Evaluation Boards

Evaluation Boards - Sensors

Part Number	Description / PDF	Quantity
TMD2672EVM ams	EVAL MODULE FOR TMD2672	3
AS5145A-SS_EK_AB ams	BOARD ADAPTER AS5145A	0
AS5147P-TS_EK_AB ams	BOARD ADAPTER AS5147P	65
AS5162-SO_EK_AB ams	ADAPTER BOARD FOR AS5162	2
AS5147-TS_EK_AB ams	BOARD ADAPTER AS5147	26
AS5040-SS_EK_DB ams	BOARD DEMO AS5040	1
TSL2540-EVM ams	EVAL BOARD FOR TSL2540	6
TMD3725-DB ams	DAUGHTER BOARD FOR THE TMD3725	1
AS5X47P-TS_EK_MB ams	EVAL KIT FOR AS5X47P	16
AS5311-TS_EK_AB ams	ADAPTER BOARD FOR AS5311	402
TMD3782EVM ams	EVAL KIT SENSOR PROXIMITY/COLOR	4
TCS3701-EVM ams	EVAL MODULE FOR THE TCS3701	2
TMD2771-DB ams	TMD2771 DAUGHTER BOARD	0
TMD2635-DB ams	DAUGHTER BOARD FOR TMD2635	10
AS6212-EK ams	AS6212 EVAL KIT	5
NANOUSB2.2 ams	NANOUSB2.2	11
AS5045-SS_EK_AB ams	BOARD ADAPTER AS5045	27
TMD2635-EVM ams	EVALUATION MODULE FOR TMD2635	11
TSL2772EVM ams	BOARD EVAL FOR TSL2772	0
TSL2572XEVM REV.2.0 ams	TSL2572X EVALUATION MODULE	4

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.