CN111093180A - NFC-based analog card switching method, terminal and computer storage medium - Google Patents
NFC-based analog card switching method, terminal and computer storage medium Download PDFInfo
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Abstract
The invention discloses an analog card switching method based on NFC, which comprises the following steps: acquiring current user behavior data; matching the current user behavior data with a preset user behavior data model, and determining the target type and target switching time of the analog card to be switched; and generating a switching instruction according to the target type and the target switching time of the analog card to be switched, and switching the type of the analog card to the target type according to the switching instruction when the target switching time is reached. The invention also discloses an analog card switching terminal based on NFC and a computer readable storage medium. The invention realizes the automatic switching function of the NFC analog card, avoids the trouble caused by manual switching and improves the payment efficiency.
Description
Technical Field
The invention relates to the technical field of wireless communication, in particular to an analog card switching method based on NFC, a terminal and a computer storage medium.
Background
Near Field Communication (NFC for short) is an emerging technology, terminals using the NFC technology can exchange data when they are close to each other, and is integrated and evolved from a non-contact Radio Frequency Identification (RFID) and interconnection technology, and by integrating functions of an induction card reader, an induction card and point-to-point Communication on a single chip, applications such as mobile payment, electronic ticketing, door access, mobile identity recognition, anti-counterfeiting and the like are realized by using an NFC terminal. In recent years, with the rapid development of intelligent terminals, the popularization of NFC terminals has brought many conveniences to the lives of people. For example, the NFC terminal can replace a bus card in the traffic field, and the terminal is used for swiping a bus; in the payment field, the NFC terminal can replace a bank card by matching with a fingerprint password function, so that the transaction safety is improved to a great extent; in the entrance guard field, the NFC terminal can replace a key or an entrance guard card, and the entrance guard can be swiped by virtue of the terminal.
However, the existing NFC terminal requires the user to manually select the analog card to be used before each use, which degrades the user experience. Therefore, how to intelligently select a required analog card, reduce manual operations, and improve card swiping payment efficiency of the NFC terminal becomes a technical problem to be solved urgently.
Disclosure of Invention
The invention mainly aims to provide an analog card switching method based on NFC, a terminal and a computer storage medium, and aims to solve the technical problems that the conventional NFC terminal requires a user to manually select an analog card to be used before each use, so that the manual operation is complicated, and the card swiping payment efficiency is low.
In order to achieve the above object, the present invention provides an analog card switching method based on NFC, where the analog card switching method based on NFC includes:
acquiring current user behavior data;
matching the current user behavior data with a preset user behavior data model, and determining the target type and target switching time of the analog card to be switched;
and generating a switching instruction according to the target type and the target switching time of the analog card to be switched, and switching the type of the analog card to the target type according to the switching instruction when the target switching time is reached.
Preferably, before the step of matching the current user behavior data with a preset user behavior data model and determining the target type and the target switching time of the simulated card to be switched, the method includes:
the method comprises the steps of collecting user behavior data in a preset time period, and establishing a user behavior data model according to the collected user behavior data.
Preferably, the step of collecting user behavior data within a preset time period and establishing the user behavior data model according to the collected user behavior data includes:
acquiring user behavior data in a preset time period, wherein the user behavior is a detected NFC card swiping event, and the user behavior data comprises a simulated card type and card swiping time corresponding to the NFC card swiping event;
classifying the collected user behavior data according to a preset time period to obtain a data set of each time unit in the time period;
determining each analog card type and switching time corresponding to each analog card type according to the data set of each time unit in the time period;
and establishing the user behavior data model according to the types of the simulation cards and the switching time.
Preferably, the step of determining each analog card type and the switching time corresponding to each analog card type according to the data set of each time unit in the time period includes:
acquiring a card swiping time sequence of each analog card type according to the data set of each time unit in the time period;
acquiring a clustering interval of the card swiping time sequence through a preset clustering algorithm;
taking the average value of the maximum value in the previous clustering interval and the minimum value in the next clustering interval in two adjacent clustering intervals as the switching time to be switched, and taking the analog card type corresponding to the next clustering interval as the analog card type to be switched, wherein the maximum value of the previous clustering interval is smaller than the minimum value of the next clustering interval.
Preferably, the preset time period is one week.
Preferably, the user behavior data further includes a card swiping location corresponding to the NFC card swiping event.
