Wearable and IoT-Based Monitoring of Indoor Air Pollutants for Personalized Environmental Exposure Assessment
Keywords:
wearable sensing; Internet of Things; indoor air quality; exposure assessment; environmental governance; low-cost sensorsAbstract
Wearable and Internet of Things based devices are transforming the assessment of personal exposure to indoor air pollutants. Conventional monitoring relies on stationary regulatory networks and occasional personal samplers, which do not capture the microenvironments where most exposure occurs. This paper presents a systems level analysis of wearable and Internet of Things based indoor air quality monitoring, focusing on architectural design, sensor capabilities, data integration, deployment constraints, robustness, fairness, governance, and policy implications. It argues that personalized exposure assessment is not merely a measurement problem but a socio-technical challenge requiring careful alignment of sensing hardware, wireless infrastructure, contextual inference, calibration, and data protection. The discussion reviews exposure assessment and sensor literature, then examines layered architectures comprising wearable nodes, local gateways, edge processing, and cloud based data services. It discusses pollutant sensing technologies and their limitations under realistic indoor conditions, including drift, cross sensitivity, power constraints, and body placement effects. The paper addresses contextual data fusion and exposure modeling, emphasizing uncertainty characterization and interoperability. Deployment considerations include building materials, ventilation, and participatory sensing. Robustness and data quality assurance are framed as continuous processes. The paper further analyzes privacy, fairness, and governance, highlighting the risk that monitoring technologies reproduce unequal exposure burdens while generating sensitive personal data. It concludes with policy and research directions for sustainable, equitable deployment of wearable and Internet of Things based environmental exposure infrastructures.
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