| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Intersil (Renesas Electronics America) |
EVAL BOARD 1 DFN |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BRD 1 RTK-251-DRPEVB U/W:R9 |
0 |
|
|
Intersil (Renesas Electronics America) |
ISL94208 EVAL BOARD 1 W/DAUGHTER |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL59110IEZ |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL12058 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVALUATION BOARD FOR ISL59911 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD 1 FOR ISL3333 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD 10LD MSOP |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FO ISL2101010 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FOR X6003 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVALUATION BOARD FOR ISL55143IRZ |
0 |
|
|
Intersil (Renesas Electronics America) |
ISL79985-EVAL EVALUATION BOARD F |
0 |
|
|
Intersil (Renesas Electronics America) |
EVALUATION BOARD GP HIP4083 |
0 |
|
|
Intersil (Renesas Electronics America) |
BOARD USB TO SMBUS INTERFACE |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD ISL12024DB 8SOIC |
0 |
|
|
Intersil (Renesas Electronics America) |
BOARD EVAL 1.25V VREF ISL21090 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL36411DRZ |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD ISL33002 8MSOP |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD 1 FOR ISL6292 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD 8LD SOIC |
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)