An IoT-Enabled System for Water Conservation, Quality Detection, and Leakage Control System
DOI:
https://doi.org/10.15662/IJEETR.2026.0802203Keywords:
Internet of Things (IoT), water management, leakage detection, water quality monitoring, flow sensors, turbidity sensor, total dissolved solids (TDS), Wi-Fi communication, cloud monitoring, automatic motor controlAbstract
This study addresses the growing challenges in water management arising from population growth, urbanization, and inefficient utilization of water resources. Traditional monitoring systems largely rely on manual supervision and periodic inspections, which often fail to identify leakages and water quality degradation at an early stage, resulting in significant water wastage and potential health risks. The project proposes an IoT-enabled water conservation system emphasizing real-time leakage detection and basic water quality monitoring. The system integrates flow sensors to detect leakage through inlet and outlet flow comparison, along with total dissolved solids (TDS) and turbidity sensors for assessing water quality parameters. Collected data is displayed locally and transmitted to a cloud platform for remote access, while automatic motor control is implemented to minimize water wastage during abnormal conditions. Wi-Fi communication is employed to support real time data transmission and mobile application access. Although alternative technologies such as ZigBee and Sigfox offer low-power and long-range communication, they were not adopted due to increased system cost, network complexity, and limited real-time data support. The proposed system aims to deliver a low-cost, reliable, and efficient solution tailored for small-scale residential and institutional applications. This study guides IoT practitioners in integrating automation and sustainability in water management
References
[1] R. S. Mathubala, M. Manasha, N. V. Nishitha, J. Thiyaa Varsini, and M. S. Vaishnavi, "IoT based water monitoring and conservation system”, International Journal of Advanced Research in Science, Communication and Technology (IJARSCT) International Open-Access, Double-Blind, Peer-Reviewed, Refereed, Multidisciplinary Online Journal Volume 5, Issue 3, March 2025.
[2] S. J, P. A. S. K, V. X. S, O. R. M. R, M. M and S. K, "Water
Leakage Detection and Recognition System," 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), Bengaluru, India, 2025, pp. 1020-1028, doi: 10.1109/IDCIOT64235.2025.10915052.
[3] R. Manwatkar, N. Chamate, and P. Malame, "IoT based water quality monitoring system," International Journal of Advanced Research in Science, Communication and Technology (IJARSCT) International journal for research Volume 13, Issue 2, 2025 DOI Link: https://doi.org/10.22214/ijraset. 2025.66030 .
[4] Bhoge, Rohit & Holey, Janhavi & Rajput, Vidhan & Rathod, Shardul & Raut, Yash & Nandankar, Praful. (2024). Leveraging IoT for Detecting Power and Water Theft in Urban Environments: A Comprehensive Review. 9. 60-68. E. Farah and I. Shahrour, "Use of data-driven methods for water leak detection and consumption monitoring in a university campus," 2024.
[5] U. G. Sharanya, K. M. Birabbi, B. H. Sahana, D. M. Kumar, N. Sharmila and S. Mallikarjunaswamy, "Design and Implementation of IoT-based Water Quality and Leakage Monitoring System for Urban Water Systems Using Machine Learning Algorithms," 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON), Bengaluru, India, 2024, pp. 1-5, doi: 10.1109/NMITCON62075.2024.10698922..
[6] Alshami, Ahmad & Saleh, Eslam & Elsayed, Moustafa & Eltoukhy, Abdelrahman & Zayed, Tarek. (2024). IoT Innovations in Sustainable Water and Wastewater Management and Water Quality Monitoring: A Comprehensive Review of Advancements, Implications, and Future Directions. IEEE Access. PP. 1-1. 10.1109/ACCESS.2024.3392573.
[7] Essamlali I, Nhaila H, El Khaili M. Advances in machine learning and IoT for water quality monitoring: A comprehensive review. Heliyon. 2024 Mar 13;10(6):e27920. doi: 10.1016/j.heliyon.2024.e27920. PMID: 38533055; PMCID: PMC10963334.
[8] Sushma, N. & H N, Suresh & Jayaramu, Mohana & Srinivasu, Parvathaneni Naga & Bhoi, Akash Kumar & Barsocchi, Paolo. (2023). A Unified Metering System Deployed for Water and Energy Monitoring in Smart City. IEEE Access. PP. 1-1. 10.1109/ACCESS.2023.3299825.
