Smart City Gnosys
Smart city article details
| Title | Development Of An Iot-Based Pipe Water Quality Monitoring And Control System For Smart City |
|---|---|
| ID_Doc | 19653 |
| Authors | Dey A.; Islam M.K.; Dhar S. |
| Year | 2024 |
| Published | 2024 3rd International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2024 |
| DOI | http://dx.doi.org/10.1109/ICAEEE62219.2024.10561879 |
| Abstract | Water is supplied every day from a central reservoir by urban authorities in most of the urban areas. In water reservoirs and pipelines, water can be contaminated by pollutants in different ways. In city areas, people by consuming contaminated water, are susceptible to various diseases. In this work, our goal was to develop a system that would detect contamination, monitor, and control pipe water supply remotely. To achieve this goal, we have developed an Internet of Things (IoT)-based water quality detecting prototype utilizing Arduino and several sensors. These sensors can measure safe and risk-level values of water based on pH, temperature, turbidity, and total dissolved solids (TDS). If any of these parameter values cross the standard limit, then the water supply will automatically turn off and send an alert message using the global system for mobile communications (GSM) module to authorities and consumers. Moreover, users can monitor water quality in real-time on our designed website. So, consumers do not have a chance to drink contaminated water from the pipeline. To measure the proficiency of the developed system, a dataset containing 10,000 data is created from the sensors, then labeled as safe or unsafe to drink based on WHO recommendations. The dataset was trained using different machine-learning algorithms. From our analysis, it is concluded that the decision tree algorithm achieved an accuracy of 99\% on the proposed system. If the system is implemented practically in the water management system, we hope it will decrease many water diseases in a great number and overall service quality will be improved. © 2024 IEEE. |
| Author Keywords | Arduino; IoT; Machine learning; pH; TDS; Turbidity; Water Quality |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
57749  | 0.936 | Teng L.M.; Yusoff K.H.; Mohammed M.N.; Jameel Al-Tamimi A.N.; Sapari N.M.; Alfiras M. | Toward Sustainable Smart Cities: Smart Water Quality Monitoring System Based On Iot Technology | Studies in Systems, Decision and Control, 487 (2024) |
| 21739 | 0.918 | Meenalochani M.; Hariharan T.; Kumar S.V. | Edge Based Device Using Machine Learning For Water Quality Management In A Smart Campus | 8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024 - Proceedings (2024) |
| 7860 | 0.91 | Hemdan E.E.-D.; Essa Y.M.; Shouman M.; El-Sayed A.; Moustafa A.N. | An Efficient Iot Based Smart Water Quality Monitoring System | Multimedia Tools and Applications, 82, 19 (2023) |
| 44383 | 0.899 | Iancu G.; Ciolofan S.N.; Drăgoicea M. | Real-Time Iot Architecture For Water Management In Smart Cities | Discover Applied Sciences, 6, 4 (2024) |
| 33995 | 0.898 | Hanifah H.P.; Supangkat S.H. | Iot-Based River Water Quality Monitoring Design For Smart Environments In Cimahi City | Proceedings of the International Conference on Electrical Engineering and Informatics, 2019-July (2019) |
| 33726 | 0.898 | Jan F.; Min-Allah N.; Düştegör D. | Iot Based Smart Water Quality Monitoring: Recent Techniques, Trends And Challenges For Domestic Applications | Water (Switzerland), 13, 13 (2021) |
| 61494 | 0.898 | Shanmugam K.; Xuen D.T.Z.; Rana M.E.; Aruljodey S. | Water Quality Monitoring System: A Smart City Application With Iot Innovation | Proceedings - International Conference on Developments in eSystems Engineering, DeSE, 2021-December (2021) |
| 11192 | 0.895 | Mishra S.; Anithakumari T.; Jain O. | Automated Detection Of Water Quality In Smart Cities Using Various Sampling Techniques | Sustainable Farming through Machine Learning Enhancing: Productivity and Efficiency (2024) |
| 25761 | 0.895 | Zyoud S. | Exploring The Promising Role Of Internet Of Things In Urban Water Systems: A Comprehensive Global Analysis Of Insights, Trends, And Research Priorities | Discover Internet of Things, 5, 1.0 (2025) |
| 61495 | 0.895 | Omambia A.; Maake B.; Wambua A. | Water Quality Monitoring Using Iot & Machine Learning | 2022 IST-Africa Conference, IST-Africa 2022 (2022) |