We offer advanced machine learning techniques that can run on the edge, enabling real-time and accurate analysis of sensor and image data, utilizing IoT-to-Cloud communications to automate data collection and model training in the cloud.

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Data collection and processing

Data collection is the first crucial step to any machine learning project. We leverage IoT-to-Cloud communications to automate data collection, making it easier and more efficient.

Optimisation and deployment to edge device

Our solutions utilize cutting-edge tools such as TensorFlow Lite Micro to optimize our trained models for deployment on microcontrollers, while utilizing FPGA-vendor toolchains or hand-coded RTL for FPGA implementations.

Edge inference

The optimized model is deployed to the edge device, where it can run in real-time and provide accurate and efficient analysis of electronic device wear, sensor, and image data.

Contact us to learn how our machine learning techniques can be tailored to improve real-time sensor and image analysis for your application.

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