| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Cirrus Logic |
MODULE COBRANET 1810 CM2 FB |
0 |
|
|
Cirrus Logic |
KIT 32BIT HD AUD DECODER DSP |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8580-6122-FT48-EV1 E |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8761MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
EVAL BOARD 96KHZ DGTL AUD RX |
0 |
|
|
Cirrus Logic |
KIT - WM8196 KIT CDB6109 MB DC |
0 |
|
|
Cirrus Logic |
KIT - WM8152 KIT CDB6109 MB DC |
0 |
|
|
Cirrus Logic |
KIT 32BIT HD AUD DECODER DSP |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8234 MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
KIT - WM8737 KIT CDB6097 MB DC |
0 |
|
|
Cirrus Logic |
KIT 3 CORE CRYSTAL 32 DSP |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8944B MINI EVAL BOAR |
0 |
|
|
Cirrus Logic |
MODULE COBRANET 1810 CM2 MT |
0 |
|
|
Cirrus Logic |
KIT - WM8215 KIT CDB6109 MB DC |
0 |
|
|
Cirrus Logic |
EVAL BOARD FOR CS4391A |
0 |
|
|
Cirrus Logic |
KIT - WM8985 KIT CDB6160 MB DC |
0 |
|
|
Cirrus Logic |
EVAL BD - BASE BRD WM9715/9713/9 |
0 |
|
|
Cirrus Logic |
EVAL BRD LOW PWR HEADPHONE |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8213 MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
ASHETON DAUGHTER BOARD |
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)