| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Roving Networks / Microchip Technology |
EVAL KIT CRYPTO |
0 |
|
 |
Roving Networks / Microchip Technology |
REF DESIGN MCP3911 PIC18F85K90 |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR USB2507 |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL EXPERIMENT KSZ8995MA |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR KSZ8051MNL |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT EVAL APPL MASS STORAGE |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR KSZ8721CL |
0 |
|
 |
Roving Networks / Microchip Technology |
PIC DEM FULL SPEED USB DEMO BRD |
0 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD POWER DISTRIBUTION SW |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT DEV FOR AT88SCXXXXC FAMILY |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR KSZ8041NL |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR KSZ8995XA |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT EVAL SMARTFUSION MOTOR CTRL |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVALUATION FOR KSZ8721BMC |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD DAUGHTER PWR LINE MODEM |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD DEMO FOR MCP215X/40 |
0 |
|
 |
Roving Networks / Microchip Technology |
KIT EVAL TCP/IP AT89C51AC2 |
0 |
|
 |
Roving Networks / Microchip Technology |
EVAL BOARD POWER DISTRIBUTION SW |
0 |
|
 |
Roving Networks / Microchip Technology |
EVALUATION BOARD FOR USB3317C |
0 |
|
 |
Roving Networks / Microchip Technology |
BOARD EVAL FOR 16BIT MCU MCP3911 |
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)