Preferably, after the step of determining each analog card type and the switching time corresponding to each analog card type according to the data set of each time unit in the time period, the method includes:
classifying the card swiping positions corresponding to the NFC card swiping events in the collected preset time period, and determining the card swiping times of each card swiping position;
verifying each analog card type and the switching time corresponding to each analog card type according to the card swiping times of each card swiping position;
the step of establishing the user behavior data model according to the types of the simulation cards and the switching time comprises the following steps:
and establishing the user behavior data model according to the verified analog card types and the switching time corresponding to the analog card types.
Preferably, after the step of collecting the user behavior data within the preset time period and establishing the user behavior data model according to the collected user behavior data, the method further includes:
and updating the user behavior data in the preset time period in real time, and establishing a new user behavior data model according to the updated user behavior data.
In addition, to achieve the above object, the present invention further provides an analog card switching terminal based on NFC, including: a memory, a processor, and an NFC-based emulated card switching program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the NFC-based emulated card switching method of any one of the above.
Furthermore, to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon an NFC-based emulated card switching program, which when executed by a processor implements the steps of the NFC-based emulated card switching method as described in any one of the above.
The method comprises the steps of obtaining current user behavior data; matching the current user behavior data with a preset user behavior data model, and determining the target type and target switching time of the analog card to be switched; and generating a switching instruction according to the target type and the target switching time of the analog card to be switched, and switching the type of the analog card to the target type according to the switching instruction when the target switching time is reached. Through the implementation mode, the method and the device can establish the user behavior data model by training and learning the historical NFC card swiping data of the user, and determine the target type and the target switching time of the analog card to be switched by acquiring the current user behavior data and matching the current user behavior data with the user behavior data in the model after the model is established, thereby realizing the automatic switching function of the NFC analog card, avoiding the trouble caused by manual switching and improving the payment efficiency.
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Fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a NFC-based analog card switching method according to a first embodiment of the present invention;
fig. 3 is a flowchart illustrating a NFC-based analog card switching method according to a second embodiment of the present invention;
fig. 4 is a schematic flowchart of a NFC-based analog card switching method according to a third embodiment of the present invention;
fig. 5 is a flowchart illustrating a NFC-based analog card switching method according to a fourth embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention.
The terminal of the embodiment of the invention can be a smart phone, and can also be a terminal device such as a PC, a tablet computer, an electronic book reader, an MP3(Moving Picture Experts Group Audio Layer III, dynamic video Experts compress standard Audio Layer 3) player, an MP4(Moving Picture Experts Group Audio Layer IV, dynamic video Experts compress standard Audio Layer 4) player, a portable computer, an intelligent bracelet, an intelligent watch and the like. In order to implement the present invention, an NFC chip needs to be disposed in the terminal device, and the NFC chip combines the functions of an inductive card reader, an inductive card and point-to-point, so that the terminal can perform identification and data exchange with a compatible device within a short distance.
As shown in fig. 1, the terminal may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that may adjust the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that may turn off the display screen and/or the backlight when the mobile terminal is moved to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally, three axes), detect the magnitude and direction of gravity when the mobile terminal is stationary, and can be used for applications (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer and tapping) and the like for recognizing the attitude of the mobile terminal; of course, the mobile terminal may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and an NFC-based analog card switching program.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call the NFC-based analog card switching program stored in the memory 1005, and perform the following operations:
acquiring current user behavior data;
matching the current user behavior data with a preset user behavior data model, and determining the target type and target switching time of the analog card to be switched;
and generating a switching instruction according to the target type and the target switching time of the analog card to be switched, and switching the type of the analog card to the target type according to the switching instruction when the target switching time is reached.
Further, the processor 1001 may call the NFC-based analog card switching program stored in the memory 1005, and also perform the following operations:
the method comprises the steps of collecting user behavior data in a preset time period, and establishing a user behavior data model according to the collected user behavior data.
Further, the processor 1001 may call the NFC-based analog card switching program stored in the memory 1005, and also perform the following operations:
acquiring user behavior data in a preset time period, wherein the user behavior is a detected NFC card swiping event, and the user behavior data comprises a simulated card type and card swiping time corresponding to the NFC card swiping event;
classifying the collected user behavior data according to a preset time period to obtain a data set of each time unit in the time period;
determining each analog card type and switching time corresponding to each analog card type according to the data set of each time unit in the time period;
and establishing the user behavior data model according to the types of the simulation cards and the switching time.
