Performance Assessment of Sewer Networks under Different Blockage Situations Using Internet-of-Things-Based Technologies

Ahmad Alshami, Moustafa Elsayed, Saeed Reza Mohandes (), Ahmed Farouk Kineber, Tarek Zayed, Ashraf Alyanbaawi and Mohammed Magdy Hamed
Additional contact information
Ahmad Alshami: Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong
Moustafa Elsayed: Department of Land Surveying and Gio Informatics, The Hong Kong Polytechnic University, Hong Kong
Saeed Reza Mohandes: Department of Mechanical, Aerospace and Civil Engineering, School of Engineering, The University of Manchester, Manchester M13 9PL, UK
Ahmed Farouk Kineber: Department of Civil Engineering, College of Engineering in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
Tarek Zayed: Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong
Ashraf Alyanbaawi: College of Science and Computer Engineering, Taibah University, Yanbu 46411, Saudi Arabia
Mohammed Magdy Hamed: Construction and Building Engineering Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), B 2401 Smart Village, Giza 12577, Egypt

Sustainability, 2022, vol. 14, issue 21, 1-24

Abstract: This study aims to model the performance of sewage networks under diverse blockage situations in terms of overflow occurrence using internet-of-things-based technologies in Hong Kong. To this end, a multi-stage methodological approach is employed, starting from collecting required data using smart sensors, utilizing novel data mining techniques, and using a case study simulation. From the results obtained, the following conclusions are drawn: (1) several sites under investigation are imbued with partial blockages, (2) the overall performance of the sewer network has a nonlinear relationship with the blockages in terms of the remaining time to overflow, (3) in cases of complete blockages, the sewer only takes few minutes to reach the manhole cover level that causes the system to experience overflow, and (4) cleaning work significantly improve the performance of the sewage network by 86%. The outcomes of this study provide a solid foundation for the concerned environmental engineers and decision-makers towards reducing the magnitude of sewer overflow and improving different aspects of our environment.

Keywords: sewer blockages; sewer overflow; performance assessment; Internet of Things; smart infrastructure management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:21:p:14036-:d:955920

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