XAM3500 is a small, secure and cost-effective module that supports many pre-trained AI models. At the heart of the module is K210 from Kendryte. A Dual Core 64bit RISC-V processor with FPU and dedicated CNN accelerator achieving 0.23TOPS under 300mW (module only). With the model embedded the module, a simple API call through one of the many interfaces makes adding AI capabilities to the system an easy task. With the IoT market in mind, security is a priority when designing the XAM3500. Utilizing the Microchip ATECC608A allows us to secure the module when communicating with cloud providers such as AWS and GCP.
Features
- K210: RISC-V Dual Core 64bit, with FPU
- Convolutional Neural Network (CNN)
- Hardware accelerator
- 0.23 TOPS under 1W
- Peripheral interfaces
- GPIO
- I2C
- UART
- SPI
- DVP (camera)
- LCD
- On-chip Security
- Supports Encrypted Firmware
- 128-bit AES Accelerator
- SHA256 Accelerator
- Power Sources
- 5V input
- 3.3V output for IO Voltage
- 1.8V output for IO Voltage
- Dimensions
- 33.02(W) x17.78(L) mm
- Microchip ATECC608A
- Trusted and Secure Authentication
- Amazon AWS and Google GCP
- Secure hardware-based key storage
- Protected storage for up to 16 Keys, certificates or data
- ECDH: FIPS SP800-56A Elliptic Curve
- Diffie-Hellman
- NIST standard P256 elliptic curve support
- SHA-256 & HMAC hash
- AES-128: encrypt/decrypt
- Trusted and Secure Authentication
- Pre-trained model
- Objects Detection (Customizable)
- Face Detection
- Age and Gender Estimation
- Simple voice commands
- Vibration abnormally detection
Documents
Resources
XaLogic GitHub
Kendryte K210 resources
Kendryte GitHub
Development Boards
Raspberry PI AI Hat – XAPIZ3500