| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
IR (Infineon Technologies) |
BOARD EVAL FOR IR1152 |
0 |
|
 |
IR (Infineon Technologies) |
KIT DES FLUOR BALLAST IRS2530D |
0 |
|
 |
IR (Infineon Technologies) |
IMOTION IMC102T-F064 IMOTION |
5 |
|
 |
IR (Infineon Technologies) |
EVAL IEWS20R5135IPB |
1 |
|
 |
IR (Infineon Technologies) |
EVAL-IMM101T-015 IS A STARTER KI |
3 |
|
 |
IR (Infineon Technologies) |
KIT_A2G_TC387_3V3_TFT |
4 |
|
 |
IR (Infineon Technologies) |
EVALUATION BOARD FOR CIPOS |
2 |
|
 |
IR (Infineon Technologies) |
ACTIVE BRIDGE BOARD KIT_ACT_BRD_ |
3 |
|
 |
IR (Infineon Technologies) |
KIT MOTOR CONTROL FOR XMC750 |
6 |
|
 |
IR (Infineon Technologies) |
BTS3080TF DEMOBOARD |
3 |
|
 |
IR (Infineon Technologies) |
EVAL KIT |
3 |
|
 |
IR (Infineon Technologies) |
40W ADAPTER EVAL BOARD P7 |
3 |
|
 |
IR (Infineon Technologies) |
BOARD DEMO FOR TLE6208-6G |
0 |
|
 |
IR (Infineon Technologies) |
EVAL COOLSIC MOSFET MOTOR DRIVER |
15 |
|
 |
IR (Infineon Technologies) |
S2GO CLOUD SECURITY OPTIGA TRUST |
34 |
|
 |
IR (Infineon Technologies) |
2500W FULL BRIDGE TOTEM |
16 |
|
 |
IR (Infineon Technologies) |
IC SBC 3 REG CAN 48VQFN |
2 |
|
 |
IR (Infineon Technologies) |
DEMOBOARD ITS4040D |
4 |
|
 |
IR (Infineon Technologies) |
EVAL AUDIOHUB NANO |
26 |
|
 |
IR (Infineon Technologies) |
EVAL 1EDN7512G |
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)