Product overview
Description
The machine learning core (MLC) in STMicroelectronics sensors is an advanced feature that enables machine learning algorithms to run directly on the sensor. This allows for autonomous data processing and decision-making, reducing the need for continuous data transmission to a central processor, thus saving energy and bandwidth.
The MLC can execute decision-tree algorithms directly on the sensor, using configurable nodes defined by "if-then-else" conditions. Input signals, represented by statistical parameters derived from sensor data, are compared against predefined thresholds for real-time processing. The MLC can also generate interrupts for changes in the decision tree's results, allowing for immediate actions based on processed data. By processing data locally, the MLC enhances power efficiency by minimizing communication with the main processor.
Examples and tutorials for the machine learning core feature available on some STMicroelectronics sensors are provided in the STMicroelectronics public GitHub repository.
The repository contains MLC configurations covering various use cases and ready to be used with the sensors. It also contains tutorials describing how to create example solutions using different ST hardware kits and software tools. Further details are available in the README section of the GitHub repository.
-
All features
- Examples and tutorials for the machine learning core feature
- Available in the STMicroelectronics public GitHub repository
