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

Artificial Intelligence Review, Год журнала: 2022, Номер 56(6), С. 4929 - 5021

Опубликована: Окт. 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

Язык: Английский

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A Comprehensive Review of Recent Research Trends on Unmanned Aerial Vehicles (UAVs)

Systems, Год журнала: 2023, Номер 11(8), С. 400 - 400

Опубликована: Авг. 2, 2023

The growing interest in unmanned aerial vehicles (UAVs) from both the scientific and industrial sectors has attracted a wave of new researchers substantial investments this expansive field. However, due to wide range topics subdomains within UAV research, newcomers may find themselves overwhelmed by numerous options available. It is therefore crucial for those involved research recognize its interdisciplinary nature connections with other disciplines. This paper presents comprehensive overview field, highlighting recent trends advancements. Drawing on literature reviews surveys, review begins classifying UAVs based their flight characteristics. then provides an current UAVs, utilizing data Scopus database quantify number documents associated each direction interconnections. also explores potential areas further development including communication, artificial intelligence, remote sensing, miniaturization, swarming cooperative control, transformability. Additionally, it discusses aircraft commonly used control techniques, appropriate algorithms research. Furthermore, addresses general hardware software architecture applications, key issues them. open source projects By presenting view aims enhance our understanding rapidly evolving highly area

Язык: Английский

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Decoding ChatGPT: A taxonomy of existing research, current challenges, and possible future directions

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2023, Номер 35(8), С. 101675 - 101675

Опубликована: Авг. 2, 2023

Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest and attention since its launch in November 2022. It shown impressive performance various domains, including passing exams creative writing. However, challenges concerns related to biases trust persist. In this work, we present a comprehensive review of over 100 Scopus-indexed publications on ChatGPT, aiming provide taxonomy ChatGPT research explore applications. We critically analyze the existing literature, identifying common approaches employed studies. Additionally, investigate diverse application areas where found utility, such as healthcare, marketing financial services, software engineering, academic scientific writing, education, environmental science, natural language processing. Through examining these applications, gain valuable insights into potential addressing real-world challenges. also discuss crucial issues trustworthiness, emphasizing need for further development areas. Furthermore, identify future directions research, proposing solutions current speculating expected advancements. By fully leveraging capabilities can unlock across leading advancements conversational AI transformative impacts society.

Язык: Английский

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Deep and transfer learning for building occupancy detection: A review and comparative analysis

Engineering Applications of Artificial Intelligence, Год журнала: 2022, Номер 115, С. 105254 - 105254

Опубликована: Авг. 2, 2022

The building internet of things (BIoT) is quite a promising concept for curtailing energy consumption, reducing costs, and promoting transformation. Besides, integrating artificial intelligence (AI) into the BIoT essential data analysis intelligent decision-making. Thus, data-driven approaches to infer occupancy patterns usage are gaining growing interest in applications. Typically, analyzing big gathered by networks helps significantly identify causes wasted recommend corrective actions. Within this context, aids improvement efficacy management systems, allowing reduction consumption while maintaining occupant comfort. Occupancy might be collected using variety devices. Among those devices optical/thermal cameras, smart meters, environmental sensors such as carbon dioxide (CO2), passive infrared (PIR). Even though latter methods less precise, they have generated considerable attention owing their inexpensive cost low invasive nature. This article provides an in-depth survey strategies used analyze sensor determine occupancy. article's primary emphasis on reviewing deep learning (DL), transfer (TL) detection. work investigates detection develop efficient system processing providing accurate information. Moreover, paper conducted comparative study readily available algorithms optimal method regards training time testing accuracy. main concerns affecting current terms privacy precision were thoroughly discussed. For detection, several directions provided avoid or reduce problems employing forthcoming technologies edge devices, Federated learning, Blockchain-based IoT.

Язык: Английский

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An innovative deep anomaly detection of building energy consumption using energy time-series images

Engineering Applications of Artificial Intelligence, Год журнала: 2023, Номер 119, С. 105775 - 105775

Опубликована: Янв. 6, 2023

Язык: Английский

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Comprehensive systematic review of information fusion methods in smart cities and urban environments

Information Fusion, Год журнала: 2024, Номер 107, С. 102317 - 102317

Опубликована: Фев. 21, 2024

Smart cities result from integrating advanced technologies and intelligent sensors into modern urban infrastructure. The Internet of Things (IoT) data integration are pivotal in creating interconnected spaces. In this literature review, we explore the different methods information fusion used smart cities, along with their advantages challenges. However, there notable challenges managing diverse sources, handling large volumes, meeting near-real-time demands various city applications. review aims to examine applications detail, incorporating quality evaluation techniques identifying critical issues while outlining promising research directions. order accomplish our goal, conducted a comprehensive search applied selective criteria. We identified 59 recent studies addressing machine learning (ML) deep (DL) These were obtained databases such as ScienceDirect (SD), Scopus, Web Science (WoS), IEEE Xplore. main objective study is provide more detailed insights by supplementing existing research. word cloud visualisation learning/deep papers shows landscape, covering both technical aspects artificial intelligence practical settings. Apart exploration, also delves ethical privacy implications arising cities. Moreover, it thoroughly examines that must be addressed realise revolution's potential fully.

Язык: Английский

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Systematic Literature Review Analysing Smart Tourism Destinations in Context of Sustainable Development: Current Applications and Future Directions

Sustainability, Год журнала: 2023, Номер 15(6), С. 5086 - 5086

Опубликована: Март 13, 2023

The growing popularity of smart tourism destinations (STDs) has increased the need to investigate their potential impact on sustainable development. This systematic literature review (SLR) aims analyse past achievements and future directions in context was conducted through a that examined 20 papers using rigorous framework research problem, primary delimitation research, definition data collection extraction tools. focuses identifying analysing current state SLRs implications for includes questions, methods, journals, dates publications, key themes. also examines limitations this field, it identifies gaps areas directions. found have been used examine impacts various aspects development, such as economic, social, environmental aspects. Additionally, there is interest cities, with focus reducing footprint promoting identified emerging literature, achievement development goals, adoption green IT, energy, waste management.

Язык: Английский

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Deep transfer learning for automatic speech recognition: Towards better generalization

Knowledge-Based Systems, Год журнала: 2023, Номер 277, С. 110851 - 110851

Опубликована: Июль 29, 2023

Язык: Английский

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Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

Applied Energy, Год журнала: 2023, Номер 333, С. 120598 - 120598

Опубликована: Янв. 10, 2023

Язык: Английский

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Intelligent energy management systems: a review

Artificial Intelligence Review, Год журнала: 2023, Номер 56(10), С. 11635 - 11674

Опубликована: Март 13, 2023

Abstract Climate change has become a major problem for humanity in the last two decades. One of reasons that caused it, is our daily energy waste. People consume electricity order to use home/work appliances and devices also reach certain levels comfort while working or being at home. However, even though environmental impact this behavior not immediately observed, it leads increased CO2 emissions coming from generation power plants. It been shown about 40% these come consumption 20% percentage could have saved if we started using more efficiently. Confronting such efficiently will affect both environment society. Monitoring real-time, changing wastage occupants automations with incorporated savings scenarios, are ways decrease global footprint. In review, study intelligent systems management residential, commercial educational buildings, classifying them categories depending on whether they provide direct indirect control. The article discusses what strengths weaknesses are, which optimization techniques do finally, insights how can be improved future.

Язык: Английский

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