confirmation module, and the payment information confirmation module is connected to the payment anomaly detection module and the geographic location analysis module. The payment information confirmation module determines the user's payment location through the geographic location acquisition module, and the payment information confirmation module further obtains the payment amount of the current user. The geographic location analysis module analyzes the payment location. If the current payment location is not on the user's usual route, the user's identity is verified through the restricted payment authentication module. If the current payment location is on the user's usual route, the payment amount at the payment location is obtained through the payment amount setting module. The payment anomaly detection module detects the user's payment amount each time. calculate The value of is the i-th payment amount of the current user at the stay area or connection node location of the payment location, To pay the amount, when When the value of is greater than a preset value, the payment anomaly detection module detects the current situation as a payment anomaly, and authenticates the identity of the user by limiting the payment authentication module. The user may make multiple consumptions in any stay area or connection node, so it is necessary to accumulate the total amount of payment made by the user in the stay area or connection node within a certain period of time, and detect whether an abnormal situation occurs based on the accumulated total amount. Because people's consumption concepts and purchasing levels will not change much over a long period of time, the user's common routes are obtained by analyzing the user's personal historical movement trajectory, and then by setting a preset value, the preset value is compared with The value of is not necessarily lower than the payment limit, because each consumption of the user cannot be lower than the payment limit, it may exceed a little, but as long as the excess amount is not much, it is within a reasonable range, so as long as When the value is less than or equal to the preset value, it can be considered to be within a reasonable range.

[0014] Furthermore, a big data analysis payment method based on geographic location, the big data analysis payment method comprises the following steps: S1: Obtain the user's geographic location information and store the geographic locations that meet the storage conditions; S2: Analyze the user's common routes based on the stored geographic locations; S3: Analyze the user's real-time location based on the user's common routes; S4: Setting the payment limit at any geographical location by analyzing the user's payment habits; S5: Detect payment anomalies by comparing the payment amount with the payment limit.

