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

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building
performance, such as reducing energy wastes and negative impacts on occupant comfort …

Open data is fueling innovation across many fields. In the domain of building science,
datasets that can be used to inform the development of operational applications-for example …

Controlling the water pump and fan in the heating, ventilation and air-conditioning (HVAC)
system is crucial for achieving optimal performance of the fan coil unit (FCU) systems. In this …

Abstract Data-driven Automated Fault Detection and Diagnosis (AFDD) is the automated
process of detecting deviations (faults) from normal operation and diagnosing the type of …

This paper introduces a portable framework for developing, scaling and maintaining energy
management and information systems (EMIS) applications using an ontology-based …

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 …

Data-driven Automated Fault Detection and Diagnosis (AFDD) are recognized as one of the
most promising options to improve the efficiency of Air-Handling Units (AHUs). In this study …

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 …

With the expansion of power grid, unaffordable computational cost and time will pose
serious challenges of time-efficient scheduling in unit commitment problem (UCP). However …