Franchise service providing method for granting franchise qualification to a specific driver based on driver training history and supporting interoperability between a taxi company and the driver granted with the franchise qualification

Abstract

A method for providing a franchise service is disclosed. For example, the method for providing a franchise service may include: an operation of identifying a target education program corresponding to a user profile in response to receiving an education application input including a user profile; an operation of checking whether a viewing completion input satisfies a predetermined condition when a viewing completion input is received from the user terminal within a predetermined threshold time for the target education program; an operation of transmitting a target certificate request including a user profile corresponding to the user terminal to a taxi operating server when the viewing completion input satisfies the predetermined condition; and an operation of calculating a target driving policy based on the viewing completion input and transmitting it to the user terminal together with the target certificate in response to receiving a target certificate from the taxi operating server.

Description

Technology Field

[0001] The present invention relates to a method for providing a franchise service that grants franchise eligibility to a specific driver based on driver training history and supports linkage between a taxi company and a driver who has been granted franchise eligibility. Background Technology

[0002] Generally, operating a taxi franchise business requires a verification process to confirm that drivers have completed a specific training course and possess driving capabilities that meet the operator's standards. However, conventional systems have primarily relied on manual human verification of training completion or simply checking whether a video playback has been finished. These methods have had drawbacks, as they fail to reflect the actual quality of the drivers' learning and result in low reliability regarding the training completion process.

[0003] Furthermore, existing franchise registration systems often determined registration approval by evaluating training completion and operational suitability separately. Consequently, they failed to reflect operational information essential for actual operation—such as drivers' activity areas, supply and demand conditions, and vehicle availability by type—leading to issues of degraded service quality and operational efficiency for both franchisees and drivers. In particular, the inability to promptly address oversupply or undersupply in specific regions or vehicle types could result in prolonged imbalances in service quality.

[0004] Furthermore, during the actual operation phase following the completion of training, there was a lack of capabilities to monitor issues in real-time or take appropriate action, such as driver deviation from designated locations, inappropriate driving patterns, and non-compliance with policies. Due to the inadequate management system following franchise registration, maintaining continuous quality was difficult, leading to a decline in the credibility of the franchise certification system. To resolve these problems, technology is required to implement the entire process—from training completion to franchise registration and actual operation monitoring—as a single integrated system. The problem to be solved

[0005] Embodiments of the present invention can automatically select educational programs based on user profiles and determine whether to issue certificates by evaluating the quality of educational viewing, thereby significantly improving the automation and reliability of the merchant registration process. In particular, since certificates are issued only when specific conditions are met, educational misconduct can be prevented, and fair judgment based on educational history is possible.

[0006] Embodiments of the present invention can alleviate regional supply and demand imbalances by providing a suitable training program that comprehensively considers driver activity areas, the number of drivers per region, and available daily driving hours. Furthermore, in cases where available driving hours are insufficient, by suggesting the most appropriate recommended area among adjacent regions, it is possible to establish a franchise entry strategy that is optimized not only for operational efficiency from the business operator's perspective but also from the driver's perspective.

[0007] Embodiments of the present invention can detect in real-time whether a driver deviates from their designated activity area after operation begins, thereby enabling immediate response to drivers who violate franchise standards. This strengthens the stability of the franchise certification system and ensures the continuous maintenance of service quality. Furthermore, by presenting appropriate training programs while considering the supply balance by vehicle type, efficient allocation of vehicle resources is also possible.

[0008] The technical problems of the present invention are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0009] An electronic device including a processor according to an embodiment of the present invention may provide a franchise service that grants franchise eligibility to a specific driver based on driver training history and supports linkage between a taxi company and a driver granted franchise eligibility, wherein the processor identifies a target training program corresponding to a user profile among a plurality of training programs in response to receiving a training application input including a user profile from a user terminal; if the processor receives a viewing completion input from the user terminal within a threshold time set for the target training program, checks whether the viewing completion input satisfies a predetermined condition set for the target training program; if the viewing completion input satisfies the predetermined condition, transmits a target certificate request including a user profile corresponding to the user terminal to a taxi operating server; and in response to receiving a target certificate from the taxi operating server, calculates a target driving policy based on the viewing completion input and transmits it to the user terminal together with the target certificate.

[0010] According to one embodiment, the method for providing a franchise service may further include the following operations: the processor confirming a desired driving area included in the user profile; the processor requesting the number of drivers registered for a target area identical to the desired driving area from the taxi operating server; the processor calculating a daily driving time proportional to the difference value obtained by subtracting the number of drivers from the threshold number when the number of drivers is less than a threshold number; and the processor identifying the target training program corresponding to the user profile among the plurality of training programs only when the daily driving time is greater than or equal to the daily desired driving time included in the training application input. For example, the method for providing a franchise service may further include the processor providing a recommendation interface to the user terminal that induces a franchise business to the recommended area with the lowest number of registered drivers among adjacent areas adjacent to the user activity area when the daily driving time is less than the daily desired driving time.

[0011] According to one embodiment, the method for providing the franchise service may further include the operation of the processor receiving location information from the user terminal at predetermined intervals during the operation time from the time of receiving the operation start input from the user terminal to the time of receiving the operation end input after the processor has transmitted the target certificate to the user terminal, and the operation of the processor transmitting a franchise cancellation request to the taxi operating server to request the revocation of the certificate issued to the user terminal when the processor identifies, based on the location information, that the location of the user terminal has moved out of the desired operation area beyond the time limit during the operation time.

[0012] According to one embodiment, the method for providing the franchise service may further include the operation of the processor verifying the desired vehicle type included in the user profile, the operation of the processor requesting the number of remaining vehicles corresponding to the desired vehicle type from the taxi operating server, and the operation of the processor identifying the target training program corresponding to the user profile among the plurality of training programs only when the number of remaining vehicles received from the taxi operating server is greater than or equal to a threshold number of vehicles.

[0013] According to one embodiment, the method for providing the franchise service may further include: an operation in which the processor requests the number of vehicle types registered for the target area and the number of registrations by vehicle type from the taxi operating server when the number of remaining vehicles received from the taxi operating server is greater than or equal to the threshold number of vehicles; an operation in which the processor identifies the average value of the number of registrations by vehicle type when the number of vehicle types exceeds three; and an operation in which the processor identifies the target education program corresponding to the user profile among the plurality of education programs only when the number of registrations of the target vehicle type corresponding to the desired operating vehicle type among the number of registrations by vehicle type is less than the average value.

[0014] An electronic device including a processor according to an embodiment of the present invention, for selecting an educational program to be completed for a taxi franchise business based on a user profile and determining whether to register for franchise based on the completion status, comprises the following steps: the processor receiving a plurality of educational programs associated with the conditions for franchise registration from a taxi operation server; the processor providing a notification to a user terminal identified based on the user profile when it receives a user profile from the taxi operation server; the processor identifying a target educational program corresponding to the user profile among a plurality of educational programs in response to receiving an educational application input including the user profile from the user terminal; the processor checking whether the viewing completion input satisfies a predetermined condition for the target educational program when it receives a viewing completion input from the user terminal within a predetermined threshold time for the target educational program; the processor transmitting a request for a target certificate including a user profile corresponding to the user terminal to a taxi operation server when the viewing completion input satisfies the predetermined condition; and the processor calculating a target driving policy based on the viewing completion input in response to receiving a target certificate from the taxi operation server. It may include an operation of transmitting to the user terminal together with the above target certificate.

[0015] According to one embodiment, the method for providing the franchise service may further include the operation of the processor confirming the daily desired driving time and the desired driving vehicle type included in the training application input, and the operation of the processor determining, among the plurality of training programs, as the target training program the training program in which the total training time corresponds to the daily desired driving time and the training target vehicle type corresponds to the desired driving vehicle type.

[0016] According to one embodiment, the method for providing a franchise service may further include the following operations: the processor confirming a desired driving area included in the user profile; the processor requesting the number of drivers registered for a target area identical to the desired driving area from the taxi operating server; the processor calculating a daily driving time proportional to the difference value obtained by subtracting the number of drivers from the threshold number when the number of drivers is less than a threshold number; and the processor identifying the target training program corresponding to the user profile among the plurality of training programs only when the daily driving time is greater than or equal to the daily desired driving time included in the training application input. For example, the method for providing a franchise service may further include the processor providing a recommendation interface to the user terminal that induces a franchise business to the recommended area with the lowest number of registered drivers among adjacent areas adjacent to the user activity area when the daily driving time is less than the daily desired driving time.

[0017] According to one embodiment, the method for providing a franchise service may further include the operation of the processor receiving location information from the user terminal at predetermined intervals during the operation time from the time of receiving an operation start input from the user terminal to the time of receiving an operation end input after the processor has transmitted the target certificate to the user terminal, and the operation of the processor transmitting a franchise cancellation request to the taxi operating server to request the revocation of the certificate issued to the user terminal when the processor identifies, based on the location information, that the location of the user terminal has moved out of the desired operation area beyond a limited time during the operation time.

[0018] According to one embodiment, the method for providing the franchise service may further include: the processor verifying the desired vehicle type included in the user profile; the processor requesting the number of remaining vehicles corresponding to the desired vehicle type from the taxi operating server; if the number of remaining vehicles received from the taxi operating server is greater than or equal to the threshold number of vehicles, the processor requesting the number of vehicle types registered for the target area and the number of registrations by vehicle type from the taxi operating server; if the number of vehicle types exceeds three, the processor identifying the average value of the number of registrations by vehicle type; and if the number of registrations by vehicle type is less than the average value, the processor identifying the target education program corresponding to the user profile among the plurality of education programs only when the number of registrations of the target vehicle type corresponding to the desired vehicle type is less than the average value.

[0019] A method for providing franchise services, wherein an electronic device including a processor according to an embodiment of the present invention verifies a driver's education completion process and dynamically determines an operation policy including a commission rate based on the verification result and provides it to a user terminal and a taxi operating server, comprises: the processor receiving a plurality of education programs associated with conditions for franchise registration from a taxi operating server; the processor providing a notification to a user terminal identified based on the user profile when it receives a user profile from the taxi operating server; the processor identifying a target education program corresponding to the user profile among a plurality of education programs in response to receiving an education application input including the user profile from the user terminal; the processor checking whether the viewing completion input satisfies a predetermined condition for the target education program when it receives a viewing completion input from the user terminal within a predetermined threshold time for the target education program; the processor transmitting a request for a target certificate including a user profile corresponding to the user terminal to a taxi operating server when the viewing completion input satisfies the predetermined condition; and the processor, in response to receiving a target certificate from the taxi operating server, determining the total viewing time and test score based on the viewing completion input. It may include an operation of calculating a target operation policy including a fee rate inversely proportional to the target and transmitting it to the user terminal together with the target certificate.

