A novel approach for detecting alerts in urban pollution monitoring with low cost sensors

Carlo Sansone, Sabato Manfredi, Edmondo Di Tucci, Saverio De Vito, Grazia Fattoruso, Francesco Tortorella

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

The problem of estimating the pollutants in urban areas is one of the most active research in recent years due to the increasing concerns about their influence on human health. Solide state sensors, increasingly small and inexpensive, are being used to build compact multisensor devices. Suffering from sensors instabilities and cross-sensitivities, they need ad-hoc calibration procedures in order to reach satisfying performance levels. In this paper we propose a novel approach based on Nonlinear AutoRegressive eXogenous model (NARX) to estimate pollutants in urban area and detecting alerts with respect to law limits. We compared our proposal with two other techniques, based on a Feed Forward Neural Network and a Semi Supervised Learning approach, respectively. Numerical simulations have been carried out to validate the proposed approach on a real dataset. © 2013 IEEE.
Original languageEnglish
DOIs
Publication statusPublished - 2013
Event2013 2nd IEEE International Workshop on Measurements and Networking, M and N 2013 - , Italy
Duration: 1 Jan 2013 → …

Conference

Conference2013 2nd IEEE International Workshop on Measurements and Networking, M and N 2013
CountryItaly
Period1/1/13 → …

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Sansone, C., Manfredi, S., Di Tucci, E., De Vito, S., Fattoruso, G., & Tortorella, F. (2013). A novel approach for detecting alerts in urban pollution monitoring with low cost sensors. Paper presented at 2013 2nd IEEE International Workshop on Measurements and Networking, M and N 2013, Italy. https://doi.org/10.1109/IWMN.2013.6663783