Real-Time Machine Learning and Wireless Sensor Network for Coastal Water Quality Monitoring in the Gulf of Aqaba
By: Ahmed Bdour
and Raha M. Alkharabsheh
and Raha M. Alkharabsheh References
- Demetillo AT, Japitana MV, Taboada EB. A system for monitoring water quality in a large aquatic area using wireless sensor network technology. Sust Environ Res. 2019;29:12. DOI: 10.1186/s42834-019-0009-4.
- Trasviña-Moreno C, Blasco R, Marco Á, Casas R, Trasviña-Castro A. Unmanned aerial vehicle based wireless sensor network for marine-coastal environment monitoring. Sensors. 2017;17:460. DOI: 10.3390/s17030460.
- Adu-Manu KS, Tapparello C, Heinzelman W, Katsriku FA, Abdulai J-D. Water quality monitoring using wireless sensor networks. ACM Trans Sens Netw. 2017;13:1-41. DOI: 10.1145/3005719.
- Steimle ET, Hall ML. Unmanned surface vehicles as environmental monitoring and assessment tools. OCEANS. 2006:1-5. DOI: 10.1109/OCEANS.2006.306949.
- Yaroshenko I, Kirsanov D, Marjanovic M, Lieberzeit PA, Korostynska O, Mason A, et al. Real-time water quality monitoring with chemical sensors. Sensors. 2020;20:3432. DOI: 10.3390/s20123432.
- Lopez-Ramirez GA, Aragon-Zavala A. Wireless sensor networks for water quality monitoring: A comprehensive review. IEEE Access. 2023;11:95120-42. DOI: 10.1109/ACCESS.2023.3308905.
- Adamo F, Attivissimo F, Guarnieri Calo Carducci C, Lanzolla AML. A smart sensor network for sea water quality monitoring. IEEE Sens J. 2015;15:2514-22. DOI: 10.1109/JSEN.2014.2360816.
- Hundt M, Schiffer M, Weiss M, Schreiber B, Kreiss CM, Schulz R, et al. Effect of temperature on growth, survival and respiratory rate of larval allis shad Alosa alosa. Knowl Manage Aquat Ecosyst. 2015:27. DOI: 10.1051/kmae/2015023.
- Abdallat R, Bdour A, Haifa AA, Al Rawash F, Almakhadmah L, Hazaimeh S. Development of a sustainable, green, and solar-powered filtration system for E. coli removal and greywater treatment. Glob J Environ Sci Manage. 2024;10:435-50. DOI: 10.22034/gjesm.2024.02.02.
- Shams MY, Elshewey AM, El-kenawy ESM, Ibrahim A, Talaat FM, Tarek Z. Water quality prediction using machine learning models based on grid search method. Multimed Tools Appl. 2024;83:35307-34. DOI: 10.1007/s11042-023-16737-4.
- Essamlali I, Nhaila H, El Khaili M. Advances in machine learning and IoT for water quality monitoring: A comprehensive review. Heliyon. 2024;10:e27920. DOI: 10.1016/j.heliyon.2024.e27920.
- Singh Y, Walingo T. Smart water quality monitoring with iot wireless sensor networks. Sensors. 2024;24:2871. DOI: 10.3390/s24092871.
- Rahu MA, Chandio AF, Aurangzeb K, Karim S, Alhussein M, Anwar MS. Toward design of internet of things and machine learning-enabled frameworks for analysis and prediction of water quality. IEEE Access. 2023;11:101055-86. DOI: 10.1109/ACCESS.2023.3315649.
- Yan X, Zhang T, Du W, Meng Q, Xu X, Zhao X. A comprehensive review of machine learning for water quality prediction over the past five years. J Mar Sci Eng. 2024;12:159. DOI: 10.3390/jmse12010159.
- Zhu L, Zhang C, Zhang C, Zhang Z, Zhou X, Liu W, et al. A new and reliable dual model- and data-driven TOC prediction concept: A TOC logging evaluation method using multiple overlapping methods integrated with semi-supervised deep learning. J Pet Sci Eng. 2020;188:106944. DOI: 10.1016/j.petrol.2020.106944.