[0020] According to one embodiment, the method for providing a franchise service may further include the operation of the processor confirming a first playback time and a second playback time, respectively, of a first mandatory education related to safety regulations and a second mandatory education related to service education that are pre-set for the target education program; the operation of the processor confirming, based on the viewing completion input, a first completion time during which the first mandatory education is played on the user terminal and a second completion time during which the second mandatory education is played; and the operation of the processor determining that the viewing completion input satisfies a predetermined condition only when the ratio of the first completion time to the first playback time is greater than or equal to a first ratio, and the ratio of the second completion time to the second playback time is greater than or equal to a second ratio that is lower than the first ratio.

[0021] According to one embodiment, the method for providing a franchise service may further include: the processor verifying a user activity area included in the user profile; the processor requesting the number of drivers registered for a target area identical to the user activity area from the taxi operating server; the processor calculating a daily operating time proportional to the difference value obtained by subtracting the number of drivers from the threshold number when the number of drivers is less than a threshold number; the processor verifying the daily operating time and the desired vehicle type included in the training application input when the daily operating time is greater than or equal to the daily desired operating time included in the training application input; and the processor determining, among the plurality of training programs, as the target training program the training program in which the mandatory completion time corresponds to the daily desired operating time and the training target vehicle type corresponds to the desired vehicle type. For example, the method for providing a franchise service may further include the processor providing a recommendation interface to the user terminal that induces a franchise business to the recommendation area with the lowest number of registered drivers among adjacent areas adjacent to the user activity area when the daily operating time is less than the daily desired operating time.

[0022] According to one embodiment, the method for providing the franchise service may further include the operation of the processor receiving location information from the user terminal at predetermined intervals during the operation time from the time of receiving the operation start input from the user terminal to the time of receiving the operation end input after the processor has transmitted the target certificate to the user terminal, and the operation of the processor transmitting a franchise cancellation request to the taxi operating server to request the revocation of the certificate issued to the user terminal when the processor identifies, based on the location information, that the location of the user terminal has moved outside the user activity area for more than a limited time during the operation time.

[0023] According to one embodiment, the method for providing the franchise service may further include: an operation in which the processor checks the desired vehicle type included in the user profile; an operation in which the processor requests the number of remaining vehicles corresponding to the desired vehicle type from the taxi operation server; an operation in which, if the number of remaining vehicles received from the taxi operation server is greater than or equal to the threshold number of vehicles, the processor requests the number of vehicle types registered for the target area and the number of registrations by vehicle type from the taxi operation server; an operation in which, if the number of vehicle types exceeds three, the processor identifies the average value of the number of registrations by vehicle type; and an operation in which the processor identifies the target education program corresponding to the user profile among the plurality of education programs only if the number of registrations of the target vehicle type corresponding to the desired vehicle type among the number of registrations by vehicle type is less than the average value.

[0024] The above-described method for providing franchise services further includes the operation of the processor calculating the commission rate based on the following [Mathematical Formula 1]; and

[0025] [Mathematical Formula 1]

[0026]

[0027] r min is the minimum commission rate set and transmitted by the taxi operation server, and r max is the maximum commission rate set and transmitted by the taxi operation server, and R T is the total viewing time (or playback ratio) of the target educational program on the user terminal relative to the total playback time of the target educational program, and R S is the test score of the user terminal for the target educational program, and A corresponds to the number of traffic accidents that occurred over the past three years for the user included in the user profile. In addition, a, b, and c correspond to the weights for the playback rate, test score, and number of traffic accidents, respectively, and

[0028] The above franchise service provision method is such that the processor, even if the total viewing time becomes greater than the total playback time, R T It may further include an action that limits the maximum value of to 1.

[0029] The above method for providing a franchise service may further include the operation of providing the playback interface, which includes a streaming URL of a preset resolution or a cache-based segment download method, when the processor receives a terminal status from the user terminal and, based on the terminal status, identifies that the user terminal is in a low-power mode or that the network quality is below a certain standard.

[0030] The above threshold time can be set in proportion to the total playback time of the target education program and simultaneously set to three days prior to the maximum franchise registration deadline set by the taxi operation server.

[0031] The above method for providing a franchise service may further include the operation of not transmitting the target certificate request to the taxi operating server if the processor identifies that the number of traffic accidents in the last three years is greater than a predetermined number based on the user profile obtained from the user terminal, even if the viewing completion input satisfies a predetermined condition.

[0032] The above method of providing a franchise service may further include the operation of the processor, based on at least one of the basic commission rate, minimum commission rate, and maximum commission rate transmitted from the taxi operation server, reducing by 1 to 2 percentage points if the test score of the user terminal for the target education program is 80 points or higher, reducing by 4 to 5% if it is 90 points or higher, reducing by 1 to 2 percentage points if the total viewing time is 90% or higher relative to the total playback time of the target education program, and reducing by 5% if it is 100%. Effects of the invention

[0033] The effects of the method for providing franchise services according to embodiments of the present invention are described as follows.

[0034] Embodiments of the present invention can automatically select an educational program based on a user profile and determine whether to issue a certificate by evaluating (or verifying) the viewing quality of the educational program, thereby significantly improving the automation and reliability of the merchant registration process. In particular, since a certificate is issued only when certain conditions are met, educational misconduct can be prevented, and fair judgment based on educational history is possible.

[0035] Embodiments of the present invention can alleviate regional supply and demand imbalances by providing a suitable training program that comprehensively considers driver activity areas, the number of drivers per region, and available daily driving hours. Furthermore, in cases where available driving hours are insufficient, by suggesting the most appropriate recommended area among adjacent regions, it is possible to establish a franchise entry strategy that is optimized not only for operational efficiency from the business operator's perspective but also from the driver's perspective.

[0036] Embodiments of the present invention can detect in real-time whether a driver deviates from their designated activity area after operation begins, thereby enabling immediate response to drivers who violate franchise standards. This strengthens the stability of the franchise certification system and ensures the continuous maintenance of service quality. Furthermore, by presenting appropriate training programs while considering the supply balance by vehicle type, efficient allocation of vehicle resources is also possible.

[0037] In addition, various effects that can be identified directly or indirectly through this document may be provided. Brief explanation of the drawing

[0038] FIG. 1 is a block diagram showing the components of an electronic device according to one embodiment of the present invention. FIG. 2 is a block diagram showing the components of a franchise service provision system including an electronic device according to an embodiment of the present invention. FIG. 3 is a flowchart of a method for providing franchise services according to an embodiment of the present invention. FIG. 4 is a flowchart of a method for providing franchise services according to an embodiment of the present invention. FIG. 5 is a flowchart of a method for providing franchise services according to an embodiment of the present invention. In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Specific details for implementing the invention

[0039] Hereinafter, some embodiments of the present invention will be described in detail with reference to exemplary drawings. It should be noted that in assigning reference numerals to the components of each drawing, the same components are given the same reference numeral whenever possible, even if they are shown in different drawings. Furthermore, in describing the embodiments of the present invention, if it is determined that a detailed description of related known components or functions would hinder understanding of the embodiments of the present invention, such detailed description is omitted.

[0040] In describing the components of the embodiments of the present invention, terms such as first, second, A, B, (a), (b), etc., may be used. These terms are intended merely to distinguish the components from other components, and the essence, order, or sequence of the components is not limited by the terms. Furthermore, unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the present invention pertains. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this application.

[0041] Hereinafter, embodiments of the present invention will be described in detail with reference to FIGS. 1 to 5.

[0043] FIG. 1 is a block diagram showing the components of an electronic device according to one embodiment of the present invention.

[0044] According to one embodiment, the electronic device (100) may include a memory (110), a processor (120), a communication interface (130), and / or a display device (140). The configuration of the electronic device (100) shown in FIG. 1 is exemplary and the embodiments of the present invention are not limited thereto. For example, the electronic device (100) may further include components not shown in FIG. 1 (e.g., a web crawler, a user interface, an input device, a notification unit, a sensor unit, or at least one of any combination thereof).

[0045] According to one embodiment, the memory (110) may store instructions or data. For example, the memory (110) may store one or more instructions that cause the electronic device (100) to perform various operations when executed by the processor (120).

[0046] For example, the memory (110) may be implemented as a single chipset with the processor (120). The processor (120) may include at least one of a communication processor or a modem.

[0047] For example, the memory (110) can store various information related to the electronic device (100). For example, the memory (110) can store information regarding the operation history of the processor (120). For example, the memory (110) can store input data acquired by the electronic device (100), output data output by the electronic device (100), data acquired from an external server and / or user terminal, etc.

[0048] For example, the memory (110) may include multiple storage devices of different types. For example, the memory (110) may include volatile and / or non-volatile storage media. For example, the memory (110) may include at least one of RAM (random-access memory), ROM (read only memory), eMMC (Embedded Multi-Media Card), or any combination thereof.

[0049] The steps of the method or algorithm described in connection with the embodiments disclosed in this specification may be directly implemented in hardware, software modules, or a combination of both, executed by the processor (120). The software modules may reside in a storage medium (i.e., memory (110)) such as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, or a CD-ROM.

[0050] For example, the memory (110) is coupled to a processor (120), and the processor (120) can read information from a storage medium and write information to a storage medium. Alternatively, the memory (110) may be integrated with the processor (120). The memory (110) and the processor (120) may reside within an application-specific integrated circuit (ASIC). The ASIC may reside within a user terminal. Alternatively, the memory (110) and the processor (120) may reside as separate components within the user terminal.

[0051] According to one embodiment, the processor (120) may be operatively connected to the memory (110), the communication interface (130), and / or the display device (140). For example, the processor (120) may control the operation of the memory (110), the communication interface (130), and / or the display device (140).

[0052] According to one embodiment, the communication interface (130) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (100) and an external device (e.g., user terminal (210) of FIG. 2, external server (220), and database, etc.), and the performance of communication through the established communication channel. The communication interface (130) may include one or more communication processors that operate independently of the processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication interface (130) may include a wireless communication module (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device through a first network (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a long-range communication network such as a computer network (e.g., LAN or WAN). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module can identify or authenticate the electronic device (100) within a communication network, such as the first network or the second network, using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in a subscriber identification module.

[0053] According to one embodiment, the display device (140) may include at least one output device that provides various information and a user interface to the user.

[0054] For example, the display device (140) may include a display device, an audio output device, a virtual reality output device, etc.

[0055] For example, the display device (140) can provide the administrator with various types of user interfaces described in the present disclosure visually and / or audibly.

[0056] The components of the electronic device (100) illustrated in FIG. 1 are exemplary, and the embodiments of the present disclosure are not limited thereto.

