Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
STM32HVMODULE

STM32HVMODULE

Maxim Integrated

HI VOLTAGE VERSION OF STM32 MODU

0

MAX96880-BAH-EVS#

MAX96880-BAH-EVS#

Maxim Integrated

EVALUATION SYSTEM MAX96880-BAH

0

MAX11068EVKIT+

MAX11068EVKIT+

Maxim Integrated

KIT SMART BATT MEASUREMENT 12CH

0

MAX846EVKIT+

MAX846EVKIT+

Maxim Integrated

EVAL KIT

0

MAX88130EVSYS#

MAX88130EVSYS#

Maxim Integrated

EVAL SYSTEM MAX88130

0

MAXM17937EVKIT#

MAXM17937EVKIT#

Maxim Integrated

EVALUATION KIT

0

MAX14850DEVBRD#

MAX14850DEVBRD#

Maxim Integrated

DEVELOPMENT BOARD FOR MAX14850,

0

MAX77849EVKIT#

MAX77849EVKIT#

Maxim Integrated

EVALUATION KIT

0

MAX77178EVKIT#

MAX77178EVKIT#

Maxim Integrated

EVALUATION KIT

0

MAX5952AEVKIT

MAX5952AEVKIT

Maxim Integrated

EVAL KIT/SYSTEM MAX5952A (HIGH-P

0

DS33X162DK

DS33X162DK

Maxim Integrated

KIT DEMO FOR DS33X162+

0

MAX9680EVKIT+

MAX9680EVKIT+

Maxim Integrated

KIT EVALUATION FOR MAX9680

0

MAX7326EVKIT+

MAX7326EVKIT+

Maxim Integrated

KIT EVAL FOR MAX7326

0

MAX4221EVKIT-SO

MAX4221EVKIT-SO

Maxim Integrated

EVALUATION KIT FOR MAX4221

0

MAXAT24EVKIT#

MAXAT24EVKIT#

Maxim Integrated

EV KIT FOR DCL W/INTEGRATED PMU

0

MAX20490EVKIT#

MAX20490EVKIT#

Maxim Integrated

EVALUATION KIT

0

MAX14935EWEVKIT#

MAX14935EWEVKIT#

Maxim Integrated

EVAL KIT FOR MAX14935

0

MAX84000EVSYS#

MAX84000EVSYS#

Maxim Integrated

EVAL SYSTEM MAX84000

0

DS28CM00EVKIT

DS28CM00EVKIT

Maxim Integrated

EVALUATION KIT

0

MAX9295DCOXEVKIT#

MAX9295DCOXEVKIT#

Maxim Integrated

EVAL 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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