| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
AUGMENTED SWITCH DEV KIT |
1 |
|
 |
Roving Networks / Microchip Technology |
ATMXT1189 DEVELOPMENT BOARD |
4 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL FOR USB5734 |
5 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO PICKIT SERIAL SPI |
3 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL USB82514 AUTO GRADE |
0 |
|
 |
Roving Networks / Microchip Technology |
PL360G55CF EVALUATION BOARD |
19 |
|
 |
Roving Networks / Microchip Technology |
EVB-KSZ9131RNX PLUG-IN EVALUATIO |
7 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION KIT WITH I2C PCB |
1 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL USB2534 |
1 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR ATA6663 |
0 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD SMART CARD BRIDG-UART |
1 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD KSZ9031MNX |
67 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO 3PH BLDC CTLR MTD6505 |
1 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION BOARD FOR LAN9303 |
0 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD FOR ATA663431 |
0 |
|
 |
Roving Networks / Microchip Technology |
DIGITAL POWER DEVELOPMENT BOARD |
7 |
|
 |
Roving Networks / Microchip Technology |
MTD6508 EVAL DAUGHTER BOARD |
6 |
|
 |
Roving Networks / Microchip Technology |
MTD6501G EVAL DAUGHTER BOARD |
7 |
|
 |
Roving Networks / Microchip Technology |
BOARD DISPLAY CTLR PLUS S1D13517 |
1 |
|
 |
Roving Networks / Microchip Technology |
LAN9252 - ETHERCAT SLAVE CONTROL |
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)