| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Analog Devices, Inc. |
BOARD EVAL FOR LT3650EDD |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR CN0292-SDZ |
0 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR ADM1260 |
0 |
|
 |
Analog Devices, Inc. |
LTC2972 DEMO BOARD |
2 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR AD5254 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR CN0216 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD VID DECODR ADV7281-MA |
3 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR AD9525 |
0 |
|
 |
Analog Devices, Inc. |
EVAL MODULE FOR ADP1050 |
0 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR HMC855LC5 |
0 |
|
 |
Analog Devices, Inc. |
DEMO BOARD FOR LTM2889-5 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD HMC778LP6CE |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD RMS TO DC CONVERTER |
28 |
|
 |
Analog Devices, Inc. |
LTC4331 QUIKEVAL EXTENDER BOARD |
13 |
|
 |
Analog Devices, Inc. |
LTC4238 DEMO BOARD - HSSS MODE, |
4 |
|
 |
Analog Devices, Inc. |
EVAL MONITOR CIRCUIT FRONT END |
0 |
|
 |
Analog Devices, Inc. |
EVAL BOARD PLL CLOCK GEN AD9554 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR AD5592 |
16 |
|
 |
Analog Devices, Inc. |
LT4256-2 DEMOBOARD - POSITIVE HI |
8 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR ADF4156 |
1 |
|
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)