Review reveals design strategies for room-temperature gas sensors in wearable IoT devices, highlighting the role of surface engineering and AI integration in reducing power consumption.
The rapid expansion of the Internet of Things and wearable electronics demands gas sensors that combine high sensitivity with ultralow power consumption. Traditional metal oxide semiconductor sensors require elevated temperatures (100–400°C) and consume substantial power, creating fundamental barriers for battery‐powered and on‐body applications. Room‐temperature operation addresses these power constraints but introduces challenges from sluggish surface kinetics and weak signal transduction. Surface functionalization strategies such as catalytic decoration and defect engineering can enhance interfacial reactivity and improve molecular selectivity. Heterojunction architectures and field‐effect transistor configurations provide signal amplification through barrier‐controlled charge transport and transconductance gain. Low‐energy activation techniques including photoactivation, pulsed heating, and temperature modulation offer pathways to accelerate surface reactions without continuous thermal input. Artificial intelligence algorithms enable the extraction of complex temporal and spectral features for pattern recognition and drift compensation in dynamic environments. However, translating laboratory prototypes into field‐ready devices requires addressing humidity interference, long‐term baseline stability, and system‐level integration under strict energy budgets. Unlike prior reviews that address these domains in isolation, this review integrates RT sensing mechanisms, low‐energy activation, real‐world deployment strategies, and AI‐enabled signal processing into a unified framework for energy‐constrained IoT and wearable applications.
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Zhou et al. (2026) studied this question.
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