- AI convergence training equipment to build a smart home for application implementation and provides connectivity
- Simulation environment that is a scaled-down two-story house to be placed on a table
- Provides HMI with built-in touchscreen to enable sensor and actuator control in GUI environment
- Provides automatic controller that controls light, ventilation fan, door, curtain motor and monitors humidity, harmful gas
- Feedback circuit is configured for all actuators enabling feedforward and feedback control
- Supports cloud and smartphone/tablet connectivity
- Supports AI accelerator to scale up machine learning-based smart home automation
- Low-level and high-level control are possible through MicroPython, Python, Pop plus library
- Provides a user-friendly interface with GUI designed on PySide6
- Supports to implement image processing and classification logic using OpenCV and MediaPipe
- Controlling the device remotely via mobile apps such as Blynk.
- Conditional operation that automatically sets the device to run based on specific condition is possible
- Scenario-based control such as away mode and sleep mode
- Supports data communication encryption using SSL/TLS and MQTT
- Supports 2FA user authentication and authorization management
- Protects sensitive data by encrypting data with AES/KDF
- Supports dashboard and remote monitoring through open source IoT platform, analytics and interactive visualization too