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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Published in | 2021 IEEE International Conference on Smart Computing (SMARTCOMP) pp. 311 - 316 |
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Main Authors | , , , , , , , , , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.08.2021
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Subjects | |
Online Access | Get full text |
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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. |
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ISSN: | 2693-8340 |
DOI: | 10.1109/SMARTCOMP52413.2021.00065 |