- Schmidt W, Raymond D, Parish D, Ashton IGC, Miller PI, Campos CJA, et al. Design and operation of a low-cost and compact autonomous buoy system for use in coastal aquaculture and water quality monitoring. Aquac Eng. 2018;80:28-36. DOI: 10.1016/j.aquaeng.2017.12.002.
- Boonsong W. Embedded wireless dissolved oxygen monitoring based on internet of things platform. J Commun. 2021;16:9:363-8. DOI: 10.12720/jcm.16.9.363-368.
- Nasser N, Ali A, Karim L, Belhaouari S. An efficient wireless sensor network-based water quality monitoring system. 2013 ACS Int Conf Computer Systems Appl (AICCSA). IEEE. 2013:1-4. DOI: 10.1109/AICCSA.2013.6616432.
- Davis KA, Lentz SJ, Pineda J, Farrar JT, Starczak VR, Churchill JH. Observations of the thermal environment on Red Sea platform reefs: a heat budget analysis. Coral Reefs. 2011;30:25-36. DOI: 10.1007/s00338-011-0740-8.
- de Ridder SA, Darcy SI, Calvert PP, Lenhart JH. Influence of analytical method, data summarization method, and particle size on total suspended solids removal efficiency. Global Solutions for Urban Drainage, Reston, VA: American Society of Civil Engineers; 2002:1-14. DOI: 10.1061/40644(2002)26.
- Choquette SJ, Duewer DL, Sharpless KE. NIST reference materials: Utility and future. Annual Rev Anal Chem. 2020;13:453-74. DOI: 10.1146/annurev-anchem-061318-115314.
- Gambin AF, Angelats E, Gonzalez JS, Miozzo M, Dini P. Sustainable marine ecosystems: Deep learning for water quality assessment and forecasting. IEEE Access. 2021;9:121344-65. DOI: 10.1109/ACCESS.2021.3109216.
- Zhang H, Zhang D, Zhang A. An innovative multifunctional buoy design for monitoring continuous environmental dynamics at Tianjin Port. IEEE Access. 2020;8:171820-33. DOI: 10.1109/ACCESS.2020.3024020.
- Bdour AN, Tarawneh Z, Almomani T. Real-time remote monitoring (RTRM) of selected water quality parameters in marine ecosystem using wireless sensor networks. Proc 14th Int Conf Environ Sci Technol. Rhodes. GNEST; 2015. ISBN: 9789607475527.
- Clapcott JE, Goodwin EO, Young RG, Kelly DJ. A multimetric approach for predicting the ecological integrity of New Zealand streams. Knowl Manage Aquat Ecosyst. 2014:03. DOI: 10.1051/kmae/2014027.
- Bdour A, Hejab A, Almakhadmah L, Hawwa M. Management strategies for the efficient energy production of brackish water desalination to ensure reliability, cost reduction, and sustainability. Glob J Environ Sci Manage. 2023;9:173-92. DOI: 10.22034/GJESM.2023.09.SI.11.
- Chen Y. An analytical process of spatial autocorrelation functions based on Moran’s index. PLoS ONE. 2021;16:e0249589. DOI: 10.1371/journal.pone.0249589.
- Dormann CF, McPherson JM, Araújo MB, Bivand R, Bolliger J, Carl G, et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography. 2007;30:609-28. DOI: 10.1111/j.2007.0906-7590.05171.x.
- Betts MG, Ganio LM, Huso MMP, Som NA, Huettmann F, Bowman J, et al. Comment on methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography. 2009;32:374-8. DOI: 10.1111/j.1600-0587.2008.05562.x.
Language: English
Page range: 335 - 352
Published on: Oct 10, 2025
Published by: Society of Ecological Chemistry and Engineering
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2025 Ahmed Bdour, Raha M. Alkharabsheh, published by Society of Ecological Chemistry and Engineering
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.