Claudio Giovanni Mattera

TL;DR: An online building energy performance monitoring and evaluation tool ObepME is proposed, serving as a basis for fault detection and diagnostics and forming a backbone for continuous commissioning, to better characterize, evaluate and bridge energy performance gaps.

TL;DR: This work proposes exploiting physical relations inside ventilation units to create virtual sensors from other sensors’ readings, introducing redundancy in the system, and uses two different measures to detect when a virtual sensor deviates from the physical one: coefficient of determination for linear models, and acceptable range.

TL;DR: In this article, the authors presented an overview of the OU44 building as a highly energy efficient teaching building at the University of Southern Denmark in Odense, which is used as a living lab building for research in energy informatics and occupancy behavior, aiming to improve the energy efficiency of public buildings.

TL;DR: A dataset collected via sensors on room-level occupant counts together with related data on indoor environmental quality that can be used for developing and evaluating data-driven applications, occupant sensing, and building analytics is released.

TL;DR: A methodology to recursively compare actual data with dynamic energy simulations at different layers of aggregation to reduce the scope in searching for faults through the development of the Online Energy Simulator, a tool to set up automated simulations using standard interfaces usable with different building systems and simulation engines.