Our first session was to give a brief overview of what and why EdgeAI is important. We also discussed generalized pipeline involved with EdgeAI applications. Two demo apps were also shared during the session.
- Offline Processing
- User Privacy & Security
- Low Power / Low Cost
- Portability
As the number of IoT devices are increasing, there is more and more data generated on the user side. Sending this data to cloud and running models there might not be scalable approach when the number of data sources increases. Data and Compute come close together when models are deployed on Edge.
- Inertial Sensor/Environmental Sensor Analytics
- Predictive Maintenance
- Body Monitoring
- Audio Analytics
- Audio Scene Classification
- Audio Event Detection
- Keyword Recognition
- Image Analytics
- Surveillance and Monitoring
- Autonomous Vehicles
- Expression Analysis to improve shopping, advertising, or driving
Here are the general steps considered while desiging EdgeAI applications.
Note that depending on usecase, some blocks might not be necessary.
- 9 axis inertial sensor (accelerometer, gyroscope, magnetometer)
- Humidity, barometric pressure and temperature sensor
- Gesture, proximity, light color/intensity sensor
- Microphone
- Price ~30 USD / ~4000 JPY, Find at Arduino Website
- 64 MHz Clock Speed
- 1 MB Flash Memory
- 256KB SRAM
