eSIM PROFILE SUGGESTION SYSTEM

Abstract

This invention relates to a system (1) that enables the analysis of eSIM profiles in electronic devices by artificial intelligence and suggests the most suitable profile to the user.

Description

1 TARIFF eSIM PROFILE SUGGESTION SYSTEM Technical Area This invention analyzes eSIM profiles on electronic devices using artificial intelligence. It relates to a system that suggests the most suitable profile to the user. Previous Technique The use of eSIMs is increasing day by day. With eSIMs, users receive... internet, voice without needing to insert a physical card into electronic devices Such rights are granted so that users can access the content that best suits them. They choose profiles. However, how much of a role does this choice play for most users? Because he had difficulty predicting how he would use it, it was easy 15 This is not the case. Therefore, in order to overcome the aforementioned deficiency, a new approach is needed. The system is needed. In the invention with application number 2022 / 785404, which is included in the prior art. 20 from existing eSIM solutions and offering the user the option of manual selection It is mentioned, but in the known technique, the user mostly prefers to choose which eSIM profile He / she needs to understand that it is appropriate. In this case, the user The experience is weak and personalization is limited. With CRM or call center... Due to the lack of integration, operator customer management remains weak. Brief Description of the Invention The goal of this invention is to analyze eSIM profiles on electronic devices using artificial intelligence. a system that suggests the most suitable profile to the user. to accomplish. 30 2 Detailed Description of the Invention The "eSIM Profile Recommendation System" implemented to achieve the purpose of this invention is attached. This is shown in the figure; Figure 1. Schematic view of the system described in the invention. The parts shown in the figure are individually numbered, and the corresponding numbers correspond to these numbers. given below: 1. System 2. Electronic device 3. Server eSIM profiles are analyzed using artificial intelligence to determine the most suitable profile for the user. The system of invention which enabled its proposal (1); -eSIM profile suggestions that allow users to use eSIMs at least one electronic device (2) that enables viewing and selection. - Internet usage via eSIM (2) on the user's electronic device, voice call frequency, roaming habits and real-time location data are continuously monitored. the collection of data, and the analysis of the collected data using an artificial intelligence (AI) based model. this involves analyzing the user's behavioral patterns, past profile preferences, and billing. evaluation and "roaming-focused for an individual user traveling abroad" Suggesting new profiles to users in the form of "eSIM profile suggestion", CRM (Customer Relationship Management) Relationship Management) and call center integration for both individual and 25+ Storing the historical data of corporate clients and the suggested profile recording the changes, displaying AI suggestions on the call center screen the suggestion is automatically sent to the operator via call or SMS / email to the user. automatic notification via the company's CRM in the corporate scenario. A "corporate control panel" is created for the authority, and from there, it can be determined which employee has 30 3 the best configured to display which profile suggestion you received It contains a small server (3). The electronic device (2) in the system (1) which is the subject of the invention, allows users to use eSIM to use, perform transactions on eSIM, and view profile suggestions 5 phones, tablets or portable devices that allow them to view the images It is any eSIM-compatible device in the form of a computer. The electronic device in question... device (2), any remote communication device in the known state of the art. to establish a connection with the server (3) using the protocol and this established connection It is configured to exchange data with the server (3) via. 10 In the preferred application of the invention, the electronic device (2), server (3) and Internet to exchange data using a data path in this manner It is being structured. The server (3) in the system in question (1) is 15 in the prior art. to communicate with an electronic device (2) using any communication protocol and data exchange with electronic device (2) through this established communication It is configured to perform. The server (3), in the electronic device (2) eSIM profile data, device usage statistics, network performance via eSIM. records, CRM customer behavior data and call center interaction data 20 It is configured to enable the collection of data. The server (3) collects data. Apache Kafka / MQTT are real-time data streaming protocols. It is configured to use. The server (3) provides time to the collected data. to apply the pre-processing steps of stamping, normalization and anonymization is configured. Server (3) reduces noise on the collected data 25 Kalman Filter for data integrity, Isolation Forest for data integrity. (Forest), for determining usage intensity, data consumption patterns, and device priority levels. To use Feature Engineering algorithms It is configured. The server (3) extracts usage profiles from the data obtained. It is configured to group similar usage profiles. Server (3) 30 K-Means Clustering analyzes device and customer behavior. 4 Principal Component Analysis (PCA) is used to identify the main factors. Component Analysis is used to predict future usage intensities. To use Time Series Analysis (ARIMA / LSTM)) is configured. Server (3), devices in the dynamic eSIM profile management process. (2) Reinforcement learning to learn to prioritize dynamically 5 The Reinforcement Learning (RL) model involves different scenarios in the decision-making process. Q-Learning and By using Deep Q-Networks (DQN) AI models, thus... Assign low-latency connections to critical devices and data to non-critical devices. It is configured to delay its consumption until Wi-Fi is available. Server (3), 10 CRM and call center integration, determined according to the user profile. Processing new eSIM profile suggestions, customer interaction in call center settings. Natural Language Processing (NLP) analyzes "complaint triggers". Analyzing and dynamically using NLP (BERT / GPT-based models) techniques. The suggestions are configured to be displayed on the electronic device (2). 15 Server (3) performs autoencoder-based anomaly detection for attempted theft. It is configured to provide the server (3) with dynamic eSIM profile suggestions to the customer. new data packages, to prepare and present energy / hardware compliance reports is being configured. Server (3), operator risk of SLA breach, CRM campaign triggers, 20 to provide pre-prepared suggestions for the call center. It is being structured. Industrial Application of the Invention The invention concerns the system (1) eSIM profiles in the electronic device (2) artificial intelligence 25 By analyzing the system, it allows the user to be recommended the most suitable profile. The system (1) takes into account the user’s past data thanks to CRM integration. It receives the information. The user is informed via the call center when necessary. For example, a roaming-advantaged profile for a frequent traveler might offer a data-intensive profile. A broadband profile is recommended for a user using this. 30 Thanks to this system (1), the right choice is available for both individual and corporate customers. The correct eSIM profile is recommended at the right time. Costs arising from choosing the wrong profile. Customer satisfaction decreases, and improves. Additionally, CRM and call center integration is included. Thanks to this, the system goes beyond being just a technical solution and becomes customer experience-focused. It becomes a service. 5 Around these basic concepts, the invention is very much related to the “eSIM Profile Suggestion System (1)”. It is possible to develop various applications, and the invention described herein It cannot be limited to examples; it is essentially as stated in the requests.

