Offshore wind farms (OWF) have emerged as a pivotal component in the transition towards
renewable energy, offering substantial potential for reducing carbon emissions and …

Large language models (LLMs) have exhibited great potential in fault diagnosis of heating,
ventilation, and air conditioning systems. However, the fault diagnosis accuracy of LLMs is …

Transfer learning-based methods have been proposed in the building field to integrate
operational data from multiple buildings for data-driven model development and thereby …

Today, a high volume of operation interval data can be efficiently captured by a diverse
range of measurements including sensors, control signals and meters, deployed in building …

Abstract In building operations, Heating, Ventilation, and Air Conditioning (HVAC) system
faults lead to substantial energy waste. Due to the rapid growth in the availability of sensing …

Forecasting future building operation states provides operators with comprehensive insights,
allowing them to understand and optimize the factors influencing various aspects of building …

Effective anomaly detection frameworks are a central pillar of the Industry 4.0 paradigm. In
this paper, we introduce an Optimal Transport (OT)-based framework for anomaly detection …

The rise of AI-powered classification techniques has ushered in a new era for data-driven
Fault Detection and Diagnosis in smart building systems. While extensive research has …

The integration of Augmented Reality (AR), Virtual Reality (VR), and Digital Twin (DT)
technologies has shown significant promise in enhancing remote collaboration, enabling …

This work presents an electrical measurement dataset from a split-system air conditioner in
normal operating conditions and with specific faults, such as incrustation in the condenser …