Project Publications

1. Bakhtawar, B., & Zayed, T. (2021). Review of Water Leak Detection and Localization Methods through Hydrophone Technology. Journal of Pipeline Systems Engineering and Practice, 12(4), 1–12. https://doi.org/10.1061/(asce)ps.1949-1204.0000574
2. Fan, H., Tariq, S., & Zayed, T. (2022). Acoustic leak detection approaches for water pipelines. Automation in Construction, 138(September 2020), 104226. https://doi.org/10.1016/j.autcon.2022.104226
3. Fares, A., Tijani, I. A., Zhang, R., & Zayed, T. (2022). Leak detection in real water distribution networks based on acoustic emission and machine learning, Environmental Technology, DOI: 10.1080/09593330.2022.2074320.
4. Hu, Z., Tariq, S., & Zayed, T. (2021). A comprehensive review of acoustic based leak localization method in pressurized pipelines. Mechanical Systems and Signal Processing, 161(April), 107994. https://doi.org/10.1016/j.ymssp.2021.107994
5. Ibrahim, K., Tariq, S., Bakhtawar, B., & Zayed, T. (2021). Application of fiber optics in water distribution networks for leak detection and localization: a mixed methodology-based review. H2Open Journal, 4(1), 244–261. https://doi.org/10.2166/h2oj.2021.102
6. Ibrahim, K., Tariq, S., Bakhtawar, B., & Zayed, T. (2021). Application of fiber optics in water distribution networks for leak detection and localization: a mixed methodology-based review. H2Open Journal, 4(1), 244–261. https://doi.org/10.2166/h2oj.2021.102
7. Tariq, S., Bakhtawar, B., & Zayed, T. (2022). Data-driven application of MEMS-based accelerometers for leak detection in water distribution networks. Science of The Total Environment, 809(xxxx), 151110. https://doi.org/10.1016/j.scitotenv.2021.151110
8. Tariq, S., Hu, Z., & Zayed, T. (2021). Micro-electromechanical systems-based technologies for leak detection and localization in water supply networks: A bibliometric and systematic review. Journal of Cleaner Production, 289, 125751. https://doi.org/10.1016/j.jclepro.2020.125751
9. Tijani, I. A., Abdelmageed, S., Fares, A., Fan, K. H., Hu, Z. Y., & Zayed, T. (2022). Improving the leak detection efficiency in water distribution networks using noise loggers. Science of the Total Environment, 821. https://doi.org/10.1016/j.scitotenv.2022.153530
10. Tijani, I. A., & Zayed, T. (2022). Gene expression programming based mathematical modeling for leak detection of water distribution networks. Measurement: Journal of the International Measurement Confederation, 188(September 2021), 110611. https://doi.org/10.1016/j.measurement.2021.110611
11. Liu, R., Tariq, S., Tijani, I.A., Fares, A., Bakhtawar, B., Fan, H., Zhang, R., Zayed, T., 2024a. Data-Driven Approaches for Vibroacoustic Localization of Leaks in Water Distribution Networks. Environ. Process. 11, 14. https://doi.org/10.1007/s40710-024-00682-x
12. Liu, R., Zayed, T., Xiao, R., 2025a. Acoustic leak localization for water distribution network through time-delay-based deep learning approach. Water Research 268, 122600. https://doi.org/10.1016/j.watres.2024.122600
13. Liu, R., Zayed, T., Xiao, R., 2025b. Explainable Machine-Learning Leak Identification Framework for Water Distribution Networks. J. Comput. Civ. Eng. 39, 04025090. https://doi.org/10.1061/JCCEE5.CPENG-6119
14. Liu, R., Zayed, T., Xiao, R., 2025c. A critical systematic review of machine learning based models for water leak detection using vibroacoustic technology. Engineering Applications of Artificial Intelligence 158, 111432. https://doi.org/10.1016/j.engappai.2025.111432
15. Liu, R., Zayed, T., Xiao, R., 2024b. Contrastive learning method for leak detection in water distribution networks. npj Clean Water 7, 118. https://doi.org/10.1038/s41545-024-00406-6
16. Liu, R., Zayed, T., Xiao, R., 2024c. Advanced acoustic leak detection in water distribution networks using integrated generative model. Water Research 254, 121434. https://doi.org/10.1016/j.watres.2024.121434
17. Bakhtawar, B., Fares, A., Zayed, T., 2025. AIoT-Driven Leak Detection in Real Water Networks Using Hydrophones. Water Resour Manage 39, 2551–2566. https://doi.org/10.1007/s11269-024-04077-3
18. Bakhtawar, B., Fares, A., Zayed, T., 2022. AI-based smart water leak detection using hydrophones . https://doi.org/10.21203/rs.3.rs-2149154/v1
19. Bakhtawar, B., Zayed, T., 2023. State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network. WIREs Water 10, e1667. https://doi.org/10.1002/wat2.1667
20. Bakhtawar, B., Zayed, T., 2021. Review of Water Leak Detection and Localization Methods through Hydrophone Technology. J. Pipeline Syst. Eng. Pract. 12, 03121002. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000574
21. Yussif, A. M., Sadeghi, H., & Zayed, T. (2023). Application of machine learning for leak localization in water supply networks. Buildings, 13(4), 849. https://doi.org/10.3390/buildings13040849
22. Zhang, R., Yussif, A. M., Tijani, I., Fares, A., Tariq, S., & Zayed, T. (2024). Acoustic localization approach for urban water distribution networks using machine learning method. Engineering Applications of Artificial Intelligence, 137, 109062. https://doi.org/10.1016/j.engappai.2024.109062
23. Zhang, R., Fares, A., Tijani, I. A., Zayed, T., Jin, Z., & Yussif, A. M. (2026). Acoustic based leak location detection for water supply pipelines in urban areas via multi-task deep learning. Engineering Applications of Artificial Intelligence, 163, 112718. https://doi.org/10.1016/j.engappai.2025.112718