CIRCUIT DEMAND FORECASTING SYSTEM AND METHOD

Abstract

The invention relates to a system and method that analyzes historical data to predict potential demand increases over specific periods and provides advance warnings and recommendations to network teams.

Description

1 TARIFF CIRCUIT DEMAND FORECASTING SYSTEM AND METHOD Technical Area The invention analyzes the circuit requirements of corporate customers in the telecommunications sector. by providing AI-powered predictions and proactive recommendations to network teams. 5 It is related to a system and method that provides this. The invention specifically analyzes historical data to identify potential occurrences in specific periods. predicting demand increases and providing advance warnings and recommendations to network teams. It is related to the system and method. State of the Art 10 Today, it is important for network teams to receive advance warning about potential demand increases. It is extremely important for the following reason: - Maintaining Network Performance: Sudden increases in demand can negatively impact network performance. It can affect and lead to slowdowns or interruptions. Those who receive prior warning Teams can take precautions by anticipating when demand will increase and ensure the network operates efficiently. He can continue his work. - Reducing the Risk of Interruptions: Unexpected increases in demand can lead to service interruptions or This can cause servers to crash. Thanks to early warning, teams can conserve resources. By restructuring, this risk of disruption can be reduced. - Resource Management: Being prepared for increased traffic, allocating server capacity or bandwidth 20 This makes it possible to take resource management measures such as increasing its breadth. This is both This prevents unnecessary strain on both the hardware and software infrastructure. - User Experience: The network's resilience to demand allows users to... It ensures a seamless and trouble-free experience. No slowdowns or Customer satisfaction is maintained as long as there are no disruptions. 25 - Reducing Operational Costs: Solving unexpected problems, This usually requires more costs. Advance warnings allow network teams to... It can reduce costs by enabling preventive maintenance. 2 - For these reasons, network teams need to anticipate and warn about increased demand. to ensure the network operates continuously, reliably and efficiently It is of critical importance. With current technology, the analysis of circuit requirements for corporate clients is generally based on past experiences. This is done through manual processes based on data, and these processes are mostly reactive. This approach is managed in a way that prevents the prediction of sudden demands and the need for resources. This leads to inefficient use and operational bottlenecks. Furthermore, its ability to respond quickly and effectively during unexpected surges in intensity is limited. As a result of the research conducted on this subject, "Data traffic forecast" numbered 2023 / 01830 was obtained. An application titled "automatic scaling system" was found. The study routinely involves 10 In addition to the amount of data collected, external conditions, extraordinary circumstances, and previous events may also affect the data. By using AI models to analyze rising traffic influenced by data trend information. time-based forecasting and prior resource expansion for increasing intensity It is related to a system that enables its implementation. The system involves corporate clients. 15 from an organization that makes predictions and recommendations for the future based on past data It cannot be mentioned. 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. The purpose of the invention is 20 The invention was created by drawing inspiration from existing situations and overcoming the aforementioned drawbacks. It aims to solve the problem. The main purpose of the invention is to provide circuits for corporate customers in the telecommunications sector. By analyzing their needs, it provides AI-powered predictions and supports network teams. The goal is to create a system and method that provides proactive suggestions. 25 Another purpose of the invention is to analyze historical data to identify events that occurred during specific periods. Anticipating potential increases in demand and providing advance warnings to network teams. The goal is to create a system and method that offers suggestions. Another aim of the invention is to ensure the proactive management of resources, Increasing operational efficiency and preventing potential congestion in advance 30 3 The goal is to develop a system and method that provides this. The system anticipates future increases in demand. By making predictions with high accuracy, it reduces operational costs and the customer It increases satisfaction. The invention is used to achieve the purposes described above, in telecommunications. By analyzing the circuit requirements of corporate clients in the sector, 5 AI-powered solutions. It is a system that provides predictions and offers proactive suggestions to network teams. Accordingly system;  Data that collects past cycle requests from users and corporate clients collection module,  The data collected by the aforementioned data collection module is processed by artificial intelligence and / or 10 By analyzing demand increases and changes using machine learning algorithms determining analysis module,  Prediction algorithms for the data analyzed via the aforementioned analysis module operating with and increasing speed in certain customer locations during specific periods The forecasting module, which anticipates that there may be demands, 15  based on predictions made by the aforementioned prediction module A suggestion module that offers preventative proactive solutions to network teams.  Recommendations generated by the aforementioned recommendation module are sent to network teams a notification system that creates the necessary notifications and alarms for transmission and forwards them to the relevant teams. system 20 It includes. The invention also provides a framework for corporate clients in the telecommunications sector. By analyzing their needs, it provides AI-powered predictions and supports network teams. It also includes a method that provides proactive suggestions. Accordingly, the method; 25  A dataset containing past circuit requests and network usage data of corporate customers continuous collection via the collection module  An analysis module for the data collected by the aforementioned data collection module analysis by using artificial intelligence and / or machine learning algorithms By doing this, past demand increases, changes, or patterns can be identified. 30  Prediction module of the data analyzed via the aforementioned analysis module processing by prediction algorithms and identifying which customers at specific periods forecasts that anticipate there may be demands for increased speed in their locations to be carried out, 4  a forecasting module by a recommendation module that can provide regulatory recommendations Based on the predictions made, proactive preventive measures are needed for network teams. offering solutions,  Regarding the suggestions generated by the suggestion module, notifications are sent via the notification system. 5 to be communicated to the teams It includes the steps involved in the process. The structural and characteristic features and all the advantages of the invention are given in the figures below. This becomes clearer thanks to the detailed explanation written with references to these figures. This will be understood as such, and therefore the evaluation will also be based on these forms and detailed explanations. 10 This should be done taking that into consideration. Ways to Help Understand the Discovery Figure 1 shows a schematic representation of the system that is the subject of the invention. Explanation of Part References 1. Data collection module 15 2. Analysis module 3. Prediction module 4. Suggestion module 5. Notification system Detailed Description of Find 20 This detailed explanation describes the preferred system and method for the invention. Their structures are explained solely to facilitate a better understanding of the subject. The invention analyzes the circuit requirements of corporate customers in the telecommunications sector. by providing AI-powered predictions and proactive recommendations to network teams. It is a system that provides. Figure 1 shows a schematic view of the system that is the subject of the invention. 25 This information is provided. Accordingly, the system provides users' and corporate clients' past transactions. data collection module (1) collecting requests, mentioned data collection module (1) The data collected is analyzed using artificial intelligence and / or machine learning algorithms. The analysis module (2) determines the increases and changes in demand by performing the aforementioned analysis The module (2) processes the data analyzed by means of prediction algorithms and specific predicting which customer locations might experience speed increase requests during certain periods forecast module (3), forecasts made by the aforementioned forecast module (3) A suggestion module that proposes preventive proactive solutions to network teams based on (4), 5 The recommendations generated by the mentioned recommendation module (4) are sent to network teams A notification system that creates the necessary notifications and alarms for transmission and forwards them to the relevant teams. (5) includes. The system works on the following principle: 10 With the data collection module (1), past circuits of users and corporate customers Requests are collected through this module. The data collection module (1) collects various from sources (network usage data, customer requests, historical data) It retrieves and stores data (such as density reports, etc.). 15 In the analysis module (2), the collected data is processed by artificial intelligence algorithms and machine learning. The past data is analyzed using learning techniques. The analysis module (2) analyzes the past data. By examining these trends, it identifies increases and changes in demand. For example, during holidays... It identifies the demands for increased speed during these periods and the characteristics of these periods. 20 He / She learns. In the prediction module (3), the analyzed data is processed using a prediction algorithm. The algorithm predicts future potential circuit demands over specific periods. (e.g., holidays, vacations) in which customer locations are speed increase requests 25% It predicts that it is possible. The prediction algorithm is based on the analyzed data. It predicts future demand increases with high accuracy. The suggestion module (4) provides suggestions to network teams based on estimated demands. It develops proactive recommendations. These recommendations aim to prepare for future peak levels. 30 It includes the necessary steps. For example, extra bandwidth in certain regions. The recommendations include ensuring that technical teams are ready in advance. 6 With the notification system (5), the suggestions generated by the suggestion module (4) are notified. Notifications are transmitted to network management and operations teams via the system. It provides sufficient time for teams to prepare in advance. The system is critical. The recommendations should be quick and effective in order to prevent bottlenecks before the periods. It enables transmission in this way. 5 Thanks to this system, the demands of corporate clients are managed proactively. Potential congestion situations are anticipated in advance and necessary precautions are taken, operationally. Costs decrease and customer satisfaction increases.

