TY - JOUR
T1 - A Low-Power Portable Gas Sensor System with Adaptive ROIC and Wi-Fi Communication for Biomedical Applications
AU - Kim, Jun Nyeong
AU - Kwon, Soon Kyu
AU - Park, Byung Choul
AU - Kim, Hyeon June
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/8
Y1 - 2025/8
N2 - This study presents a portable gas sensor system that achieves high performance while minimizing power consumption and production costs for biomedical applications. The proposed system integrates a low-power readout integrated circuit (ROIC) capable of processing large-amplitude sensor signals using a 1.2 V ADC, significantly reducing the power consumption compared with conventional high-voltage solutions. To address the inherent limitations of single-core/single-thread microcontrollers, an optimized Wi-Fi communication algorithm is implemented, enabling real-time data transmission and accurate signal reconstruction without data loss. Experimental validation using a hydrogen gas detection setup demonstrated that the system achieves less than 0.15% error in reconstructed signals, while substantially reducing overall power consumption and component cost. Comparative analysis confirms that the proposed approach achieves a performance comparable to conventional systems while offering significant reductions in energy usage and hardware expense. These results demonstrate the feasibility of a scalable, low-cost solution for portable gas sensing, particularly in biomedical applications requiring precise and reliable monitoring.
AB - This study presents a portable gas sensor system that achieves high performance while minimizing power consumption and production costs for biomedical applications. The proposed system integrates a low-power readout integrated circuit (ROIC) capable of processing large-amplitude sensor signals using a 1.2 V ADC, significantly reducing the power consumption compared with conventional high-voltage solutions. To address the inherent limitations of single-core/single-thread microcontrollers, an optimized Wi-Fi communication algorithm is implemented, enabling real-time data transmission and accurate signal reconstruction without data loss. Experimental validation using a hydrogen gas detection setup demonstrated that the system achieves less than 0.15% error in reconstructed signals, while substantially reducing overall power consumption and component cost. Comparative analysis confirms that the proposed approach achieves a performance comparable to conventional systems while offering significant reductions in energy usage and hardware expense. These results demonstrate the feasibility of a scalable, low-cost solution for portable gas sensing, particularly in biomedical applications requiring precise and reliable monitoring.
KW - adaptive signal processing
KW - biomedical gas sensing
KW - cost-effective sensor system design
KW - low-power readout circuit
KW - portable gas sensor system
KW - single-core MCU optimization
KW - Wi-Fi communication algorithm
UR - https://www.scopus.com/pages/publications/105014381296
U2 - 10.3390/chemosensors13080303
DO - 10.3390/chemosensors13080303
M3 - Article
AN - SCOPUS:105014381296
SN - 2227-9040
VL - 13
JO - Chemosensors
JF - Chemosensors
IS - 8
M1 - 303
ER -