Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
SK-86R11-BASE

SK-86R11-BASE

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2198-506-E

MB2198-506-E

Cypress Semiconductor

TOOL KIT

0

FCR4-CLUSTER-001

FCR4-CLUSTER-001

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

BBF2004-FR144SCL2-NB

BBF2004-FR144SCL2-NB

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

CYFL244-001

CYFL244-001

Cypress Semiconductor

MODULE KIT

0

MB2006-02

MB2006-02

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB91911EB

MB91911EB

Cypress Semiconductor

TOOL KIT

0

MB91901EB

MB91901EB

Cypress Semiconductor

TOOL KIT

0

MB2146-213

MB2146-213

Cypress Semiconductor

TOOL KIT

0

MB2198-606

MB2198-606

Cypress Semiconductor

TOOL KIT

0

MB2197-81

MB2197-81

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2198-616-E

MB2198-616-E

Cypress Semiconductor

TOOL KIT

0

MB2198-601SK

MB2198-601SK

Cypress Semiconductor

TOOL KIT

0

ADA-FCR4-CLUSTER-001

ADA-FCR4-CLUSTER-001

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2198-126-E

MB2198-126-E

Cypress Semiconductor

TOOL KIT

0

SK-FR80-120PMC-USB

SK-FR80-120PMC-USB

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2146-07-E-SPN

MB2146-07-E-SPN

Cypress Semiconductor

TOOL KIT

0

CY30703

CY30703

Cypress Semiconductor

KIT PROG FOR CY27EE16

0

SK-MB9EF226-003

SK-MB9EF226-003

Cypress Semiconductor

DEV KIT TOOL KIT PWR MGMT

0

MB2198-606SK

MB2198-606SK

Cypress Semiconductor

TOOL KIT

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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