| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Analog Devices, Inc. |
KIT EVAL CLOCK GENERATOR HMC1033 |
0 |
|
 |
Analog Devices, Inc. |
BOARD EVALUATION FOR ADG904 |
0 |
|
 |
Analog Devices, Inc. |
KIT MICRO EVALUATION ADM1186-2 |
0 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR ADF5355SD1Z |
16 |
|
 |
Analog Devices, Inc. |
EVAL BOARD LTC6993-4 |
2 |
|
 |
Analog Devices, Inc. |
DEMO BOARD FOR LTC4365 |
3 |
|
 |
Analog Devices, Inc. |
EVAL BOARD HMC828LP6CE |
0 |
|
 |
Analog Devices, Inc. |
DEMO BOARD LTC4236-1 |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD ADE78XXA ENERGY METER |
1 |
|
 |
Analog Devices, Inc. |
LTC7003EMSE DEMO BOARD PROTECTED |
12 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR LTC4370 |
16 |
|
 |
Analog Devices, Inc. |
LTC6908-1 SILICON OSCILLATOR DEM |
5 |
|
 |
Analog Devices, Inc. |
ADVANCED ACTIVE LEARNING MODULE |
1052 |
|
 |
Analog Devices, Inc. |
EVAL MODULE ACTIVE LEARNING |
751 |
|
 |
Analog Devices, Inc. |
BOARD EVALUATION FOR ADM1185 |
0 |
|
 |
Analog Devices, Inc. |
EVAL BOARD HMC674LC3C |
0 |
|
 |
Analog Devices, Inc. |
EVAL BOARD HMC821LP6CE |
0 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR AD9508 |
3 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR LTC4075EDD |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD HMC856LC5 |
10 |
|
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)