| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
PAC1934 4 CH DC POWER MONITOR EV |
10 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD DUAL USB UCS2112 |
1 |
|
 |
Roving Networks / Microchip Technology |
AUGMENTED SWITCH DEV KIT |
1 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION KIT FOR ATA6614 |
2 |
|
 |
Roving Networks / Microchip Technology |
WATER TOLERANT 2D TOUCH PIC BRD |
8 |
|
 |
Roving Networks / Microchip Technology |
ATEVK-MXT1066TD-A I2C EVAL KIT |
3 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION UCS1002 |
1 |
|
 |
Roving Networks / Microchip Technology |
MCP1632 SEPIC LI-ION BATTERY CHA |
0 |
|
 |
Roving Networks / Microchip Technology |
DSPICDEM MCHV-3 DEVELOPMENT SYST |
3 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL BATT CHARGER MCP73113 |
1 |
|
 |
Roving Networks / Microchip Technology |
AUGMENTED SWITCH DEV KIT - 1200V |
2 |
|
 |
Roving Networks / Microchip Technology |
ATEVK-MXT1189TDAT-C (SPI) EVALUA |
2 |
|
 |
Roving Networks / Microchip Technology |
EVB-LAN9254-DIGIO |
2 |
|
 |
Roving Networks / Microchip Technology |
HV892DB1 LIQUID LENS DRIVER DEMO |
2 |
|
 |
Roving Networks / Microchip Technology |
MCP25625 PICTAIL PLUS DAUGHTER B |
3 |
|
 |
Roving Networks / Microchip Technology |
KIT DEV USB FOR PIC16F1459 |
2 |
|
 |
Roving Networks / Microchip Technology |
IOT ETHERNET MONITORING KIT POWE |
0 |
|
 |
Roving Networks / Microchip Technology |
MTD6501D EVAL DAUGHTER BOARD |
1 |
|
 |
Roving Networks / Microchip Technology |
MCP39F501 ENERGY MONITOR PICTAIL |
0 |
|
 |
Roving Networks / Microchip Technology |
UCS1003-2 EVALUATION BOARD |
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)