| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL 1 MP CO-PROCESSOR HB |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCP382HMN15AG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV8712T |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
POWER OVER ETHERNET (POE) POWER |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
PCB MODULE WITH LV8121V |
12 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NTMFS4854NSG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCV74206V1G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NCP380HMU20 LOAD SW |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL SMART CARD INTERFACE |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NB4N527SMN |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVALUATION NCS2563D |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR FUSB303 |
5 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV8136V |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NB6N11SMNG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCN5150SOICG |
6 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD PWR BANK CTLR LC70 |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NCP380LMUAJ LOAD SW |
4 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NB3M8T3910G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCP458RFCT2G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD DAUGHTER I2C STEP DVR SOIC |
6 |
|
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)