Evaluation Boards

Evaluation Boards - Sensors

Part Number	Description / PDF	Quantity
MMC3630KJ-B MEMSIC	BOARD EVAL MMC3630KJ MAGN SENSOR	13
MMC34160PJ-B MEMSIC	BOARD EVAL MMC34160 MAGN SENSOR	2
MMC5603NJ-B MEMSIC	DEV BOARD FOR MMC5603NJ	29
MXR7900CF-B MEMSIC	BOARD EVAL FOR MXR7900CF	0
EV3635B MEMSIC	EVALUATION BOARD FOR MC3635	0
MXP7205VW-B MEMSIC	BOARD EVAL FOR MXR7205VW	0
MXR9500MZ-B MEMSIC	BOARD EVAL FOR MXR9500MZ	11
MMC5983MA-B MEMSIC	DEV BOARD FOR MMC5983MA	36
MXR2999EL-B MEMSIC	BOARD EVAL FOR MXR2999EL	0
MXR9150MZ-B MEMSIC	BOARD EVAL FOR MXR9150MZ	7
MXC62320MP-B MEMSIC	BOARD EVAL FOR MXC62320MP	0
MMC5883MA-B MEMSIC	DEVELOPMENT BOARD FOR MMC5883MA	16
MXR7305VF-B MEMSIC	BOARD EVAL FOR MXR7305VF	0
MXP7205VF-B MEMSIC	BOARD EVAL FOR MXP7205VW	0
DB3672B MEMSIC	DEMO BOARD FOR MC3672 AND MC3635	20
MXA2500EL-B MEMSIC	BOARD EVAL FOR MXA2500EL	0
MXC4005XC-B MEMSIC	MXC4XX5-B PROTOTYPING BOARD	9
MXC6655XA-B MEMSIC	EVAL BOARD FOR MXC6655	0
MXD6241AU-B MEMSIC	BOARD EVAL MXD6241 TIP OVER SENS	0
MXC6245XU-B MEMSIC	BOARD EVAL ACCEL 2AXIS MXC6245XU	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

Type	Functional Features	Application Examples
Temperature Sensor Boards	High-precision thermal sensing with digital/analog outputs	Climate control systems, medical devices
Accelerometer Boards	3-axis motion detection with programmable sensitivity	Vibration monitoring, fitness trackers
Pressure Sensor Boards	Atmospheric/differential pressure measurement	Weather stations, automotive systems
Environmental Sensor Boards	Multi-parameter detection (humidity, gas, light)	Smart agriculture, air quality monitors
Image Sensor Boards	High-resolution optical sensing with ISP integration	Surveillance 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

Parameter	Description	Importance
Measurement Range	Minimum/maximum detectable values	Determines application suitability
Accuracy	Error margin vs. reference values	Impacts system reliability
Sampling Rate	Data acquisition frequency	Defines dynamic response capability
Power Consumption	Operating current/voltage requirements	Affects battery life and thermal design
Interface Type	Communication protocol compatibility	Dictates 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

Manufacturer	Representative Product	Key Features
STMicroelectronics	STEVAL-MKI187V1	6-axis IMU with advanced calibration
Texas Instruments	BOOSTXL-ULTRASONIC	Ultrasonic sensing for distance measurement
Analog Devices	EVAL-ADICUP3029	Low-power Cortex-M4F based platform
NXP Semiconductors	FRDM-FXS-MULTI-B	Multi-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.