[9] F. Ebisi, I. P. Nikolakakos, J. V. Karunamurthi, A. N. Ahmed Binahmed Alnuaimi, E. Al Buraimi and S. Alblooshi, "Machine Learning Schemes for Leak Detection in IoT-enabled Water Transmission System," 2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD), Manama, Bahrain, 2023, pp. 1-7, doi: 10.1109/ITIKD56332.2023.10100175.
[10] Islam, M. R., Azam, S., Shanmugam, B., & Mathur, D. (2023). An Intelligent IoT and ML-Based Water Leakage Detection System. IEEE Access, 11, 123625-123649.
https://doi.org/10.1109/ACCESS.2023.3329467B.
[11] Dwarakanath, P. Kalpana Devi, A. Ranjith Kumar, A. S. M. Metwally, G. A. Ashraf, B. L. Thaminen, and others, "Smart IoT- based water treatment with a supervisory control and data acquisition (SCADA) system process," 2023.
[12] C.Nagarajan and M.Madheswaran - ‘Stability Analysis of Series Parallel Resonant Converter with Fuzzy Logic Controller Using State Space Techniques’- Taylor &Francis, Electric Power Components and Systems, Vol.39 (8), pp.780-793, May 2011. DOI: 10.1080/15325008.2010.541746
[13] C.Nagarajan and M.Madheswaran - ‘Experimental verification and stability state space analysis of CLL-T Series Parallel Resonant Converter’ - Journal of Electrical Engineering, Vol.63 (6), pp.365-372, Dec.2012. DOI: 10.2478/v10187-012-0054-2
[14] C.Nagarajan and M.Madheswaran - ‘Performance Analysis of LCL-T Resonant Converter with Fuzzy/PID Using State Space Analysis’- Springer, Electrical Engineering, Vol.93 (3), pp.167-178, September 2011. DOI 10.1007/s00202-011-0203-9
[15] S.Tamilselvi, R.Prakash, C.Nagarajan,“Solar System Integrated Smart Grid Utilizing Hybrid Coot-Genetic Algorithm Optimized ANN Controller” Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering, DOI10.1007/s40998-025-00917-z,2025
[16] S.Tamilselvi, R.Prakash, C.Nagarajan,“ Adaptive sliding mode control of multilevel grid-connected inverters using reinforcement learning for enhanced LVRT performance” Electric Power Systems Research 253 (2026) 112428, doi.org/10.1016/j.epsr.2025.112428
[17] S.Thirunavukkarasu, C. Nagarajan, 2024, “Performance Investigation on OCF and SCF study in BLDC machine using FTANN Controller," Journal of Electrical Engineering And Technology, Volume 20, pages 2675–2688, (2025), doi.org/10.1007/s42835-024-02126-w
[18] C. Nagarajan, M.Madheswaran and D.Ramasubramanian- ‘Development of DSP based Robust Control Method for General Resonant Converter Topologies using Transfer Function Model’- Acta Electrotechnica et Informatica Journal , Vol.13 (2), pp.18-31,April-June.2013, DOI: 10.2478/aeei-2013-0025.
[19] C.Nagarajan and M.Madheswaran - ‘DSP Based Fuzzy Controller for Series Parallel Resonant converter’- Springer, Frontiers of Electrical and Electronic Engineering, Vol. 7(4), pp. 438-446, Dec.12. DOI 10.1007/s11460-012-0212-0.
[20] C.Nagarajan and M.Madheswaran - ‘Experimental Study and steady state stability analysis of CLL-T Series Parallel Resonant Converter with Fuzzy controller using State Space Analysis’- Iranian Journal of Electrical & Electronic Engineering, Vol.8 (3), pp.259-267, September 2012.