[0057] At least some of the embodiments of the present disclosure may be implemented as artificial intelligence (AI) through a processor (120) and memory (110) of an electronic device (100). The processor (120) may be composed of one or more processors, and the one or more processors may be general-purpose processors such as a CPU, AP, DSP (digital signal processor), etc., graphics-dedicated processors such as a GPU, VPU (vision processing unit), or artificial intelligence-dedicated processors such as an NPU. The one or more processors may be controlled to process input data according to predefined operation rules or artificial intelligence models stored in memory (110). Alternatively, if the one or more processors are artificial intelligence-dedicated processors, the artificial intelligence-dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0058] The predefined operation rules or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that a predefined operation rules or artificial intelligence models configured to perform a desired characteristic (or purpose) are created by a basic artificial intelligence model being trained using a number of learning data by a learning algorithm. Such learning may be performed within the electronic device (100) itself where the artificial intelligence according to the present disclosure is performed, or it may be performed through a separate server and / or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0059] An artificial intelligence model may be composed of multiple neural network layers. Each of the multiple neural network layers has multiple weight values ​​and can perform neural network operations through operations between the results of previous layers and the multiple weights. The multiple weights possessed by the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, the multiple weights can be updated so that the loss value or cost value obtained from the artificial intelligence model during the learning process is reduced or minimized. Artificial neural networks may include, but are not limited to, deep neural networks (DNN), convolutional neural networks (CNN), recurrent neural networks (RNN), restricted Boltzmann machines (RBM), deep belief networks (DBN), bidirectional recurrent deep neural networks (BRDNN), or deep Q-networks.

[0060] The AI ​​model can generate predictive values ​​for determining franchise registration status and calculating driving policies (e.g., commission rates) by using inputs such as drivers' training viewing logs, completion rates by section, test scores, and driving preference information included in user profiles. The AI ​​model processes detailed training data—including playback patterns, repeated sections, and drop-off times of training videos—in vector form and performs similarity analysis with previously collected normal completion pattern vectors to automatically determine whether a viewing completion input satisfies specific conditions. This model-based determination goes beyond simple playback time comparisons to reflect drivers' actual learning behaviors, enabling a more precise evaluation of franchise suitability.

[0061] The AI ​​model can utilize operational data received from taxi operation servers, such as the number of drivers by region, the number of remaining vehicles, and the number of registered vehicles by vehicle type, to calculate training programs and franchise policies suitable for desired operating areas and vehicle types based on user profiles. The AI ​​model employs a hybrid input structure that combines the time-series variability of external operational data with the static attributes of user profiles, and learns weights corresponding to the influence of each data point. Through this, the model can automatically determine whether a specific driver is available to operate in a particular area, the appropriateness of daily operating hours, and the possibility of assigning a suitable vehicle type, thereby supporting the decision-making of optimal programs or policies for franchise registration.

[0062] The AI ​​model can function as a policy engine that automatically evaluates whether to maintain a franchise by analyzing location information, start and end times, and regional deviation patterns collected during the operation phase following certificate issuance. The AI ​​model pre-learns normal and abnormal operation patterns and probabilistically determines whether a driver has deviated from the area beyond a time limit by comparing them with the driver's real-time location vector. Furthermore, based on these determinations, it can automatically execute requests for certificate maintenance, policy adjustments, or franchise cancellation, significantly enhancing the efficiency and reliability of the franchise management process. This AI-based policy engine plays a crucial role in automating the entire franchise service process (e.g., training, registration, policy calculation, and post-management) within a consistent framework.

[0064] FIG. 2 is a block diagram showing the components of a franchise service provision system including an electronic device according to an embodiment of the present invention.

[0065] According to one embodiment, a franchise service providing system may include an electronic device (100), a user terminal (210), and an external server (220).

[0066] The electronic device (100) may be a central control device that processes user profile data including the user's education history, viewing patterns, regional information, vehicle type preference, etc., to produce various judgment results for providing franchise services. The electronic device (100) is configured to receive education application input, viewing completion input, operation start / end input, and location information from the user terminal (210), process this information, and automate the calculation of whether to issue a certificate and operation policies. These functions can be performed step-by-step through an internal policy calculation engine, an education verification module, and a vector-based judgment module.

[0067] The electronic device (100) can communicate with a user terminal (210) and / or an external server (220) via a wired LAN, wireless LAN (Wi-Fi), mobile communication network (LTE, 5G) or IoT protocol (MQTT, CoAP), etc., and may include security authentication, encryption, and data integrity verification procedures when exchanging data. Through this, the electronic device (100) can be connected to the user terminal (210) and / or the external server (220) while ensuring real-time performance and security.

[0068] The electronic device (100) can utilize operational data collected from an external server (220), such as the number of registered drivers by region, supply status by vehicle type, and vehicle inventory information, to generate vector data combined with a user profile and store it in a first and second vector database according to the recency standard. For example, data on the number of drivers and vehicle inventory that fluctuate over time is stored in the first vector database, while past training history and regional patterns are stored in the second vector database. In this way, the electronic device (100) can utilize all the latest operational information and history data necessary for determining franchise registration.

[0069] The electronic device (100) can analyze the educational program viewing log to verify the completion time of the required educational sections and determine whether pre-set conditions are met. In particular, detailed data such as the completion rate by section, whether playback is repeated, and the number of interruptions can be converted into a vector form to perform a similarity comparison with an existing normal completion pattern vector. Through this, the electronic device (100) can perform a high-precision verification function that reflects actual learning quality rather than based on simple playback time.

[0070] The electronic device (100) can transmit a request for certificate issuance to a taxi operation server and automatically calculate an operation policy based on the received certificate. The calculated operation policy may include daily operation allowance hours, allowed operation zones, allowed vehicle types, time limits, and commission rates, and is dynamically calculated by simultaneously considering multiple factors such as training completion results, regional supply and demand status, and vehicle supply situation. This policy calculation can be performed by including an AI-based policy engine or a rule-based module.

[0071] The electronic device (100) communicates with a user terminal (210) and an external server (220) via a wired or wireless network, and may include security authentication, encryption, and integrity verification procedures when transmitting data. During the user's operation, location information is received periodically, and a request for cancellation of membership can be automatically executed by determining whether the set criteria for leaving the area are satisfied. In addition, by integrally controlling the entire lifecycle, such as certificate issuance, policy calculation, and membership maintenance management, automation and stability of the entire membership service can be provided.

[0072] The user terminal (210) may correspond to a terminal that transmits and receives various data to and from an electronic device (100) through a communication interface. For example, the electronic device (100) may correspond to a management server for service distribution, service maintenance, management, repair, and service-related data collection of the aforementioned franchise service provision system, and the user terminal (210) may correspond to a mobile terminal possessed by a user corresponding to a service user utilizing the service.

[0073] The user terminal (210) may be a user interface device that transmits all actions performed by a franchise service user, such as applying for education, watching education, inputting completion of viewing, inputting start of operation, and inputting end of operation, to the electronic device (100). The user terminal may be implemented in various forms, such as a smartphone, tablet, or a display mounted in a vehicle, and communicates bidirectionally with the electronic device (100) through a network.

[0074] The user terminal (210) includes a streaming playback function for educational videos and can record playback time, playback sections, pause / playback repetitions, etc., and transmit them to the electronic device (100) as a viewing log. In addition, it can receive inputs such as whether the mandatory educational sections have been fully watched, test responses, and scores, and provide them as core data for determining franchise registration. This data is utilized for educational verification by the electronic device (100).

[0075] The user terminal (210) can store user profile information or receive it from a server and provide the desired driving area, desired vehicle type, daily desired driving time, etc., to the electronic device (100). Through this, an educational program optimized for each user's driving situation and preferences is identified and subsequently reflected in the policy calculation process.

[0076] The user terminal (210) can transmit real-time location information to the electronic device (100) by linking with a location measurement module installed in the vehicle during the operation phase. This location information is used to determine whether the user is moving out of the allowed driving zone (or the desired driving zone according to the user profile) and to calculate the time limit, and is a key factor in determining whether the franchise certification can be maintained.

[0077] The user terminal (210) displays various results to the user, such as certificates, driving policies, recommended area information, education re-guidance information, and policy adjustment notifications. The user can check the displayed information and provide additional input, thereby enabling intuitive use of the entire service leading to education, franchise registration, driving, and violation judgment.

[0078] The user terminal (210) can ensure privacy protection and data security during the process of using the franchise service by transmitting data through an encrypted channel. The user terminal (210) can maintain data integrity and security by performing authentication of the service user and transmitting a request to the electronic device (100) in an encrypted manner. Through this, the overall safety of the franchise service provision system of the present invention is improved.

[0079] The external server (220) is a data supply device that provides essential information related to taxi operations to the electronic device (100), and may include operational data such as the number of registered drivers by region (or zone), the number of remaining vehicles, the number of registered vehicles by vehicle type, and vehicle availability. This data is used for core functions such as determining eligibility for franchise registration, calculating available operating hours, and determining recommended areas.

[0080] The external server (220) can provide educational content metadata, such as a list of educational programs, information on required educational sections, playback time, test questions, and answers. Based on this data, the electronic device (100) automatically identifies an educational program suitable for the user and sets a standard value for verifying completion of the education.

[0081] The external server (220) may include a certificate server function that processes a user's request for certificate issuance. When the electronic device (100) transmits a request for certificate issuance after completing education verification, the external server (220) generates a certificate based on user information and returns it to the electronic device (100). Additionally, the issued certificate is subsequently used to determine whether to maintain the membership.

[0082] The external server (220) can provide real-time external environment data, such as local traffic volume, driving regulations, and policy change information. This data is reflected in the policy calculation process of the electronic device (100) to automatically calculate a policy suitable for the driver's actual driving environment. For example, if regulations in a specific area are tightened, the permitted driving zone can be automatically adjusted.

[0083] The external server (220) can use an integrated data provision method in the form of an API during communication with the electronic device (100) and can maintain a secure communication environment including TLS-based encryption. In addition, when a specific event occurs (e.g., policy change, sudden decrease in vehicle supply, etc.), it provides push-based notifications to the electronic device (100) to support the system in immediately reflecting the latest operational information.

[0085] FIG. 3 is a flowchart of a method for providing franchise services according to an embodiment of the present invention.

[0086] According to one embodiment, an electronic device (e.g., the electronic device (100) of FIG. 1) may perform the operations disclosed in FIG. 4. For example, at least some of the components included in the electronic device (e.g., the memory (110), processor (120), communication interface (130), and display device (140) of FIG. 1 may be configured to perform the operations of FIG. 3.

[0087] In the following embodiments, the operations S310 to S340 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 3 may be briefly explained or omitted.