[0015] Furthermore, the big data analysis payment method further includes the following steps: S1-1: The geographic information data storage module stores the starting time node information of the user's stay at the corresponding geographic location and the ending time node information of the user's departure from the corresponding geographic location while storing the geographic location information, and calculates the user's stay time at the corresponding geographic location based on the starting time node and the ending time node, and further stores the stay time in the geographic information data storage module. The geographic information data storage module filters the data according to the calculated residence time while storing the geographic information data. When the residence time is greater than or equal to the residence time threshold, the geographic information data storage module stores the corresponding geographic location; S2-1: The geographic information data storage module is connected to the common route analysis module. The common route analysis module obtains the geographic location information stored in a certain period of time through the geographic information data storage module. The common route analysis module analyzes the user's common routes based on the acquired geographic location information. Further, the storage location of the location within a certain period of time is divided into several stay areas according to the stay time. The common route analysis module connects all the location within a certain period of time in the order of time nodes, and divides the starting point location and the end point location. The common route analysis module obtains the first angle formed by the connection line of three consecutive location locations at the time node including the starting point starting from the starting point. , the three geographical locations are respectively the first location, the second location and the third location in the order of time nodes, wherein the line connecting the first location and the second location is the first straight line, the line connecting the second location and the third location is the second straight line, the line connecting the first location and the third location is the third straight line, and the first angle is the first angle between the first straight line and the second straight line, If the first angle is less than or equal to the angle threshold, the common route analysis module further obtains the first center point position of the third straight line, takes the first center point position as the first circle center, and the distance from the first center point to the second position as the first radius to preliminarily divide the first stay area, The common route analysis module takes the third location as the first starting point and obtains the second angle formed by the lines connecting the three consecutive geographical locations at the time node including the first starting point. , If the second angle is less than or equal to the angle threshold, the common route analysis module further obtains the geographical location with the longest time interval from the first starting point among the three geographical locations as the second starting point, obtains the midpoint of the second center point positions of the first starting point and the second starting point, takes the midpoint as the second circle center, further obtains the geographical location other than the first starting point and the second starting point among the three geographical locations, and calculates the distance between the second circle center and the geographical location , further calculate the distance between the second circle center and the second starting point ,Compare and the sizes of the second circle, selecting the larger one as the second radius, and dividing the second stay area according to the second center and the second radius; If the second angle If the angle is greater than the angle threshold, the common route analysis module removes the third starting point position on the line connecting the geographical locations within a certain time period, and replaces the third starting point position with the first center of the circle, that is, connects the first starting point position, the first center of the circle, and the second starting point position, and retains the first stay area at the center of the first circle with the radius of the first stay area; According to the above steps, the third stay area, the fourth stay area, ..., the nth stay area are divided, and the common route analysis module connects the first position, the first circle center, the second circle center, ..., the nth circle center, and the end point position, and attaches the radius information of the nth stay area at the nth circle center; S3-1: The payment information confirmation module obtains the user's payment operation. When it is detected that the user is performing a payment operation, the geographic location acquisition module obtains the user's real-time location information and transmits the user's real-time location information to the geographic location analysis module. The geographic location analysis module is connected to the geographic information data storage module. The geographic location analysis module obtains the user's common route information through the geographic information data storage module, and analyzes the user's real-time location based on the user's common route information. The geographic location analysis module compares the user's real-time location with the user's common route information. When the user's real-time location is on any common route, the common route classification is obtained based on whether it is a weekday or a holiday, and further confirms whether the user's real-time location is in the stop area divided on the common route. If so, the payment limit of the corresponding stay area is obtained through the payment limit setting module; If not, that is, the current real-time location is any connection node on the common route, the payment limit at the real-time location is further obtained through the payment limit setting module; When the user's real-time location is not on any common route, the user's identity is authenticated through the restricted payment authentication module; S4-1: The payment limit setting module connects to the consumption record retrieval module and the user payment habit analysis module. The user payment habit analysis module obtains the user's previous daily consumption records through the consumption record retrieval module, and obtains the location and time information of the consumption. The user payment habit analysis module classifies according to holidays and weekdays, and obtains the weekday consumption records and holiday consumption records of the corresponding geographical locations of all stay areas and connection nodes on all common routes through the consumption record retrieval module. The user habit analysis module further calculates the average daily consumption at each stay area and each connection node corresponding to the geographical location on weekdays and holidays, and the payment limit setting module uses the average daily consumption as the payment limit at each stay area and each connection node corresponding to the geographical location on weekdays and holidays; S5-1: The payment limit setting module is connected to the payment information confirmation module, and the payment information confirmation module is connected to the payment anomaly detection module and the geographic location analysis module. The payment information confirmation module determines the user's payment location through the geographic location acquisition module. The payment information confirmation module further obtains the current user's payment amount. The geographic location analysis module analyzes the payment location. If the current payment location is not on the user's usual route, the user's identity is verified through the restricted payment authentication module. If the current payment location is on the user's usual route, the payment limit setting module obtains the payment limit at the payment location. The payment anomaly detection module detects the user's payment amount each time. calculate The value of is the i-th payment amount of the current user at the stay area or connection node location of the payment location, To pay the amount, when When the value of is greater than a preset value, the payment anomaly detection module detects the current situation as a payment anomaly and authenticates the user's identity by restricting the payment authentication module.

[0016] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention stores geographical locations that meet the storage conditions, and analyzes the user's frequently used routes and the stop areas on the frequently used routes based on the stored geographical locations, further analyzes the user's real-time location based on the user's frequently used routes, sets the payment amount at any geographical location through the analysis of the user's payment habits, obtains the payment amount at the user's current real-time location, and compares the payment amount with the payment amount to detect payment anomalies. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a module schematic diagram of a big data analysis payment system based on geographic location of the present invention; Figure 2 It is a schematic diagram of the steps of a big data analysis payment method based on geographic location of the present invention. DETAILED DESCRIPTION

[0018] 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.

