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Sustainability
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Building Information Technologies and Building Energy Optimization
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Building Information Technologies and Building Energy Optimization

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 9903

Special Issue Editors

Prof. Young Il Kim

E-Mail Website
Guest Editor
Seoul National University of Science and Technology
Interests: building mechanical equipment system; HVAC&R; building energy; intelligent building; geothermal source heat pump
Prof. Ji Min Kim

E-Mail Website
Guest Editor
Seoul National University of Science and Technology
Interests: built environment; ergonomics; IoT; sustainable development; environmental economics
Prof. Dr. Sean Hay Kim

E-Mail Website
Chief Guest Editor
Seoul National University of Science and Technology
Interests: building simulation; building information modeling; building supervisory controls; facility knowledge discovery and formulation

Special Issue Information

Dear Colleagues,

Smart cities and smart buildings have been regarded as new growth engines for the future of the architecture, engineering, and construction (AEC) industry. Smart cities and buildings integrate information and communication technology (ICT), including internet of things (IoT) networks, building information modeling (BIM), big data analytics, knowledge discovery, augmented reality (AR), virtual reality (VR), etc. The integration of ICTs aims to enhance operational efficiency, performance, interoperability, communication, and service quality, and to reduce costs, resources, and risks in design, construction, operation, and maintenance, as well as the eventual dismantling and regeneration of facilities, infrastructures, and cities.

This Special Issue especially focuses on how the integration of ICTs could optimize the energy performance and sustainability of smart cities and buildings. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the Special Issue’s purview:

  • Computer-aided design, process and simulation modeling, engineering, decision support systems, guidelines, and standardization concerning facilities’ energy performance and sustainability;
  • Sensing, data acquisition, data analytics, information modeling, and knowledge management for designing, constructing, and regenerating facilities from an energy perspective;
  • Intelligent facility management, management information systems, control systems, and robotics to optimize energy performance.

We look forward to your contributions, and welcome all inquiries.

Prof. Sean Hay Kim
Prof. Young Il Kim
Prof. Ji Min Kim
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. 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

  • architecture, engineering, and construction (AEC)
  • computer-aided design
  • building information modeling (BIM)
  • smart cities
  • energy performance and sustainability
  • intelligent facility management

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Published Papers (2 papers)

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Research

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17 pages, 6601 KiB  
Article
Energy Saving of a University Building Using a Motion Detection Sensor and Room Management System
by Jong-Won Lee and Young Il Kim
Sustainability 2020, 12(22), 9471; https://doi.org/10.3390/su12229471 - 14 Nov 2020
Cited by 6 | Viewed by 6310
Abstract
To save electricity consumption in university buildings, we measured and compared the amount of electricity use with and without motion detection sensors and room management systems in underground parking lots, lecture rooms, and dormitories of a university building. The underground parking lots and [...] Read more.
To save electricity consumption in university buildings, we measured and compared the amount of electricity use with and without motion detection sensors and room management systems in underground parking lots, lecture rooms, and dormitories of a university building. The underground parking lots and lecture rooms were measured as sensors were applied and then removed during the semester. University classes are held weekly, so it can be assumed that the number of cars and people’s entering and using conditions are the same. In the university’s underground parking lots, a daily electricity savings of 39.5 Wh/(m2 day) of lights was achieved, with a savings rate of 77.6%. In the lecture rooms, these values were 25.0 Wh/(m2 day) and 32.4%, respectively. Savings in the use of air conditioning were 55.0 Wh/(m2 day), with a savings rate of 27.9%. Dormitories use electrical energy for lighting, heating, and socket outlets. As a reference group, 120 rooms were selected and the room management system was applied to 10 samples. For dormitories, daily electricity savings of 142.4 Wh/(m2 day) were achieved, with a savings rate of 28.2%. Thus, this study demonstrated that applying motion detection sensors and room management systems saved significant electrical energy in university underground parking lots, lecture rooms, and dormitories. Full article
(This article belongs to the Special Issue Building Information Technologies and Building Energy Optimization)
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Review

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36 pages, 5192 KiB  
Review
Knowledge Acquisition and Representation for High-Performance Building Design: A Review for Defining Requirements for Developing a Design Expert System
by Seung Yeoun Choi and Sean Hay Kim
Sustainability 2021, 13(9), 4640; https://doi.org/10.3390/su13094640 - 21 Apr 2021
Cited by 4 | Viewed by 3118
Abstract
New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all [...] Read more.
New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all projects can afford consultants. We expect that, in the near future, computer aids such as design expert systems can help designers by providing the role of HPB consultants. The effectiveness and success or failure of the solution offered by the expert system must be affected by the quality, systemic structure, resilience, and applicability of expert knowledge. This study aims to set the problem definition and category required for existing HPB designs, and to find the knowledge acquisition and representation methods that are the most suitable to the design expert system based on the literature review. The HPB design literature from the past 10 years revealed that the greatest features of knowledge acquisition and representation are the increasing proportion of computer-based data analytics using machine learning algorithms, whereas rules, frames, and cognitive maps that are derived from heuristics are conventional representation formalisms of traditional expert systems. Moreover, data analytics are applied to not only literally raw data from observations and measurement, but also discrete processed data as the results of simulations or composite rules in order to derive latent rule, hidden pattern, and trends. Furthermore, there is a clear trend that designers prefer the method that decision support tools propose a solution directly as optimizer does. This is due to the lack of resources and time for designers to execute performance evaluation and analysis of alternatives by themselves, even if they have sufficient experience on the HPB. However, because the risk and responsibility for the final design should be taken by designers solely, they are afraid of convenient black box decision making provided by machines. If the process of using the primary knowledge in which frame to reach the solution and how the solution is derived are transparently open to the designers, the solution made by the design expert system will be able to obtain more trust from designers. This transparent decision support process would comply with the requirement specified in a recent design study that designers prefer flexible design environments that give more creative control and freedom over design options, when compared to an automated optimization approach. Full article
(This article belongs to the Special Issue Building Information Technologies and Building Energy Optimization)
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