Introduction to embedded systems for IoT
Based on the B-U585I-IOT02A Discovery kit, this curriculum provides engineers and techies with hands-on experience to build Internet of Things systems such as wearable consumer devices, wearable medical devices, residential IoT systems, and vehicle IoT systems.
The tutorials presented by Prof. William J. Kaiser, UCLA, guides you through a full embedded system development journey: getting familiar with STM32CubeIDE, experimenting with real-time sensor data, and building applications leveraging AI at the edge.
Prerequisites
Hardware:
Software:
What you'll learn
- Introduction to STM32CubeIDE for Windows or Mac
- Sensor system signal acquisition, event detection, and configuration
- Accelerometer sensor systems with orientation and motion pattern recognition
- Machine Learning for IoT
- Motion recognition by Machine Learning
- Motion pattern recognition with rotation angle sensing and Machine Learning
- Motion pattern recognition by inertial sensing and Machine Learning for IoT
Ready to get started?
The curriculum is compiled into a single .pdf and can be accessed by clicking here or by using the links above if you'd like to access individual parts.
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