| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Intersil (Renesas Electronics America) |
KIT EVAL FOR ISL78226 |
0 |
|
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Intersil (Renesas Electronics America) |
EVALUATION BOARD 2 ISL6292 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL6730C |
0 |
|
|
Intersil (Renesas Electronics America) |
ISL55100B EVAL BOARD |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD ADC DAUGHTER CARD |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD 1 FOR ISL45042 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD ISL12008DBEV1Z |
0 |
|
|
Intersil (Renesas Electronics America) |
EVALUATION BOARD FOR ISL54210 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD |
1 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL54405 |
0 |
|
|
Intersil (Renesas Electronics America) |
ISL95852EVAL1Z BOARD 1, 1+1+1 CO |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD 1 FOR ISL88031 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD 1 FOR ISL88021/22 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVALUATION BOARD FOR ISL54065 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVALUATION BOARD FOR ISL54214 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL22102IR20Z |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BOARD LCD CONTROLLER |
0 |
|
|
Intersil (Renesas Electronics America) |
BOARD EVAL TW8820-LA1-CR |
0 |
|
|
Intersil (Renesas Electronics America) |
EVALUATION BOARD 1 ISL6298 |
0 |
|
|
Intersil (Renesas Electronics America) |
EVAL BRD FOR R9A02G011 ISL95538B |
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)