Monitoring and Predicting Water Quality in Swimming Pools

Apriandy Angdresey; Lanny Sitanayah; Vandri Josua Abram Sampul

doi:10.25042/epi-ije.082020.05

Apriandy Angdresey Department of Informatics Engineering, Faculty of Engineering, Universitas Katolik De La Salle, Manado
Lanny Sitanayah Department of Informatics Engineering, Faculty of Engineering, Universitas Katolik De La Salle, Manado
Vandri Josua Abram Sampul Department of Informatics Engineering, Faculty of Engineering, Universitas Katolik De La Salle, Manado

DOI: https://doi.org/10.25042/epi-ije.082020.05

Keywords: The Internet of Things, Data Mining, Decision Tree, Iterative Dichotomiser 3

Abstract

Water quality in public swimming pools affects human health. While changing the water too soon is wasteful, postponing changing the dirty water is not hygiene. In this paper, we propose an Internet of Things-based wireless system to monitor and predict water quality in public swimming pools. Our system utilizes an Arduino Uno, an ESP8266 ESP-01 WiFi module, a DS18B20 temperature sensor, a pH sensor, and a turbidity sensor. We predict the water quality using a data mining prediction model, namely the decision tree Iterative Dichotomiser 3 algorithm. We show by experiment that our sensor node and the wireless monitoring system work correctly. We also show by simulation using Weka that we can get 100% accuracy with a kappa statistical value of 1 and 0% error rate.