Ready Models can be deployed quickly onto existing microcontroller (MCU) hardware, such as the PSoC 6, without the cost, time, or expertise that’s required for custom development.
“If you look at the Edge AI space right now, you can probably count on one hand how many companies provide off-the-shelf models for any one solution,” said Sam Al-Attiyah, Head of Customer Success at Imagimob. “Our Ready Models have been thoroughly tested out in the field in different environments, so they are validated in terms of performance. And the fact that we are running them on small edge devices is unique.”
To ensure the robustness of the Ready Models, Imagimob creates a comprehensive list of different scenarios they can encounter, and then test those scenarios. They are also tested in different scenarios all over the world to ensure they work with no bias based on specific geographies or ethnicities.
Finally, field testing on device allows to test and document realistic model performance in an expected hardware setup. The result of all this is a model that does exactly what customers want it to when it's running in their products.
Imagimob is launching four audio-based Ready Models, including Baby Cry for baby monitors, Siren Detection for pedestrians as well as Coughing Detection and Snoring Detection which are both for wearable devices in the medtech and health sectors. Additional models are currently under development within Audio, Radar, IMU (Inertial Measurement Unit) and Capacitive Sensing.
For many companies seeking to upgrade products with smart AI features, up until now, the barriers have proved to be too high. The typical development process for a custom-made ML model not only requires the right software engineering and AI expertise, but also a great investment of time and resources for an extensive development process that spans from collecting, validating, and labelling data, to training models based on that data, deploying them on device, and then testing them in diverse environments to ensure performance expectations are met.
IMAGIMOB Ready Models, by contrast, require no or limited engineering and AI competence to implement. And with all of the development and testing work already put in, they essentially offer a shortcut to the marketplace.
“This is a much easier way for companies to begin their ML journeys – they don’t have to make such a big investment to start using it on their edge devices,” said Anders Hardebring, CEO at Imagimob. “Depending on the skillset and expertise in a company, developing a custom model for production typically takes six months to a year. With our Ready Models, they can have new Edge AI features up and running essentially overnight.”
