E
Eleni Mangina
Researcher at University College Dublin
Publications - 147
Citations - 1775
Eleni Mangina is an academic researcher from University College Dublin. The author has contributed to research in topics: Computer science & Augmented reality. The author has an hindex of 17, co-authored 123 publications receiving 993 citations. Previous affiliations of Eleni Mangina include National University of Ireland & Energy Institute.
Papers
More filters
Journal ArticleDOI
Data-driven predictive control for unlocking building energy flexibility: A review
TL;DR: This review examines recent work utilising data-driven predictive control for demand side management application with a special focus on the nexus of model development and control integration, which to date, previous reviews have not addressed.
Journal ArticleDOI
UAV Bridge Inspection through Evaluated 3D Reconstructions
TL;DR: This paper proposes a process using an imagery-based point cloud to provide safer, more economical, and less disruptive bridge inspection, including data acquisition, 3D reconstruction, quality evaluation, and subsequent damage detection.
Journal ArticleDOI
The changing role of information technology in food and beverage logistics management: beverage network optimisation using intelligent agent technology
Eleni Mangina,Ilias Vlachos +1 more
TL;DR: In this paper, a model of intelligent food supply chain that improves efficiency within the supply chain is presented, where agents can help solve specific problems of beverage supply: reduce inventories and lessen bullwhip effect, improve communication, and enable chain coordination without adverse risk sharing.
Journal ArticleDOI
Input variable selection for thermal load predictive models of commercial buildings
TL;DR: In this article, the selection of appropriate input variables, for data-driven predictive models, from wider datasets obtained from BEM systems sensors, as well as from weather data, is examined.
Journal ArticleDOI
Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis
TL;DR: A generalized framework based on existing literature for different urban energy modeling methods is proposed to assist urban planners and energy policymakers when choosing appropriate methods to develop and implement in-depth sustainable building energy planning and analysis projects based on limited available resources.