Further, the processor 1001 may call the NFC-based analog card switching program stored in the memory 1005, and also perform the following operations:
acquiring a card swiping time sequence of each analog card type according to the data set of each time unit in the time period;
acquiring a clustering interval of the card swiping time sequence through a preset clustering algorithm;
taking the average value of the maximum value in the previous clustering interval and the minimum value in the next clustering interval in two adjacent clustering intervals as the switching time to be switched, and taking the analog card type corresponding to the next clustering interval as the analog card type to be switched, wherein the maximum value of the previous clustering interval is smaller than the minimum value of the next clustering interval.
Further, the processor 1001 may call the NFC-based analog card switching program stored in the memory 1005, and also perform the following operations:
the preset time period is one week.
Further, the processor 1001 may call the NFC-based analog card switching program stored in the memory 1005, and also perform the following operations:
the user behavior data further comprises a card swiping position corresponding to the NFC card swiping event.
Further, the processor 1001 may call the NFC-based analog card switching program stored in the memory 1005, and also perform the following operations:
classifying the card swiping positions corresponding to the NFC card swiping events in the collected preset time period, and determining the card swiping times of each card swiping position;
verifying each analog card type and the switching time corresponding to each analog card type according to the card swiping times of each card swiping position;
the step of establishing the user behavior data model according to the types of the simulation cards and the switching time comprises the following steps:
and establishing the user behavior data model according to the verified analog card types and the switching time corresponding to the analog card types.
Further, the processor 1001 may call the NFC-based analog card switching program stored in the memory 1005, and also perform the following operations:
and updating the user behavior data in the preset time period in real time, and establishing a new user behavior data model according to the updated user behavior data.
The specific embodiment of the NFC-based analog card switching terminal of the present invention is substantially the same as the following embodiments of the NFC-based analog card switching method, and is not described herein again.
Referring to fig. 2, fig. 2 is a schematic flowchart of a first embodiment of an NFC-based emulated card switching method according to the present invention, where the steps of the NFC-based emulated card switching method include:
in step S10, current user behavior data is obtained.
The terminal of the embodiment of the invention can be a smart phone, and can also be a terminal device such as a PC, a tablet computer, an electronic book reader, an MP3(Moving Picture Experts Group Audio Layer III, dynamic video Experts compress standard Audio Layer 3) player, an MP4(Moving Picture Experts Group Audio Layer IV, dynamic video Experts compress standard Audio Layer 4) player, a portable computer, an intelligent bracelet, an intelligent watch and the like. In order to implement the present invention, an NFC chip needs to be disposed in the terminal device, and the NFC chip combines the functions of an inductive card reader, an inductive card and point-to-point, so that the terminal can perform identification and data exchange with a compatible device within a short distance. For convenience of illustration, the following embodiments all use a smart phone supporting the NFC function as an example. When the NFC analog card mode of the smart phone is turned on, current user behavior data needs to be acquired in real time, where the current user behavior data may include current time information and current location information, and may also include an application program used by a current user. Specifically, the system time in the background of the smart phone can be directly read by acquiring the current time information, the current position information can be acquired according to the positioning function of the smart phone, and the application program used by the current user can be directly acquired from the foreground of the operating system.
And step S20, matching the current user behavior data with a preset user behavior data model, and determining the target type and the target switching time of the simulated card to be switched.
A user behavior data model is preset in the smart phone, and the model is established by training and learning historical NFC card swiping data of a user. The model acquires the nearest NFC card swiping habit of the user through training and learning, for example, the user always swipes a parking lot access card at about 8:00, swipes a company access card at about 8:30, swipes a bank card at about 12:00, swipes a company access card at about 17:30, swipes a parking lot access card at about 18:00, swipes a home access card at about 19:00 and the like. Therefore, after the model is established, the acquired current user behavior data needs to be matched with the user behavior data model, so that the target type and the target switching time of the simulated card to be switched are determined. For example, based on the above example, if the current system time acquired by the smart phone is 11:00, the smart phone can predict that the user needs to swipe the bank card in the next 12:00 or so, and therefore, the NFC analog card can be selected to be switched to the bank card type in 11:30, so that the user is ensured to have been automatically switched to the bank card when the user needs to swipe the bank card in 12:00 or so, and the user does not need to manually switch. It should be noted that the target type of the analog card to be switched here is the type of the analog card to be switched at the current time, and the target switching time is the time for switching the analog card at the current time. As known by those skilled in the art, the target type needs to be obtained by analyzing a card swiping rule of a user according to a user behavior data model, and the target switching time needs to be selected in two adjacent card swiping periods, and a specific value can be set according to an actual situation, which is not limited in this embodiment.
