| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
EVAL BOARD FOR MXT799TAT |
0 |
|
|
Roving Networks / Microchip Technology |
EVAL BOARD LAN9313M |
0 |
|
|
Roving Networks / Microchip Technology |
KIT EVAL FOR AT83C24 FOR TDA8004 |
0 |
|
|
Roving Networks / Microchip Technology |
FSK SNIFFER LITE |
0 |
|
|
Roving Networks / Microchip Technology |
KIT DEV TOOL CRYPTOMEMORY |
0 |
|
|
Roving Networks / Microchip Technology |
ATPL210 SK 2 BOARDS |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL FOR KS8993ML |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL USB3503 HSIC TO USB2 |
0 |
|
|
Roving Networks / Microchip Technology |
VSC5627 EVAL BOARD |
0 |
|
|
Roving Networks / Microchip Technology |
C7-FARH LPC EVAL DAUGHTER BOARD |
0 |
|
|
Roving Networks / Microchip Technology |
VSC5631 EVAL BOARD |
0 |
|
|
Roving Networks / Microchip Technology |
VSC5628-A EVAL BOARD |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVAL EXPERIMENT KS8995MA |
0 |
|
|
Roving Networks / Microchip Technology |
KIT EVALUATION PS5164 W/PS051 |
0 |
|
|
Roving Networks / Microchip Technology |
BOARD EVALUATION KSZ8695P-MMB |
0 |
|
|
Roving Networks / Microchip Technology |
BATTERY MANAGER MODULE |
0 |
|
|
Roving Networks / Microchip Technology |
EVAL BOARD LAN89303 |
0 |
|
|
Roving Networks / Microchip Technology |
EVAL BOARD FOR MXT1665TAT |
0 |
|
|
Roving Networks / Microchip Technology |
KIT USB HUB DEVELOPMENT AT43312A |
0 |
|
|
Roving Networks / Microchip Technology |
EVALUATION KIT FOR ATPL100 |
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)