Big Data and Visual Analytics for Building Performance Comparison

Dimosthenis Ioannidis (1, 2) , Angeliki Fotiadou (1) , Stelios Krinidis (1) , George Stavropoulos (1) , Dimitrios Tzovaras (1) , Spiridon Likothanassis (2)

1 CERTH - Centre for Research and Technology Hellas [Athènes]
2 University of Patras

In this paper, big data and visual analytics techniques for comparing building performance under different scenarios and designs are presented. Large data consist of building information, energy consumption, environmental measurements and occupancy information, which are combined and correlated utilizing data analytics techniques, so as to extract useful semantic information about building performance. Also, visual analytics techniques are exploited to visualize them in a compact and comprehensive way taking into account properties of human cognition, perception and sense making. They analyze and visualize the performance of the buildings under comparison in the spatio-temporal domain assisting the analyst to compare them and detect patterns, templates and crucial points that are difficult to be detected otherwise. The performance comparison of different buildings or buildings of different designs or buildings with space usage rearrangement is an important factor in engineering that leads to building renovation and construction with low energy consumption and gas emissions in conjunction with comfort, utility and durability.

Mots clés: Big data analytics; Visual analytics; Building Performance

Domaines: Informatique [cs]

Dimosthenis Ioannidis, Angeliki Fotiadou, Stelios Krinidis, George Stavropoulos, Dimitrios Tzovaras, et al.. Big Data and Visual Analytics for Building Performance Comparison. 11th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2015), Sep 2015, Bayonne, France. pp.421-430, ⟨10.1007/978-3-319-23868-5_30⟩. ⟨hal-01385376⟩