Evaluation Boards - Sensors

Image Part Number Description / PDF Quantity Rfq
OV05642-ECJF-BA1F

OV05642-ECJF-BA1F

OmniVision Technologies

KIT EVAL FOR OV05642 5MP

0

OV00000-EG00-0057

OV00000-EG00-0057

OmniVision Technologies

57 FPGA (GAIA) BOARD FOR ISP 30

0

OV07675-ECJA-BA0A

OV07675-ECJA-BA0A

OmniVision Technologies

EVALUATION KIT (2-BOARD) WITH OV

0

OV02722-MPSW-24-F000

OV02722-MPSW-24-F000

OmniVision Technologies

2MP STANDARD FLEX MODULE WITH NE

0

OV07955-ETJE-BA0A

OV07955-ETJE-BA0A

OmniVision Technologies

TEST MODULE (2-BOARD) WITH OV538

0

OV09728-MRDB-FA00

OV09728-MRDB-FA00

OmniVision Technologies

720P HD FIXED FOCUS RIGID MODULE

0

OV05680-EAAC-AA0A

OV05680-EAAC-AA0A

OmniVision Technologies

PROTOTYPING MODULE FOR 5MP CLGA

0

OV05680-MYSL-22-A00T

OV05680-MYSL-22-A00T

OmniVision Technologies

5MP AUTO FOCUS RIGID FLEX MODULE

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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