Self-Adaptive Structure Enabled Energy-Efficient PM2.5 Sensing

This paper explores leveraging a special structure design of sensor enclosures to reduce PM2.5 sensing energy consumption. Finegrained air quality monitoring is essential for public health and climate. However, existing air quality measurements are limited. For example, precise measurements from the regulatory station have very limited spatial coverage. The low-cost citizen science sensor network lacks coverage in socio-economically disadvantaged regions. Mobile platforms, such as vehicles or drones, provide more efficient sampling for air quality information. However, complicated vehicle power integration/retrofitting and high cost make it inaccessible to the general public. Therefore, we propose SEEES, a Structure-Enabled Energy-Efficient Sensing solution for PM2.5 sensing that leverages a self-adaptive elastic valve that replaces air pumps or fans to regulate the airflow input. As a proof-of-concept, SEEES has been put through preliminary experiments and simulation to verify the feasibility of battery-less PM2.5 sensing.

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Publication Details

Published
2025-05-06
DOI
https://doi.org/10.1145/3722572.3727928
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
Field-Weighted Citation Impact
0.00

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article

Self-Adaptive Structure Enabled Energy-Efficient PM2.5 Sensing

Shijia Pan, Dong Yoon Lee, Shubham Rohal, J. Zhang et al.
Gas Sensing Nanomaterials and Sensors
article

Self-Adaptive Structure Enabled Energy-Efficient PM2.5 Sensing

Shijia Pan, Dong Yoon Lee, Shubham Rohal, J. Zhang, Farren Montgomery-Yale, Stephen Schertz
article en

Abstract

This paper explores leveraging a special structure design of sensor enclosures to reduce PM2.5 sensing energy consumption. Finegrained air quality monitoring is essential for public health and climate. However, existing air quality measurements are limited. For example, precise measurements from the regulatory station have very limited spatial coverage. The low-cost citizen science sensor network lacks coverage in socio-economically disadvantaged regions. Mobile platforms, such as vehicles or drones, provide more efficient sampling for air quality information. However, complicated vehicle power integration/retrofitting and high cost make it inaccessible to the general public. Therefore, we propose SEEES, a Structure-Enabled Energy-Efficient Sensing solution for PM2.5 sensing that leverages a self-adaptive elastic valve that replaces air pumps or fans to regulate the airflow input. As a proof-of-concept, SEEES has been put through preliminary experiments and simulation to verify the feasibility of battery-less PM2.5 sensing.

University of California, Merced (US), Green Valley High School (US)
University of California Merced
Affordable and clean energy
Openalex Percentile: Top 89%
Gas Sensing Nanomaterials and Sensors
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Self-Adaptive Structure Enabled Energy-Efficient PM2.5 Sensing — Shijia Pan, Dong Yoon Lee, et al. · (2025) | TGRS Research Map | TGRS