Step S30, generating a switching instruction according to the target type and the target switching time of the analog card to be switched, and switching the type of the analog card to the target type when the target switching time is reached according to the switching instruction.
After determining the target type and the target switching time of the analog card to be switched, the smart phone automatically generates a switching instruction, and controls the analog card to be switched according to the switching instruction. Specifically, the switching instruction already contains the target type and the target switching time of the analog card to be switched, so that when the smart phone responds to the switching instruction, whether the current system time reaches the target switching time or not is automatically judged, and when the target switching time is reached, the type of the analog card is switched to the target type.
In the embodiment, the target type and the target switching time of the analog card to be switched are determined by acquiring the current user behavior data and matching the current user behavior data with the preset user behavior data model, so that the automatic switching of the analog card is realized, the trouble caused by manual switching is avoided, and the payment efficiency is improved.
Further, referring to fig. 3, fig. 3 is a flowchart illustrating a second embodiment of the NFC-based emulated card switching method of the present invention, where based on the embodiment shown in fig. 2, before the step S20 matches the current user behavior data with a preset user behavior data model and determines a target type and a target switching time of the emulated card to be switched, the method includes:
step S40, collecting user behavior data in a preset time period, and establishing the user behavior data model according to the collected user behavior data.
The smart phone can analyze the acquired current user behavior data in real time only by pre-establishing a user behavior data model so as to determine the target type and the target switching time of the analog card to be switched, so that the smart phone needs to acquire the user behavior data within a preset time period and establish the user behavior data model according to the acquired user behavior data.
Specifically, the step S40 collects user behavior data in a preset time period, and establishes the user behavior data model according to the collected user behavior data, including:
step S401, collecting user behavior data in a preset time period, wherein the user behavior is a detected NFC card swiping event, and the user behavior data comprises a simulated card type and card swiping time corresponding to the NFC card swiping event.
And acquiring user behavior data in real time, and training and learning the user behavior data in the latest preset time period. It should be noted that the preset time period may be 3 months, 2 months, or 1 month, and the present embodiment is not particularly limited. The user behavior is an NFC card swiping event detected by the smart phone, the NFC card swiping event comprises an event that an NFC simulation card is used as an entrance guard card, a bank card, a bus card, a subway card and the like to carry out local payment or entrance guard control, and the user behavior data comprises simulation card types and card swiping time corresponding to the NFC card swiping event. In other words, after the smart phone detects the NFC card swiping event, the simulated card type and the card swiping time corresponding to the NFC card swiping event are stored locally or on the server side, so as to be used in subsequent analysis modeling.
Step S402, classifying the collected user behavior data according to a preset time period, and acquiring a data set of each time unit in the time period.
After user behavior data in a preset time period are collected, the user behavior data are classified according to a preset time period, and therefore a data set of each time unit in the time period is obtained. For example, when the preset time period is the last three months, if the time period is set to one month, the card swiping records from the beginning of the month to the end of the month for 30 days can be obtained, that is, each day is used as a time unit, and all the card swiping records of the day are used as a data set; if the time period is set to be one week, card swiping records of Monday to Sunday can be obtained, namely, each day is used as a time unit, and all card swiping records of the day are used as a data set. In the present invention, the preset time period and the time period may be specifically set according to actual conditions, and this embodiment is not specifically limited, and to ensure the accuracy of the result, the preset time period should be much longer than the time period, and in this embodiment, the preset time period is preferably one week.
Step S403, determining each analog card type and a switching time corresponding to each analog card type according to the data set of each time unit in the time period.
After the data sets of each time unit in the time period are obtained, a clustering algorithm preset by the smart phone analyzes and calculates each data set, and determines a clustering interval of the card swiping time of each card in each data set, so that each analog card type of all the data sets and the switching time corresponding to each analog card type are determined. Specifically, step S403 includes:
step S410, obtaining the card swiping time sequence of each analog card type according to the data set of each time unit in the time period.
