Evaluation Boards

Evaluation Boards - Sensors

Image	Part Number	Description / PDF	Quantity	Rfq
	AS5304-TS_EK_AB ams	ADAPTER BOARD FOR AS5304-2.0	0
	TMD2620-EVM ams	EVALUATION MODULE FOR TMD2620	0
	TCS3471EVM ams	EVAL MODULE FOR TCS3471	0
	NANOHDMI ams	NANOHDMI	0
	TSL4531-DB ams	EVAL BOARD FOR TSL4531	0
	CSI2100 EVALUATION K ams	EVAL BOARD FOR CSI2100	0
	CMV300M-EVAL2 ams	EVAL BOARD FOR CMV300	0
	TSL2581CSEVM ams	EVAL MODULE FOR TSL2581	0
	ORION2K_CERAMIC_GLAS ams	EVAL BOARD FOR ORION	0
	NANOUSB3_ORION4K_EVA ams	EVAL BOARD FOR ORION	0
	NANOUSB3_4LS_EVALBOA ams	EVAL BOARD FOR 4LS	0
	TCS3771-DB ams	EVAL BOARD FOR TCS3771	0
	AS5043 DB V2 ams	BOARD DEMO AS5043	0
	CHR71000-EVAL2 ams	EVAL BOARD FOR CHR70M	0
	NANOUSB3_ORION_1K_2K ams	EVAL BOARD FOR ORION	0
	TCS3471-DB ams	EVAL BOARD FOR TCS3471	0
	AS5011 DB EASYPOINT ams	BOARD EVAL AS5011 EASYPOINT	0
	AS5263-QF_EK_DB ams	BOARD DEMO FOR AS5263	0
	TSL2581FNEVM ams	EVAL MODULE FOR TSL2581	0
	CMV12000-EVAL3 ams	EVAL BOARD FOR CMV12000	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.