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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Autores principales:	Alejandrino Lawrence D., Jocson Jessica Joy D., Mirarza Micah Romina R., Dimaunahan Ericson D., Garcia Ramon G, Valiente Flordeliza L
Formato:	article
Lenguaje:	EN FR
Publicado:	EDP Sciences 2021
Materias:	Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/5be63988d4864109b5f70866ec9c5fe5
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id	oai:doaj.org-article:5be63988d4864109b5f70866ec9c5fe5
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spelling	oai:doaj.org-article:5be63988d4864109b5f70866ec9c5fe52021-12-02T17:11:57ZIoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device2267-124210.1051/e3sconf/202132504007https://doaj.org/article/5be63988d4864109b5f70866ec9c5fe52021-01-01T00:00:00Zhttps://www.e3s-conferences.org/articles/e3sconf/pdf/2021/101/e3sconf_icst2021_04007.pdfhttps://doaj.org/toc/2267-1242Laguna 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.Alejandrino Lawrence D.Jocson Jessica Joy D.Mirarza Micah Romina R.Dimaunahan Ericson D.Garcia Ramon GValiente Flordeliza LEDP SciencesarticleEnvironmental sciencesGE1-350ENFRE3S Web of Conferences, Vol 325, p 04007 (2021)
institution	DOAJ
collection	DOAJ
language	EN FR
topic	Environmental sciences GE1-350
spellingShingle	Environmental sciences GE1-350 Alejandrino Lawrence D. Jocson Jessica Joy D. Mirarza Micah Romina R. Dimaunahan Ericson D. Garcia Ramon G Valiente Flordeliza L IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device
description	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.
format	article
author	Alejandrino Lawrence D. Jocson Jessica Joy D. Mirarza Micah Romina R. Dimaunahan Ericson D. Garcia Ramon G Valiente Flordeliza L
author_facet	Alejandrino Lawrence D. Jocson Jessica Joy D. Mirarza Micah Romina R. Dimaunahan Ericson D. Garcia Ramon G Valiente Flordeliza L
author_sort	Alejandrino Lawrence D.
title	IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device
title_short	IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device
title_full	IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device
title_fullStr	IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device
title_full_unstemmed	IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device
title_sort	iot-based estimation system for microcystis aeruginosa cyanobacteria in laguna de bay using an arduino-controlled spectrophotometric device
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/5be63988d4864109b5f70866ec9c5fe5
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IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device

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