Evaluation Boards - Sensors

Image Part Number Description / PDF Quantity Rfq
LM62EVAL

LM62EVAL

Texas Instruments

EVALUATION BOARD FOR LM62

0

LM26EVAL-TPA

LM26EVAL-TPA

Texas Instruments

BOARD EVALUATION LM26CIM5-TPA

0

LM94022EVAL

LM94022EVAL

Texas Instruments

BOARD EVALUATION LM94022

0

LM76-NEVAL

LM76-NEVAL

Texas Instruments

EVALUATION BOARD FOR LM76-N

0

LM77-3EVAL

LM77-3EVAL

Texas Instruments

EVALUATION BOARD FOR LM77-3

0

LM63EVAL/NOPB

LM63EVAL/NOPB

Texas Instruments

BOARD EVALUATION LM63

0

CC2650STK-BLE

CC2650STK-BLE

Texas Instruments

BLUETOOTH SENSOR TAG

0

LM95245EB/NOPB

LM95245EB/NOPB

Texas Instruments

BOARD EVALUATION FOR LM95245

0

LM95231EVAL

LM95231EVAL

Texas Instruments

BOARD EVALUATION LM95231

0

LM86EVAL

LM86EVAL

Texas Instruments

BOARD EVALUATION LM86

0

LM9627HEADBOARD

LM9627HEADBOARD

Texas Instruments

EVALUATION BOARD FOR LM9627

0

LM95233EB/NOPB

LM95233EB/NOPB

Texas Instruments

BOARD EVALUATION FOR LM95233

0

LM26LVEB/NOPB OPB

LM26LVEB/NOPB OPB

Texas Instruments

BOARD EVAL FOR LM26LV

0

LM73EVAL/NOPB

LM73EVAL/NOPB

Texas Instruments

EVALUATION BOARD FOR LM73

0

Evaluation Boards - Sensors

1. Overview

Evaluation boards for sensors are specialized hardware platforms designed to test, validate, and develop sensor-based applications. These boards integrate sensor elements with processing units, communication interfaces, and power management modules. They play a critical role in accelerating product development cycles in industries such as IoT, industrial automation, healthcare, and consumer electronics by enabling rapid prototyping and performance characterization.

2. Major Types and Functional Classification

TypeFunctional FeaturesApplication Examples
Temperature Sensor BoardsHigh-precision thermal sensing with digital/analog outputsClimate control systems, medical devices
Accelerometer Boards3-axis motion detection with programmable sensitivityVibration monitoring, fitness trackers
Pressure Sensor BoardsAtmospheric/differential pressure measurementWeather stations, automotive systems
Environmental Sensor BoardsMulti-parameter detection (humidity, gas, light)Smart agriculture, air quality monitors
Image Sensor BoardsHigh-resolution optical sensing with ISP integrationSurveillance cameras, machine vision

3. Structure and Components

Typical evaluation boards consist of: - Sensor element (MEMS, CMOS, or discrete transducers) - Microcontroller/SoC with ADC/DAC interfaces - Communication modules (I2C, SPI, UART, BLE/Wi-Fi) - Power management ICs and voltage regulators - Debugging interfaces (JTAG, SWD) - Auxiliary components (LED indicators, potentiometers) The PCB layout optimizes signal integrity while minimizing electromagnetic interference.

4. Key Technical Specifications

ParameterDescriptionImportance
Measurement RangeMinimum/maximum detectable valuesDetermines application suitability
AccuracyError margin vs. reference valuesImpacts system reliability
Sampling RateData acquisition frequencyDefines dynamic response capability
Power ConsumptionOperating current/voltage requirementsAffects battery life and thermal design
Interface TypeCommunication protocol compatibilityDictates system integration complexity

5. Application Areas

  • Industrial Automation: Predictive maintenance systems, process control
  • Healthcare: Wearable vital sign monitors, diagnostic equipment
  • Consumer Electronics: Smart home devices, mobile accessories
  • Automotive: Tire pressure monitoring, ADAS sensors
  • Aerospace: Structural health monitoring, navigation systems

6. Leading Manufacturers and Products

ManufacturerRepresentative ProductKey Features
STMicroelectronicsSTEVAL-MKI187V16-axis IMU with advanced calibration
Texas InstrumentsBOOSTXL-ULTRASONICUltrasonic sensing for distance measurement
Analog DevicesEVAL-ADICUP3029Low-power Cortex-M4F based platform
NXP SemiconductorsFRDM-FXS-MULTI-BMulti-sensor fusion for IoT applications

7. Selection Guidelines

Key considerations include: - Match sensor specifications to target application requirements - Verify compatibility with existing development ecosystems - Evaluate power budget and form factor constraints - Consider available software support (drivers, SDKs) - Assess calibration and certification requirements Example: For a wearable health monitor, prioritize low-power accelerometers with medical-grade accuracy.

8. Industry Trends

Emerging trends include: - Integration of AI accelerators for edge computing - Development of wireless sensor nodes with energy harvesting - Advancements in MEMS fabrication for higher sensitivity - Standardization of sensor fusion algorithms - Growth of open-source hardware ecosystems Market projections indicate a 12% CAGR through 2027 driven by IoT and Industry 4.0 adoption.

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