| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
DAUGHTER BOARD CAN/LIN PICTAIL |
18 |
|
 |
Roving Networks / Microchip Technology |
MCP1012 1W DEMO BOARD |
2 |
|
 |
Roving Networks / Microchip Technology |
FLYBACK BATTERY CHARGER EVAL BD |
1 |
|
 |
Roving Networks / Microchip Technology |
EVAL KIT CRYPTO |
20 |
|
 |
Roving Networks / Microchip Technology |
AWS ZEROTOUCHSECURE PROVISIONING |
4 |
|
 |
Roving Networks / Microchip Technology |
DEMO BOARD MCP39F521 PWR MONITOR |
12 |
|
 |
Roving Networks / Microchip Technology |
ATMXT144UD-SPI-PCB DEV BOARD |
2 |
|
 |
Roving Networks / Microchip Technology |
BOARD KIT BLDC MOTOR DRIVER |
1 |
|
 |
Roving Networks / Microchip Technology |
ATMXT1189DEVELOPMENT BOARD |
4 |
|
 |
Roving Networks / Microchip Technology |
BOARD SMART CARD / SIM CARD |
6 |
|
 |
Roving Networks / Microchip Technology |
MAXTOUCH I2C EVALUATION KIT |
3 |
|
 |
Roving Networks / Microchip Technology |
MCP3912 EVALUATION BOARD |
6 |
|
 |
Roving Networks / Microchip Technology |
DEMO KIT BLDC MOTOR 12V 3-PHASE |
4 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO FOR MCP1630 LI-ION |
5 |
|
 |
Roving Networks / Microchip Technology |
PD69208T4 EVAL BOARD IEEE802.3BT |
4 |
|
 |
Roving Networks / Microchip Technology |
HV2903 HV ANALOG SWITCH EVALUATI |
1 |
|
 |
Roving Networks / Microchip Technology |
ATMXT1067 DEVELOPMENT BOARD |
4 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR ATA6823 |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO FOR MCP73831 |
6 |
|
 |
Roving Networks / Microchip Technology |
AT88CKECC PROVISIONING STARTERKT |
4 |
|
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)