With the wide adoption of building automation system, and the advancement of data,
sensing, and machine learning techniques, data-driven fault detection and diagnostics …

In recent decades, the planet has been negatively impacted by the construction industry due
to the development of various infrastructures. Thus, it became one of the most polluting …

The building sector contributes significantly to overall energy consumption and carbon
emissions. Improving renewable energy utilization in buildings is of considerable …

Developing effective energy use and management strategies requires the knowledge of
determinants and patterns of the electricity usage behavior of different consumers. This …

Artificial intelligence (AI) is fast becoming a general purpose technology with outstanding
impacts in industries worldwide, thus supporting the Industry 4.0 revolution. In particular, the …

At present, the structural transformation of energy demand of public buildings in the post-
pandemic era is not well known, and there is also a lack of fine-grained research on energy …

A novel smart metering technique capable of anomaly detection was proposed for real‐time
home power management system. Smart meter data generated in real‐time were obtained …

Purely data-driven modeling methods exhibit inherent “black box” characteristics when
applied to the air source heat pump (ASHP) systems for energy efficiency improvement …

Understanding and modeling building electricity consumption is paramount for demand-side
decarbonization. Using a data-driven approach, this study proposes a hierarchical model to …

The quality of the acquisition data in the energy system of steel industry is the basis of
prediction analysis and scheduling operation. Facing with its multi-dimensional and high …