The data set for each time unit in a time period is each analog card type and corresponding card swiping time in a day, for example, using { (C)1，T1)，(C2，T2)，(C3，T3)，…，(Cn，Tn) Denotes the card-swiping record of Monday of the week, where CnRepresenting different analog card types, TnIs represented by CnAnd (4) corresponding card swiping time sequence, wherein n is a positive integer. And since the collected user behavior data is for a preset period of time, such as 3 months, CnCorresponding TnAt least one card-swiping time exists, thus forming a card-swiping time sequence t1，t2，…,tmAnd (4) each analog card type corresponds to a card swiping time sequence.
Step S420, obtaining the clustering interval of the card swiping time sequence through a preset clustering algorithm.
After the card swiping time sequence of each analog card type is obtained, the clustering interval of the card swiping time sequence of each analog card type is obtained through a preset clustering algorithm, namely, the time period with concentrated card swiping time in each card swiping time sequence is used as the clustering interval through the clustering algorithm. For example, through counting the card swiping records of company entrance guard cards of Monday, the user finds that 8 a/m: 10 occurred 1 time, 8:20 occurred 2 times, 8: 25 occurred 4 times, at 8:29 occurred 4 times, at 8: 45, and therefore after clustering, the time period of 8:20-8:29 is taken as a clustering interval, and so on, the clustering time periods of other simulated card types in monday, and the clustering time periods of all simulated card types in tuesday, wednesday, thursday, friday, saturday and sunday can be determined. The clustering algorithm in this embodiment may be a K-MEANS algorithm, a K-medoid algorithm, a Clara algorithm, a Clarans algorithm, etc., and this embodiment is not particularly limited.
Step S430, taking an average value of a maximum value in a previous clustering interval and a minimum value in a next clustering interval in two adjacent clustering intervals as switching time to be switched, and taking an analog card type corresponding to the next clustering interval as an analog card type to be switched, wherein the maximum value of the previous clustering interval is smaller than the minimum value of the next clustering interval.
And S404, establishing the user behavior data model according to the types of the simulation cards and the switching time.
After the clustering intervals of the analog card types in each time unit are obtained, if the maximum value of the previous clustering interval in any two adjacent clustering intervals is smaller than the minimum value of the next clustering interval, the average value of the maximum value in the previous clustering interval and the minimum value in the next clustering interval is used as the switching time to be switched, and the analog card type corresponding to the next clustering interval is used as the analog card type to be switched. After determining each analog card type and switching time, establishing a user behavior data model.
As a different embodiment, the analog card type may be automatically switched to the next analog card type after selecting a preset threshold value after the maximum value in the previous clustering interval.
It should be noted that, when the maximum value of the previous clustering interval in two adjacent clustering intervals is greater than the minimum value of the next clustering interval, the clustering density in the clustering algorithm needs to be modified so that the maximum value of the previous clustering interval is less than the minimum value of the next clustering interval, thereby ensuring the accuracy of the type of the analog card to be switched and the switching time.
In the embodiment, historical user behavior data in a preset time period are collected, and the user data are trained and learned, so that a user behavior data model is established, each analog card type and switching time corresponding to each analog card type in each time unit can be clear based on the model, and the analog card type and the switching time which are required to be switched at the current time of a user can be conveniently determined.
Further, referring to fig. 4, fig. 4 is a flowchart illustrating a third embodiment of the NFC-based analog card switching method according to the present invention, where based on the embodiment shown in fig. 3, the user behavior data further includes a card swiping position corresponding to the NFC card swiping event. After the step S403 determines each analog card type and the switching time corresponding to each analog card type according to the data set of each time unit in the time period, the method includes:
step S501, classifying the card swiping positions corresponding to the NFC card swiping events in the collected preset time period, and determining the card swiping times of each card swiping position.
The user behavior data comprises the simulated card type and the card swiping time corresponding to the NFC card swiping event, and also comprises the card swiping position corresponding to the NFC card swiping event. Therefore, when the user is detected to have the NFC card swiping, the card swiping positions corresponding to the NFC card swiping events can be synchronously collected, the collected card swiping positions in the preset time period are classified, and the card swiping times corresponding to different card swiping positions every day are determined according to the classification result.
Step S502, verifying each analog card type and the switching time corresponding to each analog card type according to the card swiping times of each card swiping position.
