DOI: https://doi.org/10.14710/jsp.2024.24800

Automated Monitoring System for Rainwater Harvesting Tank at Telkom University

*Erna Sri Sugesti  -  Doctoral Program of Electrical engineering, Telkom University | Telkom University |, Indonesia
Aris Hartaman  -  Asus Department, Telkom University | Telkom University |, Indonesia
Kharisma Bani Adam scopus  -  Energy System Engineering Study Program, Telkom University | Telkom University |, Indonesia
Deni Wahyu Dewanata  -  Asus Department, Telkom University | Telkom University |, Indonesia
Noval Ramadhana Latief  -  Students of Telecommunication Engineering Study Program, Telkom University | Telkom University |, Indonesia
Rafi Fadyan Ananda Sularto  -  Students of Telecommunication Engineering Study Program, Telkom University | Telkom University |, Indonesia
Jeremia Jordan Marbun  -  Students of Telecommunication Engineering Study Program, Telkom University | Telkom University |, Indonesia
Taufan Umbara  -  Director of Asus Department, Telkom University | Telkom University |, Indonesia
Open Access Copyright (c) 2024 Erna Sri Sugesti, Aris Hartaman, Kharisma Bani Adam, Deni Wahyu Dewanata, Noval Ramadhana Latief, Rafi Fadyan Ananda Sularto, Jeremia Jordan Marbun, Taufan Umbara
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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Abstract
The use of ground tank constructed by Telkom University for Rainwater Harvesting (RWH), is limited to environmental maintenance due to concerns regarding the quality of water in the underground tank. Therefore, this research aims to develop a remote monitoring device that uses Internet of Things (IoT) technology to monitor the pH, water surface, submerged materials, and water clarity levels in ground tank. To achieve the requirements, pH, ultrasonic-based volume, Total Dissolved Solids (TDS), and Turbidity sensors were selected due to the IoT connectivity. The enabling device, namely the ESP 32 microcontroller and Blynk platform were installed on monitoring dashboard on a tablet computer with 4GB of RAM. The result showed that calibration of each sensor had good accuracy, except for the Turbidity sensor due unavailable materials. In conclusion, the RWH monitoring system is suitable for use.
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