Claims

6 REQUESTS 1. eSIM profiles are analyzed using artificial intelligence to provide the most suitable solution for the user. that enables profile recommendations; - Provides eSIM profile suggestions that allow users to use eSIMs. 5 at least one electronic device that allows it to view and make selections (2) and - Internet usage via eSIM (2) on the user's electronic device, voice call frequency, roaming habits, and real-time location data continuous collection, processing of collected data with an artificial intelligence (AI) based model 10 the analysis of user behavior patterns, past profile preferences, and the evaluation of their bills and "an individual user traveling abroad The new profile is presented to users as "roaming-focused eSIM profile recommendation". recommending CRM (Customer Relationship Management) and call center services. with its integration, both individual and corporate customers have been using it for the past 15 years. storing data and recording suggested profile changes the automatic display of AI suggestions on the call center screen the suggestion is forwarded to the operator, via call or SMS / email to the user. automatic notification, company on CRM in the enterprise scenario A "corporate control panel" is created for the official, and from there, which 20 to enable viewing which profile recommendation the employee received a system characterized by containing at least one configured server (3) (1).

2. Users can use eSIM, and transactions can be made on eSIM. allows them to perform these actions and view profile suggestions. eSIM recognized by phone, tablet or portable computer electronic device (2) characterized by any compatible device A system like the one in claim 1 (1). 7 3. Connect to the server (3) using any remote communication protocol. to establish and exchange data with the server (3) through this established connection characterized by an electronic device (2) configured to perform A system like the one in Request 1 or 2 (1).

4. Data exchange with the server (3) using a data bus in the form of the Internet. characterized by an electronic device (2) configured to perform a system like the one in Request 3 (1).

5. Communicate with an electronic device (2) using any communication protocol 10 to establish and to send data via electronic device (2) through this established communication Characterized by the server (3) configured to carry out the transaction. a system like any of the above-mentioned requests (1).

6. eSIM profile data via eSIM (2) on the electronic device, device 15 Usage statistics, network performance logs, CRM customer behavior to ensure the collection of data and call center interaction data from the above requests characterized by the server (3) configured for a system like any other (1).

7. Real-time data stream in Apache Kafka / MQTT format when collecting data. characterized by the server (3) configured to use its protocols a system like any of the above-mentioned requests (1).

8. Timestamping, normalization, and anonymization of the collected data. 25 characterized by the server (3) configured to perform its operations a system like any of the above requests (1).

9. Kalman filter to reduce noise on the collected data. (Kalman Filter), Isolation Forest for data integrity, 30 to determine usage intensity, data consumption patterns, and device priority levels. 8 Using Feature Engineering algorithms from the above requests characterized by the server (3) configured for a system like any other (1).

10. Structured to generate usage profiles from the collected data. in any of the above requests characterized by the server (3) such a system (1).

11. K-Means Clustering (K-) for grouping similar usage profiles Averages (Clustering), 10 key factors in device and customer behavior Principal Component Analysis (PCA) to reveal Analysis), to predict future usage intensities over time. To use Time Series Analysis (ARIMA / LSTM)) from the above requests characterized by the configured server (3) a system like any other (1). 15 12. Prioritization between devices (2) in the dynamic eSIM profile management process Reinforcement learning for dynamic learning The Learning (RL) model is used for different scenarios in the decision-making process. Q-Learning and 20 to generate optimal eSIM profile recommendations. Using Deep Q-Networks (DQN) AI models This allows assigning low-latency connections to critical devices and minimizing others. to delay devices' data consumption until Wi-Fi is available from the above requests characterized by the configured server (3) a system like any other (1). 25 13. CRM and call center integration, tailored to user profiles. Processing newly suggested eSIM profiles, Call Center Natural Language analyzes customer “complaint triggers” in their interactions. Processing (Natural Language Processing – NLP- (BERT / GPT based 30 (models) techniques for analyzing and making dynamic suggestions to electronic devices 9 (2) is characterized by the server (3) configured to display on (2). a system like any of the above-mentioned requests (1).

14. Performing autoencoder-based anomaly detection for attempted theft. 5 of the above requests characterized by the server (3) configured to do so. a system like any other (1).

15. Providing customers with dynamic eSIM profile suggestions and new data packages. structured to prepare and submit energy / equipment compliance reports 10 of the above requests characterized by server (3) such a system (1).

16. Operator risk of SLA violation, CRM campaign triggers, for call center. with the server (3) configured to provide pre-prepared suggestions A system like any of the above characterized claims 15 (1). 25