Are you into measurements and/or data processing to gain real-time and actionable insights? Then we may have an interesting tool to help you. Our distributed data processing framework is designed specifically for professionals like you who work with measurements from various sources.
This framework enables measurement processing in subsequent blocks (fully synchronized when there are multiple inputs). Processing blocks can run across embedded PCs, servers and desktops, creating a seamless flow of data to create meaning. We recently added seamless execution of trained machine learning models into data flows, to unlock the full potential of your data.
We’d love to hear your ideas and explore how our framework can support your specific use cases. Let’s collaborate to take your measurements, data processing and/or machine learning models to the next level!
Our framework is continually evolving. It initially focused on synchronized electrical measurements, featuring blocks for generating voltage/current/power synchrophasors, FFTs, and harmonic distortions.
But this is just the beginning! Our framework isn’t limited to electrical measurements; it can easily handle inertial data, audio, images, and other time-stamped data.
Key Features:
- Real-Time Distributed Measurement & Processing: Stream your data and generate actionable insights instantly, whether you’re working on edge devices, desktops, (cloud) servers or a combination of them.
- Data storage and analysis: Measurements and outputs can be easily be stored in real-time databases, made accessible through web services, and analysed in dashboards.
- Framework Versatility: Originally geared towards synchronized electrical measurements, our framework can process a wide range of data types, including inertial data, audio, images, and any other time-stamped data.
- ML Inference Block: This powerful component enables real-time execution of machine learning models on live sensor data and outputs from other processing blocks. You can easily perform anomaly detection, pattern recognition, clustering, prediction, and more!
This platform was successfully tested in a number of R&D projects. If you are interested we would love to hear from you.