| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Nuvoton Technology Corporation America |
COMPACT AUDIO BASE BOARD + NAU84 |
0 |
|
|
Nuvoton Technology Corporation America |
COMPACT AUDIO BASE BRD + NAU8822 |
0 |
|
 |
Nuvoton Technology Corporation America |
BOARD EVAL FOR NAU8812 |
0 |
|
 |
Nuvoton Technology Corporation America |
EVALUATION SYSTEM FOR W681512 |
0 |
|
 |
Nuvoton Technology Corporation America |
KIT DEVELOPMENT FOR W682510 |
0 |
|
 |
Nuvoton Technology Corporation America |
BOARD DEMO FOR ISD3900 |
0 |
|
 |
Nuvoton Technology Corporation America |
USB AUDIO CONTROLLER DEV KIT |
0 |
|
 |
Nuvoton Technology Corporation America |
EVALUATION SYSTEM FOR W681310 |
0 |
|
 |
Nuvoton Technology Corporation America |
KIT DEVELOPMENT FOR W682310 |
0 |
|
 |
Nuvoton Technology Corporation America |
BOARD DEMO FOR ISD3800 |
0 |
|
 |
Nuvoton Technology Corporation America |
KIT DEV/EVAL FOR W6810 |
0 |
|
 |
Nuvoton Technology Corporation America |
EVALUATION SYSTEM FOR W6810 |
0 |
|
 |
Nuvoton Technology Corporation America |
BOARD DEMO FOR ISD15100 |
0 |
|
 |
Nuvoton Technology Corporation America |
BOARD DEMO FOR ISD2360 SOP |
0 |
|
 |
Nuvoton Technology Corporation America |
BOARD DEMO FOR ISD2100 |
0 |
|
|
Nuvoton Technology Corporation America |
EVALUATION SYSTEM FOR ISD5100 |
0 |
|
|
Nuvoton Technology Corporation America |
KIT DEVELOPMENT FOR W681310 |
0 |
|
|
Nuvoton Technology Corporation America |
BOARD DEMO FOR ISD17120 |
0 |
|
|
Nuvoton Technology Corporation America |
KIT DEVELOPMENT FOR W6811 |
0 |
|
|
Nuvoton Technology Corporation America |
DEMO BOARD "PARROT" ISD1000/2500 |
0 |
|
Evaluation and Demonstration Boards and Kits are hardware platforms designed to facilitate the development, testing, and demonstration of electronic systems. They serve as critical tools for engineers and developers to prototype applications, validate designs, and accelerate time-to-market. These boards integrate processors, sensors, communication interfaces, and software ecosystems, enabling rapid experimentation across diverse industries such as IoT, automotive, and industrial automation.
| Type | Functional Features | Application Examples |
|---|---|---|
| Microcontroller Development Boards | Embedded CPUs, GPIOs, integrated peripherals | IoT devices, robotics |
| FPGA Evaluation Boards | Reconfigurable logic, high-speed interfaces | Communication systems, AI accelerators |
| Sensor Expansion Kits | Multi-sensor integration (temperature, motion, etc.) | Smart agriculture, environmental monitoring |
| Wireless Communication Modules | Bluetooth/Wi-Fi/LoRa protocols, antenna interfaces | Connected healthcare, smart cities |
Typical architecture includes: - Processing Units: Microcontrollers, FPGAs, or SoCs - Memory: RAM, Flash, EEPROM - Interfaces: USB, UART, SPI, I2C, Ethernet - Power Management: Regulators, battery connectors - Software Stack: SDKs, device drivers, IDEs Physical designs often feature standardized form factors (e.g., Arduino Uno, Raspberry Pi HATs) for modular expansion.
| Parameter | Description |
|---|---|
| Processor Performance (MHz/GHz) | Determines computational capability |
| Memory Capacity (RAM/Flash) | Affects program complexity and data storage |
| Interface Types | Dictates peripheral compatibility |
| Power Consumption (mW/MHz) | Critical for battery-operated devices |
| Operating Temperature (-40 C to +85 C) | Defines environmental durability |
- Internet of Things (IoT): Smart home controllers, edge AI nodes - Automotive: ADAS sensor fusion platforms - Industrial Automation: PLC controllers, predictive maintenance systems - Consumer Electronics: Wearables, AR/VR prototypes
| Manufacturer | Representative Products |
|---|---|
| STMicroelectronics | STM32 Nucleo Series, SensorTile Kit |
| Intel | Intel Edison, Movidius Neural Compute Stick |
| Xilinx | Zynq UltraScale+ MPSoC Evaluation Kit |
| Arduino | Arduino MKR Series, Nano 33 IoT |
Key considerations: 1. Match processor capabilities to application complexity 2. Verify interface compatibility with target peripherals 3. Assess software ecosystem maturity (e.g., ROS support) 4. Evaluate power budget requirements 5. Consider long-term availability and community support
- Growing adoption of RISC-V-based evaluation platforms - Integration of AI/ML accelerators in edge computing boards - Expansion of open-source hardware ecosystems - Increased focus on energy-efficient architectures for IoT - Standardization of form factors (e.g., SparkFun's Qwiic system)