Open AccessWeb-Based Automated Rainwater Storage and Water Quality Monitoring Design Using K-Nearest Neighbor Method
Author(s) -
Hendra Jatnika,
Yudhi S. Purwanto,
Moch. Farid Rifai,
Rian Hasiando Silaen
Publication year - 2021
Publication title -
jurnal e-komtek
Language(s) - English
Resource type - Journals
eISSN - 2622-3066
pISSN - 2580-3719
DOI - 10.37339/e-komtek.v5i1.551
Subject(s) - rainwater harvesting , turbidity , water quality , container (type theory) , environmental science , population , water resources , environmental engineering , computer science , engineering , mechanical engineering , ecology , oceanography , demography , sociology , biology , geology
Clean water is a basic human need that is used for daily activities. However, as the population increases, the need for water also increases. One method of conserving water resources is Rainwater Storage. Conventional rainwater storage cannot be appropriately monitored, maintain water quality, and only works like a container, which, if left to continue, can result in the collected rainwater becoming a source of disease and dangerous for users. This research aims to create an automatic rainwater collection system and water quality monitoring that can control the flow of water that will enter the reservoir to keep the water entering the reservoir of good quality. In the manufacture of this system, three sensors are used, including a pH sensor, a water turbidity sensor, and a TDS (Total Dissolved Solids) sensor. In determining water quality, the k-Nearest Neighbor (k-NN) method is used to classify whether the water is feasible, less feasible, or not suitable for consumption. Data transmission uses the ESP8266 WiFi module, and monitoring data can be viewed on the website. Testing the system using an experimental method, and in testing, it is found that this system can classify water quality with an accuracy rate of 70%.