[0019] See also Figure 1-Figure 2 , the present invention provides a technical solution: A big data analysis payment system based on geographic location, the big data analysis payment system includes a geographic information data storage module, a common route analysis module, a geographic location acquisition module, a geographic location analysis module, a payment information confirmation module, a consumption record retrieval module, a user payment habit analysis module, a payment limit setting module, a payment anomaly detection module, and a payment restriction authentication module. The geographic information data storage module is used to pre-store the geographic location information data of the user each time and the user's frequently used routes. The frequently used routes are classified according to holidays and weekdays. The frequently used route analysis module is used to analyze the user's frequently used routes based on the user's geographic location information. The geographic location acquisition module is used to obtain the user's real-time geographic location. The geographic location analysis module is used to analyze whether the user's current real-time geographic location is within the payment restriction range. The payment information confirmation module is used to confirm the payment information when the user performs a payment operation. The consumption record retrieval module is used to retrieve the user's daily consumption records. The user payment habit analysis module is used to analyze the user's daily payment habits. The payment limit setting module is used to set the payment limit according to the user's daily payment habits. The restricted payment authentication module is used when the user's payment behavior is restricted by geographic location. The payment anomaly detection module is used to detect anomalies in the payment process. The user verifies his own identity through the restricted payment authentication module.

[0020] The geographic information data storage module stores the starting time node information of the user's stay at the corresponding geographic location and the ending time node information of leaving the corresponding geographic location while storing the geographic location information, and calculates the user's stay time at the corresponding geographic location based on the starting time node and the ending time node, and further stores the stay time in the geographic information data storage module. The geographic information data storage module filters the data according to the calculated residence time while storing the geographic information data. When the residence time is greater than or equal to the residence time threshold, the geographic information data storage module stores the corresponding geographic location.

[0021] The geographic information data storage module is connected to the common route analysis module. The common route analysis module obtains the geographic location information stored in a certain period of time through the geographic information data storage module. The common route analysis module analyzes the user's common routes based on the acquired geographic location information. Further, the storage location of the location within a certain period of time is divided into several stay areas according to the stay time. The common route analysis module connects all the location within a certain period of time in the order of time nodes, and divides the starting point location and the end point location. The common route analysis module obtains the first angle formed by the connection line of three consecutive location locations at the time node including the starting point starting from the starting point. , the three geographical locations are respectively the first location, the second location and the third location in the order of time nodes, wherein the line connecting the first location and the second location is the first straight line, the line connecting the second location and the third location is the second straight line, the line connecting the first location and the third location is the third straight line, and the first angle is the first angle between the first straight line and the second straight line, If the first angle is less than or equal to the angle threshold, the common route analysis module further obtains the first center point position of the third straight line, takes the first center point position as the first center of the circle, and preliminarily divides the first stay area into the first radius.

[0022] The common route analysis module takes the third location as the first starting point and obtains the second angle formed by the lines connecting the three consecutive geographical locations at the time node including the first starting point. , If the second angle is less than or equal to the angle threshold, the common route analysis module further obtains the geographical location with the longest time interval from the first starting point among the three geographical locations as the second starting point, obtains the midpoint of the second center point positions of the first starting point and the second starting point, takes the midpoint as the second circle center, further obtains the geographical location other than the first starting point and the second starting point among the three geographical locations, and calculates the distance between the second circle center and the geographical location , further calculate the distance between the second circle center and the second starting point ,Compare and the sizes of the second circle, selecting the larger one as the second radius, and dividing the second stay area according to the second center and the second radius; If the second angle If the angle is greater than the angle threshold, the common route analysis module removes the third starting point position on the line connecting the geographical locations within a certain time period, and replaces the third starting point position with the first center of the circle, that is, connects the first starting point position, the first center of the circle, and the second starting point position, and retains the first stop area at the center of the first circle with the radius of the first stop area. According to the above steps, the third stay area, the fourth stay area, ..., the nth stay area are divided, and the common route analysis module connects the first position, the first center of the circle, the second center of the circle, ..., the nth center of the circle, and the end position, and attaches the radius information of the nth stay area at the nth center of the circle.

[0023] The payment information confirmation module obtains the user's payment operation. When it is detected that the user is performing a payment operation, the geographic location acquisition module obtains the user's real-time location information and transmits the user's real-time location information to the geographic location analysis module. The geographic location analysis module is connected to the geographic information data storage module. The geographic location analysis module obtains the user's frequently used route information through the geographic information data storage module and analyzes the user's real-time location based on the user's frequently used route information.

