| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
BOARD EVAL PS700 W/POWERINFO2 |
0 |
|
|
Roving Networks / Microchip Technology |
EVAL BOARD FOR MXT2954T2 |
0 |
|
|
Roving Networks / Microchip Technology |
KIT MCP2120/2150 FOR IRDA COMM |
0 |
|
|
Roving Networks / Microchip Technology |
EVAL BOARD USB3320 |
0 |
|
|
Roving Networks / Microchip Technology |
KIT EVAL ATA6870/ATMEGA32HVB |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL USB2422 USB 2.0 |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL EXPERIMENT KS8721B |
0 |
|
|
Roving Networks / Microchip Technology |
VSC5636 EVAL BOARD |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD ADD-ON FOR XPLAIN DEV |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL EXPERIMENT KS8993F |
0 |
|
|
Roving Networks / Microchip Technology |
KIT EVALUATION FOR AT73C240 |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL FOR AT73C211 |
0 |
|
|
Roving Networks / Microchip Technology |
USB HUB/EMBEDDED FUNCTION DEVKIT |
0 |
|
|
Roving Networks / Microchip Technology |
AES CRYPTO MEMORY DEMO KIT |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD DEMO PICDEM USB |
0 |
|
|
Roving Networks / Microchip Technology |
KIT EVAL FOR AT42QT1110 |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL EXPERIMENT KS8695P |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD DEMO FOR U4037B |
0 |
|
|
Roving Networks / Microchip Technology |
USB2642 EVAL BOARD |
0 |
|
|
Roving Networks / Microchip Technology |
USB 2.0 PHY EVALUATION BOARD |
0 |
|
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)