IoT-Based Smart River Water Quality Monitoring: A Bibliometric Analysis and Research Agenda for Sustainable Environmental Management

This study presents a bibliometric analysis of research on IoT-based river water quality monitoring systems published between 2010 and 2025.  Data retrieved from Scopus (389 documents) were analyzed using VOSviewer to identify publication trends, leading authors, institutions, countries, research themes, and technological developments.  Results show a sharp increase in publications after 2020, reflecting growing global interest in sustainable water management through IoT solutions.  India, Malaysia, and France emerged as major contributors, with notable collaborative clusters across Asia and Europe.  The most monitored parameters are conductivity (99.5%), pH (63.8%), and temperature (35.2%), highlighting their centrality in IoT-based monitoring systems.  Emerging research themes include the integration of AI, machine learning, and blockchain for predictive analytics and secure data management.  While IoT systems offer real-time monitoring, key challenges remain in energy efficiency, data standardization, and long-term field deployment.  This paper highlights current achievements, identifies gaps, and suggests future directions for advancing IoT-based water monitoring as a tool for sustainable environmental management.

IoT
water quality monitoring system
sustainable environmental management
  1. Abbasov R., Karimov R., Jafarova N.  Ecosystem and Socioeconomic Values of Clean Water.  Ecosystem Services in Azerbaijan.  71–121 (2022).
  2. Abu-Zeid M. A.  Water and sustainable development: the vision for world water, life and the environment.  Water Policy.  1 (1), 9–19 (1998).
  3. Arthington A. H., Naiman R. J., McClain M. E., Nilsson C.  Preserving the biodiversity and ecological services of rivers: new challenges and research opportunities.  Freshwater Biology.  55 (1), 1–16 (2010).
  4. Wang H., He G.  Rivers: Linking nature, life, and civilization.  River.  1 (1), 25–36 (2022).
  5. Chakraborty S. K.  River pollution and perturbation: perspectives and processes.  Riverine Ecology.  2, 443–530 (2021).
  6. Saxena V.  Water quality, air pollution, and climate change: investigating the environmental impacts of industrialization and urbanization.  Water, Air, & Soil Pollution.  236, 73 (2025).
  7. Shrivastava D. S., Khan T. K. H., Sunanda M., Paripuranam T. D., Binumol M., Krishnaveni M.  Climate change and its impact on water quality in major river basins worldwide.  International Journal of Environmental Sciences.  11 (8s), 37–47 (2025).
  8. Ahmed U., Mumtaz R., Anwar H., Mumtaz S., Qamar A. M.  Water quality monitoring: from conventional to emerging technologies.  Water Supply.  20 (1), 28–45 (2019).
  9. Belletti B., Rinaldi M., Buijse A. D., Gurnell A. M., Mosselman M.  A review of assessment methods for river hydromorphology.  Environmental Earth Sciences.  73, 2079–2100 (2015).
  10. Campanale C., Savino I., Pojar I., Massarelli C., Uricchio V. F.  A practical overview of methodologies for sampling and analysis of mcroplastics in riverine environments.  Sustainability.  12 (17), 6755 (2020).
  11. Cassidy R., Jordan P.  Limitations of instantaneous water quality sampling in surface-water catchments: comparison with near-continuous phosphorus time-series data.  Journal of Hydrology.  405 (1–2), 182–193 (2011).
  12. Mutunga T., Sinanovic S., Harrison C. S.  Integrating wireless remote sensing and sensors for monitoring pesticide pollution in surface and groundwater.  Sensors.  24 (10), 3191 (2024).
  13. Park J., Kim K. T., Lee W. H.  Recent advances in information and communications technology (ICT) and sensor technology for monitoring water quality.  Water.  12 (2), 510 (2020).
  14. Sathio A. A., Singh V., Anwar S., Vavekanand R.  Real-time industrial water pollution evaluation using edge–cloud IoT architecture and multi-parameter sensing.  NDT.  3 (3), 21 (2025).
  15. Sambas A., Andriana A., Fadzli S. A., Gundara G., Mujiarto, Refiadi G., Rusyn V.  Design and development of microhydro power plant based on the Arduino Uno and Internet of Things (IoT).  Journal of Advanced Research in Micro and Nano Engineering.  28 (1), 60–68 (2025).
  16. Patria L., Sambas A., Sulaiman I. M., Mohamed M. A., Rusyn V., Samila A.  Weed detection on carrots using convolutional neural network and Internet of Thing based smartphone.  Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Srodowiska.  14 (3), 96–100 (2024).
  17. Adjovu G. E., Stephen H., James D., Ahmad S.  Overview of the application of remote sensing in efective monitoring of water quality parameters.  Remote Sensing.  15 (7), 1938 (2023).
  18. Raghul M., Porchelvan P.  A critical review of remote sensing methods for inland water quality monitoring: progress, limitations, and future perspectives.  Water, Air, & Soil Pollution.  235, 159 (2024).
  19. Ramadas M., Samantaray A. K.  Applications of remote sensing and GIS in water quality monitoring and remediation: a state-of-the-art review.  Water Remediation.  225–246 (2017).
  20. Jayaraman P., Nagarajan K. K., Partheeban P., Krishnamurthy V.  Critical review on water quality analysis using IoT and machine learning models.  International Journal of Information Management Data Insights.  4 (1), 100210 (2024).
  21. Flores-Iwasaki M., Guadalupe G. A., Pachas-Caycho M., Chapa-Gonza S., Mori-Zabarburu R. C., Guerrero-Abad J. C.  Internet of Things (IoT) sensors for water quality monitoring in aquaculture systems: a systematic review and bibliometric analysis.  AgriEngineering.  7 (3), 78 (2025).
  22. Chen S.-L., Chou H.-S., Huang C.-H., Chen C.-Y., Li L.-Y., Huang C.-H., Chen Y.-Y., Tang J.-H., Chang W.-H., Huang J.-S.  An intelligent water monitoring IoT system for ecological environment and smart cities.  Sensors.  23 (20), 8540 (2023).
  23. Jabbar W. A., Ting T. M., Hamidun M. F. I., Kamarudin A. H. C., Wu W., Sultan J., Alsewari A. A., Ali M. A. H.  Development of LoRaWAN-based IoT system for water quality monitoring in rural areas.  Expert Systems with Applications.  242, 122862 (2024).
  24. Mounce S. R.  Data science trends and opportunities for smart water utilities.  ICT for Smart Water Systems: Measurements and Data Science.  1–26 (2020).
  25. Quintana D., Felix-Herran L. C., Tudon-Martinez J. C., Lozoya-Santos J. de J.  On smart water system developments: a systematic review.  Water.  17 (17), 2571 (2025).
  26. Zakaria M. I., Jabbar W. A., Sulaiman N.  Development of a smart sensing unit for LoRaWAN-based IoT flood monitoring and warning system in catchment areas.  Internet of Things and Cyber-Physical Systems.  3, 249–261 (2023).