| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
BOARD EVAL FOR MCP39F501 |
1 |
|
 |
Roving Networks / Microchip Technology |
ATMXT1067TD SPI BASED EVALUATION |
2 |
|
 |
Roving Networks / Microchip Technology |
BOARD DAUGHTER PICTAIL ETHERNET |
3 |
|
 |
Roving Networks / Microchip Technology |
MCP39F511N POWER MONITOR DEMONST |
2 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION KSZ8842-16MQL |
4 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION BOARD |
0 |
|
 |
Roving Networks / Microchip Technology |
DEV BOARD FOR ATA663231 |
0 |
|
 |
Roving Networks / Microchip Technology |
ATMXT144U-DEV-PCB |
0 |
|
 |
Roving Networks / Microchip Technology |
VOLTAGE SUPERVISOR BARE BRD 5PAK |
0 |
|
 |
Roving Networks / Microchip Technology |
ATM90E36A DEMO BOARD |
3 |
|
 |
Roving Networks / Microchip Technology |
WATER TOLERANT 2D TOUCH AVR BRD |
7 |
|
 |
Roving Networks / Microchip Technology |
MTD6508 EVAL MOTHER BOARD |
2 |
|
 |
Roving Networks / Microchip Technology |
SIC GATE DRIVER EVALUATION PRODU |
5 |
|
 |
Roving Networks / Microchip Technology |
AUTOMOTIVE NETWORKING DEVELOPMEN |
3 |
|
 |
Roving Networks / Microchip Technology |
ATMXT288UD-I2C-PCB DEV BOARD |
3 |
|
 |
Roving Networks / Microchip Technology |
POE EVB |
4 |
|
 |
Roving Networks / Microchip Technology |
REFERENCE DESIGN MCP1631HV |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION EMC1182 |
5 |
|
 |
Roving Networks / Microchip Technology |
DEVELOPMENT PCB |
1 |
|
 |
Roving Networks / Microchip Technology |
REFERENCE DESIGN PWR-PTH MCP7383 |
2 |
|
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)