[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] The contribution of data-driven technologies in achieving the sustainable development goals

N Bachmann, S Tripathi, M Brunner, H Jodlbauer - Sustainability, 2022 - mdpi.com
The United Nations' Sustainable Development Goals (SDGs) set out to improve the quality of
life of people in developed, emerging, and developing countries by covering social and …

[HTML][HTML] Hybridised artificial neural network model with slime mould algorithm: a novel methodology for prediction of urban stochastic water demand

SL Zubaidi, IH Abdulkareem, KS Hashim… - Water, 2020 - mdpi.com
Urban water demand prediction based on climate change is always challenging for water
utilities because of the uncertainty that results from a sudden rise in water demand due to …

[HTML][HTML] Big data and the united nations sustainable development goals (UN SDGs) at a glance

H Hassani, X Huang, S MacFeely… - Big Data and Cognitive …, 2021 - mdpi.com
The launch of the United Nations (UN) 17 Sustainable Development Goals (SDGs) in 2015
was a historic event, uniting countries around the world around the shared agenda of …

[HTML][HTML] A novel methodology for prediction urban water demand by wavelet denoising and adaptive neuro-fuzzy inference system approach

SL Zubaidi, H Al-Bugharbee, S Ortega-Martorell… - Water, 2020 - mdpi.com
Accurate and reliable urban water demand prediction is imperative for providing the basis to
design, operate, and manage water system, especially under the scarcity of the natural …

[HTML][HTML] A novel methodology to predict monthly municipal water demand based on weather variables scenario

SL Zubaidi, K Hashim, S Ethaib, NSS Al-Bdairi… - Journal of King Saud …, 2022 - Elsevier
This study provides a novel methodology to predict monthly water demand based on several
weather variables scenarios by using combined techniques including discrete wavelet …

Novel approach for burst detection in water distribution systems based on graph neural networks

A Zanfei, A Menapace, BM Brentan, M Righetti… - Sustainable Cities and …, 2022 - Elsevier
Sustainable management of water resources is a key challenge for the well-being and
security of current and future society worldwide. In this regard, water utilities have to ensure …

Applications of XGBoost in water resources engineering: A systematic literature review (Dec 2018–May 2023)

M Niazkar, A Menapace, B Brentan, R Piraei… - … Modelling & Software, 2024 - Elsevier
Abstract Applications of Machine Learning methods make a paradigm shift in the domain of
water resources engineering. This study not only presents the story of emerging eXtreme …

IoT-enabled water distribution systems—A comparative technological review

NK Velayudhan, P Pradeep, SN Rao… - IEEE …, 2022 - ieeexplore.ieee.org
Water distribution systems are one of the critical infrastructures and major assets of the water
utility in a nation. The infrastructure of the distribution systems consists of resources …

[HTML][HTML] Urban water consumption at multiple spatial and temporal scales. A review of existing datasets

A Di Mauro, A Cominola, A Castelletti, A Di Nardo - Water, 2021 - mdpi.com
Over the last three decades, the increasing development of smart water meter trials and the
rise of demand management has fostered the collection of water demand data at …