[0024] The location analysis module compares the user's real-time location with the user's common route information. When the user's real-time location is on any common route, the common route classification is obtained based on whether it is a weekday or a holiday, and further confirms whether the user's real-time location is in the stop area divided on the common route. If so, the payment limit of the corresponding stay area is obtained through the payment limit setting module; If not, that is, the current real-time location is any connection node on the common route, the payment limit at the real-time location is further obtained through the payment limit setting module; When the user's real-time location is not on any common route, the user's identity is authenticated through the restricted payment authentication module.

[0025] The payment limit setting module is connected to the consumption record retrieval module and the user payment habit analysis module. The user payment habit analysis module obtains the user's previous daily consumption records through the consumption record retrieval module, and obtains the location and time information of the consumption. The user payment habit analysis module classifies according to holidays and weekdays, and obtains the weekday consumption records and holiday consumption records of the corresponding geographical locations of all stay areas and connection nodes on all common routes through the consumption record retrieval module. The user habit analysis module further calculates the average daily consumption at the geographical locations corresponding to each stay area and each connection node on weekdays and holidays, and the payment limit setting module uses the average daily consumption as the payment limit at the geographical locations corresponding to each stay area and connection node on weekdays and holidays.

[0026] The payment limit setting module is connected to the payment information confirmation module, and the payment information confirmation module is connected to the payment anomaly detection module and the geographic location analysis module. The payment information confirmation module determines the user's payment location through the geographic location acquisition module. The payment information confirmation module further obtains the current user's payment amount. The geographic location analysis module analyzes the payment location. If the current payment location is not on the user's usual route, the user's identity is verified through the restricted payment authentication module. If the current payment location is on the user's usual route, the payment limit setting module obtains the payment limit at the payment location. The payment anomaly detection module detects the user's payment amount each time. calculate The value of is the i-th payment amount of the current user at the stay area or connection node location of the payment location, To pay the amount, when When the value of is greater than a preset value, the payment anomaly detection module detects the current situation as a payment anomaly and authenticates the user's identity by restricting the payment authentication module.

[0027] A big data analysis payment method based on geographic location, the big data analysis payment method comprising the following steps: S1: Obtain the user's geographic location information and store the geographic locations that meet the storage conditions; S2: Analyze the user's common routes based on the stored geographic locations; S3: Analyze the user's real-time location based on the user's common routes; S4: Setting the payment limit at any geographical location by analyzing the user's payment habits; S5: Detect payment anomalies by comparing the payment amount with the payment limit.

