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    Artificial Intelligence & Machine Learning

    DATA HAS A BETTER IDEA

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    INTELLIGENT STEERING
    WITH X-BRAiN

    As a cloud native and big data driven platform, X-BRAiN is steering end to end IoT use cases with its AI and machine learning core. From an architectural point of view, X-BRAiN manages dedicated micro services for each service packet, providing the flexibility to quickly react to changes and to adjust the interaction between each of those services.

    COMBINING AI & ML
    SERVICES AND ALGORITHMS

    The AI and ML services that are used within X-BRAiN are following the same overall principle. By being decoupled from each other, services and dedicated algorithms can be combined in a flexible manner, with respect to the specific use case. Moreover, by having this service mesh in hand, the AI and ML core is actively linked to all X-BRAiN services.

    THE EXPANDABLE
    AI CORE OF X-BRAiN

    The AI core of X-BRAiN benefits from our comprehensive data lakes that are used to train ML based algorithms such as neural networks, in order to perform advanced forecasting tasks based on broad history data. Beside that, X-BRAiN is able to connect to external data sources for applying machine learning capabilities.

    DATA SOURCES

    X-BRAiN is actively gathering and managing a large amount of data that has been collected by IoT devices, using data bases like BigQuery, PostGRES and Co. After performing a GDPR compliant process of ghosting and data anonymization, our AI and ML algorithms are able to train mathematical models and apply advanced forecasting.In overall, X-BRAiN is not limited to its internal data sources. By being able to integrate with external machine learning platforms, X-BRAiN benefits from other established solutions like Google TensorFlow and Co.

    X-BRAiN ANALYSERS

    X-BRAiN Analysers are configurable software packages that are able to detect specific events based on sensor measurements. They can be based on very simple decision rules or on complicated mathematical models. In general, XBRAiN Analysers can be categorised into several groups.Simple threshold analysers can be used for detecting if a report is exceeding or undershooting a predefined limit, geofence analysers are able to detect if an asset is entering or leaving a predefined area, deviation analysers can be used for detecting if reports are deviating compared to expected behaviours and advanced AI and ML analysers can be applied to object detection or pose recognition.X-BRAiN analysers can be actively assigned to a specific IoT device by the user, which is done in the X-BRAiN internal inventory. They are the first step for turning a device smart and are tightly linked to the AI service orchestration service for further processing.

    AI SERVICE ORCHESTRATION
    AND ML ALGORITHMS

    The AI and ML services that are used within X-BRAiN are following the same overall principle. By being decoupled from each other, services and dedicated algorithms can be combined in a flexible manner, with respect to the specific use case. Moreover, by having this service mesh in hand, the AI and ML core is actively linked to all X-BRAiN services.

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