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Making Big Data Small and Relevant

Edge Analytics software allows data produced by sensor-rich assets like machines, equipment and devices to be pre-processed in real-time closer to where it is created. 

There are several technical and business drivers and benefits with Crosser Edge Analytics architecture, including:

Cost Savings

Significant data reduction by removing dirty data and irrelevant data. Get significant cloud, analytics and network connectivity cost savings.

Innovate with More Data

Edge Analytics allows you to collect more data points without increasing your cost of data. More data - more innovation possibilities.

Transform Raw Data to Insights

Collect raw data, transform it, analyze it and act on the insights in real-time.

Local Intelligence and Automation

Run local triggers between machines or PLC’s with ultra-low latency. Runs autonomously without cloud connectivity.

Typical Deployment Scenarios

Crosser IoT Edge Analytics Overview

Edge

The Edge Analytics software is deployed on a IoT gateway on a remote unit, or embedded, and processes the sensor data from that single unit.

Field Edge Aggregation

Also called Fog Computing. The Edge Analytics software is typically deployed on an IoT gateway and processes the sensor data from multiple field units.

On-Premise Edge

Typically on a factory shop floor or building with multiple machines. The Edge Analytics software is installed on a server/virtual machine and processes sensor data from multiple on-premise machines and data sources.

Business case objectives and use-cases

Edge Analytics is a key layer in the Industrial IoT or Industry4.0 technology stack. Smart and cost efficient data collection and analytics is a fundamental part.

Business case objectives includes:

Crosser IoT Edge Business Drivers

The main use-cases to achieve this are:

Condition Monitoring

Predictive Maintenance

Industrial Process Optimization

Asset Performance Management

Read more about how our customers engage IoT Edge Use Cases →

No data. No party.

Getting access to relevant data in a central location,
either cloud or data center, is the fundamental starting-point
to enable these main use-cases and meet the business objectives.

Crosser Edge Analytics solution is purpose-built to address
the key challenges for Industrial IoT, including:

Crosser Factory Floor Challenges Overview

Factory floor challenges

  • High number of sensor tags - constant changes
  • Many data sources: PLC, DCS, MES, Historians and databases
  • Many protocols: OPC, Modbus, MQTT, SCADA and more
  • Separated networks 
  • OT and IT team collaboration

Explore use-cases →

Condition Monitoring - Remote Assets Challenges

Remote assets challenges

  • Moving from basic telemetry to monitoring all subcomponent
  • How to collect more data but transfer less?
  • Limited and costly connectivity
  • Unreliable and intermittent connectivity
  • Managing large volume of assets
  • Inside customer firewalls

Bring Your Own AI - Edge MLOps made Easy

Bring, Manage and Deploy your own ML models with Crosser Edge MLOps functionality:

  • The Crosser Edge Node is open to run any ML framework
  • Central Resource Library for your trained models in Crosser Cloud
  • Drag-and-drop for all other steps in the data pipeline
  • One operation to deploy ML models to any number of Edge Nodes

Learn more about Edge MLOps →

Crosser for Azure

Run Crosser with your favourite Azure service, or any other cloud.

  • Edge Analytics for Azure
  • Edge Analytics for Azure IoT Edge
  • On-Premise Streaming Analytics for Azure Stack
  • Cloud Streaming Analytics on your Azure VM

Read more about Crosser for Microsoft Azure →

Read more about Crosser for other Cloud & IoT Platforms →  

Start Innovating Today

Try Crosser for Free

Sign up for a free trial account. Design and deploy your first Flows today.

  1. Sign up
  2. Login and start designing your data flows
  3. Run the flow in Crosser test environment or download local test node
  4. Test with real data

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