Embedding AI Smartness in Legacy Building Systems and Appliances
摘要截稿:
全文截稿: 2024-07-31
影响因子: 4.937
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 3区
• 小类 : 能源与燃料 - 3区
Overview
During the past decade, several initiatives for increasing operational efficiency in buildings have emerged. To increase the energy efficiency in buildings, typical passive renovation strategies have gained share in the market, spanning from circular insulation materials to adaptive phase changing ones, with highly promising results in practice. However, the recent advances towards democratizing the access to processing power at the edge and to data measurements has enabled more inventive approaches for more elaborate AI. AI-powered active demand management and decision-making in modern smart grids can also contribute to building sustainability during operation. Smart solutions, which include the use of advanced technologies and energy-efficient measures, can play a significant role in achieving these goals. However, embedding smartness in buildings’ operation is not a trivial exercise. Modern smart infrastructure and appliances are still quite expensive for the average end-user, while existing legacy systems do not allow elaborate internal interventions without jeopardizing their warranty. Therefore, within the past years, an increasing interest for increasing smartness of building systems instead of replacing them, has emerged in the market.
This special issue aims to facilitate interdisciplinary research and sharing of cutting-edge views in the fields mentioned above.
The topics to be covered in this issue may include, but are not limited to:
Predictive health condition assessment and maintenance to reduce downtimes.
Rendering legacy appliances into smart connected ones in an interoperable manner.
Distributed and collective intelligence for buildings load control.
Flexibility forecasting and tariff-based demand response at the edge.
Practical approaches for proactive assessment and predictive modelling for advanced decision-making and automated control.
Energy-efficient heating, ventilation, and air conditioning (HVAC) systems: Heat pumps, AHUs, Chillers, Split Unit ACs
Policies, regulations, and financial mechanisms to incentivize the implementation of embedded smart solutions.
Original papers on these topics and short reviews are welcome for submission.
Guest editors:
Prof. Elias KosmatopoulosProfessor of Applied Automatic ControlDemocritus University of ThraceAreas of Expertise: Automatic Control, Neural Networks, IoT, AI
Prof.Dr.-Ing. Mohammadreza AghaeiProfessor/Senior ResearcherDepartment of Sustainable Systems Engineering (INATECH), University of Freiburg, 79110 Freiburg, GermanyDepartment of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU), 6009 Ålesund, NorwayAreas of Expertise: Energy transition; energy flexibility; renewable energy systems; solar photovoltaics; autonomous monitoring
Dr. Behzad NajafiAssistant ProfessorEnergy Department, Politecnico di Milano (Milan, Italy)Areas of Expertise: Smart buildings, Machine learning-based modelling of indoor environments, HVAC systems, and buildings, Demand flexibility in buildings, Smart meter-driven building characterization, micro generation systems’ optimization
Dr. Iakovos MichailidisPost-Doc AssociateCentre for Research and Technology HellasAreas of Expertise: building energy management systems, reinforcement learning applications in building climate control, energy data healing, predictive maintenance for domestic appliances using deep ML, optimal and adaptive control
Manuscript submission information:
We sincerely welcome manuscripts containing novel, high quality, and unpublished research results. The invited submissions will be processed and reviewed in the same way as open submissions. Original papers on these topics and short reviews are welcome for submission. All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers.
Manuscript should be submitted via journal online submission system at: Editorial Manager by selecting the Article Type of " VSI: Embed_AI_Legacy_Appliance ". A detailed submission guideline is available as “Guide for Authors”.
Once your manuscript is accepted, it will go into production and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.
Important Dates:
Submission Open Date: 01 April 2024
Manuscript Submission Deadline: 31 July 2024