| Image | Part Number | Description / PDF | Quantity | Rfq |
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EVAL BAORAD FOR XR68C92 44PLCC |
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EVAL BOARD FOR XR17V254 144LQFP |
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EVAL BOARD FOR XR17C158-A 144TQF |
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EVAL BOARD FOR L2551-A 32QFN |
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EVAL BOARD FOR XR16L580 48TQFP |
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EVAL BOARD FOR ST16C554 6PLCC |
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EVAL BOARD FOR XRD98L61AIV |
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EVAL BOARD FOR XR16C854 100QFP |
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EVAL BOARD FOR V2752 32QFN |
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EVAL BOARD FOR XR19L200 32QFN |
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EVAL BOARD FOR V2550 32QFN |
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EVAL BOARD FOR XRD9859 |
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EVAL BOARD FOR 68M752 49BGA |
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EVAL BOARD FOR M2750-A 48TQFP |
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EVAL BOARD FOR XR16M670-C 32QFN |
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EVAL BOARD FOR XR16V698-A 100QFP |
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EVAL BOARD FOR XR16V654 48QFN |
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EVAL BOARD FOR XR68M752 32QFN |
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EVAL BOARD FOR XR16M564-A 64LQFP |
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EVAL BOARD FOR XR16V654 68PLCC |
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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)