After obtaining the card-swiping times of each card-swiping position in each time unit, the analog card types obtained in step S403 and the switching time corresponding to each analog card type may be verified according to the card-swiping times of each card-swiping position. For example, based on the above example, it is determined that the user swipes the company access card 10 times in the period of 8:20-8:29 and swipes the parking lot access card 9 times in the period of 7:55-8:05 every monday according to the user behavior data model, and thus it can be known that the user is generally in the company in the period of 8:20-8:29 and is generally in the parking lot at home in the period of 7:55-8:05, and therefore, when the current time of the system is 8: 15, acquiring current position information, if the current position information is near a company, indicating that a user will reach the company for swiping a card within expected time, and indicating that each previously determined analog card type and the switching time corresponding to each analog card type are correct; if the current position information is not near the company, the user cannot reach the company card swiping within the expected time, and the previously determined simulation card types and the switching time corresponding to the simulation card types are to be corrected.
Step S503, establishing the user behavior data model according to each verified analog card type and the switching time corresponding to each analog card type.
When the determined simulated card types and the switching time corresponding to the simulated card types are to be corrected, marking the card swiping records to be corrected, correcting the card swiping records, and establishing a new user behavior data model according to the verified simulated card types and the switching time corresponding to the simulated card types.
In the embodiment, the established user behavior data model is verified by combining the card swiping position information, so that the problem that the type of switching of the analog card is wrong due to special conditions of a user is avoided, and the accuracy of automatic switching of the analog card is improved.
Further, referring to fig. 5, fig. 5 is a schematic flowchart of a fourth embodiment of the NFC-based analog card switching method according to the present invention, where based on the embodiment shown in fig. 3, after the step S40 collects user behavior data in a preset time period, and establishes the user behavior data model according to the collected user behavior data, the method further includes:
and step S60, updating the user behavior data in the preset time period in real time, and establishing a new user behavior data model according to the updated user behavior data.
The smart phone collects user behavior data in real time and updates the user behavior data in a preset time period in real time, so that the data in the user behavior data model always keep the latest NFC card swiping data of the user. It should be noted that the update data may be updated in a daily cycle, for example, data in the user behavior data model is updated every morning, or may be updated in a cycle of each NFC card swipe, for example, the latest card swipe record is stored after each card swipe, and the earliest card swipe record is deleted.
In the embodiment, the user behavior data model is always kept with the latest data through the user behavior data in the preset time period, so that the automatic switching of the simulation card can be used as the corresponding change according to the card swiping habit of the user when the card swiping habit of the user changes, and the accuracy of the automatic switching of the simulation card is further improved.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where an NFC-based emulated card switching program is stored on the computer-readable storage medium, and when executed by a processor, the NFC-based emulated card switching program implements the following operations:
acquiring current user behavior data;
matching the current user behavior data with a preset user behavior data model, and determining the target type and target switching time of the analog card to be switched;
and generating a switching instruction according to the target type and the target switching time of the analog card to be switched, and switching the type of the analog card to the target type according to the switching instruction when the target switching time is reached.
Further, when executed by the processor, the NFC-based emulated card switching program further performs the following:
the method comprises the steps of collecting user behavior data in a preset time period, and establishing a user behavior data model according to the collected user behavior data.
Further, when executed by the processor, the NFC-based emulated card switching program further performs the following:
acquiring user behavior data in a preset time period, wherein the user behavior is a detected NFC card swiping event, and the user behavior data comprises a simulated card type and card swiping time corresponding to the NFC card swiping event;
classifying the collected user behavior data according to a preset time period to obtain a data set of each time unit in the time period;
determining each analog card type and switching time corresponding to each analog card type according to the data set of each time unit in the time period;
and establishing the user behavior data model according to the types of the simulation cards and the switching time.
Further, when executed by the processor, the NFC-based emulated card switching program further performs the following:
acquiring a card swiping time sequence of each analog card type according to the data set of each time unit in the time period;
acquiring a clustering interval of the card swiping time sequence through a preset clustering algorithm;
taking the average value of the maximum value in the previous clustering interval and the minimum value in the next clustering interval in two adjacent clustering intervals as the switching time to be switched, and taking the analog card type corresponding to the next clustering interval as the analog card type to be switched, wherein the maximum value of the previous clustering interval is smaller than the minimum value of the next clustering interval.
Further, when executed by the processor, the NFC-based emulated card switching program further performs the following:
the preset time period is one week.
Further, when executed by the processor, the NFC-based emulated card switching program further performs the following:
the user behavior data further comprises a card swiping position corresponding to the NFC card swiping event.