Claims

7 REQUESTS 1. Analyzing the circuit requirements of corporate customers in the telecommunications sector. by providing AI-powered predictions and proactive solutions to network teams. It is a system that provides suggestions, and its feature is;  Data that collects past circuit requests from users and corporate customers 5 collection module (1),  data collected by the mentioned data collection module (1) by artificial intelligence and / or by analyzing demand increases using machine learning algorithms and Analysis module that determines changes (2),  Predict the data analyzed through the mentioned analysis module (2) 10 It operates with algorithms and monitors which customer locations experience speed increases during specific periods. forecast module (3) which predicts that there may be an increase in demand.  based on the predictions made by the mentioned prediction module (3) Suggestion module that offers preventive proactive solutions to network teams (4),  The recommendations generated by the aforementioned recommendation module (4) are sent to network teams 15 a notification system that creates the necessary notifications and alarms for transmission and forwards them to the relevant teams. system (5) It includes.

2. Analyzing the circuit requirements of corporate customers in the telecommunications sector. 20 by providing AI-powered predictions and proactive solutions to network teams. It is a method that provides suggestions, and its characteristic feature is;  A dataset containing past circuit requests and network usage data of corporate customers Continuous collection via collection module (1),  An analysis of the data collected by the mentioned data collection module (1) 25 artificial intelligence and / or machine learning algorithms by module (2) by analyzing past demand increases, changes or Identifying patterns,  Prediction module of the data analyzed via the mentioned analysis module (2) (3) processing by prediction algorithms and which 30 in certain periods forecasts that anticipate requests for increased speed at customer locations to be carried out, 8  a recommendation module (4) and a forecast module (3) that can offer regulatory recommendations Based on predictions made by [organization name], preventive measures are provided to network teams. offering proactive solutions,  through the notification system (5) of the suggestions generated by the suggestion module (4) forwarded to the relevant teams 5 It includes the steps of the process.

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