PolyU Department of Building and Real Estate
Smart and Sustainable Drainage Network (SSDN) in Hong Kong using Artificial Intelligence and Machine Learning techniques
Project Publications
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Abdelkhalek, S., & Zayed, T. (2023). A multi-tier deterioration assessment models for sewer and stormwater pipelines in Hong Kong. Journal of Environmental Management, 345, 118913.
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Alshami, A., Elsayed, M., Mohandes, S. R., Kineber, A. F., Zayed, T., Alyanbaawi, A., & Hamed, M. M. (2022). Performance assessment of sewer networks under different blockage situations using Internet-of-Things-based technologies. Sustainability, 14(21), 14036.
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Mohandes, S. R., Kaddoura, K., Singh, A. K., Elsayed, M. Y., Banihashemi, S., Antwi-Afari, M. F., ... & Zayed, T. (2024). Application of a hybrid fuzzy-based algorithm to investigate the environmental impact of sewer overflow. Smart and Sustainable Built Environment.
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Alshami, A., Elsayed, M., Ali, E., Eltoukhy, A. E., & Zayed, T. (2023). Monitoring blockage and overflow events in small-sized sewer network using contactless flow sensors in Hong Kong: Problems, causes, and proposed solution. IEEE access, 11, 87131-87149.
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Sojobi, A. O., & Zayed, T. (2022). Impact of sewer overflow on public health: A comprehensive scientometric analysis and systematic review. Environmental research, 203, 111609.
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Owolabi, T. A., Mohandes, S. R., & Zayed, T. (2022). Investigating the impact of sewer overflow on the environment: A comprehensive literature review paper. Journal of Environmental Management, 301, 113810.