AI- and Data-Driven Urban Solutions for Sustainability, Resilience, and City Operations
This special issue belongs to the section "Sustainable Urban and Rural Development".
Special Issue Information
Dear Colleagues,
Cities are pivotal to achieving the Sustainable Development Goals, yet rapid urbanization, climate stressors, and infrastructure constraints are widening gaps in livability, equity, and environmental performance. This Special Issue invites original research and reviews on AI- and data-driven methods that deliver measurable sustainability and resilience gains in real urban settings. We particularly welcome work that bridges methodological innovation with deployment realities—including hurdles such as data quality, governance, privacy, cybersecurity, interoperability, cost, and operational constraints—and that reports transparent assumptions and reproducible evaluation protocols.
We seek contributions spanning urban sensing/IoT, edge–cloud analytics, machine learning for city operations, and digital twins and simulation for decision support. Topics include scheduling and optimization for urban services (resource allocation, fleet/workforce scheduling, maintenance planning, multi-objective optimization, and MILP/metaheuristics); sustainable mobility (traffic, public transport, micromobility, and EV charging); energy management for buildings/districts; water and waste optimization; circular economy applications; and environmental monitoring using remote sensing and UAVs. Submissions may include case studies, datasets, benchmarks, toolkits, and policy-relevant analyses, but should clearly articulate data sources, governance considerations, and the sustainability indicators used.
Smart city research is extensive but often fragmented and weakly connected to sustainability metrics and governance realities. Consequently, this Special Issue emphasizes cross-domain integration, trustworthy and responsible AI (relying on privacy, security, fairness, and transparency), and evidence through benchmarking and real-world validation, helping cities translate smart solutions into durable improvements in sustainability, resilience, and quality of life.
Dr. Mahdi Jemmali
Guest Editor
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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.
Keywords
- smart cities
- sustainable urban development
- urban resilience
- urban analytics
- internet of things (IoT)
- edge computing
- artificial intelligence
- digital twins
- intelligent transportation systems
- energy management
- remote sensing
- UAV monitoring
- privacy and cybersecurity
- trustworthy AI
- scheduling
- operations research
- resource allocation
- metaheuristics
- multi-objective optimization
- MILP
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