[HTML][HTML] AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

Y Himeur, M Elnour, F Fadli, N Meskin, I Petri… - Artificial Intelligence …, 2023 - Springer
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …

[HTML][HTML] A review of the use of artificial intelligence methods in infrastructure systems

L McMillan, L Varga - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
The artificial intelligence (AI) revolution offers significant opportunities to capitalise on the
growth of digitalisation and has the potential to enable the 'system of systems' approach …

Applications of machine learning to water resources management: A review of present status and future opportunities

AA Ahmed, S Sayed, A Abdoulhalik, S Moutari… - Journal of Cleaner …, 2024 - Elsevier
Water is the most valuable natural resource on earth that plays a critical role in the socio-
economic development of humans worldwide. Water is used for various purposes, including …

[HTML][HTML] A critical review of short-term water demand forecasting tools—what method should i use?

A Niknam, HK Zare, H Hosseininasab, A Mostafaeipour… - Sustainability, 2022 - mdpi.com
The challenge for city authorities goes beyond managing growing cities, since as cities
develop, their exposure to climate change effects also increases. In this scenario, urban …

A review of operational control strategies in water supply systems for energy and cost efficiency

AL Reis, MAR Lopes, A Andrade-Campos… - … and Sustainable Energy …, 2023 - Elsevier
Water supply systems (WSS) are intensive energy demanding infrastructures relying on
water storage tanks and pumping systems for delivering water to consumers which face …

Smart meters data for modeling and forecasting water demand at the user-level

JE Pesantez, EZ Berglund, N Kaza - Environmental Modelling & Software, 2020 - Elsevier
Smart meters installed at the user-level provide a new data source for managing water
infrastructure. This research explores the use of machine learning methods, including …

A novel deep neural network architecture for real-time water demand forecasting

T Salloom, O Kaynak, W He - Journal of Hydrology, 2021 - Elsevier
Short-term water demand forecasting (StWDF) is the foundation stone in the derivation of an
optimal plan for controlling water supply systems. Deep learning (DL) approaches provide …

Riprap incipient motion for overtopping flows with machine learning models

M Najafzadeh, G Oliveto - Journal of Hydroinformatics, 2020 - iwaponline.com
Riprap stones are frequently applied to protect rivers and channels against erosion
processes. Many empirical equations have been proposed in the past to estimate the unit …

[HTML][HTML] Towards digitalization of water supply systems for sustainable smart city development—Water 4.0

KB Adedeji, AA Ponnle, AM Abu-Mahfouz, AM Kurien - Applied Sciences, 2022 - mdpi.com
Urban water supply systems are complex and dynamic in nature, and as a result, can be
considered complex to manage owing to enhanced urbanization levels, climate change …

[HTML][HTML] Improving short-term water demand forecasting using evolutionary algorithms

J Stańczyk, J Kajewska-Szkudlarek, P Lipiński… - Scientific Reports, 2022 - nature.com
Modern solutions in water distribution systems are based on monitoring the quality and
quantity of drinking water. Identifying the volume of water consumption is the main element …