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IoT and WSN based Effluent Treatment Plant Monitoring System

EasyChair Preprint no. 5023

19 pagesDate: February 25, 2021

Abstract

Contaminated water became a major issue for our country from the last few decades. One of the main reasons behind this scenario is urbanization and industrialization. Every industry should have an Effluent Treatment Plant (ETP) for treating industrial wastewater and safe disposal to the environment. We implement a system that monitors whether an industry uses ETP or not. To monitor ETP, we need to monitor the untreated wastewater quality. The traditional way offers us a method that is time-consuming and inefficient. To solve this problem, we adopt a model based on Wireless Sensor Networking (WSN), which allows us to keep track of the water quality parameters in real-time. This paper proposes a water quality monitoring system that uses WSN and Internet of Things (IoT) based devices to monitor different parameters of water: temperature by a temperature sensor, turbidity by a turbidity sensor, and pH by a pH sensor. Moreover, the microcontroller of Arduino Uno R3 collects the parameter values from these sensors and transmits the values to the IoT-based cloud server using the GSM module. The GSM module also used to alert the supervisors by sending SMS in case of an emergency. Integrating modules such as sensors, Arduino Uno R3, GSM module, enhances the purpose of the desired system. Finally, we calculate the Water Quality Index (WQI) for the pH and turbidity data to report the water quality status. Also, we compare the WQI status with our cloud status, and it shows an excellent performance.

Keyphrases: GSM module, IoT, real-time application, sensor, water quality, WQI, WSN

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:5023,
  author = {Md. Saikat Islam Khan and Anichur Rahman and Sifatul Islam and Mostofa Kamal Nasir and Shahab S. Band and Amir Mosavi},
  title = {IoT and WSN based Effluent Treatment Plant Monitoring System},
  howpublished = {EasyChair Preprint no. 5023},

  year = {EasyChair, 2021}}
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