Advances in Intelligent Building Management for Energy, Emission and Comfort
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".
Deadline for manuscript submissions: 20 October 2024 | Viewed by 122
Special Issue Editor
Interests: digital construction; building information modelling; digital twin; construction management; building materials; building design and retrofit; energy rating; building performance and simulation; life cycle assessment; sustainable construction; sustainable building technology; life cycle cost analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The building sector accounts for 40% of total energy consumption globally. Therefore, reducing energy consumption in the building sector is crucial for environmental sustainability. Strategies to predict building energy consumption and enhance building energy performance are being investigated worldwide with different dynamic methods. However, a number of energy-efficient buildings are actually consuming more energy than predictions indicate. This is due to inexperienced building managers, non-adherence to building operational manuals, the degradation of building services and the lack of a feedback system to alert the facility manager to the potential misuse or overuse of energy.
Modern buildings are equipped with a Building Management System (BMS) that can schedule the operation of different service equipment and record the energy consumption of lighting, heating and cooling systems and mechanical and plug-in loads. However, it does not have the intelligence to analyze and identify energy waste, nor does it provide any feedback to the facility manager regarding consumption patterns or recognize any energy waste. The systematic analysis of these data sets to extract hidden knowledge and provide suggestions for improvement using artificial intelligence, machine learning and data analytics is an emerging science in the building sector.
This Special Issue, “Advances in Intelligent Building Management for Energy, Emission and Comfort” aims to reflect the current state of the art and new developments in the application of artificial intelligence, machine learning and data analytics for intelligent building management to improve building energy efficiency, increase thermal comfort and reduce carbon emissions. This Special Issue will provide a comprehensive background for architects, building operational managers, building service engineers, researchers and experts in the field. Topics to be considered in this Special Issue include but are not limited to the keywords.
Dr. Md Morshed Alam
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. Buildings is an international peer-reviewed open access monthly 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 2600 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
- supervised and unsupervised data analytics
- building management system
- energy consumption pattern
- artificial intelligence
- building operational data
- building energy efficiency
- machine learning
- building automation systems
