Advancements in Smart Electrochemical Gas Sensors: Bridging IoT, Self-powering, and Machine Learning for Healthcare

Abstract

Electrochemical gas sensors have attracted significant attention due to their high sensitivity and selectivity in detecting various gases. These sensors are critical in personal health management, with applications in breath analysis, air quality monitoring, and toxic substance detection. Recent advancements in microelectronics, materials science and computational technologies have driven the development of smart electrochemical gas sensors, enhancing their functionality with improved miniaturization, real-time data analysis, and remote monitoring capabilities. Furthermore, the integration of the Internet of Things, self-powered technologies and machine learning has expanded the potential of these sensors, enabling smart healthcare systems to adapt to complex and dynamic environments just as humans do. In this paper, the basic sensing mechanism, detection methods and the latest development of three kinds of electrochemical gas sensors are reviewed. In addition, we studied their applications in breath analysis, air quality monitoring, and toxic substance detection. Finally, current challenges, limitations, and future prospects are addressed, emphasizing the need for improved stability, selectivity, and energy efficiency to realize the next generation of electrochemical gas sensors.