| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Analog Devices, Inc. |
BOARD EVAL FOR ADF4360-3 |
3 |
|
 |
Analog Devices, Inc. |
BOARD USB DATA COLLECTION |
38 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR ADN4650 |
8 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR ADCMP604 SC70-6 |
1 |
|
 |
Analog Devices, Inc. |
EVALUATION BOARD AD9543 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD HMC783LP6CE |
1 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR LT1373CS8 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR LTC6601-1 |
2 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR ADUM226 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR ADM3051 |
1 |
|
 |
Analog Devices, Inc. |
LTC1569CS8-7 - DC ACCURATE, TUNA |
2 |
|
 |
Analog Devices, Inc. |
DEMO BOARD FOR LTC6948-1 |
5 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR AD9516-3 2.0GHZ |
0 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR LTC3576EUFE |
2 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR AD5172 |
1 |
|
 |
Analog Devices, Inc. |
BOARD EVALUATION FOR ADM1062LF |
3 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR AD2S1200 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD SILICON OSC |
0 |
|
 |
Analog Devices, Inc. |
BOARD DEMO FOR LT3092EDD |
17 |
|
 |
Analog Devices, Inc. |
EVAL BOARD SYNC BOOST DC REG |
25 |
|
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)