Enhanced Leak Detection in Water Distribution System Using IoT

Authors

  • G Sindhu Dept. of Computer Science, Dr.Mahalingam College of Engineering and Technology, Coimbatore, India
  • T Sathya Shanmathi Dept. of Computer Science, Dr.Mahalingam College of Engineering and Technology, Coimbatore, India
  • AV Menakadevi Dept. of Computer Science, Dr.Mahalingam College of Engineering and Technology, Coimbatore, India
  • K Srinivasan Dept. of Computer Science, Dr.Mahalingam College of Engineering and Technology, Coimbatore, India

DOI:

https://doi.org/10.26438/ijcse/v8i2.6973

Keywords:

Global System for Mobile Communication(GSM), Hall Effect Sensor, Raspberry-pi, Leakage Detection

Abstract

Water leakages in underground distribution of water through pipelines are the major issue faced by all. The inspections made by Human resources to find leakage are difficult in the real time. In this project, we propose a leak detection system to continuously monitor the underground water pipelines to make the man work easier. This system detects the leak as soon as any damages made to the pipelines due to several factors such as the pipe’s age, improper installation, and natural disasters. Here the water management staff is informed about the leakages through message. The staff will be able to determine the leak of water and its precise location of the leakage. The system is made up of basic components: sensors, GSM module, Raspberry-pi. Mobile phone’s message and the mail is the alert transmitter of the system to the user and higher authorities in case of water leaks. This project helps the water department workers to identify the underground water leakage in an effective way and reduces the wastage of water which is unnoticed by humans.

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Published

2020-02-28
CITATION
DOI: 10.26438/ijcse/v8i2.6973
Published: 2020-02-28

How to Cite

[1]
G. Sindhu, T. S. Shanmathi, A. Menakadevi, and K. Srinivasan, “Enhanced Leak Detection in Water Distribution System Using IoT”, Int. J. Comp. Sci. Eng., vol. 8, no. 2, pp. 69–73, Feb. 2020.

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Section

Research Article