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A Web-Based Approach for Classifying Environmental Pollutants Using Portable E-nose Devices

electronic nose
neural networks
fuzzy
web applications
intelligent systems
Herrero JL, Lozano J, Santos JP, Fernandez JA, Marcelo JIS
IEEE Intell Syst, vol. 31(3), 2016, pp. 108-112
http://dx.doi.org/10.1109/MIS.2016.48

Poor air quality is a major public health concern in both developed and developing countries. Continued exposure to environments with high pollutant content is estimated to cause nearly 2.5 million premature deaths per year all over the world, including 370,000 in Europe. The worldwide concern about pollution is reflected in the development and implementation of increasingly stringent policies to limit the wide range of contaminants that contribute to poor air quality. However, the sensing of these contaminants in a comprehensive, reliable, and low-cost manner still remains a major challenge. Electronic noses are intelligent systems that can classify and quantify different gases and odors. In this article, the authors evaluate which classification approaches are most effective for identifying and distinguishing between environmental pollutants, and they describe a novel Web-based software framework that incorporates these classifiers to detect pollutants.

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