AI in Sustainable and Resilient Infrastructures: Construction, Management, and Maintenance

Dear Colleagues,

Civil infrastructure systems across the globe are increasingly strained by the combined effects of climate change, accelerated urbanization, asset deterioration, and growing resource limitations. At the same time, advances in artificial intelligence (AI) and data‑centric engineering are transforming how we design, build, operate, and maintain civil infrastructure.

This Special Issue invites contributions that leverage the power of AI to improve sustainability (e.g., lower embodied/operational carbon, circularity, lifecycle performance) and resilience (e.g., multi‑hazard robustness, recovery, and adaptability) across the entire infrastructure lifecycle from low‑carbon design and planning through to safe and efficient construction and to predictive operations, asset management, and maintenance.

We welcome methodological innovations, sensing and data integration frameworks, and decision support tools under uncertainty, as well as rigorous case studies that translate AI into practice, codes/standards, and policy, especially under climate stressors and compound events. Submissions should emphasize technical soundness, transparency/reproducibility, and pathways to deployment into real infrastructure programs.

Potential topics include, but are not limited to, the following:

A. Sustainable Planning and Design

• AI‑assisted low‑carbon/circular design; embodied/operational carbon prediction; lifecycle assessment (LCA/LCCA).
• Materials informatics for low‑impact materials; design for deconstruction and reuse.
• Multi‑objective optimization of cost–carbon–resilience trade‑offs.
• Optimizing construction and demolition wastes using GIS and remote sensing technologies.

B. Construction Engineering and Management

• Schedule and cost forecasting; risk analytics; and resource and logistics optimization.
• Artificial intelligence to predict cost contingency and analyze construction delays.
• Natural language processing for automated and intelligent contract administration.
• Computer vision for site safety, quality, and progress monitoring; AI for QA/QC and claim analytics.
• Robotics and autonomous systems for construction; digital thread from design to site.
• Smart and mature knowledge management systems.
• Progress monitoring using AI and remote sensing technologies.

C. Operations, Asset Management, and Maintenance

• Structural and geotechnical health monitoring (SHM/GHM); damage detection and prognosis.
• Remaining useful life (RUL) prediction and prescriptive maintenance strategies; risk‑based inspection planning.
• AI‑enabled digital twins and knowledge graphs; integrated BIM–GIS–SCADA data fusion.

D. Resilience, Risk, and Climate Adaptation

• AI for multi‑hazard modeling including earthquake, wind, flood/compound flooding, heat waves, and wildfire.
• Networked infrastructure resilience across transport, energy, water, and telecommunications systems; interdependency modeling.
• Adaptation pathways and resilience metrics for infrastructure system under deep uncertainty.

E. Inspection, Sensing, and Data

• Unmanned aerial, underwater, and ground vehicles (UAVs, UUVs, and UGVs) and drone‑borne inspection; computer vision-based non-destructive evaluation (NDE); and distributed sensing technologies.
• Synthetic data generation, data augmentation, reinforcement learning, generative AI, domain adaptation, and transfer learning for infrastructure applications.
• Data governance, privacy/security, and MLOps for critical infrastructure systems.

F. Governance, Ethics, and Adoption

• Human‑in‑the‑loop decision support systems; assurance, verification, and validation of AI models.
• Standards, codes, and procurement enabling AI adoption; equity and societal impacts.
• Benchmark datasets, open science, and reproducibility in AI for civil infrastructure.

(Submissions focused purely on AI method development without a clear infrastructure application or evaluation are out of scope.)

Dr. Mohammed Alsharqawi
Dr. Eslam Mohammed Abdelkader
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Infrastructures is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence (AI) for civil infrastructure
• large language models (LLM) in smart infrastructure
• sustainable construction and lifecycle assessment (LCA)
• circular economy and green construction
• lean construction and value stream mapping
• computer vision and robotics in construction
• digital twins and BIM–GIS integration
• structural health monitoring (SHM)
• non-destructive evaluation (NDE)
• predictive and prescriptive maintenance
• climate change adaptation and infrastructure resilience
• remote sensing, Internet of Things (IoT), and SCADA systems
• decision support systems and risk analytics