Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
CY4611B

CY4611B

Cypress Semiconductor

KIT USB TO ATA REFERENCE DESIGN

0

CYV15G0101DX-VIDEO

CYV15G0101DX-VIDEO

Cypress Semiconductor

BOARD EVAL HOTLINK II VIDEO

0

SK-MB9EF120-002

SK-MB9EF120-002

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2198-305-E

MB2198-305-E

Cypress Semiconductor

TOOL KIT

0

MB2132-465

MB2132-465

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB91919-805

MB91919-805

Cypress Semiconductor

TOOL KIT

0

MB2198-101

MB2198-101

Cypress Semiconductor

TOOL KIT

0

MB2146-271

MB2146-271

Cypress Semiconductor

TOOL KIT

0

MB2198-558-E

MB2198-558-E

Cypress Semiconductor

TOOL KIT

0

CY3290-CYAT8168X-001

CY3290-CYAT8168X-001

Cypress Semiconductor

DEVELOPMENT KIT

0

MB2132-454

MB2132-454

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2198-704-E

MB2198-704-E

Cypress Semiconductor

TOOL KIT

0

MB2198-121

MB2198-121

Cypress Semiconductor

TOOL KIT

0

MB2198-01

MB2198-01

Cypress Semiconductor

TOOL KIT

0

MB2146-303B-E

MB2146-303B-E

Cypress Semiconductor

TOOL KIT

0

MB2198-752-E

MB2198-752-E

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2146-303A

MB2146-303A

Cypress Semiconductor

TOOL KIT

0

IC149100014B5

IC149100014B5

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2198-304A-E

MB2198-304A-E

Cypress Semiconductor

TOOL KIT

0

C10256

C10256

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

Evaluation and Demonstration Boards and Kits

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.

TypeFunctional FeaturesApplication Examples
Microcontroller Development BoardsEmbedded CPUs, GPIOs, integrated peripheralsIoT devices, robotics
FPGA Evaluation BoardsReconfigurable logic, high-speed interfacesCommunication systems, AI accelerators
Sensor Expansion KitsMulti-sensor integration (temperature, motion, etc.)Smart agriculture, environmental monitoring
Wireless Communication ModulesBluetooth/Wi-Fi/LoRa protocols, antenna interfacesConnected 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.

ParameterDescription
Processor Performance (MHz/GHz)Determines computational capability
Memory Capacity (RAM/Flash)Affects program complexity and data storage
Interface TypesDictates 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

ManufacturerRepresentative Products
STMicroelectronicsSTM32 Nucleo Series, SensorTile Kit
IntelIntel Edison, Movidius Neural Compute Stick
XilinxZynq UltraScale+ MPSoC Evaluation Kit
ArduinoArduino 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)

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