Edge Devices

EDGE COMPUTING AT ITS BEST

DESIGNED FOR X-BRAiN INTEGRATION

BENEFIT FROM OUR X-BRAiN-INTERNAL EDGE CAPABILITIES

Edge computing brings the computational workload closer to the IoT devices that gather the data instead of sending it on a direct way to the cloud-based X-BRAiN instance. By this, latency issues between the IoT devices and the cloud-based X-BRAiN instance can be avoided and companies can save money by reducing the amount of data that needs to be sent and processed in the cloud.

MULTI-ACCESS EDGE COMPUTING & X-BRAiN GATEWAYS

Our portfolio of high-performance edge computing devices is composed of entry and mid level servers (x86) and our unique Google Coral Board. Install them locally on site in order to have a light version of XBRAiN running on premise, along with all the applicable analytics.

ENTRY AND MID-LEVEL APPLIANCES

Use our comprehensive portfolio of high-performance edge computing devices and install them locally for having a light version of X-BRAiN running on-site, along with all the applicable analytics.

Apply local pre-processing and manipulation of data that has been collected by sensors, run machine learning models or accelerate the computational workload. Our devices can also act as 5G anchor in order to enable Ultra Reliable Low Latency Communication (URLLC) or act as X-BRAiN gateway in order to integrate your building infrastructure via industry protocols such as BACnet, Profibus, Modbus and more.

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5G CORAL BOARD

Our in-house developed 4.9 and 5G capable Google Coral Board is combining the abilities of a 5G connectivity enabler and an edge computing device with the possibility to attach peripheral sensor modules for applying advanced 5G use cases like HD video streaming.

Compared to the entry and mid level appliances, the Google Coral Module can be mounted straight on moving devices like drones in the Smart City and Smart Maintenance domain.

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At a Glance

CAPABILITIES & ADVANTAGES

Ultra-Reliable Low-Latency Connectivity (URLLC)

By using our portfolio of edge devices, computational tasks can be performed locally on site without being dependent to the latency of sending the data to the cloud-based X-BRAIN instance.By this, notifications, alerts or other processes can be triggered in real-time, allowing to apply user cases that are heavily dependent on a reliable and fast connection.

Pre-Processing of Data

Our portfolio of edge devices is capable of running advanced computational processes as well as machine learning algorithms directly on the device.By this, pre-processing tasks such as filtering of video material, cleaning of sensor data and masking of images can be applied before sending it to the cloud-based X-BRAiN instance, reducing data size and associated costs.

5G and Edge Computing

5G networks inherit considerable processing power allowing them to independently perform processing tasks that can be underpinned by edge computing capabilities.By this, advanced 5G use cases such as video surveillance using pan-tilt cameras or drones in combination with object detection algorithms can be applied.Additional potential use cases are self driving cars as well as robotics.

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