Evaluation Boards

Evaluation Boards - Sensors

Part Number	Description / PDF	Quantity
AS5145B-SS_EK_MB ams	KIT EVAL MOTOR POSITION AS5145B	1
AS5134-SS_EK_AB ams	ADAPTER BOARD FOR AS5134	3
AS7341 EVAL KIT ams	EVAL KIT FOR AS7341	47
TMD3702VC-DB ams	DAUGHTER BOARD FOR THE TMD3702VC	0
AS5172B-TS_EK_AB ams	AS5172B ADAPTER BOARD	4
AS5050A-QF_EK_AB ams	EVAL BOARD ROTARY ENCODER	9
AS5140-SS_EK_AB ams	BOARD ADAPTER AS5140	2
TMD2771EVM ams	EVAL MODULE FOR TMD2771	1
TSL2541-EVM ams	EVAL MODULE FOR THE TSL2541	1
TMG3993EVM ams	EVAL MODULE FOR TMG3993	2
AS5600L-WL_EK_AB ams	AS5600L ADAPTERBOARD WLCSP	2
AS5132-SS_EK_AB ams	ADAPTER BOARD FOR AS5132	1
AS5247-MF_EK_AB ams	ADAPTER BOARD FOR AS5247	3
AS5134-SS_EK_DB ams	BOARD DEMO AS5134	1
TCS3707-DB ams	DAUGHTER BOARD FOR THE TCS3707	1
AS7263 DEMO KIT ams	DEMO/EVAL KIT AS7263	4
TMD2772-DB ams	TMD2772X DAUGHTER BOARD	0
TMD2772EVM ams	EVAL MODULE FOR TMD2772	1
AS7264N DEMO KIT ams	DEMO/EVAL KIT AS7264A	2
AS6214-EK ams	AS6214 EVAL KIT	1

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.