[0088] According to one embodiment, the processor (120) may, in response to receiving an education application input including a user profile from a user terminal, identify a target education program corresponding to the user profile among a plurality of education programs and transmit an interface for playing the target education program to the user terminal (S310).

[0089] According to operation S310, the electronic device (100) may perform a step of selecting a target education program required for the driver based on a user profile received from the driver. This step is intended to induce customized membership that goes beyond simple completion of education and is suited to the driver's characteristics and the needs of the platform.

[0090] For example, the processor (120) may receive an education application input from a user terminal. For example, the education application input is data generated at the stage where a user enters their information and applies for the completion of a specific education program to participate in a taxi franchise business, and may include a user profile that includes the user's name, contact information, driving experience, driver's license type, current affiliation (e.g., individual taxi, corporate taxi, unaffiliated, etc.), desired driving area (e.g., Gangnam-gu, Seoul, Haeundae-gu, Busan, etc.), desired driving time (e.g., daytime, nighttime, late-night, etc.), desired vehicle type (e.g., medium-sized, large-sized, electric vehicle, premium, luxury, etc.), whether there is prior franchise experience, accident history summary, violation history summary, etc. For example, the education application input may be generated by the user sequentially responding to questions on an app or web screen of the user terminal, or by loading a pre-saved user profile and clicking an education application button.

[0091] For example, the processor (120) can extract items included in the user profile from the received training application inputs and then query a list of multiple training programs and their respective metadata that have been received in advance from a storage device or a taxi operation server. For example, each training program may have a training title such as “Basic Training for Beginner Franchise Drivers,” “Safety Training Specialized for Late-Night Driving,” “Tourist Destination-Centered Driving Service Training,” or “Large Vehicle / Luxury Vehicle Driving Manners Training,” along with metadata such as the target audience (e.g., beginners / experienced drivers), target vehicle type, target driving area type (e.g., urban, tourist destination, airport / station center, etc.), total training hours, required completion hours, whether it is online / offline, whether it includes a test, difficulty level, and recommended target audience (e.g., those who wish to focus on late-night driving).

[0092] For example, the processor (120) can match the user profile with the training program metadata to identify the target training program that is most suitable for the user profile among multiple training programs. For example, if the user has a profile such as “mainly late-night driving,” “centered in Gangnam-gu, Seoul,” “driving medium-sized vehicles,” or “no accident history,” the processor (120) may prioritize training programs that have a high proportion of late-night safety training and include many driving cases in the city center (or congested areas). In one embodiment, the processor (120) may use a scoring function to score the suitability of each training program with the user profile, and determine the program with the maximum suitability score as the target training program. For example, the suitability score may be calculated by assigning weights to items such as whether the desired driving area matches, whether the desired time zone matches, whether the vehicle type matches, and whether the training difficulty is suitable according to the driving experience level, and then summing them up.

[0093] For example, the processor (120) can identify a target training program by using an artificial intelligence model (e.g., a classification model or a recommendation model) to input a user profile and receive the most suitable training program ID as output. In this case, the artificial intelligence model can predict which training program is most effective for a specific type of driver by using the profiles of drivers who previously applied for membership, the training programs they actually completed, and their subsequent driving performance (e.g., accident rate, customer evaluation score, etc.) as training data. Through this, the target training program identification step can be extended beyond simple rule-based methods to learning-based intelligent recommendations.

[0094] For example, when the processor (120) identifies a target training program, it can generate playback preparation information that supports immediate playback of the target training program on a user terminal. For example, the playback preparation information may include streaming URLs of multiple videos included in the target training program, domain information of a content server, a DRM (Digital Rights Management) token, information on the encoding method required for video playback (e.g., HLS, MPEG-DASH), a playlist of sections of the target training program, information on required viewing intervals, an estimated time required, and a result report format to be transmitted upon completion of viewing. The processor (120) can package this playback preparation information into a structured form based on JSON or XML and then transmit it to a user terminal via a wireless LAN, a mobile communication network (LTE / 5G), or a message channel within an application. Based on the received information, the user terminal can initialize the playback screen of the training program and display interfaces such as “Start Training,” “Preview,” and “Required Viewing Interval Guide” to the user.

[0095] For example, the processor (120) may provide customized playback information that takes into account the network quality and terminal status of the user terminal included in the user profile to facilitate the smooth playback of the target educational program. For example, after receiving the terminal status from the user terminal, if the processor (120) identifies, based on the terminal status, that the user terminal is in low-power mode or that the network quality is below a certain standard, it may provide playback information including a streaming URL of a preset resolution (e.g., a relatively low resolution) or a cache-based segment download method. Additionally, the processor (120) may support the user in intuitively understanding which segments must be watched by displaying important segments and mandatory completion segments of the educational program in advance on the user terminal. In some embodiments, the processor (120) may also provide the expected appearance point of the quiz / test segment included in the video, thereby controlling the user terminal to automatically display a popup at that time. Through this, the user can complete the educational program without interruption, and the processor (120) can stably continue the flow of subsequent condition verification and certificate request processing.

[0096] Additionally or generally, the processor (120) can check the daily desired driving time and desired driving vehicle type included in the training application input, and among the multiple training programs, determine the training program in which the total training time corresponds to the daily desired driving time and the training target vehicle type corresponds to the desired driving vehicle type as the target training program.

[0097] For example, when the processor (120) receives an application for training from a user terminal, it may first extract values ​​corresponding to the desired daily driving hours and the desired vehicle type from among the multiple fields included in the application for training input. The application for training input may be configured in the form of, for example, JSON, XML, or form data, and may include a desired_daily_hours field indicating “how many hours of actual driving are desired per day” and a desired_vehicle_type field indicating “what type of vehicle is desired for driving.” On the application for training screen, the user may select time options such as “driving only 4 hours a day” or “driving 8 hours full-time” or directly enter the time, and regarding the vehicle type, the user may select at least one of a standard taxi, a large taxi, a model taxi, a luxury / premium taxi, an electric taxi, etc.

[0098] For example, the processor (120) can read the value corresponding to desired_daily_hours from the received training application input in the form of an integer or a real number (e.g., 4.0, 8.0) and store it as the daily desired driving hours. Since this value later becomes a comparison standard with the “total training hours required to complete training,” the processor (120) can verify the range of the value (e.g., whether it is between 1 and 16 hours) and the data format, and if an abnormal value is entered, it can send an error message or a correction request interface to the user terminal. For example, if the user enters an unrealistic value such as 0 hours or 24 hours, it can be implemented to provide a notice saying, “Please set the daily desired driving hours to be between 1 hour and 12 hours.”

[0099] For example, the processor (120) can identify the desired vehicle type by checking the desired_vehicle_type value in the same training application input. This value can be mapped internally to a predefined vehicle type code (e.g., STD = Standard, DLX = Exemplary, PRM = Premium, LARGE = Large, etc.), and the processor (120) can use this code information as a filtering condition for the “training target vehicle type”. In some embodiments, if the user inputs multiple vehicle types in combination (e.g., Standard + Large), the processor (120) may select one basic vehicle type with priority or perform logic to match a separate training program to each of the multiple vehicle types.

[0100] For example, the processor (120) can determine which of the multiple training programs received from the taxi operation server the user actually needs to complete, i.e., the target training program, based on the previously identified daily desired driving time and desired driving vehicle type. Each training program may include information as metadata, such as (i) the total training time of the program (e.g., sum of playback lengths or minimum time required for completion), (ii) the training target vehicle type (e.g., standard, large, premium), (iii) the training difficulty, (iv) whether it is mandatory or optional, and (v) whether there is an evaluation test. The processor (120) can perform matching with values ​​identified in the user profile, focusing on the total training time and training target vehicle type fields among these.

[0101] More specifically, the processor (120) can first filter a list of multiple training programs to include only those programs where the training target vehicle type matches the user's desired driving vehicle type. For example, if the user desires a “Premium Taxi,” only programs where the training target vehicle type is PRM can be kept as candidates, and programs dedicated to general / large / luxury vehicles can be excluded. Subsequently, among the candidates filtered in this way, it can determine whether the total training time (or total playback time) corresponds to the user's desired daily driving time. In one embodiment, the processor may be configured to prioritize the selection of “a program where the total training time is less than or equal to the desired daily driving time” or “a program where the total training time is equal to or close to the desired daily driving time within a pre-set tolerance range.”

[0102] For example, if a user wishes to drive for 4 hours a day, the processor (120) may prioritize matching a program with a total training time of 3 to 4 hours and exclude a long-term training program of 8 hours. This reduces the inefficiency of drivers with limited driving conditions being forced to complete long-term training. Conversely, for drivers who wish to drive full-time (e.g., 8 hours a day) and drive high-end vehicles, the processor may automatically recommend and match training programs that have a longer total training time and include a more advanced curriculum.

[0103] In another embodiment, the processor (120) may select a target training program by assigning weights according to a policy when multiple training programs satisfy the same vehicle type / similar time conditions. For example, it may be configured to prioritize the latest training programs that reflect recently revised laws or safety guidelines, or to prioritize the selection of programs with high past student evaluations. In this way, the operation provides a technical effect that simultaneously improves the efficiency of the franchise service and driver satisfaction by linking user desired conditions (e.g., desired driving time and desired vehicle type) with training program attributes (e.g., total training time and target vehicle type) and automatically selecting an appropriate level of training program that is neither excessive nor insufficient.

[0104] According to one embodiment, when the processor (120) receives a viewing completion input from a user terminal within a pre-set threshold time for a target education program, it can check whether the viewing completion input satisfies a predetermined condition for the target education program (S320).

[0105] For example, when a target education program is determined, the processor (120) may provide a notification or UI screen that guides the user terminal to start watching the program. At this time, the processor (120) may set a threshold time in advance by considering the length (e.g., total playback time), difficulty level, and franchise registration deadline of the target education program, and the threshold time may be set proportionally to the total playback time of the target education program and simultaneously set up to 3 days prior to the maximum franchise registration deadline. For example, if the target education program is basic education totaling 2 hours, the threshold time may be set to “within 48 hours from the time when education can start,” and if the target education program is long-term education of 12 hours, a longer threshold time may be set, such as “within 7 days.” The threshold time may be defined by referring to a policy transmitted from the taxi operation server or may be referenced from an internal policy table of the electronic device (100).

[0106] For example, while the user is actually watching the educational video, the user terminal may transmit a viewing log, including the playback start time, pause time, playback end time, playback time per section, sections skipped by the user, and repeat playback sections, to the electronic device (100) in real time or at regular intervals, or transmit it all at once when the viewing is completed. The viewing completion input may include the response results and scoring results for tests (e.g., multiple choice, short answer, situational quiz, etc.) included in the educational program, along with these viewing logs. The processor (120) may record the time of receiving the viewing completion input as a timestamp and first check whether it was received within a threshold time set for the target educational program. For example, the processor (120) may count the threshold time from the time when an educational start notification is sent to the user terminal or the time when the educational guide page is first executed on the user terminal, and verify whether the viewing completion input was received within this time.