[21] C.Nagarajan and M.Madheswaran, “Analysis and Simulation of LCL Series Resonant Full Bridge Converter Using PWM Technique with Load Independent Operation” has been presented in ICTES’08, a IEEE / IET International Conference organized by M.G.R.University, Chennai.Vol.no.1, pp.190-195, Dec.2007
[22] Suganthi Mullainathan, Ramesh Natarajan, “An SPSS and CNN modelling based quality assessment using ceramic materials and membrane filtration techniques”, Revista Materia (Rio J.) Vol. 30, 2025, DOI: https://doi.org/10.1590/1517-7076-RMAT-2024-0721
[23] M Suganthi, N Ramesh, “Treatment of water using natural zeolite as membrane filter”, Journal of Environmental Protection and Ecology, Volume 23, Issue 2, pp: 520-530,2022
[24] Boujelben, M., Benmessaoud, Z., Abid, M., & Elleuchi, M. (2023). An efficient system for water leak detection and localization based on IoT and lightweight deep learning. Internet of Things, 24, 100995. https://doi.org/10.1016/j.iot.2023. 100995.
[25] T. Tejaswi, C. Manoj, P. Venkata Daivakeshwar Naidu, T. Santhosh, P. Venkata Sai Akhil and V. Ganesan, "Nexus of Water Quality prediction by ANN," 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), Chennai, India, 2022, pp. 1-5, doi: 10.1109/ICSES55317.2022.9914054.
[26] . Jan, Farmanullah & Min Allah, Nasro & Saeed, Saqib & Iqbal, Sardar & Ahmed, Rashad. (2022). IoT-Based Solutions to Monitor Water Level, Leakage, and Motor Control for Smart Water Tanks. Water. 14. 309 10.3390/w14030309.
[27] elayudhan, N. K., Pradeep, P., Rao, S. N., Devidas, A. R. and Ramesh, M. V. (2022) 'IoT-enabled water distribution systems a comparative technological review', IEEE Access, (31 pp). doi: 10.1109/ACCESS.2022.3208142.
[28] Islam, Gazi & Hossain, Md & Faruk, Md & Nur, Fernaz & Hasan, Nayeem & Khan, Md. Khalid & Tumpa, Zerin. (2022). IoT-Based Intelligent Gas Leakage Detection and Fire Protection System. International Journal of Interactive Mobile Technologies (iJIM).
16. 49-70. 10.3991/ijim.v16i21.30311.
[29] P Shri Tharanyaa, Abin Satheesan, R Saravanakumar and D Sharmila,”IoT Based Water flow Monitoring, Theft Avoidance and Alert system for Water Supply”, J P Shri Tharanyaa et al 2021 IOP Conf. Ser.: Mater. Sci. Eng. 1084 012122 DOI 10.1088/1757- 899X/1084/1/012122,(2021).
[30] Singh, M., & Ahmed, S. (2020). IoT based smart water management systems: A systematic review. Materials Today: Proceedings, 46, 5211-5218.
https://doi.org/10.1016/j.matpr.2020.08.588S. P. Khabusi and R. Jindal, "Pressure dependent piped water theft detection with IoT- based remote billing and location alert,”.
[31] Ayamga, Michael & Nakpih, Callistus. (2024). An IoT-Based Water Leakage Detection and Localization System. Asian Journal of Research in Computer Science. 17. 1-14. 10.9734/AJRCOS/2024/v17i3421.
[32] Kiran, A., Rubini, P., & Kumar, S. S. (2025). Comprehensive review of privacy, utility and fairness offered by synthetic data. IEEE Access.
[33] Padmapriya, V. M., Thenmozhi, K., Hemalatha, M., Thanikaiselvan, V., Lakshmi, C., Chidambaram, N., & Rengarajan, A. (2025). Secured IIoT against trust deficit-A flexi cryptic approach. Multimedia Tools and Applications, 84(9), 5625-5652.
[34] Pandi Prabha, S., & Rengarajan, A. (2025, February). Decentralized Resource Allocation Model Using Multi-agent Reinforcement Learning for Cloud Environment. In International Conference on Universal Threats in Expert Applications and Solutions (pp. 71-82). Singapore: Springer Nature Singapore.
[35] Anbazhagan, K. (2024). Trustworthy and Adaptive AI Systems for Enterprise Analytics Cybersecurity and Decision Optimization Using API-First and Cloud-Native Architectures. International Journal of Technology, Management and Humanities, 10(03), 65-74.
[36] Gopinathan, V. R. (2025). AI-Powered Kubernetes Orchestration for Complex Cloud-Native Workloads. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(6), 13215-13225.
