Tu-SML-05 - Multi-Season Field Evaluation of a Temperature-Modulated SMOX Sensor Array for NO2 and O3 Monitoring

Event

EUROSENSORS 2026
2026-09-06 - 2026-09-09
Zurich

Band

Poster

Chapter

Signal Analysis, Machine Learning, Physics-Informed Machine Learning And Artificial Intelligence For Sensing

Author(s)

F. Schmidt, A. Kobald, U. Weimar, N. Barsan - University of Tuebingen,Tuebingen (Germany), P. Tosato, A. Gaiardo - Bruno Kessler Foundation,Trento (Italy)

Pages

704 - 705

DOI

10.5162/eurosensors2026/Tu-SML-05

ISBN

978-3-910600-12-6

Price

free

Abstract

Semiconducting metal oxide gas sensor arrays, when combined with temperature modulation, have demonstrated promising performance in laboratory tests for outdoor air-quality applications. However, their suitability for long-term field deployment across multiple seasons remains insufficiently validated. In this study, the system was deployed alongside an air-quality reference station over 17 months. The model for predicting NO2 and O3 achieved a normalized root-mean-square error of less than 8%, demon- strating robust multi-season outdoor performance.