| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Texas Instruments |
EVAL MODULE FOR FE427A |
3 |
|
 |
Texas Instruments |
EVALUATION MODULE AFE4490 |
7 |
|
 |
Texas Instruments |
EVAL MODULE FOR TSC2017 |
2 |
|
 |
Texas Instruments |
EVAL BOARD FOR DRV10970 BLDC MTR |
15 |
|
 |
Texas Instruments |
KIT BASIC STARTER MULTI-CAL SYST |
2 |
|
 |
Texas Instruments |
KIT PERFORMANCE DEMO ADS131E08 |
2 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPS22968 |
5 |
|
 |
Texas Instruments |
TUSB214EVM |
0 |
|
 |
Texas Instruments |
EVALUATION MODULE AFE4400 |
3 |
|
 |
Texas Instruments |
EVAL BOARD FOR TPS3702 |
3 |
|
 |
Texas Instruments |
EVAIL MOD |
5 |
|
 |
Texas Instruments |
EVALUATION BOARD FOR LM5068 |
1 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPS65381 |
2 |
|
 |
Texas Instruments |
EVAL BOARD FOR LM3658 |
2 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPS23753A-001 |
5 |
|
 |
Texas Instruments |
ULTRASONIC SENSOR |
41 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPS2003-016 |
12 |
|
 |
Texas Instruments |
EVAL MODULE HD3SS460 |
3 |
|
 |
Texas Instruments |
DEVELOPMENT INTERFACE |
8 |
|
 |
Texas Instruments |
KIT PERFORMANCE DEMO ADS130E08 |
1 |
|
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)