[0028] The big data analysis payment method also includes the following steps: S1-1: The geographic information data storage module stores the starting time node information of the user's stay at the corresponding geographic location and the ending time node information of the user's departure from the corresponding geographic location while storing the geographic location information, and calculates the user's stay time at the corresponding geographic location based on the starting time node and the ending time node, and further stores the stay time in the geographic information data storage module. The geographic information data storage module filters the data according to the calculated residence time while storing the geographic information data. When the residence time is greater than or equal to the residence time threshold, the geographic information data storage module stores the corresponding geographic location; S2-1: The geographic information data storage module is connected to the common route analysis module. The common route analysis module obtains the geographic location information stored in a certain period of time through the geographic information data storage module. The common route analysis module analyzes the user's common routes based on the acquired geographic location information. Further, the storage location of the location within a certain period of time is divided into several stay areas according to the stay time. The common route analysis module connects all the location within a certain period of time in the order of time nodes, and divides the starting point location and the end point location. The common route analysis module obtains the first angle formed by the connection line of three consecutive location locations at the time node including the starting point starting from the starting point. , the three geographical locations are respectively the first location, the second location and the third location in the order of time nodes, wherein the line connecting the first location and the second location is the first straight line, the line connecting the second location and the third location is the second straight line, the line connecting the first location and the third location is the third straight line, and the first angle is the first angle between the first straight line and the second straight line, If the first angle is less than or equal to the angle threshold, the common route analysis module further obtains the first center point position of the third straight line, takes the first center point position as the first circle center, and the distance from the first center point to the second position as the first radius to preliminarily divide the first stay area, The common route analysis module takes the third location as the first starting point and obtains the second angle formed by the lines connecting the three consecutive geographical locations at the time node including the first starting point. , If the second angle is less than or equal to the angle threshold, the common route analysis module further obtains the geographical location with the longest time interval from the first starting point among the three geographical locations as the second starting point, obtains the midpoint of the second center point positions of the first starting point and the second starting point, takes the midpoint as the second circle center, further obtains the geographical location other than the first starting point and the second starting point among the three geographical locations, and calculates the distance between the second circle center and the geographical location , further calculate the distance between the second circle center and the second starting point ,Compare and the sizes of the second circle, selecting the larger one as the second radius, and dividing the second stay area according to the second center and the second radius; If the second angle If the angle is greater than the angle threshold, the common route analysis module removes the third starting point position on the line connecting the geographical locations within a certain time period, and replaces the third starting point position with the first center of the circle, that is, connects the first starting point position, the first center of the circle, and the second starting point position, and retains the first stop area at the center of the first circle with the radius of the first stop area. According to the above steps, the third stay area, the fourth stay area, ..., the nth stay area are divided, and the common route analysis module connects the first position, the first circle center, the second circle center, ..., the nth circle center, and the end point position, and attaches the radius information of the nth stay area at the nth circle center; S3-1: The payment information confirmation module obtains the user's payment operation. When it is detected that the user is performing a payment operation, the geographic location acquisition module obtains the user's real-time location information and transmits the user's real-time location information to the geographic location analysis module. The geographic location analysis module is connected to the geographic information data storage module. The geographic location analysis module obtains the user's common route information through the geographic information data storage module, and analyzes the user's real-time location based on the user's common route information. The geographic location analysis module compares the user's real-time location with the user's common route information. When the user's real-time location is on any common route, the common route classification is obtained based on whether it is a weekday or a holiday, and further confirms whether the user's real-time location is in the stop area divided on the common route. If so, the payment limit of the corresponding stay area is obtained through the payment limit setting module; If not, that is, the current real-time location is any connection node on the common route, the payment limit at the real-time location is further obtained through the payment limit setting module; When the user's real-time location is not on any common route, the user's identity is authenticated through the restricted payment authentication module; S4-1: The payment limit setting module connects to the consumption record retrieval module and the user payment habit analysis module. The user payment habit analysis module obtains the user's previous daily consumption records through the consumption record retrieval module, and obtains the location and time information of the consumption. The user payment habit analysis module classifies according to holidays and weekdays, and obtains the weekday consumption records and holiday consumption records of the corresponding geographical locations of all stay areas and connection nodes on all common routes through the consumption record retrieval module. The user habit analysis module further calculates the average daily consumption at each stay area and each connection node corresponding to the geographical location on weekdays and holidays, and the payment limit setting module uses the average daily consumption as the payment limit at each stay area and each connection node corresponding to the geographical location on weekdays and holidays; S5-1: The payment limit setting module is connected to the payment information confirmation module, and the payment information confirmation module is connected to the payment anomaly detection module and the geographic location analysis module. The payment information confirmation module determines the user's payment location through the geographic location acquisition module. The payment information confirmation module further obtains the current user's payment amount. The geographic location analysis module analyzes the payment location. If the current payment location is not on the user's usual route, the user's identity is verified through the restricted payment authentication module. If the current payment location is on the user's usual route, the payment limit setting module obtains the payment limit at the payment location. The payment anomaly detection module detects the user's payment amount each time. calculate The value of is the i-th payment amount of the current user at the stay area or connection node location of the payment location, To pay the amount, when When the value of is greater than a preset value, the payment anomaly detection module detects the current situation as a payment anomaly and authenticates the user's identity by restricting the payment authentication module.

