Smart Drainage Monitoring and Clog Identification Using IOT

Authors

  • Shruthi Shri A. S.  Department of Electronics and Communication Engineering Kongu Engineering College Perundurai, Tamil Nadu, India

Keywords:

Clog detection, float sensors, and IOT(Internet of Things)

Abstract

The Sewage Outlet System monitoring has been a difficult and tedious task. A clog in the sewage pipe will lead to overflow and stagnation of sewer water along the streets. The environmental issues and diseases that arise to sewage stagnation are disastrous. The irregular maintenance of sewage Outlet System has caused huge catastrophes in the state claiming many human lives. The project proposes a novel mechanism to monitor sewage outlet pipes. The clog in the pipe will be sent to the remote server by means of IOT. Another advantage of the project is that clogs in drainage pipes can be detected as soon as it is formed rather than detecting it after the sewage water starts overflowing into the roads causing serious inconvenience to the public and revenue loss to the government. The system, in addition, does not require any human labor to detect the clog. Thus the clogs can be detected easily without any human interference. Therefore, a variety of sensors and clog detecting modules are placed in various positions along the drainage network and the data is collected using IOT. Thus the project will provide an efficient means of monitoring the drainage or sewage outlet system providing a way for the smarter sewer system and detecting the clog formation at its very existence, and helps maintain a clean environment, avoiding deadly contagious diseases helping the entire human race lead a healthy peaceful life.

References

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Published

2017-12-31

Issue

Section

Research Articles

How to Cite

[1]
Shruthi Shri A. S., " Smart Drainage Monitoring and Clog Identification Using IOT, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 8, pp.649-653, November-December-2017.