A False Positive Reduction System For Continuous Water Quality Monitoring

Water monitoring systems continuously working ensure real-time pollutant detection capabilities according to their sensitivity and specificity. It is necessary to balance such features because, although being able to sense several substances is a desired feature, the reduction of false positives is...

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Bibliographic Details
Published in2021 IEEE International Conference on Smart Computing (SMARTCOMP) pp. 311 - 316
Main Authors Bria, A., Ferrigno, L., Gerevini, L., Marrocco, C., Molinara, M., Bruschi, P., Cicalini, M., Manfredini, G., Ria, A., Cerro, G., Simmarano, R., Teolis, G., Vitelli, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2021
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Summary:Water monitoring systems continuously working ensure real-time pollutant detection capabilities according to their sensitivity and specificity. It is necessary to balance such features because, although being able to sense several substances is a desired feature, the reduction of false positives is a primary goal a classification system should have. High false positive makes the system unusable. The current solution enables a 24/7 service with a sampling rate equal to 0.6 Hz. Our goal is to limit false positives to 1 per day, thus achieving 99.99% accuracy at least. In this paper, we add a false positive reduction module to our pre-existent system, aiming to manage false positive boosters as sensor drift and signal oscillations. Obtained results, using a Multi Layer Perceptron classifier, confirm the false positive reduction while keeping high true positive rates.
ISSN:2693-8340
DOI:10.1109/SMARTCOMP52413.2021.00065