| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
MODULE ADAPTER BOARD XM3 - 1200V |
7 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL FOR MCP401X |
2 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL FOR PIC18F87J72 |
2 |
|
 |
Roving Networks / Microchip Technology |
ATMXT1665 SPI DEVELOPMENT BOARD |
4 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO LIN SBC FOR ATA6623 |
0 |
|
 |
Roving Networks / Microchip Technology |
STARTER KIT SMARTFUSION2 SOC |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT DEV TOUCH PAD LP PROJ CAP |
3 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION KIT WITH I2C PCB |
1 |
|
 |
Roving Networks / Microchip Technology |
DEMO BOARD FOR MCP73871 |
4 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL FOR MCP73837/8 |
1 |
|
 |
Roving Networks / Microchip Technology |
SERIAL MEMORY SINGLE-WIRE EVALUA |
16 |
|
 |
Roving Networks / Microchip Technology |
CRYPTOAUTHENTICATION XPLAIND PRO |
86 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO FOR MCP3421 |
1 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEV SPI SRAM PICTAIL |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL MCP3914 |
0 |
|
 |
Roving Networks / Microchip Technology |
DSPICDEM MCHV-2 DEV SYSTEM |
2 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO LCD GPIO EXP KEYPAD |
3 |
|
 |
Roving Networks / Microchip Technology |
ATMXT1066TD DEV BOARD |
2 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION KIT WITH HSBB & SPI C |
1 |
|
 |
Roving Networks / Microchip Technology |
MTD6501C EVAL DAUGHTER BOARD |
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)