| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR HI FREQ 16QFN |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR FAN3240 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR MC33340 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR NCP1653 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD EVALUATION BBG NBSG16BA |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD DEMO SPI STEPPER DRIVER NQ |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD EVALUATION FOR ADT7462 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR ZSPM9015 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT NCN49597PD11G |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD AX-EO01-USB01-868 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR FSAM20SM60A |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
KIT EVAL INDUSTRIAL 3062X FAMILY |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
KIT EVAL FOR S-FSK PLC MODEM |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
NVIDIA VOLTA |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL 2 MP CO-PROCESSOR HB |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR NB3N3011 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
NCP51820GAN2GEVB EVALUATI |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NCP346SN1 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
KIT EVALUATION NCV7052X |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR ADT 7462 |
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)