[0107] For example, the processor (120) can determine whether the viewing completion input satisfies a predetermined condition for the target education program. The predetermined condition may consist of, for example, (1) whether 90% or more of the total video playback time has been actually played, (2) whether a predetermined percentage or more of the required sections (e.g., safety regulations part, service manners part, etc.) have been watched, (3) whether the time during which the playback speed is set to 2x speed or higher is less than a certain percentage of the total, and (4) whether the test score is 70 points or higher. For example, the processor (120) may separately set a minimum completion rate for each section for the target education program that is divided into several detailed sections (e.g., first mandatory education, second mandatory education, elective education, etc.). For example, for the first mandatory training (e.g., training related to safety regulations), the ratio of the completion time (or the time actually played by the user terminal) to the playback time (or the total length of the training video) must be at least the first ratio (e.g., 90% or 0.9), and for the second mandatory training (e.g., training related to services), the ratio must be at least the second ratio (e.g., 80% or 0.8), which is lower than the first ratio, so that the input of completion of viewing can be determined to satisfy the specified conditions.

[0108] As an example, the processor (120) can determine whether the conditions are satisfied by calculating the completion time for each section using the viewing log data included in the viewing completion input and comparing it with the minimum ratio set for each section. For example, the processor (120) can determine that the conditions for the first mandatory education are satisfied if the playback time of the first mandatory education according to the viewing completion input is 30 minutes and the actual completion time is 27 minutes or more (or the completion rate is 90% or more), and can determine that the conditions for the first mandatory education are satisfied if the playback time of the second mandatory education is 40 minutes and the completion time is 32 minutes or more (or the completion rate is 80% or more). If either of the mandatory educations falls short of the standards, the processor (120) can determine that the conditions are not satisfied and immediately provide a request to re-watch the education or a request to complete supplementary education for the relevant mandatory education.

[0109] According to one embodiment, the processor (120) may transmit a target certificate request including a user profile corresponding to the user terminal to a taxi operating server when the viewing completion input satisfies a predetermined condition (S330).

[0110] For example, if the processor (120) determines that the viewing completion input satisfies a predetermined condition, it may generate a target certificate request message requesting the issuance of a certificate to the taxi operation server. The target certificate request may include (1) a terminal identifier for identifying the user terminal (e.g., terminal ID, app installation ID, etc.), (2) a user ID or membership number for identifying the user, (3) summary information of the user's user profile (e.g., driving history, license type, desired driving area, desired vehicle type, desired daily driving time, etc.), (4) program ID and version information of the target education program completed, (5) completion date information (or, time of completion of education), (6) education verification results (e.g., completion rate by section, test score, pass / fail status), etc.

[0111] For example, a target certificate request can be generated as structured data in JSON or Protocol Buffers format and transmitted to a taxi operation server via an HTTPS-based secure channel. Based on the received certificate request data, the taxi operation server can review internal policies or regulations (e.g., zone-specific qualification requirements, legal mandatory training status, etc.) and ultimately determine whether to issue the merchant certificate.

[0112] For example, the target certificate request may include summary indicators regarding the user's accident history or violation history (e.g., number of accidents in the last 3 years, whether there have been serious traffic law violations, etc.). This is to enable the taxi operation server to issue a certificate by comprehensively considering not only whether the training has been completed but also the driver's basic trustworthiness. For example, even if all training has been completed, the server may apply a policy to withhold issuance or require supplementary training if there is an excessive accident history. Additionally or generally, even if the viewing completion input satisfies a predetermined condition, if the processor (120) identifies that the number of traffic accidents in the last 3 years is more than a predetermined number (e.g., 10 times) based on the user profile obtained from the user terminal, the processor may not send the target certificate request to the taxi operation server.

[0113] Through this, the processor (120) can support the taxi operation server in operating a more sophisticated franchise approval policy by not only transmitting information corresponding to the completion of training, but also by packaging and transmitting various indicators representing the quality of training completion together. Additionally, the certificate request message may include a unique request ID that can be referenced in the event of future franchise cancellation or policy change, and this request ID may be configured to be linked to the certificate and traceable throughout the system.

[0114] According to one embodiment, the processor (120) can respond to receiving a target certificate from a taxi operation server, calculate a target operation policy based on a viewing completion input, and transmit it to a user terminal along with the target certificate (S340).

[0115] For example, when the processor (120) receives a target certificate from a taxi operation server, it can record the received target certificate in a storage device and calculate a target operation policy based thereon. The target operation policy may be broadly composed of (1) a policy on available operating hours, (2) a policy on available operating areas, (3) a policy on available vehicle types and vehicle classes, and (4) a policy on commission rates and settlement methods. The processor (120) can calculate each policy element in real time by synthesizing information such as the results of watching training, test scores, the user's desired operating conditions, the driver supply status by region, and the supply status by vehicle type.

[0116] For example, in the case of a driver whose test score based on the results of completing training is 90 points or higher and whose mandatory training completion rate is 100%, the processor (120) may produce a policy that allows a relatively lower commission rate and a wider driving area. In another example, in the case of a driver whose test score based on the results of completing training is 70 points or higher but less than 80 points and whose mandatory training completion rate is not 100%, the policy may be gradually relaxed over a subsequent period if customer evaluations collected over a specified period (e.g., 3 months) satisfy a threshold criterion. The policy calculation logic described above may be implemented by a rule-based engine defined in the policy table, or by an artificial intelligence model that has learned past drivers' training / driving performance data.

[0117] For example, the target operation policy may include a commission rate. In this case, the processor (120) may calculate a commission rate inversely proportional to the total viewing time and test score, thereby providing an incentive structure so that drivers who diligently complete the training and receive a high test score can benefit from a lower commission rate. For example, the processor (120) may finely adjust the commission rate based on at least one of the basic commission rate (e.g., 20%), minimum commission rate (e.g., 15%), and maximum commission rate (e.g., 30%) transmitted from the taxi operation server, such as a 1-2 percentage point reduction if the test score is 80 points or higher, a 4-5 percentage point reduction if it is 90 points or higher, a 1-2 percentage point reduction if the total viewing time is 90% or higher relative to the total playback time of the target training program, and a 5 percentage point reduction if it is 100%. At this time, the processor (120) may implement the commission rate calculation process using a policy function defined by a formula or a machine learning model.

[0118] For example, the processor (120) can transmit the target driving policy calculated in this way to a user terminal along with certificate information and, if necessary, synchronize it with a taxi operation server. The user terminal can display the received certificate and driving policy on the screen to help the driver intuitively understand under what conditions they can start operating as a member. For example, specific policy items such as “operation possible in Gangnam-gu, Seoul and 3 adjacent districts, maximum daily operation of 10 hours, night driving allowed, operation of medium-sized / electric vehicles allowed, commission rate of 18% applied” can be provided in a card-type or list-type GUI. Additionally, the processor (120) can set a pre-set validity period (e.g., 2 years) in the policy information and generate a notification that induces re-evaluation and / or re-completion of training upon expiration of the validity period.

[0119] Additionally or generally, the processor (120) receives a plurality of training programs related to the conditions of franchise registration from a taxi operation server, and upon receiving user identification information from the taxi operation server, provides a notification to a user terminal identified based on the user identification information, and then receives a training application input including a user profile from the user terminal.

[0120] That is, before receiving an education application input from a user terminal, the processor (120) may periodically or upon request receive a list of education programs containing multiple education programs associated with franchise registration conditions from a taxi operation server during the initial stage of providing franchise services.

[0121] For example, the list of training programs may include a unique identifier for each training program, the purpose of training, the vehicle type to be trained, the required completion time, evaluation criteria, a playback URL, DRM-related information, and training operation policies. The processor (120) stores the received list of training programs in memory and can build foundational data that can automatically select target training programs based on user conditions (e.g., desired driving area, desired vehicle type, desired daily driving time, past training / accident history, etc.). Through this, the electronic device (100) can perform the selection of an optimized training program for each user without large-scale data exchange with an operation server.

[0122] For example, when the processor (120) receives a message from a taxi operation server containing user identification information (e.g., user ID, terminal UUID, franchise application status value), it can use this identification information to identify the user terminal and send a notification (e.g., push notification, in-app message, text notification via SMS gateway) to the identified user terminal to announce the start of the franchise training application process. This notification may include whether the training program needs to be taken, the estimated completion time, the status of eligibility for franchise application, and the method of application. Upon receiving the notification, the user terminal may display a training application screen or an action button designated by the processor (120) to the user, thereby enabling the user to immediately submit a training application input.

[0123] For example, when a user proceeds with an education application by following a route guided through a notification, the user terminal can transmit an education application input, including a user profile (e.g., desired driving area, desired vehicle type, desired daily driving time, basic personal information, past education / accident history, etc.), to the processor (120). The processor (120) can match a target education program based on the received user profile and automatically perform subsequent procedures such as verifying viewing conditions, requesting a certificate, and calculating a driving policy. Through such procedures, the system of the present invention can implement an efficient and consistent flow of education / franchise application and policy provision through server-based coordination while minimizing user intervention.

[0125] FIG. 4 is a flowchart of a method for providing franchise services according to an embodiment of the present invention.

[0126] According to one embodiment, an electronic device (e.g., the electronic device (100) of FIG. 1) may perform the operations disclosed in FIG. 4. For example, at least some of the components included in the electronic device (e.g., the memory (110), processor (120), communication interface (130), and display device (140) of FIG. 1 may be configured to perform the operations of FIG. 4.

[0127] In the following embodiments, the operations S410 to S420 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 4 may be briefly explained or omitted.

[0128] According to one embodiment, the processor (120) can calculate a commission rate inversely proportional to the total viewing time and test score target based on the viewing completion input (S410).

[0129] According to one embodiment, the processor (120) can provide a target operation policy including a fee rate to a user terminal along with a target certificate (S420).

[0130] For example, when the processor (120) receives a target certificate issued for a specific driver from a taxi operation server, it may perform a target operation policy calculation step to determine under what conditions the driver can actually start operating a franchise. At this time, the target operation policy may be composed of a set of multiple policy parameters, such as, for example, (i) daily operating hours, (ii) operating zones, (iii) permitted vehicle types and classes, and (iv) commission rates received by the platform (or taxi operation company). For example, the commission rate may be calculated to be inversely proportional to how diligently the driver completed the training and how well they passed the evaluation.

