| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION KSZ8862-10FL |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR KSZ8041RNL |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL FOR MCP8024 |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT DVR BOARD EVAL SYSTEM MXDEV1 |
0 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION BOARD 10/100 PHY |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT EVALUATION FOR MCP73861,2 |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL BATT CHARGER TC110 |
0 |
|
 |
Roving Networks / Microchip Technology |
CRYPTOAUTHENTICATION XPLAIND PRO |
0 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD HIGH SIDE LOAD SWITCH |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEVELOPMENT IRDA |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL MAC/PHY FOR KSZ8851 |
0 |
|
 |
Roving Networks / Microchip Technology |
DEVELOPMENT KIT MULTI-TOUCH PCAP |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR KSZ9021RN |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION KSZ8841-16MQL |
0 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD POWER DISTRIBUTION SW |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD DES MCP3909 ENERGY METER |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT EVAL KSZ8041FTL EXPERIMENT |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO DSPICDEM.NET 1 |
0 |
|
 |
Roving Networks / Microchip Technology |
REF DESIGN MCP1630V BI-DIR 4CELL |
0 |
|
 |
Roving Networks / Microchip Technology |
REF DESIGN MOD AUTO AMBNT LIGHT |
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)