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Edge Computing

Industry 4.0 is based on the convergence of OT and IT using modern technologies that are significantly easier to use and faster to deploy in order to extract business value from integrating machine data, shop floor data, enterprise data and cloud applications.

OSIsoft PI System is one of the most widely deployed solutions for capturing and storing machine data within manufacturing, energy, utilities, pharma, transportation and facility management. 

The use of machine learning (ML) models is becoming more and more common in industrial IoT applications, especially for use cases such as anomaly detection and predictive maintenance. ML models are typically trained in the cloud using large stored datasets and iterative processing on powerful servers.

Kepware is one of the leaders in industrial connectivity, by providing drivers for almost any type of machine-level protocol. The main use case is to collect data from machines and deliver it to centralized platforms for analysis - but what if you want to take action on your data already on the factory floor? This is where Crosser comes in.

Using video cameras as sensors in industrial IoT applications is becoming more and more popular. The reason is of course that it opens up for many interesting applications.

Extracting valuable insights out of data collected from machine sensors can be hard, often requiring analyzing data from many sensors in parallel.
Due to the complexity, machine learning (ML) methods are becoming more and more popular to analyze these datasets.

If you are in manufacturing, process industry, oil & gas or other asset-rich industries with many machines & equipment there is a good chance you are thinking about how to leverage this data in a better way. Either to gain insights to improve your processes or for optimizing your maintenance for an improved uptime.

Based on customer requests we have implemented support for running Crosser Edge Streaming Analytics on Azure IoT Edge. Now you can innovate much faster and without the cost, risk and developer dependencies that come with writing code.

Your data scientists are among your most valuable assets. But if you are not making full use of edge analytics then you could be wasting their time.  

Almost everyone that have tried to do some experiments with IoT projects has come across Node-RED, whether this was for a private hobby project or a business application. The reason is of course that Node-RED is a great tool, easy to get started with, large community support and free!

Try Crosser For Free

Start innovating today. How it works:

1. Get an account
2. Log in and start designing your flows in the sandbox
3. Download the Crosser Container to your local test node
4. Test with real data