Smart Cities, Connected Communities, and Environmental Sustainability
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".
Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 9599
Special Issue Editors
Interests: transportation modeling; applied operations research; shared and autonomous mobility services; alternative fuel technologies; data-driven decision-making
Interests: smart cities; connected communities; transportation systems; environmental sustainability
Special Issue Information
Dear Colleagues,
Cities and communities are witnessing profound changes as they enter a new era in which community members are increasingly connected with their surrounding built and natural environments, and with each other, through rapidly evolving intelligent technologies. These changes promise improved wellbeing and prosperity but pose significant challenges at the complex intersection of technology and society. The goal of this Special Issue is to contribute to the growing body of scientific and engineering work that will enable smart and connected communities to bring about new levels of economic opportunity and growth, safety and security, health and wellness, accessibility and inclusivity, and overall quality of life.
In this Special Issue, we invite submissions on the topic of Smart Cities, Connected Communities, and Environmental Sustainability to appear in the journal Sustainability. Specifically, we invite submissions contributing new, innovative models, analysis frameworks, supporting decision-making tools, policy studies on emerging technologies and their impacts on cities and communities, exploring household and consumer behaviors through data, and discussing lessons learned from real case studies.
The overarching theme of this Special Issue is Smart Cities, Connected Communities, and Environmental Sustainability which includes but is not limited to the following areas:
- Equity and fairness implications of smart cities and connected communities;
- Sustainable smart transportation systems and their mobility technologies, products, and services;
- Alternative fuel vehicle technologies and energy systems modeling;
- Community wellbeing related to socializing and connecting across virtual/real worlds;
- Energy consumption and sustainability impacts of automation, deep-learning AI, and other technologies in smart cities;
- Societal impacts of automation, deep-learning AI, and other technologies, including trust-worthiness and privacy;
- Integrated modeling or urban systems under emerging technologies and services;
- Modeling and analysis of emerging mobility technologies, products, and services;
- Data-driven decision-making in sustainable systems modeling;
- Application of emerging 3D data (e.g., lidar point clouds) toward constructing, visualizing, and modeling urban infrastructure for smart cities, including AVs, wayfinding, and other human activities.
Dr. Jee Eun Kang
Dr. Roger Chen
Dr. Daniel Rodríguez Román
Guest Editors
Manuscript Submission Information
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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. 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
- connected communities
- transportation systems
- equity
- trust
- deep-learning AI
- data-driven decision making
- autonomous systems
- point cloud visualization
- energy systems
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