Evaluation Boards - Embedded - MCU, DSP

Image Part Number Description / PDF Quantity Rfq
102990007

102990007

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FLYING STONE TINY ZERO-ONE STM32

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109990070

109990070

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SODAQ MBILI ATMEGA1284P EVAL BRD

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102990162

102990162

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INTEL EDISON EDISON EVAL BRD

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102990031

102990031

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FLYING STONE TINY ZERO-ONE STM32

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102990218

102990218

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AUTOMATIONBOARD ATMEGA328P EVAL

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113110004

113110004

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HIKEY 960 KIRIN 960 EVAL BRD

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102990193

102990193

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PHOENARD ATMEGA2560 EVAL BRD

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102990064

102990064

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86DUINO ONE VORTEX86EX EVAL BRD

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107010001

107010001

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RESPEAKER MIC ARRAY - FAR-FIELD

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102100001

102100001

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INTEL EDISON EDISON EVAL BRD

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102080004

102080004

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ARCH MAX STM32F407 EVAL BRD

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102990172

102990172

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UF0 STM32F051 EVAL BRD

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102010017

102010017

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SEEEDUINO STALKER V3 ATMEGA328P

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102010006

102010006

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RAINBOWDUINO ATMEGA328 EVAL BRD

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109990041

109990041

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HYDRABUS STM32F405 EVAL BRD

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102010003

102010003

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SEEEDUINO CLIO ATMEGA32U4 EVAL

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102990283

102990283

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INTEL EDISON EDISON EVAL BRD

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114990494

114990494

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HIKEY KIRIN 6220 EVAL BRD

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102110268

102110268

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NVIDIA JETSON NANO DEVELOPER KIT

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102080001

102080001

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ARCH LPC11U24 DEV EVAL BRD

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Evaluation Boards - Embedded - MCU, DSP

1. Overview

Evaluation Boards (Dev Boards) for Embedded MCUs (Microcontroller Units) and DSPs (Digital Signal Processors) are specialized hardware platforms designed to facilitate the development, testing, and prototyping of embedded systems. These boards provide a physical environment to validate processor capabilities, peripheral integration, and software algorithms before final product deployment. They play a critical role in accelerating development cycles for applications ranging from IoT devices to industrial automation systems.

2. Major Types and Functional Classification

TypeFunctional FeaturesApplication Examples
MCU Evaluation BoardsARM Cortex-M series, integrated peripherals (UART, SPI, I2C), low-power modesSmart sensors, wearables, home automation
DSP Development KitsHigh-speed floating-point processing, SIMD instructions, real-time signal analysisAudio processing, radar systems, motor control
SoC Embedded BoardsIntegrated CPU+GPU+FPGA, multimedia acceleration, OS supportEdge computing, robotics, automotive infotainment
FPGA-based Prototyping BoardsReconfigurable logic, hardware-software co-design, high-speed I/O5G communication, AI inference accelerators

3. Structure and Components

Typical evaluation boards consist of:

  • PCB base with processor/microcontroller soldered onboard
  • Memory modules (SRAM, Flash, DDR)
  • Debugging interfaces (JTAG, SWD, UART)
  • Power management unit (voltage regulators, PMICs)
  • Peripheral connectors (GPIO, ADC/DAC, Ethernet)
  • Expansion headers for add-on modules (shields, PMODs)
  • Onboard sensors/actuators (depending on application focus)

4. Key Technical Specifications

ParameterImportance
Processor ArchitectureDetermines computational capabilities and software ecosystem compatibility
Maximum Clock FrequencyImpacts processing speed and real-time performance
Memory BandwidthAffects data throughput for signal processing applications
Peripheral IntegrationReduces external component requirements and system complexity
Power ConsumptionCritical for battery-powered and thermal-constrained applications
Debugging CapabilitiesEnables efficient firmware development and hardware verification

5. Application Fields

Key industries utilizing evaluation boards:

  • Industrial Automation: PLCs, motor drives, predictive maintenance systems
  • Consumer Electronics: Smart home devices, AR/VR headsets
  • Automotive: ADAS prototyping, ECU development
  • Medical: Portable diagnostic equipment, wearable health monitors
  • Communications: 5G baseband processing, software-defined radios
  • Energy: Smart grid controllers, solar inverters

6. Leading Manufacturers and Representative Products

ManufacturerProduct SeriesKey Features
STMicroelectronicsSTM32 Nucleo SeriesARM Cortex-M cores, Arduino compatibility, mbed OS support
Texas InstrumentsTMDX SeriesC2000 DSPs for power electronics, Code Composer Studio integration
NXP Semiconductorsi.MX RT SeriesARM Cortex-M7 based crossover processors, LCD interface support
XilinxZynq UltraScale+ MPSoCARM Cortex-A53 + FPGA fabric, AI acceleration with DPU

7. Selection Guidelines

Key considerations when choosing evaluation boards:

  • Match processor architecture to target application requirements (e.g., ARM for general-purpose, DSP for signal processing)
  • Verify peripheral compatibility with system design (number of timers, communication interfaces)
  • Assess expansion capabilities for future upgrades
  • Evaluate software toolchain maturity (IDE, compilers, RTOS support)
  • Consider power consumption specifications for end-application scenarios
  • Check available community resources and technical documentation

8. Industry Trend Analysis

Emerging trends shaping evaluation board development:

  • Increased integration of AI acceleration cores (e.g., Google Edge TPU integration)
  • Rise of RISC-V based evaluation platforms for customizable computing
  • Enhanced security features (trusted execution environments, hardware encryption)
  • Development of low-power wide-area network (LPWAN) enabled boards for IoT
  • Adoption of heterogeneous computing architectures (CPU+GPU+DSP+FPGA)
  • Cloud-connected evaluation platforms for remote testing and collaboration
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