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Title Sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant
ID_Doc 13205
Authors Matheri, AN; Mohamed, B; Ntuli, F; Nabadda, E; Ngila, JC
Title Sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant
Year 2022
Published
DOI 10.1016/j.pce.2022.103152
Abstract Rapid urbanization, population increase, emerging contaminants and increasing water scarcity have put a major constraint on the wastewater treatment system. Scarcity of water is steering current way of water recycle, and the drive focus towards resource recovery. Zero waste pathway in circular bioeconomy can bring transformation of wastewater commercialization by adding value with resource recovery. The complex biological reactions, unforeseen microbial behaviours, lack of reliable on-line instrumentation, complex modelling, lack of visualize techniques, low-quality industrial measurements and highly time-varying intensive data-driven operations call for the intelligence techniques and operations. The study is a review of sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant. Water surveillance and monitoring, circular economy and sustainability, automation pyramid, digital transformation, artificial intelligence, data pipeline, digital twin, data mining, and data-driven visualization, cyber-physical systems and water-energyhealth management were reviewed. The deployment of the digital systems has evidently proven to bridges the gap between the data-driven soft sensor, operation and control systems in WWTP. Accurate prediction of the WWTP variables can support process design and control, reduce operation cost, improve system reliability, predictive maintenance and troubleshooting, increase water quality, increase stakeholder's engagement and endorse optimization of the plant performance. This procures the best compliance with international standards and diversification. The inclusion of life cycle environmental or cost management technologies in optimization models is an interesting pathway towards sustainable water treatment in-line with sustainable development goals, circular bioeconomy and industry 4.0.
Author Keywords Circular bioeconomy; Data pipeline; Digital twin; Process design; Sensor; Wastewater treatment
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000800213100001
WoS Category Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water Resources
Research Area Geology; Meteorology & Atmospheric Sciences; Water Resources
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