Multi-Sensor Environmental Monitoring System for Smart Health Care
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, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{CO}_{2}$</tex>, 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.
Authors
- Jian Yang (ORCID: https://orcid.org/0000-0003-4019-3671)
- Ruixue Huang (ORCID: https://orcid.org/0000-0001-9280-6551)
- Min Huang (ORCID: https://orcid.org/0000-0001-7141-7434)
- Weikang Wang (ORCID: https://orcid.org/0000-0002-4783-7540)
- WU Shu-qin (ORCID: https://orcid.org/0000-0002-2958-6602)
- Y.F. Xie
Institutions
- Guangxi Normal University (CN)
- Guilin University of Electronic Technology (CN)
Publication Details
- Published
- 2025-04-25
- DOI
- https://doi.org/10.1109/iccea65460.2025.11102476
- Citations
- 1
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.49