Issue |
E3S Web Conf.
Volume 325, 2021
ICST 2021 – The 2nd Geoscience and Environmental Management Symposium
|
|
---|---|---|
Article Number | 04007 | |
Number of page(s) | 6 | |
Section | Environmental Development Technology | |
DOI | https://doi.org/10.1051/e3sconf/202132504007 | |
Published online | 17 November 2021 |
IoT-based Estimation System for Microcystis aeruginosa Cyanobacteria in Laguna de Bay using an Arduino-controlled Spectrophotometric Device
1
School of Electrical, Electronics and Computer Engineering, Mapua University Manila, Philippines
2
Department of Physics, Mapua University Manila, Philippines
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.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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