Special Issue "Building and Urban Energy Prediction-Big Data Analysis and Sustainable Design"
Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 36758
Interests: building/urban energy modeling, simulation, and visualization
Owing to advancements in computer design, in today’s world, there are two sensational trends that support sustainable building design and engineering, namely, real-time building energy prediction/big data analysis and technology revolution.
On one hand, traditional building energy modeling and simulation tools have been widely employed for prediction analysis. Coupled with empirical validation, the accuracy of these tools has been tested and improved. Among others, existing buildings have benefited from building energy big data analysis such as deep learning to understand the behavior of building systems and their occupants in order to effectively provide thermal comfort yet reduce overall energy use. Low-cost, low-energy sensor technologies coupled with wireless data transfer have enabled onsite building and occupant-related data acquisition and have proved to be effective tools to validate prediction as necessary.
On the other hand, the remarkable and timely evolution of technologies supporting building design, engineering, operation, and maintenance cannot be understated. Technologies such as advances in geographic information system (GIS) mapping technology, unmanned aerial vehicles (UAVs), and virtual/augmented reality (VR/AR) promise superior data acquisition and exploration. These technologies are not only here to stay but poised for exponential growth. UAV or drone technologies have been used in building construction and maintenance phases; for example, UAVs have been used as human safety systems during the building construction phase, and these can be integrated with thermal imaging systems to inspect thermal bridging effects that affect energy use during the building operation phase. Similarly, VR/AR technologies have been re-introduced to the building design and engineering paradigm, although these technologies were “tested” for sustainable design a decade ago, and they were found to be unaffordable and cumbersome to use.
This Special Issue “Building Energy Prediction/Big Data Analysis and Sustainable Design” invites authors to submit papers that explore the nexus between building energy and technology revolution. Topics may include but are not limited to the following:
- Building energy modeling and simulation;
- Machine learning and automated building(s) model development;
- Building energy big data analysis;
- Sensor technologies for building data acquisition;
- Building outdoor/indoor air quality and comfort measurements;
- Virtual reality (VR), augmented reality (AR) in sustainable design and engineering;
- Urban energy modeling and simulation;
- Urban energy visualization techniques;
- Sustainability approaches for large campuses or urban systems.
Dr. Ravi Srinivasan
Dr. Mahabir Bhandari
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 2000 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.
- Building energy modeling
- Machine learning
- Automated building model development
- Big data analysis
- Sensor and control technologies
- Virtual reality and augmented reality visualization
- Urban energy modeling