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.
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.
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.