Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques
Ghezlane Halhoul Merabet,Ghezlane Halhoul Merabet,Mohamed Essaaidi,Mohamed Ben Haddou,Basheer Qolomany,Junaid Qadir,Muhammad Anan,Ala Al-Fuqaha,Ala Al-Fuqaha,Mohamed Riduan Abid,Driss Benhaddou +10 more
TLDR
A comprehensive and an in-depth systematic review of AI-based techniques used for building control systems by assessing the outputs of these techniques, and their implementations in the reviewed works, as well as investigating their abilities to improve the energy-efficiency, while maintaining thermal comfort conditions.Abstract:
Building operations represent a significant percentage of the total primary energy consumed in most countries due to the proliferation of Heating, Ventilation and Air-Conditioning (HVAC) installations in response to the growing demand for improved thermal comfort. Reducing the associated energy consumption while maintaining comfortable conditions in buildings are conflicting objectives and represent a typical optimization problem that requires intelligent system design. Over the last decade, different methodologies based on the Artificial Intelligence (AI) techniques have been deployed to find the sweet spot between energy use in HVAC systems and suitable indoor comfort levels to the occupants. This paper performs a comprehensive and an in-depth systematic review of AI-based techniques used for building control systems by assessing the outputs of these techniques, and their implementations in the reviewed works, as well as investigating their abilities to improve the energy-efficiency, while maintaining thermal comfort conditions. This enables a holistic view of (1) the complexities of delivering thermal comfort to users inside buildings in an energy-efficient way, and (2) the associated bibliographic material to assist researchers and experts in the field in tackling such a challenge. Among the 20 AI tools developed for both energy consumption and comfort control, functions such as identification and recognition patterns, optimization, predictive control. Based on the findings of this work, the application of AI technology in building control is a promising area of research and still an ongoing, i.e., the performance of AI-based control is not yet completely satisfactory. This is mainly due in part to the fact that these algorithms usually need a large amount of high-quality real-world data, which is lacking in the building or, more precisely, the energy sector. Based on the current study, from 1993 to 2020, the application of AI techniques and personalized comfort models has enabled energy savings on average between 21.81 and 44.36%, and comfort improvement on average between 21.67 and 85.77%. Finally, this paper discusses the challenges faced in the use of AI for energy productivity and comfort improvement, and opens main future directions in relation with AI-based building control systems for human comfort and energy-efficiency management.read more
Citations
More filters
Journal ArticleDOI
An overview of machine learning applications for smart buildings
Kari Alanne,Seppo Sierla +1 more
TL;DR: In this paper, the authors discuss the learning ability of buildings with a system-level perspective and present an overview of autonomous machine learning applications that make independent decisions for building energy management, and conclude that the buildings' adaptability to unpredicted changes can be enhanced at the system level through AI-initiated learning processes and by using digital twins as training environments.
Journal ArticleDOI
Applications of IoT for optimized greenhouse environment and resources management
Chrysanthos Maraveas,Dimitrios Piromalis,Konstantinos G. Arvanitis,Thomas Bartzanas,Dimitrios Loukatos +4 more
TL;DR: The role of IoT in precision agriculture and smart greenhouses has been reinforced by recent R&D projects, growing commercialization of IoT infrastructure, and related technologies such as satellites, artificial intellige nce, sensors, actuators, uncrewed aerial vehicles, big data analytics, intelligent machines, and radio-frequency identification devices as discussed by the authors .
Journal ArticleDOI
Evaluating the Connection between Thermal Comfort and Productivity in Buildings: A Systematic Literature Review
TL;DR: The main conclusions found in this study were: the vast majority of research uses subjective measures and/or a combination of methods to evaluate productivity; performance/productivity can be attained within an ampler temperature range; few studies present ways of calculating productivity.
Journal ArticleDOI
Performance and energy optimization of building automation and management systems: Towards smart sustainable carbon-neutral sports facilities
Mariam Ahmed Elnour,Fodil Fadli,Yassine Himeur,Ioan Petri,Yacine Rezgui,Nader Meskin,Ahmad Mohammad Ahmad +6 more
TL;DR: In this article , the authors present a review article addressing the research gap in building operation management and optimization for sports facilities compared to other types of buildings and SFs located in hot climatic zones compared to cold ones.
Journal ArticleDOI
Thermal comfort performance and energy-efficiency evaluation of six personal heating/cooling devices
TL;DR: In this article , the authors evaluated and compared the thermal comfort effectiveness and energy consumption of six different personal heating/cooling devices (including warm air blower, electric radiant heater, heated cushion, desk fan, floor fan, and ventilated cushion).
References
More filters
Journal ArticleDOI
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal Article
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
TL;DR: The QUOROM Statement (QUality Of Reporting Of Meta-analyses) as mentioned in this paper was developed to address the suboptimal reporting of systematic reviews and meta-analysis of randomized controlled trials.
Book
Reinforcement Learning: An Introduction
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Related Papers (5)
The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: energy implications of AI-based thermal comfort controls
Energy-Efficient Thermal Comfort Control in Smart Buildings via Deep Reinforcement Learning.
Guanyu Gao,Jie Li,Yonggang Wen +2 more