[HTML][HTML] The role of deep learning in urban water management: A critical review

G Fu, Y **, S Sun, Z Yuan, D Butler - Water Research, 2022 - Elsevier
Deep learning techniques and algorithms are emerging as a disruptive technology with the
potential to transform global economies, environments and societies. They have been …

Artificial intelligence in the AEC industry: Scientometric analysis and visualization of research activities

A Darko, APC Chan, MA Adabre, DJ Edwards… - Automation in …, 2020 - Elsevier
Abstract The Architecture, Engineering and Construction (AEC) industry is fraught with
complex and difficult problems. Artificial intelligence (AI) represents a powerful tool to assist …

BIM, machine learning and computer vision techniques in underground construction: Current status and future perspectives

MQ Huang, J Ninić, QB Zhang - Tunnelling and Underground Space …, 2021 - Elsevier
The architecture, engineering and construction (AEC) industry is experiencing a
technological revolution driven by booming digitisation and automation. Advances in …

Machine learning in natural and engineered water systems

R Huang, C Ma, J Ma, X Huangfu, Q He - Water Research, 2021 - Elsevier
Water resources of desired quality and quantity are the foundation for human survival and
sustainable development. To better protect the water environment and conserve water …

Review on automated condition assessment of pipelines with machine learning

Y Liu, Y Bao - Advanced Engineering Informatics, 2022 - Elsevier
Pipelines carrying energy products play vital roles in economic wealth and public safety, but
incidents continue occurring. Condition assessment of pipelines is essential to identify …

Machine learning for risk and resilience assessment in structural engineering: Progress and future trends

X Wang, RK Mazumder, B Salarieh… - Journal of Structural …, 2022 - ascelibrary.org
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

A deep learning-based framework for an automated defect detection system for sewer pipes

X Yin, Y Chen, A Bouferguene, H Zaman… - Automation in …, 2020 - Elsevier
The municipal drainage system is a key component of every modern city's infrastructure.
However, as the drainage system ages its pipes gradually deteriorate at rates that vary …

Classification and analysis of deep learning applications in construction: A systematic literature review

R Khallaf, M Khallaf - Automation in construction, 2021 - Elsevier
In recent years, the construction industry has experienced an expansion in the multitude of
projects and emergent information. With the advent of deep learning, new opportunities …

Recent advances in sensing and assessment of corrosion in sewage pipelines

S Foorginezhad, M Mohseni-Dargah… - Process Safety and …, 2021 - Elsevier
Corrosion is known as the gradual destruction of materials, leading to structural integrity loss
and deteriorates the surface function. Regarding sewage pipelines, corrosion is vital due to …

DefectTR: End-to-end defect detection for sewage networks using a transformer

LM Dang, H Wang, Y Li, TN Nguyen, H Moon - Construction and Building …, 2022 - Elsevier
The sanitary sewer is a crucial underground infrastructure of any country that collects
wastewater and carries it to the treatment plant. The damage triggered by various factors …