[HTML][HTML] An overview of machine learning applications for smart buildings

K Alanne, S Sierla - Sustainable Cities and Society, 2022 - Elsevier
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …

[HTML][HTML] A systematic literature review on the use of artificial intelligence in energy self-management in smart buildings

J Aguilar, A Garces-Jimenez, MD R-moreno… - … and Sustainable Energy …, 2021 - Elsevier
Buildings are one of the main consumers of energy in cities, which is why a lot of research
has been generated around this problem. Especially, the buildings energy management …

Tackling climate change with machine learning

D Rolnick, PL Donti, LH Kaack, K Kochanski… - ACM Computing …, 2022 - dl.acm.org
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

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

AN Sayed, Y Himeur, F Bensaali - Engineering applications of artificial …, 2022 - Elsevier
The building internet of things (BIoT) is quite a promising concept for curtailing energy
consumption, reducing costs, and promoting building transformation. Besides, integrating …

Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities

C Persello, JD Wegner, R Hänsch… - … and Remote Sensing …, 2022 - ieeexplore.ieee.org
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …

Advanced data analytics for enhancing building performances: From data-driven to big data-driven approaches

C Fan, D Yan, F **ao, A Li, J An, X Kang - Building Simulation, 2021 - Springer
Buildings have a significant impact on global sustainability. During the past decades, a wide
variety of studies have been conducted throughout the building lifecycle for improving the …

The interaction between humans and buildings for energy efficiency: A critical review

T Harputlugil, P de Wilde - Energy Research & Social Science, 2021 - Elsevier
Buildings consume energy for different purposes. One core function is to provide healthy
and comfortable living conditions for the humans that inhabit these buildings. The …

Data mining in the construction industry: Present status, opportunities, and future trends

H Yan, N Yang, Y Peng, Y Ren - Automation in Construction, 2020 - Elsevier
The construction industry is experiencing remarkable growth in the data generation. Data
mining (DM) from considerable amount of data in the construction industry has emerged as …

Systematic review of deep learning and machine learning for building energy

S Ardabili, L Abdolalizadeh, C Mako, B Torok… - Frontiers in Energy …, 2022 - frontiersin.org
The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …

Data augmentation and dense-LSTM for human activity recognition using WiFi signal

J Zhang, F Wu, B Wei, Q Zhang… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Recent research has devoted significant efforts on the utilization of WiFi signals to recognize
various human activities. An individual's limb motions in the WiFi coverage area could …