This lecture focuses on the basic technologies of Embedded Intelligence, e.g., to acquire information from human beings and the environment, to build models with them and applications on top.
- Questions, problems to be solved and examples
- The attributes and application areas of different sensors
- Different signal processing and machine learning methods for different activity recognition tasks
- Keypoints to be considered in building the architecture for activity recognition
- Dynamic sensor configuration
- Performance evaluation