Further, when executed by the processor, the NFC-based emulated card switching program further performs the following:
classifying the card swiping positions corresponding to the NFC card swiping events in the collected preset time period, and determining the card swiping times of each card swiping position;
verifying each analog card type and the switching time corresponding to each analog card type according to the card swiping times of each card swiping position;
the step of establishing the user behavior data model according to the types of the simulation cards and the switching time comprises the following steps:
and establishing the user behavior data model according to the verified analog card types and the switching time corresponding to the analog card types.
Further, when executed by the processor, the NFC-based emulated card switching program further performs the following:
and updating the user behavior data in the preset time period in real time, and establishing a new user behavior data model according to the updated user behavior data.
The specific embodiment of the computer-readable storage medium of the present invention is substantially the same as the embodiments of the NFC-based analog card switching method described above, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An analog card switching method based on NFC is characterized in that the steps of the analog card switching method based on NFC comprise:
acquiring current user behavior data;
matching the current user behavior data with a preset user behavior data model, and determining the target type and target switching time of the analog card to be switched;
and generating a switching instruction according to the target type and the target switching time of the analog card to be switched, and switching the type of the analog card to the target type according to the switching instruction when the target switching time is reached.
2. The NFC-based emulated card switching method of claim 1, wherein before the step of matching the current user behavior data with a preset user behavior data model to determine a target type and a target switching time for the emulated card to be switched, comprising:
the method comprises the steps of collecting user behavior data in a preset time period, and establishing a user behavior data model according to the collected user behavior data.
3. The NFC-based analog card switching method according to claim 2, wherein the step of collecting the user behavior data within a preset time period and establishing the user behavior data model according to the collected user behavior data includes:
acquiring user behavior data in a preset time period, wherein the user behavior is a detected NFC card swiping event, and the user behavior data comprises a simulated card type and card swiping time corresponding to the NFC card swiping event;
classifying the collected user behavior data according to a preset time period to obtain a data set of each time unit in the time period;
determining each analog card type and switching time corresponding to each analog card type according to the data set of each time unit in the time period;
and establishing the user behavior data model according to the types of the simulation cards and the switching time.
4. The NFC-based emulated card switching method of claim 3, wherein the step of determining, according to the data set for each time unit in the time period, each emulated card type and a switching time corresponding to each emulated card type includes:
acquiring a card swiping time sequence of each analog card type according to the data set of each time unit in the time period;
acquiring a clustering interval of the card swiping time sequence through a preset clustering algorithm;
taking the average value of the maximum value in the previous clustering interval and the minimum value in the next clustering interval in two adjacent clustering intervals as the switching time to be switched, and taking the analog card type corresponding to the next clustering interval as the analog card type to be switched, wherein the maximum value of the previous clustering interval is smaller than the minimum value of the next clustering interval.
5. An NFC-based analog card switching method according to claim 3, characterised in that the preset time period is one week.
6. An NFC-based emulated card switching method of claim 3, wherein the user behavior data further includes a card swipe location corresponding to the NFC card swipe event.
7. The NFC-based emulated card switching method of claim 6, wherein after the step of determining each emulated card type and a switching time corresponding to each emulated card type from the data set for each time unit in the time period, the method comprises:
classifying the card swiping positions corresponding to the NFC card swiping events in the collected preset time period, and determining the card swiping times of each card swiping position;
verifying each analog card type and the switching time corresponding to each analog card type according to the card swiping times of each card swiping position;
the step of establishing the user behavior data model according to the types of the simulation cards and the switching time comprises the following steps:
and establishing the user behavior data model according to the verified analog card types and the switching time corresponding to the analog card types.
8. An NFC-based analog card switching method according to claim 2 or 3, wherein after the step of collecting the user behavior data within a preset time period and establishing the user behavior data model according to the collected user behavior data, the method further comprises:
and updating the user behavior data in the preset time period in real time, and establishing a new user behavior data model according to the updated user behavior data.
9. An NFC-based analog card switching terminal, comprising: memory, a processor and an NFC-based emulated card switching program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the NFC-based emulated card switching method of any of claims 1 to 8.
10. A computer-readable storage medium having stored thereon an NFC-based emulated card switching program, characterized in that the NFC-based emulated card switching program, when executed by a processor, implements the steps of the NFC-based emulated card switching method of any of claims 1 to 8.
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