Abstract
Water is a fundamental and essential requirement for human existence, as nearly 70% of our body is constituted with water. Consumption of deteriorated water quality can lead to the cause of various life-threatening diseases such as Cholera, typhoid, etc. Annually, an estimated 3.4 million individuals die from drinking polluted water. Despite numerous technological advancements, traditional methods continue to be employed for monitoring water quality. These methods are very inefficient as they are quite time-consuming, expensive, and cannot provide real-time information for monitoring water quality. Therefore, this article suggested a model designed on the Internet of Things (IoT) that addresses the existing underlying water quality issues and could replace the conventional way of water monitoring systems. To check the water quality parameters, several sensors (SNs) have been used to collect the real-time data and transfer further for analysis purposes via a range of machine learning techniques, including XGBoost, random forest, AdaBoost, and decision tree. These methods exhibit robust performance in terms of accuracy, precision, recall, and f1 score. Through the combination of the IoT and ML, the proposed real-time water quality monitoring (WQM) system offers continuous monitoring, analysis, and prediction of water quality parameters. The integration of these technologies and outcomes of experimental works prove that the proposed model can help to safeguard the availability of potable and clean water resources for present and future generations.
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Data Availability
The data and material that support the findings of this study are available from the corresponding author, Subhasish Banerjee, upon reasonable request.
References
Benedict S. Serverless blockchain-enabled architecture for iot societal applications. IEEE Trans Comput Social Syst. 2020;7(5):1146–58.
Curry E, Hasan S, Kouroupetroglou C, Fabritius W, ul Hassan U, Derguech W. Internet of things enhanced user experience for smart water and energy management. IEEE Internet Comput. 2018;22(1):18–28.
Deep B, Mathur I, Joshi N. Coalescing IoT and Wi-Fi technologies for an optimized approach in urban route planning. Environ Sci Pollut Res. 2020;27:34434–41.
Demissie H, Lu S, Jiao R, Liu L, Xiang Y, Ritigala T, Wang D. Advances in micro interfacial phenomena of adsorptive micellar flocculation: principles and application for water treatment. Water Res. 2021;202:117414.
Li M, He P, Zhao L. Dynamic load balancing applying water-filling approach in smart grid systems. IEEE Internet Things J. 2017;4(1):247–57.
Di Luccio D, Riccio A, Galletti A, Laccetti G, Lapegna M, Marcellino L, Montella R. Coastal Marine data crowdsourcing using the internet of floating things: improving the results of a water quality model. IEEE Access. 2020;8:101209–23.
Wang D, Xiang H. Composite control of post-chlorine dosage during drinking water treatment. IEEE Access. 2019;7:27893–8.
Ajith JB, Manimegalai R, Ilayaraja V. (2020, February). An IoT based smart water quality monitoring system using cloud. In 2020 International conference on emerging trends in information technology and engineering (ic-ETITE) (pp. 1–7). IEEE.
Anuradha T, Bhakti CR, Pooja D. IoT based low cost system for monitoring of water quality in real time. Int Res J Eng Technol (IRJET). 2018;5(5):60–72.
Sengupta B, Sawant S, Dhanawade M, Bhosale S. Water quality monitoring using IoT. Int Res J Eng Technol. 2019;6(6):695–701.
Geetha S, Gouthami SJSW. Internet of things enabled real time water quality monitoring system. Smart Water. 2016;2(1):1–19.
Hamid SA, Rahim AMA, Fadhlullah SY, Abdullah S, Muhammad Z, Leh NAM. (2020, August). IoT based water quality monitoring system and evaluation. In 2020 10th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) (pp. 102–106). IEEE.
Kumar MJV, Samalla K. Design and Development of water quality monitoring system in IoT. Int J Recent Technol Eng (IJRTE). 2019;7(5S3):2277–3878.
Mukta M, Islam S, Barman SD, Reza AW, Khan MSH. (2019, February). IoT based smart water quality monitoring system. In 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS) (pp. 669–673). IEEE.
Pasika S, Gandla ST. Smart water quality monitoring system with cost-effective using IoT. Heliyon. 2020;6(7):e04096.
Konde S, Deosarkar S. IoT based water quality monitoring system, in Proceedings (ICCIP), 2(3), pp 202, 2020.
Sugapriyaa T, Rakshaya S, Ramyadevi K, Ramya M, Rashmi PG. Smart water quality monitoring system for real-time applications. Int J Pure Appl Math. 2018;118(7):1363–9.
Priya SK, Shenbagalakshmi G, Revathi T. (2018, April). IoT based automation of real time in-pipe contamination detection system in drinking water. In 2018 International conference on communication and signal processing (ICCSP) (pp. 1014–1018). IEEE.
Moparthi NR, Mukesh C, Sagar PV. (2018, February). Water quality monitoring system using IoT. In 2018 Fourth international conference on advances in electriclectronics, information, communication and bio-informatics (AEEICB) (pp. 1–5). IEEE.
Olatinwo SO, Joubert TH. Enabling communication networks for water quality monitoring applications: a survey. IEEE Access. 2019;7:100332–62.
Serra H, Bastos I, de Melo JL, Oliveira JP, Paulino N, Nefzaoui E, Bourouina T. A 0.9-V analog-to-digital acquisition channel for an IoT water management sensor node. IEEE Trans Circuits Syst II Express Briefs. 2019;66(10):1678–82.
AlMetwally SAH, Hassan MK, Mourad MH. Real time internet of things (IoT) based water quality management system. Procedia CIRP. 2020;91:478–85.
Huan J, Li H, Wu F, Cao W. Design of water quality monitoring system for aquaculture ponds based on NB-IoT. Aquacult Eng. 2020;90:102088.
Di Luccio, D., Riccio, A., Galletti, A., Laccetti, G., Lapegna, M., Marcellino, L., ... & Montella, R. (2020). Coastal marine data crowdsourcing using the Internet of Floating Things: Improving the results of a water quality model. IEEE Access, 8, 101209-101223.
Lakshmikantha V, Hiriyannagowda A, Manjunath A, Patted A, Basavaiah J, Anthony AA. IoT based smart water quality monitoring system. Global Transitions Proc. 2021;2(2):181–6.
Roy SK, Misra S, Raghuwanshi NS, Das SK. AgriSens: IoT-based dynamic irrigation scheduling system for water management of irrigated crops. IEEE Internet Things J. 2020;8(6):5023–30.
Bhardwaj A, Dagar V, Khan MO, Aggarwal A, Alvarado R, Kumar M, Proshad R. Smart IoT and machine learning-based framework for water quality assessment and device component monitoring. Environ Sci Pollut Res. 2022;29(30):46018–36.
Adeleke IA, Nwulu NI, Ogbolumani OA. A hybrid machine learning and embedded IoT-based water quality monitoring system. Internet Things. 2023;22:100774.
Jéquier E, Constant F. Water as an essential nutrient: the physiological basis of hydration. Eur J Clin Nutr. 2010;64(2):115–23.
Source/Link. https://www.kaggle.com/datasets/gulabsah23/water-quality-dataset
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Rai, S., Poduval, D.S., Anand, U. et al. An Effective Smart Water Quality Monitoring and Management System Using IoT and Machine Learning. SN COMPUT. SCI. 5, 846 (2024). https://doi.org/10.1007/s42979-024-03208-2
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DOI: https://doi.org/10.1007/s42979-024-03208-2