We are thrilled to announce that BrickML has won "Best Sensor Product of the Year" at tinyML Summit 2023! This is a huge honor for us, and we are grateful to the judges for recognizing BrickML’s innovative technology.
Designed and built in conjunction with Reloc, BrickML is a low-power, high-performance embedded device designed to run machine learning inferences at the edge in industry settings. It is specifically built to be plug-and-play, making it quick and easy to implement. Simply connect BrickML to motors, pumps, or other machinery, seamlessly collect data, train the model, and then deploy the model back into the BrickML device to measure machine health and create immediate actionable insights.
BrickML utilizes all relevant hardware and software aspects of Edge Impulse’s own Industrial Monitoring reference design. Its industrial-grade, waterproof and dust-proof housing incorporates the compute, sensors, and connectivity required for a typical end-point industrial monitoring device. BrickML is fully integrated into Edge Impulse’s industry-leading edge ML platform, allowing for easy addition of advanced AI algorithms. This minimizes development time and accelerates time to market by providing customers with both a highly integrated flexible kit for custom development as well as ready-to-use fully trained edge ML models.
“This is a very exciting innovation, because when we talk about TinyML, we’re talking about embedding the actual sensors into the endpoints to really save on energy,” said award presenter Adam Fuks. “It has huge potential for adoption and impact as a product.”
BrickML can be used for a variety of applications, including:
- Embedded machine learning
- Inference at the edge
- Anomaly detection
- Voice and sound classification
- Motor current signal analysis
- Environmental condition analysis
- Connected intelligent sensors
BrickML will be available very soon from Mouser; we are excited to see how it will be used to solve real-world problems and improve the efficiency and reliability of industrial machinery.