Systems and methods for transportable cellular networks

    公开(公告)号:US12047787B2

    公开(公告)日:2024-07-23

    申请号:US17735844

    申请日:2022-05-03

    CPC classification number: H04W16/24 H04W84/005

    Abstract: A system for providing temporary, transportable cellular communications networks is disclosed. The system includes at least one mobile base station and a control system. The mobile base station can include an aerial vehicular base station with a frame and propellers mounted on the frame that enable flight of the aerial vehicular base station while the control system is configured to control the flight path and functioning of the aerial vehicular base station. The aerial vehicular base station includes hardware and software components for providing cellular network coverage for short ranges. The control system determines the safe flight path for the aerial vehicular base station to reach a service location to provide cellular network coverage. The aerial vehicular base station identifies the closest base stations and available spectrum at the service location to provide communication services for the user equipment at the service location.

    Artificial intelligence based solution generator

    公开(公告)号:US11176470B2

    公开(公告)日:2021-11-16

    申请号:US16028939

    申请日:2018-07-06

    Abstract: A solution generation and planning system uses Artificial Intelligence (AI) techniques such as machine learning (ML) data models, predictive analytics and natural language processing (NLP) techniques for generating outputs to aid decision making in the domain of public infrastructure development. The problem statement is analyzed using the NLP techniques to generate word tokens which are employed in identifying issues that aid in selection of appropriate data sources from a plurality of discrete data sources. In addition, data models trained to produce probable solutions for the issue are also selected. The probable solutions are presented to the user who selects one of the probable solutions for implementation. Feedback from the implementation is also incorporated so that the data models are updated per the latest information obtained from the implementation of the user-selected solution.

    MANAGEMENT OF EXTRACT TRANSFORM LOAD (ETL) JOBS VIA A MODEL THAT IS BASED ON A BAYESIAN NETWORK

    公开(公告)号:US20200004863A1

    公开(公告)日:2020-01-02

    申请号:US16024091

    申请日:2018-06-29

    Abstract: A device may receive, from a user device, a request for a set of forecasts of an extract transform load (ETL) completion time for a group of ETL jobs associated with an organization. The device may obtain a set of performance indicators associated with the group of ETL jobs. The device may filter the set of performance indicators using one or more filtering techniques. The device may generate the set of forecasts of the ETL completion time by using a data model to process the set of performance indicators and/or a set of assumptions associated with a set of recommendations for reducing the ETL completion time. The device may provide the set of forecasts of the ETL completion time to the user device. The device may perform one or more actions that cause the ETL system to execute the group of ETL jobs within a threshold completion time.

    Predicting performance of a network order fulfillment system

    公开(公告)号:US11502894B2

    公开(公告)日:2022-11-15

    申请号:US17094491

    申请日:2020-11-10

    Abstract: A system may monitor transaction data pertaining to a plurality of transaction types received by a network order fulfillment system. The system may classify the transaction data into a plurality of alarm types based on pre-defined impact of an alarm type to a given transaction type. The system may analyze a plurality of performance parameters influencing a performance of the network order fulfillment system, and identify a performance parameter exhibiting an anomaly based on historical data, a current status of the plurality of the performance parameters and a predefined prediction model. The system may ascertain whether the identified performance parameter negatively impacts the performance of the network order fulfillment system, based on evaluation rules. The system may proactively implement a remediation action to remediate a potential fault caused by the identified performance parameter when the identified performance parameter negatively impacts the performance of the network order fulfillment system.

    Management of extract transform load (ETL) jobs via a model that is based on a bayesian network

    公开(公告)号:US10936614B2

    公开(公告)日:2021-03-02

    申请号:US16024091

    申请日:2018-06-29

    Abstract: A device may receive, from a user device, a request for a set of forecasts of an extract transform load (ETL) completion time for a group of ETL jobs associated with an organization. The device may obtain a set of performance indicators associated with the group of ETL jobs. The device may filter the set of performance indicators using one or more filtering techniques. The device may generate the set of forecasts of the ETL completion time by using a data model to process the set of performance indicators and/or a set of assumptions associated with a set of recommendations for reducing the ETL completion time. The device may provide the set of forecasts of the ETL completion time to the user device. The device may perform one or more actions that cause the ETL system to execute the group of ETL jobs within a threshold completion time.

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