[0131] To this end, after receiving the target certificate, the processor (120) may refer to the session-by-session viewing log and test result data of the target training program associated with the target certificate. The data for reference may be stored in the viewing completion input received from the user terminal and may include the total viewing time (or the cumulative time the driver actually played the video included in the target training program) and the test score (e.g., 0 to 100 points). The processor (120) may calculate the final fee rate using these two values ​​and a predefined reference value (e.g., total playback time of the training program, reference fee rate, minimum / maximum fee rate, weight, etc.), generate a target driving policy including the result of this calculation, and then transmit it to the user terminal along with the target certificate.

[0132] For example, the processor (120) can calculate the commission rate based on the following mathematical formula 1.

[0133]

[0134] For example, r min is the minimum commission rate set and transmitted by the taxi operation server, and r max is the maximum commission rate set and transmitted by the taxi operation server, and R T is the total viewing time (or playback ratio) of the target educational program on the user terminal relative to the total playback time of the target educational program, and R S is the test score of the user terminal for the target education program, and A corresponds to the number of traffic accidents that occurred in the last three years for the user included in the user profile. In addition, a, b, and c correspond to weights for the playback rate, test score, and number of traffic accidents, respectively. Here, the processor (120) R even if the total viewing time becomes greater than the total playback time. T The maximum value of can be limited to 1.

[0135] For example, the minimum fee rate could be 15% (i.e., 0.15) and the maximum fee rate 30% (i.e., 0.30), with a being 1.0, b being 2.0, and c being 0.5. In this case, if the first user has had 0 traffic accidents in the last 3 years (i.e., A=0) and has watched all target educational programs (i.e., R T = 1) and if the test score is identified as 90 points, the commission rate calculated for the first user may be measured as relatively low at approximately 15.9%. On the other hand, even if the second user has watched the entire target education program and the test score is 90 points, the same as the first user, if there have been 3 traffic accidents in the last 3 years (i.e., A=3), the commission rate calculated for the second user may be higher than that of the first user at approximately 16.8%.

[0136] The processor (120) provides technical advantages that, through the fee rate calculation logic according to mathematical formula 1, it can eliminate non-linear bias that may occur in a simple weighted average method and reflect the increase in risk due to increased accident history in a continuous and gradual form.

[0137] In particular, the number of traffic accidents is reflected in a logarithmic form; this acts to increase the commission rate as the number of accidents rises, but is converted into a gradual logarithmic increase to prevent an infinite surge even in cases of very high accident rates. Accordingly, this provides a technical effect where even a small number of accidents have a certain impact on the increase in the commission rate, while preventing excessive spikes for drivers with high-frequency accidents. Furthermore, by using an exponential function structure, the commission rate exhibits the characteristic of gradually converging to the minimum rate as viewing time and test scores increase, while conversely, it enables non-linear adjustment that gradually moves toward the maximum rate as the number of accidents increases.

[0138] Thus, mathematical formula 1 for calculating the commission rate realizes risk-based dynamic commission rate adjustment that cannot be provided by a simple weighted sum method by calculating indicators of different natures, such as (1) educational integrity, (2) evaluation score, and (3) accident history, into a single integrated exponential function model. Furthermore, since the sensitivity to changes in the user's past accident history can be precisely adjusted through a combination of logarithmic and exponential functions, there is a technical effect of significantly improving the sophistication and adaptability of driver safety evaluation and franchise operation policies.

[0140] FIG. 5 is a flowchart of a method for providing franchise services according to one embodiment of the present invention.

[0141] According to one embodiment, an electronic device (e.g., the electronic device (100) of FIG. 1) may perform the operations disclosed in FIG. 5. For example, at least some of the components included in the electronic device (e.g., the memory (110), processor (120), communication interface (130), and display device (140) of FIG. 1 may be configured to perform the operations of FIG. 5.

[0142] In the following embodiments, the operations of S510 to S530 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 5 may be briefly explained or omitted.

[0143] According to one embodiment, the processor (120) can check the first playback time and the second playback time of each of the first mandatory training and the second mandatory training related to service training, which are pre-set for the target training program (S510).

[0144] For example, the processor (120) can check the respective first and second playback times by referring to metadata regarding the first mandatory training related to safety regulations and the second mandatory training related to service training within the target training program. Here, the first mandatory training may be a section containing content directly related to accident prevention and compliance with regulations, such as, for example, compliance with traffic laws, prohibition of drunk driving, compliance with speed limits, guidance on seatbelts when passengers board, and emergency response procedures in the event of an accident, and the second mandatory training may be a section containing content related to improving service quality, such as passenger interaction, friendliness, maintaining cleanliness, handling customer complaints, and manners for providing destination guidance.

[0145] For example, the processor (120) can determine which section of the total educational content included in the target education program the first mandatory education and the second mandatory education are located in, and what the total playback time of each mandatory section is, through content metadata that is defined together when the target education program is stored on the taxi operation server. For example, if the target education program consists of a total playback time of 120 minutes, the first 40 minutes of which consist of the first mandatory education related to safety regulations (e.g., first playback time = 40 minutes), the following 30 minutes consist of the second mandatory education related to service education (e.g., second playback time = 30 minutes), and the remaining 50 minutes consist of optional education (or optional section), the metadata may include attributes such as the start time, end time, section ID, section type (e.g., mandatory / optional), and section category (e.g., safety / service / other) of each mandatory education section.

[0146] For example, the processor (120) may, based on the metadata described above, recognize in advance the total playback time of the first mandatory training (or, first playback time) and the total playback time of the second mandatory training (or, second playback time) for the target training program, and store the corresponding values ​​in internal memory or a policy table. This process may be performed in advance before the actual user watches the training, and may be used as a reference value to calculate the ratio of playback time to completion time during the subsequent step of analyzing viewing logs. In some embodiments, the processor (120) may directly query the playback time information of the first mandatory training and / or the second mandatory training through an education content management API provided by a taxi operation server, or may cache it locally in advance and load it at the time of selecting the target training program.

[0147] According to one embodiment, the processor (120) can check the first completion time when the first mandatory education is played on the user terminal and the second completion time when the second mandatory education is played on the user terminal based on the viewing completion input (S520).

[0148] For example, the processor (120) can receive a viewing completion input transmitted from a user terminal after the user has completed watching the target education program, and by analyzing the viewing log information included therein, calculate the first completion time for the first mandatory education and the second completion time for the second mandatory education, respectively. Here, the viewing log information is a record of changes in playback status along a time axis and may include event data such as at least the playback start time, playback end time, pause time, rewind / fast-forward time, and current playback position (e.g., timecode or frame position). Additionally, according to some embodiments, completion information by section may be included in the form of aggregating “how many seconds the corresponding section was played” for a specific section of the education content (e.g., in 5-minute units or in chapter units).

[0149] For example, the processor (120) can analyze the viewing log information to determine whether the educational section being played at each point in time corresponds to the first mandatory education, the second mandatory education, or other sections such as elective education. For example, if the first mandatory education section is set to 0 to 40 minutes and the second mandatory education section is set to 40 to 70 minutes in the metadata, the sum of the cumulative playback time during the period when the playback position in the viewing log information is between 0 to 40 minutes can be calculated as the first completion time, and the sum of the cumulative playback time during the period when it is between 40 to 70 minutes can be calculated as the second completion time. At this time, if the same section is played multiple times due to rewinding or repeated playback, the processor (120) may calculate the cumulative completion time including that time, or may set an upper limit according to a policy, such as “maximum playback time is recognized only up to 1.5 times the section playback time.”

[0150] In another embodiment, the user terminal transmits the current playback position and playback status (e.g., playing or stopped) to the electronic device (100) at regular intervals (e.g., every 10 or 30 seconds) during viewing, and the processor (120) can calculate the completion time by integrating or summing consecutive samples. For example, if the “playing” state is recorded 180 times at 10-second intervals within the first mandatory training period, the first completion time becomes 10 seconds × 180 = 1800 seconds (= 30 minutes). This method can enable relatively accurate estimation of viewing time even in environments where the network condition is unstable or the terminal is connected intermittently.

[0151] According to one embodiment, the processor (120) can determine that the viewing completion input satisfies a predetermined condition only when the ratio of the first completion time to the first playback time is greater than or equal to the first ratio, and the ratio of the second completion time to the second playback time is greater than or equal to the second ratio which is lower than the first ratio (S530).

[0152] For example, the processor (120) can calculate a completion rate by comparing the first completion time and the second completion time calculated as above with the first playback time and the second playback time, respectively, that are pre-set for the target education program. The completion rate for the first mandatory education can be calculated, for example, as the first completion time / first playback time, and the completion rate for the second mandatory education can be calculated as the second completion time / second playback time. The processor (120) can compare the completion rate with a standard rate (e.g., first rate and second rate) pre-defined by the taxi operation server. Here, the first rate may mean a minimum completion rate standard for the first mandatory education (e.g., 90% or 0.9), and the second rate may mean a minimum completion rate standard for the second mandatory education (e.g., 80% or 0.8).

[0153] For example, the processor (120) can determine whether a viewing completion input satisfies a predetermined condition using a first ratio and a second ratio with the following logic. That is, the processor (120) can determine that the viewing completion input satisfies a predetermined condition only when (i) R1, which is the ratio of the first completion time (L1) to the first playback time (T1), is greater than or equal to the first ratio, and at the same time (ii) R2, which is the ratio of the second completion time (L2) to the second playback time (T2), is greater than or equal to the second ratio, which is set to a value lower than the first ratio. For example, in the case of the first mandatory training directly related to safety, the completion ratio standard can be set to 90% (e.g., first ratio = 0.9), and in the case of the second mandatory training corresponding to service training, it can be set to 80% (e.g., second ratio = 0.8). In this case, the processor (120) recognizes the user as having passed the safety regulation-related training only when they have watched most of the section, and the service-related training only when they have watched a certain portion (e.g., 80%) or more.

[0154] As an example, the playback time of the first mandatory education may be 40 minutes and the playback time of the second mandatory education may be 30 minutes, and the first ratio may be set to 0.9 and the second ratio to 0.8. If the first user actually watches the first mandatory education for 40 minutes, so that the ratio of the first completion time to the first playback time becomes 1, and the second mandatory education is watched for only 25 minutes, so that the ratio of the second completion time to the second playback time is calculated to be approximately 0.83, the processor (120) may determine that the specified conditions are satisfied because each ratio exceeds the first ratio and the second ratio, respectively. On the other hand, if the second user watches the first mandatory education for only 30 minutes, so that the ratio of the first completion time to the first playback time is calculated to be approximately 0.7, even if the second mandatory education is watched for 30 minutes, the ratio of the first completion time to the first playback time falls short of the first ratio, so the processor (120) may determine that the viewing completion input does not satisfy the specified conditions. In other words, in the structure of the present invention, the completion standards for essential safety training can be applied more strictly than those for service training, thereby achieving a technical effect of enforcing a minimum level of compliance with safety regulations.

