Internet of Things and Embedded Machine Learning

 

Based on the STMicroelectronics SensorTile development kit, this curriculum provides young engineers and techies with the foundations required to build Internet of Things systems such as wearable consumer devices, wearable medical devices, residential IoT systems, and vehicle IoT systems.

Prepared by:

   Prof. William J. Kaiser, UCLA
 

 

Internet of Things and Embedded Machine Learning Curriculum


These tutorials introduce professional IDEs for embedded systems, the SensorTile device and sensors, along with complete applications including a series of machine learning systems.

 

 

Student projects


Reference designs have been developed by student teams that include novel systems for motion classification with SensorTile data sources and machine learning methods design.

 

 

What is the SensorTile?


The SensorTile is a tiny, square-shaped IoT module engineered for makers packed with powerful processing capabilities, Bluetooth® Low Energy connectivity, a wide spectrum of motion & environmental MEMS sensors, and a microphone.

 

 

App for iOS and Android


The STBLESensor app provides access to all the environmental and motion sensor data from the SensorTile (or other BLE-connected device), including fusion, plot, activity recognition, carry position, acceleration event, BlueVoice, speech-to-text, beamforming, sound source localization, pedometer, switch, motion intensity, compass, cloud logging, node status, and more.

 

 

Resources


Support material for the platform is available for free download.

 

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