Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
S5U13517P00C200

S5U13517P00C200

Epson

EVAL BOARD S1D13517

0

S5U13513P00C100

S5U13513P00C100

Epson

BOARD EVAL/SOFTWARE FOR S1D13513

0

S5U13781P00C100

S5U13781P00C100

Epson

EVAL BOARD FOR S1D13781

0

S5U13781R01C100

S5U13781R01C100

Epson

ARDUINO/MBED SHIELD FOR S1D13781

2

S5U13L01P00C100

S5U13L01P00C100

Epson

EVAL BOARD FOR S1D13L01

0

S5U13L03P00C100

S5U13L03P00C100

Epson

EVAL BOARD FOR S1D13L03

0

S5U1R72V17F0300

S5U1R72V17F0300

Epson

EVAL BOARD FOR S1R72V17

0

S5U1R72V27F0100

S5U1R72V27F0100

Epson

EVAL BOARD FOR S1/2R72V27

0

S5U1R72U16F0100

S5U1R72U16F0100

Epson

EVAL BOARD FOR S1R72U16

0

S5U13U11P00C100

S5U13U11P00C100

Epson

EVAL BOARD FOR S1D13U11

0

S5U2R72C05F0100

S5U2R72C05F0100

Epson

EVAL BOARD FOR S2R72C05

0

S5U13700P00C000

S5U13700P00C000

Epson

EVAL BOARD FOR S1D13700

0

S5U1R72U06F0100

S5U1R72U06F0100

Epson

EVAL BOARD FOR S1R72U06

0

S5U13515P00C100

S5U13515P00C100

Epson

EVAL BOARD FOR S1D13515

0

S5U1S60K00H0400

S5U1S60K00H0400

Epson

EVAL BOARD FOR S1S60000

0

S5U13748P00C100

S5U13748P00C100

Epson

EVAL BOARD FOR S1D13748

0

S5U13L02P00C100

S5U13L02P00C100

Epson

EVAL BOARD FOR S1D13L02

0

S5U13709P00C100

S5U13709P00C100

Epson

EVAL BOARD FOR S1D13709

0

S5U1V30S344E0600

S5U1V30S344E0600

Epson

EVAL BOARD FOR S1V3034

0

S5U13506P00C100

S5U13506P00C100

Epson

EVAL BOARD FOR S1D13506

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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