[0156] According to one embodiment, the processor (120) checks the desired driving area included in the user profile, requests the number of registered drivers for the same target area as the desired driving area from the taxi operation server, and if the number of drivers is less than a threshold number, calculates the daily driving time proportional to the difference value obtained by subtracting the number of drivers from the threshold number, and can identify the target training program corresponding to the user profile among a plurality of training programs only if the daily driving time is greater than or equal to the daily desired driving time included in the training application input. If the daily driving time is less than the daily desired driving time, a recommendation interface can be provided to the user terminal to induce a franchise business to the recommended area with the lowest number of registered drivers among adjacent areas adjacent to the desired driving area.

[0157] For example, the processor (120) can first identify the desired driving area included in the user profile. The desired driving area refers to the geographical range where the user intends to primarily operate through the taxi franchise business, and can be defined, for example, by administrative district units (e.g., city / district / county), specific commercial areas, areas around airports / stations, special tourism zones, etc. In the user profile, such desired driving areas may be stored in the form of text information or codes, for example, “Gangnam-gu, Seoul,” “Haeundae-gu, Busan,” or “Incheon International Airport Area.” In some embodiments, the desired driving area is not limited to a single area but may include a list of multiple areas (e.g., Gangnam-gu + Seocho-gu), in which case the processor (120) can manage a set or priority for multiple areas together.

[0158] For example, the processor (120) can determine the desired driving zone by loading a user profile from memory or a database and referring to values ​​stored in specific fields (e.g., preferred_region, preferred_zone_code, etc.). At this time, the desired driving zone may not be a simple text string, but may be mapped to a predefined zone code (e.g., Zone ID) for linkage with a taxi operation server. For example, the string “Gangnam-gu, Seoul” may be internally replaced and stored as a code such as “REGION_1100”, and the processor (120) may use this code value as an input value for subsequent operations (e.g., requesting the number of registered drivers, calculating recommended zones, etc.). Through this, the electronic device (100) can manage various zones using a standardized code system and can easily perform linkage with regional supply and demand information.

[0159] For example, after the processor (120) identifies a desired operating area, it may request the number of registered drivers from the taxi operation server to determine the number of taxi drivers who have already completed franchise registration in that area. At this time, the processor (120) may generate a request message containing an area code (or target area) corresponding to the previously identified desired operating area and transmit it to the API endpoint of the taxi operation server via a network. The request message may include filter conditions for the target area code, the time of the request or reference date, and driver type (e.g., corporate / individual, general / premium, etc.), and may also include additional parameters such as time zone conditions (e.g., daytime / nighttime) and franchise brand distinction.

[0160] For example, a taxi operation server can query affiliate driver information stored in an internal database, aggregate the number of drivers registered in a specific target area, and then provide the result to an electronic device (100) in the form of a response message. For example, if the desired operating area is “Gangnam-gu” and there are currently 320 affiliate drivers registered in Gangnam-gu, the taxi operation server can send a response containing the value “driver_count = 320”. A processor (120) can parse the received response to extract the number of drivers registered for the target area. Through this, the electronic device (100) can perform a quantitative judgment reflecting the supply and demand status of each area, rather than deciding whether to allow affiliation based solely on the individual user's personal wishes.

[0161] For example, the processor (120) can calculate the daily operating hours during which additional drivers can operate in a target area by comparing the number of registered drivers received from the taxi operation server with a threshold number pre-set by the taxi operation server. Here, the threshold number refers to the optimal or maximum appropriate number of drivers set considering the population, quality of service, traffic congestion, supply versus demand, etc., in a specific area, and, for example, the processor (120) can dynamically adjust the threshold number based on the reference value received from the taxi operation server and the number of registered drivers.

[0162] For example, the processor (120) can calculate the daily operating hours in proportion to the difference value obtained by subtracting the number of registered drivers from the threshold number only when the number of registered drivers is less than the threshold number. For example, the average operating hours that one driver can handle per day in a target area may be pre-set to 8 hours, and if the threshold number is 400 and the number of registered drivers is 320, the difference value is calculated to be 80, and the processor (120) can calculate the allowable daily operating hours per new driver based on this difference value and the total amount of operating hours to be covered overall. As another example, the larger the difference value, the longer the daily operating hours that a new driver can secure become, and if the difference value becomes 0 or negative (or if the number of registered drivers is already greater than or equal to the threshold number), a warning notification can be provided to the user terminal stating that the daily operating hours are 0 and registration is not possible.

[0163] As one example, the processor (120) can calculate the maximum daily driving time for a newly registered driver as 10 hours if the difference value is 50 or more, the maximum daily driving time as 6 to 8 hours if the difference value is 10 or more and less than 50, and restrict the registration of the newly registered driver for the target area if the difference value is 0 or less.

[0164] For example, the processor (120) may calculate the maximum daily operating time corresponding to the difference value by referring to an internal policy table or function (e.g., a linear function, a step function), and use this to compare with the user's desired daily operating time in a subsequent step. By doing so, the present invention can provide the effect of dynamically adjusting the operating range of new drivers based on objective supply and demand indicators (e.g., a threshold number relative to the number of drivers).

[0165] For example, the processor (120) can determine whether a new affiliate driver can actually drive for the desired amount of time in the area by comparing the calculated daily driving time with the daily desired driving time included in the user profile or training application input. The daily desired driving time may be a value directly entered by the user during the training application stage (e.g., “want to drive 8 hours a day,” “want to drive 4 hours part-time,” etc.) and may be stored as a value in the field within the user profile in the time unit.

[0166] For example, the processor (120) can proceed with a flow to identify a target training program corresponding to the user profile among multiple training programs only when the daily operating time is greater than or equal to the daily desired operating time. That is, the training and franchise procedure based on that area can continue only when it is determined from the perspective of the electronic device (100) that “there is room to operate for the time you want in this area.” Conversely, if the daily operating time is less than the daily desired operating time, that is, if it is difficult to secure the level of operating time desired by the user in that area, the flow can be switched to not proceeding with the matching of training programs based on the target area or recommending training targeting a different area. Through this structure, the electronic device (100) can provide a more realistic franchise process that considers actual profitability and operational feasibility throughout the entire “training-franchising-operation” process, rather than simply registering a franchise upon completion of training. As an example, if a driver wishes to drive for 10 hours a day but only 4 hours are allowed for new drivers in a specific overcrowded area, matching them with a training program based on that area is inefficient for both the driver and the operator. Therefore, the present invention can prevent such mismatches in advance during this comparison step.

[0167] For example, if the processor (120) determines that the daily operating time is shorter than the user's daily desired operating time, it may not simply notify the user that franchise registration is not possible, but instead select the area with the lowest number of registered drivers among the adjacent areas adjacent to the desired operating area as the recommended area, and provide a recommendation interface to the user terminal to induce franchise business to the recommended area. Here, the adjacent areas may be defined based on administrative district boundaries, distance criteria (e.g., distance between center points), or commercial area clustering information managed by the taxi operation server. For example, if "Gangnam-gu" is desired, "Seocho-gu," "Songpa-gu," "Yongsan-gu," etc., may be set as candidates for adjacent areas.

[0168] For example, the processor (120) may request a list of adjacent areas and the number of registered drivers for each adjacent area from the taxi operation server, and select one or more areas from the responded data that have the lowest number of registered drivers or the largest available daily operating hours to determine as recommended areas. Afterward, a GUI containing a message such as “It is difficult to satisfy your desire to operate for 10 hours a day in Gangnam-gu, which you currently wished for. Among the adjacent areas, ‘Songpa-gu’ has a relatively small number of drivers, so it may be possible to operate for 10 hours a day. Would you like to proceed with franchise training based on Songpa-gu?” may be displayed on the user terminal. The recommendation interface may be configured in various ways, such as in the form of buttons (e.g., ‘Change to Songpa-gu and proceed’, ‘View other areas’, etc.), a map-displayed area selection screen, or a text list format.

[0169] Through such a recommended area guidance function, the present invention can automatically suggest a compromise point that simultaneously satisfies the user's daily desired driving time and the operator's supply and demand policy. Unlike existing systems that simply conclude with "affiliation is not possible in that area," this presents reasonable alternatives to adjacent areas, thereby increasing the driver's affiliation conversion rate and enabling the operator to achieve balanced supply and demand adjustments between overcrowded and underserved areas. Ultimately, the present invention provides a technical effect that simultaneously improves the efficiency and fairness of affiliation matching through a series of processes including "affiliation application based on desired area, analysis of supply and demand status, and recommendation of adjacent areas in case of shortage."

[0171] According to one embodiment, the processor (120) transmits a target certificate to a user terminal, and then receives location information from the user terminal at predetermined intervals during the operation time from the time of receiving an operation start input from the user terminal to the time of receiving an operation end input. If, based on the location information, it identifies that the location of the user terminal has moved out of the desired operation area beyond the time limit during the operation time, the processor may transmit a request for cancellation of membership to the taxi operation server to request the revocation of the certificate issued to the user terminal.

[0172] For example, the processor (120) may remain in a waiting state from the time it transmits the target certificate to the user terminal until it receives a driving start input, and then switch to a driving time management mode when it receives a driving start input indicating that the user intends to start actual driving. At this time, the driving start input may be in the form of pressing a “driving start” button on an application screen within the user terminal, or it may be a signal automatically generated based on whether the vehicle is started or a driving signal detected by an IoT module within the vehicle. The processor (120) may store the driving start time as a timestamp and define the time interval until the driving end input is received as a driving session.

[0173] For example, the processor (120) may receive location information including current location coordinates (e.g., latitude, longitude) from a location information module (e.g., GPS, GLONASS, LTE triangulation, etc.) stored in the user terminal at regular intervals during the operation time. The interval setting may be configured in various ways, such as 5 seconds, 30 seconds, 1 minute, etc., and may be adjustable according to service operation policies or regional regulatory compliance requirements. The processor (120) may continuously record the operation route based on the timestamp of the received location information and store it in an internal record buffer to calculate the time of stay inside or outside the desired operation area. This location information may include not only GPS coordinates but also auxiliary data such as speed information, heading, altitude, terminal signal strength, and base station ID, thereby improving the reliability of the location information or correcting signal spikes.

[0174] For example, the processor (120) can continuously determine whether the user's current location is included in the desired driving area based on location information received at regular intervals. The desired driving area may consist of a single polygon data (or administrative area boundary) or multiple areas. The processor (120) may apply a point-in-polygon algorithm or a GIS-based boundary determination algorithm to determine whether the location coordinates exist within the area boundary.

