| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Analog Devices, Inc. |
BOARD EVAL LTC6995-1 |
2 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD KSZ9031RNX |
48 |
|
 |
TextSpeak |
TEXT TO SPEECH,TTS MULTI-LINGUAL |
100 |
|
 |
Newhaven Display, Intl. |
BREAKOUT 1.69" COLOR OLED GLASS |
87 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPS2556DRB-423 |
6 |
|
 |
Texas Instruments |
MODULE EVAL FOR DRV595 |
8 |
|
 |
IR (Infineon Technologies) |
KIT H-BRIDGE IFX9201 |
64 |
|
 |
Roving Networks / Microchip Technology |
PL485 EVALUATION KIT |
3 |
|
 |
Roving Networks / Microchip Technology |
DEMO BOARD PWR MOD MCP39F511 |
11 |
|
 |
Maxim Integrated |
EVAL KIT OPTO ISO 3.75KV |
119 |
|
 |
APS |
SCR (THYRISTOR) 3-PHASE CONTROL |
50 |
|
 |
Texas Instruments |
DRV8889-Q1EVM |
26 |
|
 |
Freescale Semiconductor, Inc. (NXP Semiconductors) |
BC3770 BOARD WITH FRDM-KL25Z |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL MCP3913 |
1 |
|
 |
IR (Infineon Technologies) |
LITE LDO SBC BOARD |
2 |
|
 |
TDK InvenSense |
EVAL BOARD FOR ICS-52000 |
2 |
|
 |
Touchstone Semiconductor |
KIT DATA ACQUISITION CAPTURE |
5 |
|
 |
Texas Instruments |
EVALUATION BOARD FOR BQ27425 |
4 |
|
 |
EPC |
EVAL BOARD GAN ZVS CLASS D AMP |
6 |
|
 |
Analog Devices, Inc. |
KIT EVAL HMC822LP6CE 2FO |
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)