Avishek Gupta, Md. Mynul Islam, Md. Rafiqul Islam, Zafar Sadek, Tarik Reza Toha, Anupom Mondol, Shaikh Mohammad Mominul Alam
{"title":"Devising an IoT-Based Water Quality Monitoring and pH Controlling System for Textile ETP","authors":"Avishek Gupta, Md. Mynul Islam, Md. Rafiqul Islam, Zafar Sadek, Tarik Reza Toha, Anupom Mondol, Shaikh Mohammad Mominul Alam","doi":"10.1109/ECCE57851.2023.10101616","DOIUrl":null,"url":null,"abstract":"In our country, a great number of industries especially textile industries consume a large amount of water at different textile processes, and at the same time, contaminated water is discharged into the environment at high volume because of a lack of proper monitoring and controlling system. There is a significant number of research works about water quality monitoring and controlling system, which are not automated and also have no notification system for abnormal situations. We propose an IoT-based automatic system with a water quality monitoring device and a pH-controlling device that provides water quality information and transmits data through Wi-Fi and Bluetooth for both online and offline conditions. The monitoring device can detect several important water quality parameters like DO, ORP, TDS, Temperature, EC, and pH. Our device can detect the abnormal value of the water and alarm the users through SMS and Email. The pH controlling device can control pH automatically and dose chemicals at required quantities adaptively in need to neutralize. To improve the sensor value, we calibrated pH, TDS, and EC sensors by developing equations from regression analysis. Between different regressions, we choose polynomial regression (order 2) as it shows the highest coefficient of determination value, which is 0.97655, 0.999, and 0.9999 for pH, TDS, and EC sensors, respectively. We implement our monitoring device in four textile industries and measure the quality parameters of the inlet and outlet points of the effluent treatment plant of each factory. Our monitoring device can detect water quality parameters and can identify between less and well-treated water. This monitoring device can be used at any water treatment plant and the pH controlling device can control the pH of any process, especially a wastewater treatment plant.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECCE57851.2023.10101616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In our country, a great number of industries especially textile industries consume a large amount of water at different textile processes, and at the same time, contaminated water is discharged into the environment at high volume because of a lack of proper monitoring and controlling system. There is a significant number of research works about water quality monitoring and controlling system, which are not automated and also have no notification system for abnormal situations. We propose an IoT-based automatic system with a water quality monitoring device and a pH-controlling device that provides water quality information and transmits data through Wi-Fi and Bluetooth for both online and offline conditions. The monitoring device can detect several important water quality parameters like DO, ORP, TDS, Temperature, EC, and pH. Our device can detect the abnormal value of the water and alarm the users through SMS and Email. The pH controlling device can control pH automatically and dose chemicals at required quantities adaptively in need to neutralize. To improve the sensor value, we calibrated pH, TDS, and EC sensors by developing equations from regression analysis. Between different regressions, we choose polynomial regression (order 2) as it shows the highest coefficient of determination value, which is 0.97655, 0.999, and 0.9999 for pH, TDS, and EC sensors, respectively. We implement our monitoring device in four textile industries and measure the quality parameters of the inlet and outlet points of the effluent treatment plant of each factory. Our monitoring device can detect water quality parameters and can identify between less and well-treated water. This monitoring device can be used at any water treatment plant and the pH controlling device can control the pH of any process, especially a wastewater treatment plant.