[0029] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0030] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A big data analysis payment system based on geographic location, characterized by: The big data analysis payment system includes a geographic information data storage module, a common route analysis module, a geographic location acquisition module, a geographic location analysis module, a payment information confirmation module, a consumption record retrieval module, a user payment habit analysis module, a payment limit setting module, a payment anomaly detection module, and a payment restriction authentication module. The geographic information data storage module is used to pre-store the geographic location information data of the user each time and the user's frequently used routes. The frequently used routes are classified according to holidays and weekdays. The frequently used route analysis module is used to analyze the user's frequently used routes according to the user's geographic location information. The geographic location acquisition module is used to acquire the user's real-time geographic location. The geographic location analysis module is used to analyze whether the user's current real-time geographic location is within the payment restricted range. The payment information confirmation module is used to confirm the payment information when the user performs a payment operation. The consumption record retrieval module is used to retrieve the user's daily consumption records. The user payment habit analysis module is used to analyze the user's daily payment habits. The payment limit setting module is used to set the payment limit according to the user's daily payment habits. The restricted payment authentication module is used when the user's payment behavior is restricted by geographic location. The payment anomaly detection module is used to detect anomalies in the payment process. The user verifies his own identity through the restricted payment authentication module.

2. A geographical location-based big data analysis payment system according to claim 1, characterized in that: The geographic information data storage module stores the starting time node information of the user's stay at the corresponding geographic location and the ending time node information of the user's departure from the corresponding geographic location while storing the geographic location information, and calculates the user's stay time at the corresponding geographic location based on the starting time node and the ending time node, and further stores the stay time in the geographic information data storage module. The geographic information data storage module filters the data according to the calculated residence time while storing the geographic information data. When the residence time is greater than or equal to the residence time threshold, the geographic information data storage module stores the corresponding geographic location.

3. A geographical location-based big data analysis payment system according to claim 1 or 2, characterized in that: The geographic information data storage module is connected to the common route analysis module, and the common route analysis module obtains the geographic location information stored in a certain period of time through the geographic information data storage module, and the common route analysis module analyzes the user's common routes according to the acquired geographic location information. Further, the plurality of stay areas are divided according to the stay time of the geographical locations stored in the certain time period, the common route analysis module connects all the geographical locations in the certain time period in the order of time nodes, and divides the starting position and the end position, and the common route analysis module obtains the first angle formed by the connection line of three consecutive geographical locations at the time node including the starting position from the starting point. , the three geographical locations are respectively the first location, the second location and the third location in the order of time nodes, wherein the line connecting the first location and the second location is the first straight line, the line connecting the second location and the third location is the second straight line, the line connecting the first location and the third location is the third straight line, and the first angle is the first angle between the first straight line and the second straight line, If the first angle is less than or equal to the angle threshold, the common route analysis module further obtains the first center point position of the third straight line, takes the first center point position as the first center of the circle, and preliminarily divides the first stay area into the first radius.

4. A geographical location-based big data analysis payment system according to claim 3, characterized in that: The common route analysis module takes the third position as the first starting point and again obtains the second angle formed by the connection lines of three consecutive geographical locations at the time node including the first starting point. , If the second angle is less than or equal to the angle threshold, the common route analysis module further obtains the geographical location with the longest time interval from the first starting point among the three geographical locations as the second starting point, obtains the midpoint of the second center point positions of the first starting point and the second starting point, takes the midpoint as the second circle center, further obtains the geographical location other than the first starting point and the second starting point among the three geographical locations, and calculates the distance between the second circle center and the geographical location , further calculate the distance between the second circle center and the second starting point ,Compare and the sizes of the second circle, selecting the larger one as the second radius, and dividing the second stay area according to the second center and the second radius; If the second angle If the angle is greater than the angle threshold, the common route analysis module removes the third starting point position on the line connecting the geographical locations within a certain time period, and replaces the third starting point position with the first center of the circle, that is, connects the first starting point position, the first center of the circle, and the second starting point position, and retains the first stay area at the center of the first circle with the radius of the first stay area. According to the above steps, the third stay area, the fourth stay area, ..., the nth stay area are divided, and the common route analysis module connects the first position, the first center of the circle, the second center of the circle, ..., the nth center of the circle, and the end point position, and attaches the radius information of the nth stay area at the nth center of the circle.

5. The big data analysis payment system based on geographic location according to claim 1, characterized in that: The payment information confirmation module obtains the user's payment operation. When it is detected that the user is performing a payment operation, the geographic location acquisition module obtains the user's real-time location information and transmits the user's real-time location information to the geographic location analysis module. The geographic location analysis module is connected to the geographic information data storage module. The geographic location analysis module obtains the user's frequently used route information through the geographic information data storage module and analyzes the user's real-time location based on the user's frequently used route information.

