Proceedings of the 11th International Applied Business and Engineering Conference, ABEC 2023, September 21st, 2023, Bengkalis, Riau, Indonesia

Research Article

Water Quality Monitoring System of Bengkalis PDAM Based on The Internet of Things

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  • @INPROCEEDINGS{10.4108/eai.21-9-2023.2342920,
        author={Muhamad  Nasir and Tengku  Musri and Eva  Kurniawaty},
        title={Water Quality Monitoring System of Bengkalis PDAM Based on The Internet of Things},
        proceedings={Proceedings of the 11th International Applied Business and Engineering Conference, ABEC 2023, September 21st, 2023, Bengkalis, Riau, Indonesia},
        publisher={EAI},
        proceedings_a={ABEC},
        year={2024},
        month={2},
        keywords={monitoring system pdam water internet of things quality},
        doi={10.4108/eai.21-9-2023.2342920}
    }
    
  • Muhamad Nasir
    Tengku Musri
    Eva Kurniawaty
    Year: 2024
    Water Quality Monitoring System of Bengkalis PDAM Based on The Internet of Things
    ABEC
    EAI
    DOI: 10.4108/eai.21-9-2023.2342920
Muhamad Nasir1,*, Tengku Musri1, Eva Kurniawaty1
  • 1: Politeknik Negeri Bengkalis
*Contact email: nasir@polbeng.ac.id

Abstract

PDAM is a company engaged in the distribution of clean water for the community. The water quality monitoring system for the Bengkalis PDAM for each household is still carried out manually. That is, it is still monitored by having to see it directly. If the monitoring system is replaced using a more modern design, it will greatly facilitate the users. One of the systems proposed to overcome these problems is an internet-based monitoring system of things. This system uses turbidity, pH, and LM35 sensors to detect water turbidity, water acidity and water temperature, which can be accessed anywhere and anytime. This system makes it easy to monitor PDAM water quality. The system created uses the Django base python framework and SQLite as the database. This system was tested on several PDAM water samples in Bengkalis City. The results of the output data of the turbidity sensor, pH sensor and LM35 sensor are displayed on the website as graphs and numbers.