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1711919 Vol 9 · Issue 5 Download Paper

IoT-Based Smart Water Quality Monitoring System Architectures, Challenges, and Future Trends

Ravi Khile Shravani Karvande Pradnya Katbane Saniya Shaikh

Subject area: Science,Engineering and Technology  ·  Area of research: Blockchain, IoT, Smart Water Monitoring

DOI: 10.64388/IREV9I5-1711919

Abstract

Water quality has become one of the most crucial global concerns due to increased pollution from industrial, agricultural, and domestic activities. Conventional laboratory testing methods are time- consuming and lack the capability for continuous analysis. The Internet of Things (IoT) provides a promising solution through distributed sensor networks, wireless connectivity, and intelligent data analytics. This paper provides a comprehensive review of IoT-based smart water quality monitoring systems, focusing on architecture, sensor technologies, communication protocols, cloud integration, and advanced analytics. Twenty-five research articles published between 2016 and 2025 were analyzed to identify technological trends and existing gaps. The study highlights major challenges such as sensor drift, network latency, energy optimization, and data security. Future trends like edge computing, artificial intelligence, and blockchain integration are also explored. This review aims to consolidate existing knowledge and propose design considerations for scalable, efficient, and sustainable water quality monitoring solutions.

Keywords

Internet of Things (IoT), Smart Water Monitoring, Sensor Networks, LoRaWAN, Cloud Analytics, Edge AI, Blockchain, Sustainable Water Systems.

References

[1] WHO, “Drinking-water fact sheet,” World Health Organization,2022.

[2] P. Patel, “Water Quality Monitoring: Challenges and Future Prospects,” Journal of Environmental Engineering,2019.

[3] A. Kumar et al., “IoT-enabled Sensor Network for Water Quality Monitoring,” IEEE Access, 2018.

[4] S. Patil, “Low-Cost IoT-Based Water Monitoring,”IEEEAccess,2016.

[5] R. Rathod et al., “Wireless Water Quality Measurement Using Raspberry Pi,” IJET, 2017.

[6] S. Sharma and A. Mehta, “LoRa-Based Smart Water Monitoring,” MDPI Sensors, 2021.

[7] V. Lakshmikantha, “IoT Smart Water Quality System,” IEEE IoT Conference, 2021.

[8] H. Forhad, “Industrial IoT Water Plant Monitoring,”IEEEAccess,2022.

[9] K. Gupta, “AI-Enabled Water Quality Prediction,”Springer, 2023.

[10] T. Nguyen, “Edge Computing for IoT Water Monitoring,”MDPISensors, 2023.

[11] L. Zhang, “Energy Efficient LoRaWAN for IoT,” IEEE Communications Letters, 2023.

[12] A. Verma, “Blockchain-Assisted IoT Water Systems,” IEEE Transactions on IoT, 2024.

[13] R. Khan et al., “Federated Learning in IoT Water Networks,” Elsevier Journal of Smart Systems, 2025.

[14] M. Reddy et al., “AI-Driven Anomaly Detection for Water Quality,” MDPI Applied Sciences, 2024.

[15] A. Prasad, “Hybrid Fog-Cloud Architecture for IoT Monitoring,” IEEE Sensors Journal, 2022.

[16] P. Akhtar et al., “Security Models for IoT-based Environmental Systems,” Springer IoT Review, 2023.

[17] J. Singh, “Calibration and Error Analysis in IoT Sensors,” IJESRT,2021.

[18] L. Sun, “Digital Twin Integration for Smart Water Networks,” IEEE Transactions on Industrial Informatics, 2024.

[19] A. Kumar, “Green IoT Approaches in Smart Environment Systems,” MDPI Sustainability, 2023.

[20] World Bank, “Water Governance and Smart Cities Report,” World Bank Publications, 2024.

How to cite this paper

Ravi Khile, Shravani Karvande, Pradnya Katbane, Saniya Shaikh "IoT-Based Smart Water Quality Monitoring System Architectures, Challenges, and Future Trends" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 596-607 https://doi.org/10.64388/IREV9I5-1711919
Ravi Khile, Shravani Karvande, Pradnya Katbane, Saniya Shaikh "IoT-Based Smart Water Quality Monitoring System Architectures, Challenges, and Future Trends" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1711919
Ravi Khile, Shravani Karvande, Pradnya Katbane, Saniya Shaikh (2025). IoT-Based Smart Water Quality Monitoring System Architectures, Challenges, and Future Trends. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1711919
Ravi Khile, Shravani Karvande, Pradnya Katbane, Saniya Shaikh "IoT-Based Smart Water Quality Monitoring System Architectures, Challenges, and Future Trends" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1711919
@article{1711919,
      author = {Ravi Khile, Shravani Karvande, Pradnya Katbane, Saniya Shaikh},
      title = {IoT-Based Smart Water Quality Monitoring System Architectures, Challenges, and Future Trends},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {596-607},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1711919.pdf},
      abstract = {Water quality has become one of the most crucial global concerns due to increased pollution from     industrial, agricultural, and domestic activities. Conventional laboratory testing methods are time- consuming and lack the capability for continuous analysis. The Internet of Things (IoT) provides a promising solution through distributed sensor networks, wireless connectivity, and intelligent data analytics. This paper provides a comprehensive review of IoT-based smart water quality monitoring systems, focusing on architecture, sensor technologies, communication protocols, cloud integration, and advanced analytics. Twenty-five research articles published between 2016 and 2025 were analyzed to identify technological trends and existing gaps. The study highlights major challenges such as sensor drift, network latency, energy optimization, and data security. Future trends like edge computing, artificial intelligence, and blockchain integration are also explored. This review aims to consolidate existing knowledge and propose design considerations for scalable, efficient, and sustainable water quality monitoring solutions.},
      keywords = {Internet of Things (IoT), Smart Water Monitoring, Sensor Networks, LoRaWAN, Cloud Analytics, Edge AI, Blockchain, Sustainable Water Systems.},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1711919}
  }