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Identification of Spatially Extended Pollution Sources by Means of Blind Sources Separation Algorithms

[+] Author Affiliations
Luca Cedola, Mauro Villarini, Enzo Fioriti

Università degli Studi di Roma “La Sapienza”, Rome, Italy

Maurizio Carlini

Università degli Studi della Tuscia, Viterbo, Italy

Paper No. ESDA2006-95586, pp. 463-467; 5 pages
doi:10.1115/ESDA2006-95586
From:
  • ASME 8th Biennial Conference on Engineering Systems Design and Analysis
  • Volume 3: Dynamic Systems and Controls, Symposium on Design and Analysis of Advanced Structures, and Tribology
  • Torino, Italy, July 4–7, 2006
  • ISBN: 0-7918-4250-9 | eISBN: 0-7918-3779-3
  • Copyright © 2006 by ASME

abstract

Blind Source Separation (BSS) is able to recover original source signals from their mixtures. Well-known sources are brain electric activity, acoustic phenomena, earthquakes. Here we apply BSS to air pollution analysis identificating gas emissions using only sensor measurements mutually and statistically independent. This application consents an independent, low cost and real time environmental monitoring system. Besides, a real-world pollution case from an industrial region of central Italy is presented and processed by BSS.

Copyright © 2006 by ASME

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