[0175] For example, if the processor (120) identifies that the location of the user terminal during operation has deviated from the desired driving area, it may record the time of deviation and compare it with an allowed time limit (e.g., grace period) to make a final determination of whether an actual violation has occurred. The time limit may be set to a value such as 2 minutes or 5 minutes, for example, to account for simple route correction or short-term deviations from the area that are unavoidable due to the road structure. If the processor (120) determines that the time limit has been exceeded while the user is out of the area, it may immediately send a request for cancellation of membership (or a request to revoke the certificate) to the taxi operation server. The request for cancellation of membership may include detailed data such as user identification information, certificate identifier, deviation route information, time of deviation, and cumulative time of deviation.

[0176] Through such a mechanism, the present invention moves beyond a simple registration / authentication-based system and provides a technical effect of maintaining franchise service quality by verifying real-time policy compliance during operation. Additionally, the electronic device (100) enables the zone-breaking-based automatic certificate revocation procedure to serve as a safety mechanism that prevents the franchise system from indiscriminately abusing operating zones.

[0178] According to one embodiment, the processor (120) checks the desired vehicle type included in the user profile, requests the number of remaining vehicles corresponding to the desired vehicle type from the taxi operation server, and can identify the target training program corresponding to the user profile among a plurality of training programs only if the number of remaining vehicles received from the taxi operation server is greater than or equal to the threshold number of vehicles.

[0179] For example, the processor (120) can check the desired vehicle type stored in the user profile, and the desired vehicle type can be classified into standard taxi, premium taxi, luxury taxi, large taxi, etc., and if stored in a JSON-based structure, it can be implemented in the form of, for example, "desired_vehicle_type": "premium". In some embodiments, multiple subdivided vehicle types may be identified based on whether it is an electric vehicle / hybrid, brand, number of seats, and operating rate system. The processor (120) prioritizes reading the relevant field among the education application inputs submitted by the user terminal, and if it is missing from the user profile, it may recommend a basic vehicle type or provide a separate input step.

[0180] For example, the processor (120) may send a request message to a taxi operation server to determine the number of remaining vehicles available for operation with the desired vehicle type after confirming the desired vehicle type. The number of remaining vehicles refers to the number of spare vehicles not assigned to the vehicle type, and this can be calculated based on the number of available vehicles in a vehicle pool managed by the taxi operation server (or taxi operator), excluding vehicles currently in operation, under repair, or assigned to reservations.

[0181] For example, the processor (120) may send a request message to a taxi operation server including additional parameters such as a desired vehicle type code, a target area code, the time of the request, vehicle size, or fuel type. The taxi operation server may respond after querying the number of remaining vehicles of the corresponding vehicle type in the internal dispatch / operation management system, and for example, if the number of remaining vehicles of a “premium taxi” is 12, the server may reply to the electronic device (100) including the value remaining_vehicle_count = 12.

[0182] For example, the processor (120) determines whether there is room to add new drivers for the vehicle type by using the received remaining number of vehicles and comparing it with a threshold number of vehicles (or, minimum number of operational vehicles) in a subsequent step. That is, the training program matching proceeds only if new membership is possible from the perspective of vehicle supply and demand.

[0183] For example, the processor (120) can determine whether the number of remaining vehicles is greater than or equal to a pre-set threshold number of vehicles. The threshold number of vehicles refers to the minimum number of vehicles required set by the taxi operator for the service quality and dispatch stability of a specific vehicle type. For example, in the case of a premium taxi, a policy may be applied requiring that at least 5 remaining vehicles be secured for a new driver to join.

[0184] For example, if the number of remaining vehicles is less than the threshold number of vehicles, the processor (120) may provide an interface that informs the user that the vehicle type is currently saturated with supply and therefore cannot proceed with franchising, or that encourages the selection of another vehicle type. Conversely, if the number of remaining vehicles is greater than or equal to the threshold number of vehicles, the processor (120) may subsequently proceed with the process of finally identifying a target education program that matches the user profile.

[0185] In other words, this embodiment serves as a technical element for securing policy stability in vehicle supply and demand, and plays a role in preventing in advance the problem of deteriorating dispatch quality caused by an excessive increase in the new participation of specific vehicle models.

[0187] According to one embodiment, the processor (120) requests the number of vehicle types registered for a target area and the number of registrations per vehicle type from the taxi operation server when the number of remaining vehicles received from the taxi operation server is greater than or equal to the threshold number of vehicles, and when the number of vehicle types exceeds 3, identifies the average value of the number of registrations per vehicle type, and only when the number of registrations per vehicle type is less than the average value of the target vehicle type corresponding to the desired operating vehicle type among the number of registrations per vehicle type, can identify the target training program corresponding to the user profile among the plurality of training programs.

[0188] For example, if the processor (120) confirms that there is a sufficient number of remaining vehicles, it may request a query from a taxi operation server to determine the types of vehicles currently in operation in the target area and the number of registered drivers for each vehicle type. Through this, the electronic device (100) can determine whether a specific vehicle type is excessively numerous or has little competition in the area, and use this as base data to determine which vehicle type a new driver can strategically choose. For example, the request message may include a target area code, a vehicle type information request flag, and a specific brand / detailed vehicle type filter. For example, the taxi operation server may return the number of registered vehicles by type to the electronic device (100) in a table format, such as “General (150), Premium (30), Premium (20), Large (10).” For example, after receiving this data, the processor (120) analyzes the diversity and distribution of vehicle types and can use it to calculate the average number of registered vehicles in a subsequent step.

[0189] For example, if the number of vehicle types existing in the target area exceeds 3, the processor (120) can calculate the average value of the number of registrations per vehicle type to determine the level of competition. For example, based on data returned from the taxi operation server as “General: 150 / Premium: 30 / Premium: 20 / Large: 10,” the processor (120) can identify that there are a total of 4 vehicle types and the average value of the number of registrations per vehicle type is (150 + 30 + 20 + 10) / 4 = 52.5. The average value is used as a baseline to determine whether a specific vehicle type is excessively numerous or insufficient in the area, and can be used as a useful indicator to calculate whether the vehicle type a new driver wishes to register is a vehicle type with excessively fierce competition. Generally, a weighted average, median, etc., may be used, and this can be adjusted according to the operator's policy settings.

[0190] For example, the processor (120) can determine whether the number of registered drivers for a desired vehicle type is less than the calculated average value, which can be understood as a control policy to allow new membership only when a specific vehicle type is not in a state of oversupply in the market. For example, if the number of registered drivers for a premium vehicle type is 20 and the average value is 52.5, the processor (120) can determine that the vehicle type is suitable for new drivers because there is less competition.

[0191] Conversely, in cases where the number of registered vehicles is much higher than the average, such as regular taxis (e.g., 150 people), the processor can prevent a concentration of specific vehicle types and maintain supply and demand balance by restricting the identification of new franchise training programs for those vehicle types.

[0192] Finally, the processor (120) may identify and provide a target training program to a user terminal only when the number of registered target vehicles corresponding to the desired driving vehicle type is less than the average value. This step can be understood as a technical means to maintain diversity of driver experience and supply and demand balance.

[0194] The above description is merely an illustrative explanation of the technical concept of the present invention, and those skilled in the art to which the present invention pertains will be able to make various modifications and variations within the scope of the essential characteristics of the present invention.

[0195] Accordingly, the embodiments disclosed in this invention are intended to illustrate, not limit, the technical concept of the invention, and the scope of the technical concept of the invention is not limited by these embodiments. The scope of protection of this invention shall be interpreted by the claims below, and all technical concepts within an equivalent scope shall be interpreted as being included within the scope of rights of this invention.

Claims

Claim 1 A method for providing a franchise service in which an electronic device including a processor grants franchise eligibility to a specific driver based on a driver training history and supports linkage between a taxi company and a driver granted franchise eligibility, wherein the processor performs the operation of identifying a target training program corresponding to the user profile among a plurality of training programs in response to receiving a training application input including a user profile from a user terminal; the processor performs the operation of checking whether the viewing completion input satisfies a predetermined condition for the target training program when the processor receives a viewing completion input from the user terminal within a predetermined threshold time for the target training program; the processor performs the operation of transmitting a target certificate request including a user profile corresponding to the user terminal to a taxi operating server when the viewing completion input satisfies the predetermined condition; and the processor performs the operation of calculating a target driving policy based on the viewing completion input and transmitting it to the user terminal together with the target certificate in response to receiving a target certificate from the taxi operating server. The method for providing a franchise service includes: the processor confirming a desired driving area included in the user profile; the processor requesting the number of drivers registered for a target area identical to the desired driving area from the taxi operating server; the processor calculating a daily driving time proportional to the difference value obtained by subtracting the number of drivers from the threshold number when the number of drivers is less than a threshold number; and the processor identifying the target training program corresponding to the user profile among the plurality of training programs only when the daily driving time is greater than or equal to the daily desired driving time included in the training application input.A method for providing a franchise service further comprising: the operation of the processor providing a recommendation interface to the user terminal that induces a franchise business to the recommendation zone with the lowest number of registered drivers among adjacent zones adjacent to the desired driving zone when the daily operating time is less than the daily desired driving time; Claim 2 delete Claim 3 The method of providing a franchise service according to claim 1 further comprises: an operation in which the processor, after transmitting the target certificate to the user terminal, receives location information from the user terminal at predetermined intervals during the operation time from the time of receiving the operation start input from the user terminal to the time of receiving the operation end input; and an operation in which, if the processor identifies, based on the location information, that the location of the user terminal has moved out of the desired operation area by more than a limited time during the operation time, transmits a franchise cancellation request to the taxi operating server requesting the revocation of the certificate issued to the user terminal. Claim 4 In paragraph 3, the method for providing a franchise service further comprises: an operation in which the processor verifies a desired vehicle type included in the user profile; an operation in which the processor requests the number of remaining vehicles corresponding to the desired vehicle type from the taxi operating server; and an operation in which the processor identifies the target training program corresponding to the user profile among the plurality of training programs only when the number of remaining vehicles received from the taxi operating server is greater than or equal to a threshold number of vehicles. Claim 5 In claim 4, the method for providing a franchise service further comprises: an operation in which the processor requests the number of vehicle types registered for the target area and the number of registrations by vehicle type from the taxi operating server when the number of remaining vehicles received from the taxi operating server is greater than or equal to the threshold number of vehicles; an operation in which the processor identifies the average value of the number of registrations by vehicle type when the number of vehicle types exceeds three; and an operation in which the processor identifies the target education program corresponding to the user profile among the plurality of education programs only when the number of registrations of the target vehicle type corresponding to the desired operating vehicle type among the number of registrations by vehicle type is less than the average value.

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