AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

Artificial Intelligence Review, Journal Year: 2022, Volume and Issue: 56(6), P. 4929 - 5021

Published: Oct. 15, 2022

In theory, building automation and management systems (BAMSs) can provide all the components functionalities required for analyzing operating buildings. However, in reality, these only ensure control of heating ventilation air conditioning system systems. Therefore, many other tasks are left to operator, e.g. evaluating buildings' performance, detecting abnormal energy consumption, identifying changes needed improve efficiency, ensuring security privacy end-users, etc. To that end, there has been a movement developing artificial intelligence (AI) big data analytic tools as they offer various new tailor-made solutions incredibly appropriate practical management. Typically, help operator (i) tons connected equipment data; and; (ii) making intelligent, efficient, on-time decisions performance. This paper presents comprehensive systematic survey on using AI-big analytics BAMSs. It covers AI-based tasks, load forecasting, water management, indoor environmental quality monitoring, occupancy detection, The first part this adopts well-designed taxonomy overview existing frameworks. A review is conducted about different aspects, including learning process, environment, computing platforms, application scenario. Moving on, critical discussion performed identify current challenges. second aims at providing reader with insights into real-world analytics. Thus, three case studies demonstrate use BAMSs presented, focusing anomaly detection residential office buildings performance optimization sports facilities. Lastly, future directions valuable recommendations identified reliability intelligent

Language: Английский

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Cyber security in smart cities: A review of deep learning-based applications and case studies

Sustainable Cities and Society, Journal Year: 2020, Volume and Issue: 66, P. 102655 - 102655

Published: Dec. 16, 2020

Language: Английский

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An overview of machine learning applications for smart buildings

Sustainable Cities and Society, Journal Year: 2021, Volume and Issue: 76, P. 103445 - 103445

Published: Oct. 13, 2021

The efficiency, flexibility, and resilience of building-integrated energy systems are challenged by unpredicted changes in operational environments due to climate change its consequences. On the other hand, rapid evolution artificial intelligence (AI) machine learning (ML) has equipped buildings with an ability learn. A lot research been dedicated specific applications for phases a building's life-cycle. reviews commonly take specific, technological perspective without vision integration smart technologies at level whole system. Especially, there is lack discussion on roles autonomous AI agents training boosting process complex abruptly changing environments. This review article discusses system-level presents overview that make independent decisions building management. We conclude buildings’ adaptability can be enhanced system through AI-initiated processes using digital twins as greatest potential efficiency improvement achieved integrating solutions timescales HVAC control electricity market participation.

Language: Английский

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Artificial Intelligence Evolution in Smart Buildings for Energy Efficiency

Applied Sciences, Journal Year: 2021, Volume and Issue: 11(2), P. 763 - 763

Published: Jan. 14, 2021

The emerging concept of smart buildings, which requires the incorporation sensors and big data (BD) utilizes artificial intelligence (AI), promises to usher in a new age urban energy efficiency. By using AI technologies consumption can be reduced through better control, improved reliability, automation. This paper is an in-depth review recent studies on application (AI) buildings building management system (BMS) demand response programs (DRPs). In addition elaborating principles applications AI-based modeling approaches widely used use prediction, evaluation framework introduced for assessing research conducted this field across major domains, including energy, comfort, design, maintenance. Finally, includes discussion open challenges future directions buildings.

Language: Английский

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Federated learning for smart cities: A comprehensive survey

Sustainable Energy Technologies and Assessments, Journal Year: 2022, Volume and Issue: 55, P. 102987 - 102987

Published: Dec. 31, 2022

Language: Английский

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A deep learning approach for prediction of air quality index in a metropolitan city

Sustainable Cities and Society, Journal Year: 2021, Volume and Issue: 67, P. 102720 - 102720

Published: Jan. 20, 2021

Language: Английский

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Smart city and cyber-security; technologies used, leading challenges and future recommendations