6. A geographical location-based big data analysis payment system according to claim 4 or 5, characterized in that: The geographic location analysis module compares the user's real-time location with the user's common route information. When the user's real-time location is on any common route, the common route classification is obtained according to whether it is a weekday or a holiday, and further confirms whether the user's real-time location is in a stop area divided on the common route. If so, the payment limit of the corresponding stay area is obtained through the payment limit setting module; If not, that is, the current real-time location is any connection node on the common route, the payment limit at the real-time location is further obtained through the payment limit setting module; When the user's real-time location is not on any common route, the user's identity is authenticated through the restricted payment authentication module.

7. A geographical location-based big data analysis payment system according to claim 6, characterized in that: The payment limit setting module is connected to the consumption record retrieval module and the user payment habit analysis module. The user payment habit analysis module obtains the user's past daily consumption records through the consumption record retrieval module, and obtains the location and time information of the consumption. The user payment habit analysis module classifies according to holidays and weekdays, and obtains the weekday consumption records and holiday consumption records of the geographical locations corresponding to the connection nodes on all the stay areas and all the commonly used routes through the consumption record retrieval module. The user habit analysis module further calculates the average daily consumption at the geographical locations corresponding to each stay area and each connection node on weekdays and holidays, and the payment amount setting module uses the average daily consumption as the payment amount at the geographical locations corresponding to each stay area and connection node on weekdays and holidays.

8. A geographical location-based big data analysis payment system according to claim 7, characterized in that: The payment limit setting module is connected to the payment information confirmation module, and the payment information confirmation module is connected to the payment anomaly detection module and the geographic location analysis module. The payment information confirmation module determines the user's payment location through the geographic location acquisition module, and the payment information confirmation module further obtains the payment amount of the current user. The geographic location analysis module analyzes the payment location. If the current payment location is not on the user's usual route, the user's identity is verified through the restricted payment authentication module. If the current payment location is on the user's usual route, the payment amount at the payment location is obtained through the payment amount setting module. The payment anomaly detection module detects the user's payment amount each time. calculate The value of is the i-th payment amount of the current user at the stay area or connection node location of the payment location, To pay the amount, when When the value of is greater than a preset value, the payment anomaly detection module detects the current situation as a payment anomaly and authenticates the identity of the user by limiting the payment authentication module.

9. A big data analysis payment method based on geographic location, characterized in that: The big data analysis payment method comprises the following steps: S1: Obtain the user's geographic location information and store the geographic locations that meet the storage conditions; S2: Analyze the user's common routes based on the stored geographic locations; S3: Analyze the user's real-time location based on the user's common routes; S4: Setting the payment limit at any geographical location by analyzing the user's payment habits; S5: Detect payment anomalies by comparing the payment amount with the payment limit.

