AI-Powered Device Capabilities: Automatic Detection and Dynamic Operation Method

Abstract

The invention relates to an AI-powered device capability automation and dynamic operation method used in telecommunication networks for device inventory management, marketing segmentation, and network resource optimization processes. It involves automatically extracting LTE (Long-Term Evolution) Category (Cat) values ​​of subscriber devices from official sources using artificial intelligence and taking proactive actions (campaigns, technical profile updates, etc.) based on this data.

Description

1 TARIFF AI-Powered Device Capabilities: Automatic Detection and Dynamic Operation Method Technical Area The invention relates to device inventory management and marketing in telecommunication networks. In the segmentation and network resource optimization processes of subscriber devices using LTE (Long-Term Evolution) Artificial Category (Cat) values automatic extraction of intelligence from official sources and proactive action based on this data artificial intelligence used to take actions (campaigns, technical profile updates, etc.) The intelligence-assisted device capability relates to automatic detection and dynamic operation methods. 10 State of the Art Today, device inventory management and marketing in telecommunication networks. In the segmentation and network resource optimization processes, subscriber devices are classified as LTE. capabilities, GSMA (GSM Association®) or global TAC (Type Allocation Code / Tip The allocation code is tracked using static lists retrieved from databases. The technique here is 15. The problem is that the technical specifications of newly released or niche brand devices don't match global data. Delayed or incomplete reflection in their databases (only the model name is available, no category information) This involves entering the device. This situation allows the operator to correctly access devices with high-speed capabilities. inability to segment, assigning a low-speed profile to the wrong subscriber, or high-speed This prevents the offering of suitable package deals to owners of high-performance devices. 20 In conclusion, due to the negative aspects described above and the current solutions being the subject of discussion... Due to its shortcomings, an improvement is needed in the relevant technical field. It has been made. Purpose of the Invention The invention was created by drawing inspiration from existing situations and addressing the aforementioned drawbacks. 25 It aims to solve the problem. The main purpose of the invention is to enable devices to be controlled via artificial intelligence (AI Web Agent). manufacturers' official websites, technical specification sheets, and certifications organizations (FCC (Federal Communications Commission)) 2 (etc.) by scanning and instantly or periodically updating the LTE Cat (LTE category) value of the relevant device model. The goal is to develop a method that captures data in this way. The data obtained is processed using natural language processing (NLP). Normalized using Natural Language Processing and integrated into internal databases. This is done, and automatic actions are triggered that are appropriate to the device's technical capabilities. The structural and characteristic features and all the advantages of the invention are given in the figures and 5 below. This becomes clearer thanks to the detailed explanation written with references to these figures. This will be understood, and therefore the evaluation should also take these forms and detailed explanations into consideration. It needs to be done by taking precautions. Figures that will help understand the invention. Figure 1 shows the elements that enable the realization of the method described in the invention. It is a representative drawing that shows the relationship between them. Explanation of Part References 1. External data sources 2. Operator device database 3. Network coverage data 15 4. AI agent server 5. Device capability module 6. Data retrieval and extraction module 7. Data validation and normalization module 8. Decision and matching engine 20 9. Action Output Interface Detailed Description of the Invention In this detailed explanation, the preferred configurations of the method in question are described only. This is explained to facilitate a better understanding of the subject. The elements that enabled the realization of the method described in the invention are: 25 3 - external data sources (1) - operator device database (2) - network coverage data (3) - AI agent server (4) - device competency module (5) 5 - data retrieval and extraction module (6) - Data validation and normalization module (7) - decision and matching engine (8) and - is the action output interface (9). External data sources (1), official technical specifications of device manufacturers (Apple®, Samsung® etc.) 10 These are the pages. In the operator device database (2), mobile GSM operator (For example: Turkish This page contains the TAC and model information of active subscriber devices within Telekom®. Network coverage data (3) is a dataset that includes regional 4.5G / 5G capacity and speed limits. AI agent server (4) high capacity web browsing and text analysis It is the processing unit. Device capability module (5), data retrieval and extraction module (6), data 15 Main module including verification and normalization module (7) and decision and matching engine (8) It is the software layer. Data retrieval and extraction module (6), LTE category from official sites. It is the unit that finds information and processes unstructured text. Data validation and normalization module (7) checks and standardizes the consistency of the extracted data It is an algorithm. The decision and matching engine (8) determines the device capability and subscriber needs or 20 It is the engine that matches the network limit. Action output interface (9), automatic SMS the delivery, network speed profile update, or sales report It is the interface through which it is presented. The steps involved in the invention are as follows:  TAC and 25 of the active subscriber devices in the operator device database (2) Identifying device models that lack LTE category information from their model data.  by the AI ​​agent server (4) for the specified device models, the device using model names as keywords for external data sources (1) scanning,  via the data extraction and debugging module (6) in the device competency module (5), 30 Formal technical specifications containing tables or text, with external data sources (1) LTE category data and download and upload category data from their pages sorting, 4  Processing the extracted data into the operator device database (2) and device competency with the data validation and normalization module (7) in the module (5) a numerical conversion into value  by the decision and matching engine (8) in the device competency module (5), digital Thanks to this data converted into value, network coverage data (3) and subscriber 5 device capabilities are taken into account (this data allows, for example, the network's 4x4 MIMO In a region that supports Multiple Input Multiple Output, Subscribers whose devices are compatible with this technology (Category 16 and above) will automatically (identified) determining appropriate actions on a subscriber basis and special offers SMS sending including presentation, network speed profile update, sales report 10 At least one of the submission actions is sent via the action output interface (9) triggering. The method described in the invention will result in a special offer that will provide subscribers with a higher speed experience. Offers or technical updates are communicated instantly. The method described in this invention utilizes the following elements / features: 15  AI Web Scraper / Agent: Dynamic Large Language Model (LLM) extracts technical data from web pages. Model-based agents.  NLP (Natural Language Processing) Normalization: Different The writing formats (e.g., "Category 16", "Cat. 16", "DL 1Gbps") are standard digital 20 A model that converts data.  IMEI / TAC Mapping (IMEI-TAC Matching): The process of matching the retrieved data with the operator's subscriber information. Matching with the device list.

Claims

REQUESTS 1. Automatic LTE category information of subscriber devices in telecommunication networks. to be determined as such and dynamic operational actions based on this information AI-powered device capability for creation of automatic detection and It is a dynamic operation method and its characteristic is; 5  TAC of active subscriber devices in the operator device database (2) Identifying device models that lack LTE category information from their model data.  by the AI ​​agent server (4) for the specified device models, the device using model names as keywords for external data sources (1) scanning, 10  via the data extraction and debugging module (6) in the device competency module (5), Formal technical specifications containing tables or text, with external data sources (1) LTE category data and download and upload category data from their pages sorting,  Processing the extracted data into the operator device database (2) and device competency 15 with the data validation and normalization module (7) in the module (5) a numerical conversion into value  by the decision and matching engine (8) in the device competency module (5), digital Thanks to this data which is converted into value, network coverage data (3) and subscriber Determining appropriate actions on a subscriber basis, taking into account device capabilities. 20 SMS messages containing special offer presentations, network speed profile updates, At least one of the sales report submission actions action output interface (9) triggered via It includes the steps of the process.

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