Multi-Sensor Environmental Monitoring System for Smart Health Care
Weikang Wang, WU Shu-qin, Min Huang, Yuanqiong Xie, Jianbo Yang, Ruixue Huang · 2025
This study proposes a heterogeneous multimodal sensing fusion system for smart healthcare, improving the single-dimensional perception of traditional environmental monitors. An STM32-based edge intelligence architecture integrates optical-gas-biological sensors: VEML7700/BMP180 enable light intensity-air pressure dual-modal compensation; DHT11/SGP30 establish a joint model for temperature, humidity,$\text{CO}_{2}$, and VOCs. The LD6002 sensor array fuses ECG, acceleration, and infrared data, with fall detection accuracy enhanced via an improved DTW algorithm. Hardware design uses hierarchical power domains: the TPS63020 chip independently controls sensor, MCU, and communication module power, reducing standby consumption through asynchronous triggering. Prototype tests verify accurate collection of environmental and physiological data.