Energy Reports, Journal Year: 2021, Volume and Issue: 7, P. 7999 - 8012

Published: Sept. 3, 2021

Today, some cities around the world have tended to use new technologies and become smart city. New improve quality of citizens' life. However, any technology raises issues challenges. In a city, vulnerable action an individual or organization can put entire city at risk. Due reliance various components on information communication technology, cyber-security challenges (such as leakage malicious cyber-attacks) in this field affect behavior. Therefore, order respond enthusiastic acceptance global technologies, cyber security must develop same direction. The aim paper is survey discus explanation security, cities, available relevant literature that technology. For purpose, present study focuses four main i.e. grid, Smart building, transportation system, healthcare. particular, summary two deep learning method programs well correlation are discussed. Furthermore, effective functional solutions maintaining user privacy explained. next progress trends with described. Solutions need be devised address each issues. research showed meeting these depends hard work governments, developers equipment software companies providing IT services. addition, designing flexible systems high protection capabilities essential prevent serious incidents lead disastrous financial, data, credit loss public trust.

Language: Английский

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A Survey on IoT-Enabled Smart Grids: Emerging, Applications, Challenges, and Outlook

Energies, Journal Year: 2022, Volume and Issue: 15(19), P. 6984 - 6984

Published: Sept. 23, 2022

Swift population growth and rising demand for energy in the 21st century have resulted considerable efforts to make electrical grid more intelligent responsive accommodate consumers’ needs better while enhancing reliability efficiency of modern power systems. Internet Things (IoT) has appeared as one enabling technologies smart grids by delivering abundant cutting-edge solutions various domains, including critical infrastructures. As IoT-enabled devices continue flourish, major challenges is security issues, since IoT are connected through Internet, thus making vulnerable a diverse range cyberattacks. Given possible cascading consequences shutting down system, cyberattack on would disastrous implications stability all grid-connected Most gadgets our homes, workplaces, hospitals, trains require electricity run. Therefore, entire subject cyberattacks when single device hacked. Such attacks supplies may bring cities standstill, resulting massive economic losses. result, an important element address before large-scale deployment IoT-based In this report, first, we review architecture infrastructure grids; then, focus issues regarding their implementation. Lastly, main outcome study, highlight advanced that can help be resilient secure overcoming existing cyber physical attacks. regard, future, broad implementation data transmission systems based blockchain techniques necessary safeguard against cyber-physical adversaries.

Language: Английский

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A bibliometric review of net zero energy building research 1995–2022

Energy and Buildings, Journal Year: 2022, Volume and Issue: 262, P. 111996 - 111996

Published: March 4, 2022

Language: Английский

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A three-layer game theoretic-based strategy for optimal scheduling of microgrids by leveraging a dynamic demand response program designer to unlock the potential of smart buildings and electric vehicle fleets

Applied Energy, Journal Year: 2023, Volume and Issue: 347, P. 121440 - 121440

Published: June 26, 2023

The proliferation of the number Smart Buildings (SBs) and fleet Electric Vehicles (EVs) in Distribution Systems (DSs) makes need for new strategies to coordinate them with microgrid (MG) scheduling inevitable. Therefore, this article proposes a three-layer risk-averse game theoretic-based strategy SBs EV fleets MGs scheduling. In first layer strategy, Demand Response Program (DRP) is designed where dynamic incentive tariffs are calculated based on consumption pattern subscribers. Then, second layer, done decentralized space considering their participation DRP. Eventually, third operators have received power exchange information order carry out accordance it. Day-Ahead (DA) DS through implementation cooperative theory. Fluctuations uncertain operational parameters such as load demand, radiation wind embedded model by scenario-based technique Risk-Averse (RA) adopted manage them. Running proposed 69-node containing four showed that can use potential improve voltage characteristics high-demand period reduce total daily costs 13.66% designing dynamic-tariff Moreover, results reveal using Peer-to-Peer (P2P) option not only reduced losses system but also about 8%.

Language: Английский

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