10. A method for payment based on geographic location big data analysis according to claim 9, characterized in that: The big data analysis payment method further comprises the following steps: S1-1: The geographic information data storage module stores the starting time node information of the user's stay at the corresponding geographic location and the ending time node information of the user's departure from the corresponding geographic location while storing the geographic location information, and calculates the user's stay time at the corresponding geographic location based on the starting time node and the ending time node, and further stores the stay time in the geographic information data storage module. The geographic information data storage module filters the data according to the calculated residence time while storing the geographic information data. When the residence time is greater than or equal to the residence time threshold, the geographic information data storage module stores the corresponding geographic location; S2-1: The geographic information data storage module is connected to the common route analysis module. The common route analysis module obtains the geographic location information stored in a certain period of time through the geographic information data storage module. The common route analysis module analyzes the user's common routes based on the acquired geographic location information. Further, the storage location of the location within a certain period of time is divided into several stay areas according to the stay time. The common route analysis module connects all the location within a certain period of time in the order of time nodes, and divides the starting point location and the end point location. The common route analysis module obtains the first angle formed by the connection line of three consecutive location locations at the time node including the starting point starting from the starting point. , the three geographical locations are respectively the first location, the second location and the third location in the order of time nodes, wherein the line connecting the first location and the second location is the first straight line, the line connecting the second location and the third location is the second straight line, the line connecting the first location and the third location is the third straight line, and the first angle is the first angle between the first straight line and the second straight line, If the first angle is less than or equal to the angle threshold, the common route analysis module further obtains the first center point position of the third straight line, takes the first center point position as the first circle center, and the distance from the first center point to the second position as the first radius to preliminarily divide the first stay area, The common route analysis module takes the third location as the first starting point and obtains the second angle formed by the lines connecting the three consecutive geographical locations at the time node including the first starting point. , If the second angle is less than or equal to the angle threshold, the common route analysis module further obtains the geographical location with the longest time interval from the first starting point among the three geographical locations as the second starting point, obtains the midpoint of the second center point positions of the first starting point and the second starting point, takes the midpoint as the second circle center, further obtains the geographical location other than the first starting point and the second starting point among the three geographical locations, and calculates the distance between the second circle center and the geographical location , further calculate the distance between the second circle center and the second starting point ,Compare and the sizes of the second circle, selecting the larger one as the second radius, and dividing the second stay area according to the second center and the second radius; If the second angle If the angle is greater than the angle threshold, the common route analysis module removes the third starting point position on the line connecting the geographical locations within a certain time period, and replaces the third starting point position with the first center of the circle, that is, connects the first starting point position, the first center of the circle, and the second starting point position, and retains the first stay area at the center of the first circle with the radius of the first stay area. According to the above steps, the third stay area, the fourth stay area, ..., the nth stay area are divided, and the common route analysis module connects the first position, the first circle center, the second circle center, ..., the nth circle center, and the end point position, and attaches the radius information of the nth stay area at the nth circle center; S3-1: The payment information confirmation module obtains the user's payment operation. When it is detected that the user is performing a payment operation, the geographic location acquisition module obtains the user's real-time location information and transmits the user's real-time location information to the geographic location analysis module. The geographic location analysis module is connected to the geographic information data storage module. The geographic location analysis module obtains the user's common route information through the geographic information data storage module, and analyzes the user's real-time location based on the user's common route information. The geographic location analysis module compares the user's real-time location with the user's common route information. When the user's real-time location is on any common route, the common route classification is obtained based on whether it is a weekday or a holiday, and further confirms whether the user's real-time location is in the stop area divided on the common route. If so, the payment limit of the corresponding stay area is obtained through the payment limit setting module; If not, that is, the current real-time location is any connection node on the common route, the payment limit at the real-time location is further obtained through the payment limit setting module; When the user's real-time location is not on any common route, the user's identity is authenticated through the restricted payment authentication module; S4-1: The payment limit setting module connects to the consumption record retrieval module and the user payment habit analysis module. The user payment habit analysis module obtains the user's previous daily consumption records through the consumption record retrieval module, and obtains the location and time information of the consumption. The user payment habit analysis module classifies according to holidays and weekdays, and obtains the weekday consumption records and holiday consumption records of the corresponding geographical locations of all stay areas and connection nodes on all common routes through the consumption record retrieval module. The user habit analysis module further calculates the average daily consumption at each stay area and each connection node corresponding to the geographical location on weekdays and holidays, and the payment limit setting module uses the average daily consumption as the payment limit at each stay area and each connection node corresponding to the geographical location on weekdays and holidays; S5-1: The payment limit setting module is connected to the payment information confirmation module, and the payment information confirmation module is connected to the payment anomaly detection module and the geographic location analysis module. The payment information confirmation module determines the user's payment location through the geographic location acquisition module. The payment information confirmation module further obtains the current user's payment amount. The geographic location analysis module analyzes the payment location. If the current payment location is not on the user's usual route, the user's identity is verified through the restricted payment authentication module. If the current payment location is on the user's usual route, the payment limit setting module obtains the payment limit at the payment location. The payment anomaly detection module detects the user's payment amount each time. calculate The value of is the i-th payment amount of the current user at the stay area or connection node location of the payment location, To pay the amount, when When the value of is greater than a preset value, the payment anomaly detection module detects the current situation as a payment anomaly and authenticates the user's identity by restricting the payment authentication module.

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