DATA SOURCE CORRELATION TECHNIQUES FOR MACHINE LEARNING AND CONVOLUTIONAL NEURAL MODELS

    公开(公告)号:US20240249170A1

    公开(公告)日:2024-07-25

    申请号:US18626244

    申请日:2024-04-03

    CPC classification number: G06N7/01 G06N20/00

    Abstract: A data model computing device receives a first data model with a first set of attributes, a first margin of error, a first set of predictions, and an underlying data set. Subsequently, the data model computing device receives a second data model with a second set of attributes, as the test data for a machine learning module. Based on the first and second data model, the machine learning function generates a second set of predictions and a second margin of error. The data model computing device performs a statistical analysis on the first and second set of predictions and the first and second margin of error to determine if the second set of predictions converge with the first set of predictions and second margin of error is narrower than the first margin of error, to determine if the second data model improves the prediction results of the machine learning module.

    SERVER-SIDE REMEDIATION FOR INCOMING SENSOR DATA

    公开(公告)号:US20240086274A1

    公开(公告)日:2024-03-14

    申请号:US17944791

    申请日:2022-09-14

    CPC classification number: G06F11/0793 G06F11/0721

    Abstract: Incoming sensor data from a data collection device may be received at the data processing platform that includes the plurality of data processing microservices. A data processing microservice of the data processing platform may detect that the incoming sensor data from the data collection device caused an error. As a result, the incoming sensor data may be queued in a faulty data cache of the data processing platform. Subsequently, at least one of the data processing microservice or the incoming sensor data stored in the faulty data cache may be modified such that the incoming sensor data is processed by the data processing microservice without the error. Following the processing, the incoming sensor data may be deleted from the faulty data queue of the data processing platform.

    PROVIDING ALTERNATE COMMUNICATION PROXIES FOR MEDIA COLLECTION DEVICES

    公开(公告)号:US20220400364A1

    公开(公告)日:2022-12-15

    申请号:US17344781

    申请日:2021-06-10

    Abstract: Described herein are techniques that may be used to facilitate interactions between a media collection device and a remote computing device via the use of a proxy device. Such techniques may comprise establishing a first communication session between a media collection device and a proxy device via a short-range communication channel, transmitting, by the media collection device to the proxy device, status information via the first communication session, at least a portion of the status information subsequently forwarded by the proxy device to a remote computing device, determining that the media collection device is to be activated, upon determining that the media collection device is to be activated, establishing a second communication session between the media collection device and the remote computing device via a long-range communication channel, and transmitting, by the media collection device to the computing device, media content via the second communication session.

    AUTOMATED CORRELATION OF MEDIA DATA TO EVENTS

    公开(公告)号:US20220377282A1

    公开(公告)日:2022-11-24

    申请号:US17328283

    申请日:2021-05-24

    Abstract: Described herein are techniques that may be used to automatically correlate a portion of a media data to an event. Such techniques may comprise receiving, from one or more data sources, at least one media data associated with a first time and a first location. The techniques may further comprise receiving an indication of an event associated with a second time and a second location and determining whether a geographic proximity between the first location and the second location is within a threshold distance. Upon determining the geographic proximity is within the threshold distance, the techniques may further comprise determining a portion of the at least one media data for which a temporal proximity is within a threshold timeframe, and upon determining the temporal proximity is within the threshold timeframe, creating a correlation between the at least one media data and the event.

    SAFETY DETECTION CONTROLLER
    16.
    发明申请

    公开(公告)号:US20220174454A1

    公开(公告)日:2022-06-02

    申请号:US17107764

    申请日:2020-11-30

    Abstract: This disclosure describes techniques that enable a safety detection controller to analyze and infer a likelihood of a safety concern impacting a monitored individual at a real-time event. More specifically, a safety detection controller may receive sensor data from a monitored device associated with a particular individual. The sensor data may be captured from the environment that is proximate to the monitored device. The safety detection controller is further configured to analyze the sensor data to infer the identities of third-party individuals proximate to the monitored device and determine whether those individuals pose a safety concern to the monitored individual.

    DATA SOURCE CORRELATION TECHNIQUES FOR MACHINE LEARNING AND CONVOLUTIONAL NEURAL MODELS

    公开(公告)号:US20220172087A1

    公开(公告)日:2022-06-02

    申请号:US17107865

    申请日:2020-11-30

    Abstract: A data model computing device receives a first data model with a first set of attributes, a first margin of error, a first set of predictions, and an underlying data set. Subsequently, the data model computing device receives a second data model with a second set of attributes, as the test data for a machine learning module. Based on the first and second data model, the machine learning function generates a second set of predictions and a second margin of error. The data model computing device performs a statistical analysis on the first and second set of predictions and the first and second margin of error to determine if the second set of predictions converge with the first set of predictions and second margin of error is narrower than the first margin of error, to determine if the second data model improves the prediction results of the machine learning module.

    SENTIMENT ANALYSIS FOR SITUATIONAL AWARENESS

    公开(公告)号:US20220171969A1

    公开(公告)日:2022-06-02

    申请号:US17107824

    申请日:2020-11-30

    Abstract: A Network Operation Center may receive video data, sensor data and third-party data for a situation that a police officer or security service personnel has been called to. Using the video data, a sentiment analysis engine may generate a sentiment data file that contains the sentiment of at least one individual involved in the situation. Using the video data, sensor data, third party data and the sentiment data file, the sentiment analysis engine may generate a safety quality value for the situation. Subsequently, the safety quality value is compared to a predetermined sentiment value to establish a safety rating and confidence interval for the situation. Furthermore, the sentiment analysis engine may generate a situational awareness file, that contains the safety rating and confidence interval, and route it to the field computing device of the officer for evaluation and implementation.

    CHOOSING RELATED ASSETS FOR AN ASSET BUCKET

    公开(公告)号:US20240370960A1

    公开(公告)日:2024-11-07

    申请号:US18143987

    申请日:2023-05-05

    Abstract: This disclosure describes techniques for implementing an asset bucket on user devices for organizing assets in a database. Assets may include, without limitation, stored multimedia data from various sources, grouped multimedia data, events, conditions, parameters, environmental data, and other data or telemetry data that are stored in a network operating center (NOC) server database or a third-party database. The asset bucket may include a persistent working space that can be rendered as a pane on a device's user interface for organizing assets that can be selected from a rendered window or windows on the device's user interface and/or directly inputted on the persistent working space. By configuring the asset bucket to facilitate performance of actions on the selected assets, the asset bucket may improve generation of reports on these selected assets.

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