Machine and Deep Learning for the Smart and Sustainable Built Environment

Dear Colleagues,

The field of the sustainable built environment covers a variety of subject areas, including building design, sustainable construction, smart materials, and management indoor spaces. The smart and sustainable built environment refers to an urban area where multiple interactions occur between people and smart (indoor and outdoor) spaces in a sustainable environment. To achieve a smart and sustainable built environment, new technologies such as semantically rich digital building and city information models (CIM and BIM) play a key role, in addition to digital twins, which represent the digital replica of the real built assets in real time will be a key contributor of the smart and sustainable built environment. The data infrastructure will comprise the CIM, BIM, and digital twins, but in order to achieve real benefits, the data in the infrastructure need to be processed to generate information (and knowledge) to support the decision-making processes.

The focus of this Special Issue covers the use and implementation of new machine and deep learning techniques and technologies to assist decision making for achieving and managing the smart and sustainable built environment. The scope covers a wide range of areas, CIM, BIM, and digital twins as the building blocks of the data infrastructure, and machine and deep learning techniques and technologies to support the decision-making processes. The purpose of this Special Issue is to provide a collection of recent research on new AI technologies which would support the development and management of the smart and sustainable built environment. This Special Issue will contribute to the existing literature by providing new research outputs, implementation examples, and case studies on implementing AI technologies for the sustainable built environment. This Special Issue will report high-quality research on machine and deep learning to help in achieving smart and sustainable built environments. Key topics include, but are not limited to, the following:

• Data infrastructures for smart and sustainable built environments;
• Information acquisition techniques (sensor-based and image-based) for smart and sustainable built environments;
• Building information models, modelling, and management (BIM, IFC, etc.);
• 3D digital city modelling and management (CityGML, IndoorGML, CityJSON, etc.);
• Supervised machine and deep learning techniques for smart and sustainable built environments;
• Unsupervised machine and deep learning techniques for smart and sustainable built environments;
• Hyperparameter optimization, feature selection, and attention mechanisms for smart and sustainable built environments;
• Reinforcement learning for smart and sustainable built environments;
• Image and video acquisition and processing for smart and sustainable built environments;
• Advanced neural network applications for smart and sustainable built environments;
• Optimization and soft computing applications for smart and sustainable built environments;
• Multi-criteria decision-making (MCDM) and AI for smart and sustainable built environments.

Dr. Umit Isikdag
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 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. 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.

• AI
• machine learning
• deep learning
• AEC
• built environment
• BIM
• GIS
• CityGML
• indoor GML
• ANN