Roles of artificial intelligence in construction engineering and management: A critical review and future trends
With the extensive adoption of artificial intelligence (AI), construction engineering and
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …
Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
A review of data-driven fault detection and diagnostics for building HVAC systems
With the wide adoption of building automation system, and the advancement of data,
sensing, and machine learning techniques, data-driven fault detection and diagnostics …
sensing, and machine learning techniques, data-driven fault detection and diagnostics …
[HTML][HTML] Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …
installed in residential buildings. If leveraged properly, that data could assist end-users …
[HTML][HTML] An overview of machine learning applications for smart buildings
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …
challenged by unpredicted changes in operational environments due to climate change and …
Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review
MS Mirnaghi, F Haghighat - Energy and Buildings, 2020 - Elsevier
Abnormal operation of HVAC systems can result in an increase in energy usage as well as
poor indoor air quality, thermal discomfort, and low productivity. Building automated systems …
poor indoor air quality, thermal discomfort, and low productivity. Building automated systems …
Deep learning for anomaly detection: A survey
R Chalapathy, S Chawla - ar**s as
possible between the training data and outputs, where each training data will predict as a …
possible between the training data and outputs, where each training data will predict as a …
An innovative deep anomaly detection of building energy consumption using energy time-series images
Deep anomaly detection (DAD) is essential in optimizing building energy management.
Nonetheless, most existing works concerning this field consider unsupervised learning and …
Nonetheless, most existing works concerning this field consider unsupervised learning and …
Review of smart meter data analytics: Applications, methodologies, and challenges
The widespread popularity of smart meters enables an immense amount of fine-grained
electricity consumption data to be collected. Meanwhile, the deregulation of the power …
electricity consumption data to be collected. Meanwhile, the deregulation of the power …