| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Texas Instruments |
EVAL MODULE FOR SN65LVDS4 |
21 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR ADP5061CB |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV8702V |
2 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION KSZ8842-16MQL |
4 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR LTC7860 |
1 |
|
 |
Texas Instruments |
DEVELOPMENT DATA ACQUISITION |
74456 |
|
 |
STMicroelectronics |
EVAL BOARD PLC MOD STREET LIGHT |
12 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPS2379-106 |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NS3L500MTG |
0 |
|
 |
Future Designs, Inc. |
RENESAS SYNERGY 7.0" RES TOUCH L |
0 |
|
 |
MaxLinear |
EVAL BOARD FOR XR33053 |
4 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR ADF4108EB1Z |
3 |
|
 |
Marutsuelec |
TOSHIBA TB62261FTAG EVAL BOARD |
5 |
|
 |
Texas Instruments |
BOARD EVAL FOR LMX25311415 |
5 |
|
 |
Maxim Integrated |
EVAL KIT MAX5974C |
17 |
|
 |
Texas Instruments |
EVAL BOARD FOR SN6505B DRIVER |
15 |
|
 |
APS |
SCR (THYRISTOR) 3-PHASE CONTROL |
50 |
|
 |
Texas Instruments |
EVAL MODULE FOR CDCLVC1112 |
5 |
|
 |
Silicon Labs |
BOARD EVAL XO/VCXO I2C PROGRMBL |
7 |
|
 |
Analog Devices, Inc. |
EVALUATION BOARD I.C. |
3 |
|
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)