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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 2, 2022.
Abstract: A rise in the population of a region implies an increase in water consumption and such a continuous increase in the usage of water worsens wastewater generation by the region. This escalation in wastewater (influent) requires the Wastewater Treatment Plants (WWTPs) to operate efficiently in order to process the demand for sewage disposal (effluent). This research paper is based upon visualizing and analyzing the parameters of influent like COD, BOD, TSS, pH, MPN and also, the parameters of effluent like COD, BOD, DO, pH and MPN of Bharwara WWTP situated in Lucknow, India which is the largest UASB-based wastewater treatment plant in Asia. We also design and implement an initial model using the machine learning based techniques to analyze as well as predict the parameters of influent and effluent of the WWTP. Model Performance is measured using Mean Squared Error (MSE) and Correlation Coefficient (R). For analyzing and designing the model, the parameters of influent and effluent have been collected over a period of 26 months on a daily basis covering the variations between seasons and climate. As a result, the model shall provide a better quality of effluent along with consuming the plant resources in an efficient manner.
Parul Yadav, Aditya Chaudhary, Anand Keshari, Nitish Kumar Chaudhary, Priyanshu Sharma, Kumar Saurabh and Brijesh Singh Yadav, “Data Visualization of Influent and Effluent Parameters of UASB-based Wastewater Treatment Plant in Uttar Pradesh” International Journal of Advanced Computer Science and Applications(IJACSA), 13(2), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130271
@article{Yadav2022,
title = {Data Visualization of Influent and Effluent Parameters of UASB-based Wastewater Treatment Plant in Uttar Pradesh},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130271},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130271},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {2},
author = {Parul Yadav and Aditya Chaudhary and Anand Keshari and Nitish Kumar Chaudhary and Priyanshu Sharma and Kumar Saurabh and Brijesh Singh Yadav}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.