IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device

Laguna de Bay, the largest freshwater lake in the Philippines, provides livelihood to the fishermen and serves as a source of potable water to the locals. However, freshwater quality has degraded, whereas one of the main contributors are Cyanobacteria that produce cyanotoxins. Existing studies that...

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Bibliographic Details
Published in:	E3S web of conferences Vol. 325; p. 4007
Main Authors:	Alejandrino, Lawrence D., Jocson, Jessica Joy D., Mirarza, Micah Romina R., Dimaunahan, Ericson D., Garcia, Ramon G, Valiente, Flordeliza L
Format:	Journal Article Conference Proceeding
Language:	English
Published:	Les Ulis EDP Sciences 2021
Subjects:	Algorithms Cyanobacteria Drinking water Estimation Freshwater lakes Microcystis Spectrophotometry Support vector machines Water analysis Water sampling
Online Access:	Get full text
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Summary:	Laguna de Bay, the largest freshwater lake in the Philippines, provides livelihood to the fishermen and serves as a source of potable water to the locals. However, freshwater quality has degraded, whereas one of the main contributors are Cyanobacteria that produce cyanotoxins. Existing studies that uses a similar device are either too expensive or too bulky. The purpose of this study is to estimate the cyanobacteria concentration by using a low-cost 16-channel spectrophotometric device to determine the level of severity efficiently. Using Linear Regression, the dataset is modelled by the algorithm to estimate the number of cyanobacteria present on the water sample, while Support Vector Machine (SVM) algorithm for severity level classifier. This study achieved high accuracy in estimating the cyanobacteria using linear regression and classifying the level of severity by support vector machine.
ISSN:	2267-1242 2555-0403 2267-1242
DOI:	10.1051/e3sconf/202132504007