| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV8711T |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NB3H5150MNG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD DAUGHTER LIN STEP DVR SOIC |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NB6L14MMNG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
MARS TI933 SERIALIZER BOA |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV8805SV |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NB4L16MMN |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
MULTI-SENSE |
13 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NB3L208KMNG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NB3N65027 CLK SYNTH |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD DEMO SPI ST DRIVER VREG NQ |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NCP5104BA36WG |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCP382HMN20AG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
NIS6350MT1 EVAL BOARD |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
PCB MODULE WITH LV8714TA |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVALUATION BOARD ADT7462 |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
REFERENCE DESIGN PCBA FOR |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR STK984-190-E |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD IMAGE SENSOR |
0 |
|
|
Sanyo Semiconductor/ON Semiconductor |
EVALUATION BOARD ADT7473 |
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)